Direct-Fed Microbials and Prebiotics for Animals: Science and Mechanisms of Action [2 ed.] 3031405110, 9783031405112

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Todd R. Callaway Steven C. Ricke   Editors

Direct-Fed Microbials and Prebiotics for Animals Science and Mechanisms of Action Second Edition

Direct-Fed Microbials and Prebiotics for Animals

Todd R. Callaway  •  Steven C. Ricke Editors

Direct-Fed Microbials and Prebiotics for Animals Science and Mechanisms of Action Second Edition

Editors Todd R. Callaway Department of Animal and Dairy Sciences University of Georgia Athens, GA, USA

Steven C. Ricke Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences University of Wisconsin Madison, WI, USA

ISBN 978-3-031-40511-2    ISBN 978-3-031-40512-9 (eBook) https://doi.org/10.1007/978-3-031-40512-9 © Springer Nature Switzerland AG 2012, 2023 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Preface

We are excited to bring you this updated second edition of Direct-Fed Microbials and Prebiotics for Animals: Science and Mechanisms of Action. The past years have been an exciting time to research how direct-fed microbials (DFMs) can benefit animal producers, consumers, and the environment. We discuss the changes in our thoughts on DFMs that have happened during the intervening years and the expansion of our understanding of how DFMs work in food animals. Further, we have increased our understanding of the normal microbial population of the gut of food animal species, which has altered our perspective on how direct-fed microbials impact this native population and alter it to improve food safety and animal health. Interactions between the microbial population of animals and host animal wellbeing/production efficiency have also become better defined thanks to developments in next-generation sequencing. The entire concept of these books emerged from the 2009 American Dairy Science Association DISCOVER conference, titled “Probiotics in Animal Agriculture: Science and Mechanisms of Action,” because the chair (Dr. Stan Gilliland) and others saw the need for a discussion on the state of the art for the direction of the animal production and direct-fed microbial industries. The need for scientific analysis on DFM actions and benefits, as well as how DFMs actually work, became apparent, and despite the increase in our knowledge, we have found more questions than answers in how these products affect animal performance, environmental impacts/sustainability, food safety, and animal health. Since the last edition, a veritable avalanche of research into the composition and activity of the gastrointestinal microbial ecosystem (microbiome) in food animals has been produced (Poole et al. 2013; Modi et al. 2014; Myer et al. 2015; Ricke et al. 2017, 2022; Ban and Guan 2021; Jeni et al. 2021; Welch et al. 2021a, b; Dittoe et al. 2022; Weinroth et al. 2022). These projects have built on the early work of seminal researchers such as Gordon, Ley, Turnbaugh, and Lyte, and have expanded our understanding of how microbes interact with each other and with the host animal (Xu and Gordon 2003; Ley et al. 2006; Turnbaugh et al. 2006, 2009; Lyte 2010, 2013; Cryan et al. 2019). Merging the growing interest in the gut microbial ecosystem with the growing need for nonantibiotic approaches to improving food animal v

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growth performance, animal health, and food safety has become a top priority in the past decade. Concerns about the dissemination of antimicrobial resistance genes have virally spread around the world and have led to the implementation of methods to reduce the use of antimicrobials in food animal production, especially their use as growth promotants (Gaskins et al. 2002; FDA 2015). Increasing regulations on the use of antimicrobials have provided an impetus to the food animal industry to explore a variety of alternatives to antibiotics (ATAs) that replicate the benefits of antimicrobial use (in impacts on production efficiency and on animal and human health). One of the best-established approaches has been the use of direct-fed microbial products to improve animal production efficiency and animal wellbeing (Callaway et  al. 2021; Low et al. 2021). Supplementing the diets of food animals with DFMs has become more widely accepted over the past decade. The beneficial impacts of feeding DFMs have been determined in cattle, swine, poultry, and fish, including generally improved health, improved feed utilization efficiency, rapider growth, increased milk and egg production, improved reproductive efficiency, and the reduced carriage of foodborne pathogenic bacteria that can harm human consumers. For years, much of the incorporation of the use of DFMs into animal production has been limited because of a lack of consistency in production results; however, as scientific analyses have clarified the modes of action, performance consistency has improved. In spite of these improvements, many questions remain about DFMs in general but also about the interactions between DFMs, the native microbial population, host nutrition, and the host immune system. Further information has come to light about the impacts of DFMs in a variety of animal species and production systems, indicating that modern DFMs can improve performance better than ever before.

Definitions In this book, we use the same definitions as we did previously, with some specific additions. A probiotic is defined as “a preparation or a product containing viable, defined microorganisms in sufficient numbers to alter the micro-flora (by implantation or colonization) in a compartment of the host and that exert beneficial health effects in the host” (Schrezenmeir and De Vrese 2001). A direct-fed microbial (DFM) is a term of art for a broad category of probiotic products used in food animals (Wierup et al. 1988; Fuller 1989; Schrezenmeir and De Vrese 2001), and this category has been subdivided in recent years into many subcategories on the basis of their composition and modes of action. Eubiotics, postbiotics, prebiotics, nutraceuticals, and synbiotics are all categories of products that can be included in DFMs. In general, eubiotics are living organisms (typically either bacteria or fungi) that can be fed to the animal (Miniello et al. 2017). This is contrasted with postbiotics, which are nonliving products, often made from fungal fermentations, including cellular wreckage and fermentation end products (Loh et al. 2014; Tomasik and Tomasik

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2020; Salminen et al. 2021). Prebiotics in turn are compounds that are not digested/ degraded by the host animal but are utilized by members of the microbial ecosystem, providing them a competitive advantage, which in turn can cause a shift in the microbiome composition of the gut of food animals and have been termed colonic food (Gibson and Roberfroid 1995; Collins and Gibson 1999; Crittenden 1999; Ricke 2018). Nutraceuticals are not included in this book, per se, but are included here for the sake of completeness; however, they are bioactive compounds that are found in foods and that produce changes in the microbial ecosystem (Gupta et al. 2014; Joyce and Gahan 2016). Synbiotics are combinatorial approaches, often incorporating several modes of action/products, such as a eubiotic coupled with a postbiotic that contains some prebiotic compounds (Collins and Gibson 1999; Schrezenmeir and De Vrese 2001). Many DFM products on the market may (intentionally or inadvertently) contain several compounds that produce a more synbiotic effect that alters the gastrointestinal microbial population and produces impacts on host physiology, health, wellbeing, safety, or productivity. Athens, GA, USA Madison, WI, USA

Todd R. Callaway Steven C. Ricke

References Ban Y, Guan LL (2021) Implication and challenges of direct-fed microbial supplementation to improve ruminant production and health. J Anim Sci Biotechnol 12(1):1–22 Callaway TR, Lillehoj HS, Chuanchuen R, Gay CG (2021) Alternatives to antibiotics: a symposium on the challenges and solutions for animal health and production. Antibiotics 10:471–486. https://doi.org/10.3390/antibiotics10050471 Collins DM, Gibson GR (1999) Probiotics, prebiotics, and synbiotics: approaches for modulating the microbial ecology of the gut. Am J Clin Nutr 69:1052S–1057S Crittenden RG (1999) Prebiotics. In: Tannock GW (ed) Probiotics: a critical review. Horizon Scientific Press, Wymondham, pp 141–156 Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, Codagnone MG, Cussotto S, Fulling C, Golubeva AV, Guzzetta KE, Jaggar M, Long-Smith CM, Lyte JM, Martin JA, Molinero-Perez A, Moloney G, Morelli E, Morillas E, O’Connor R, Cruz-Pereira JS, Peterson VL, Rea K, Ritz NL, Sherwin E, Spichak S, Teichman EM, van de Wouw M, Ventura-Silva AP, ­WallaceFitzsimons SE, Hyland N, Clarke G, Dinan TG (2019) The microbiota-gut-brain Axis. Physiol Rev 99(4):1877–2013. https://doi.org/10.1152/physrev.00018.2018 Dittoe DK, Olson EG, Ricke SC (2022) Impact of the gastrointestinal microbiome and fermentation metabolites on broiler performance. Poult Sci 101:101786. https://doi.org/10.1016/j. psj.2022.101786 FDA (2015) Veterinary feed directive. Fed Regist 80:31707–31735 Fuller R (1989) Probiotics in man and animals. J Appl Bacteriol 66:365–378 Gaskins HR, Collier C, Anderson D (2002) Antibiotics as growth promotants: mode of action. Anim Biotechnol 13:29–42. https://doi.org/10.1081/ABIO-­120005768 Gibson GR, Roberfroid MB (1995) Dietary modulation of the human colonic microbiota: introducing the concept of prebiotics. J Nutr 125(6):1401–1412. https://doi.org/10.1093/jn/125.6.1401 Gupta C, Prakash D, Rostagno M, Callaway T, Sharma G (2014) Synbiotics: promoting gastrointestinal health. In: Phytochemicals of nutraceutical importance, CABI International, Oxfordshire, UK, pp 61–78

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Jeni RE, Dittoe DK, Olson EG, Lourenco J, Corcionivoschi N, Ricke SC, Callaway TR (2021) Probiotics and potential applications for alternative poultry production systems. Poult Sci 100(7):101156. https://doi.org/10.1016/j.psj.2021.101156 Joyce SA, Gahan CGM (2016) Bile acid modifications at the microbe-host interface: potential for nutraceutical and pharmaceutical interventions in host health. Annu Rev Food Sci Technol 7:313–333. https://doi.org/10.1146/annurev-­food041715-­033159 Ley RE, Turnbaugh PJ, Klein S, Gordon JI (2006) Human gut microbes associated with obesity. Nature 444:1022–1023 Loh TC, Choe DW, Foo HL, Sazili AQ, Bejo MH (2014) Effects of feeding different postbiotic metabolite combinations produced by Lactobacillus plantarum strains on egg quality and production performance, faecal parameters and plasma cholesterol in laying hens. BMC Vet Res 10. https://doi.org/10.1186/1746-­6148-­10-­149 Low CX, Tan LT, Ab Mutalib NS, Pusparajah P, Goh BH, Chan KG, Letchumanan V, Lee LH (2021) Unveiling the impact of antibiotics and alternative methods for animal husbandry: a review. Antibiotics (Basel) 10(5). https://doi.org/10.3390/antibiotics10050578 Lyte M (2010) The microbial organ in the gut as a driver of homeostasis and disease. Med Hypotheses 74:634–638 Lyte M (2013) Microbial endocrinology in the microbiome-gut-brain axis: how bacterial production and utilization of neurochemicals influence behavior. PLoS Pathog 9(11):e1003726. https://doi.org/10.1371/journal.ppat.1003726 Miniello V, Diaferio L, Lassandro C, Verduci E (2017) The importance of being eubiotic. J Prob Health 5(162):1–12 Modi SR, Collins JJ, Relman DA (2014) Antibiotics and the gut microbiota. J Clin Invest 124(10):4212–4218 Myer PR, Smith TP, Wells JE, Kuehn LA, Freetly HC (2015) Rumen microbiome from steers differing in feed efficiency. PLoS One 10(6):e0129174. https://doi.org/10.1371/journal. pone.0129174 Poole TL, Suchodolski JS, Callaway TR, Farrow RL, Loneragan GH, Nisbet DJ (2013) The effect of chlortetracycline on faecal microbial populations in growing swine. J Glob Antimicrob Resist 1(3):171–174 Ricke SC (2018) Impact of prebiotics on poultry production and food safety. Yale J Biol Med 91:151–159 Ricke SC, Hacker J, Yearkey K, Shi Z, Park SH, Rainwater C (2017) Chapter 19: Unravelling food production microbiomes: concepts and future directions. In: Ricke SC, Atungulu GG, Park SH, Rainwater CE (eds) Food and feed safety systems and analysis. Elsevier Inc., San Diego, pp 347–374. https://doi.org/10.1016/B9780-­12-­811835-­1.00019-­1 Ricke SC, Dittoe DK, Olson EG (2022) Microbiome applications for laying hen performance and egg production. Poult Sci. 101:101784. https://doi.org/10.1016/j.psj.2022.101784 Salminen S, Collado MC, Endo A, Hill C, Lebeer S, Quigley EMM, Sanders ME, Shamir R, Swann JR, Szajewska H, Vinderola G (2021) The International Scientific Association of Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of postbiotics. Nat Rev Gastroenterol Hepatol 18(9):649–667. https://doi.org/10.1038/s41575-­021-­00440-­6 Schrezenmeir J, De Vrese M (2001) Probiotics, prebiotics, and synbiotics-­approaching a definition. Am J Clin Nutr 73(Suppl):354s–361s Tomasik P, Tomasik P (2020) Probiotics, non-dairy prebiotics and postbiotics in nutrition. Appl Sci 10:1470. https://doi.org/10.3390/app10041470 Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI (2006) An obesityassociated gut microbiome with increased capacity for energy harvest. Nature 444:1027–1031 Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon JI (2009) A core gut microbiome in obese and lean twins. Nature 457(7228):480–484 Weinroth MD, Belk AD, Dean C, Noyes N, Dittoe DK, Rothrock MJ Jr, Ricke SC, Myer PR, Henniger MT, Ramírez GA, Oakley BB, Summers KL, Miles AM, AultSeay TB, Yu Z, Metcalf J, Wells J (2022) Considerations and best practices in animal science 16S rRNA gene sequencing microbiome studies. J Anim Sci 100:1–18. https://doi.org/10.1093/jas/skab346

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Welch CB, Lourenco JM, Krause TR, Seidel DS, Fluharty FL, Pringle TD, Callaway TR (2021a) Evaluation of the fecal bacterial communities of angus steers with divergent feed efficiencies across the lifespan from weaning to slaughter. Front Vet Sci 8:597405. https://doi.org/10.3389/ fvets.2021.597405 Welch CB, Lourenco JM, Seidel DS, Krause TR, Rothrock MJ, Pringle TD, Callaway TR (2021b) The impact of pre-slaughter fasting on the ruminal microbial population of commercial angus steers. Microorganisms 9(12). https://doi.org/10.3390/microorganisms9122625 Wierup M, Wold-Troell M, Nurmi E, Hakkinen M (1988) Epidemiological evaluation of the Salmonella-controlling effect of a nationwide use of a competitive exclusion culture in poultry. Poult Sci 72:643–457 Xu J, Gordon JI (2003) Honor thy symbionts. Proc Natl Acad Sci U S A 100:1045210459

Contents

Part I The Gastrointestinal Tract of Food Animals and Impact of Feed Additives  1 Commensal  Gastrointestinal Microbiota as a Complex Interactive Consortia ������������������������������������������������������������������������������    3 J. A. Patterson, Todd R. Callaway, and Steven C. Ricke  2 The  Poultry Gastrointestinal Tract: An Overview of Microbial Ecology��������������������������������������������������������������������������������   21 Steven C. Ricke, L. A. Wythe, and A. Scheaffer  3 Current  Understanding of the Crosstalk Between Direct-Fed Microbials and Indigenous Microbiome in the Gastrointestinal Tract: Applications and Challenges in Food-Producing Animals��������   35 Tao Ma and Le Luo Guan  4 Advancements  in Poultry Nutrition and Genetics, the Role of Antibiotic Growth Promoters, and the Introduction of Feed Additive Alternatives������������������������������������������������������������������   59 L. A. Wythe, D. K. Dittoe, and Steven C. Ricke  5 Prebiotics  with Plant and Microbial Origins����������������������������������������   81 Celeste Alexander, Ching-Yen Lin, Brittany M. Vester Boler, George C. Fahey Jr., and Kelly S. Swanson  6 Prospects  for Prebiotic and Postbiotic Applications in Poultry ����������  103 Steven C. Ricke, L. A. Wythe, E. G. Olson, and A. Scheaffer Part II Probiotics: Current Status and Future Challenges of Practical Applications  7 Probiotics  in Poultry Preharvest Food Safety: Historical Developments and Current Prospects����������������������������������������������������  127 A. V. S. Perumalla, L. A. Wythe, and Steven C. Ricke xi

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 8 Probiotics  and Prebiotics: Application to Pets��������������������������������������  167 Ching-Yen Lin, Celeste Alexander, Brittany M. Vester Boler, George C. Fahey Jr., and Kelly S. Swanson  9 Direct-Fed  Microbial Supplementation and the Swine Gastrointestinal Tract Microbial Population: Current Challenges and Future Prospects ����������������������������������������������������������  229 Ellen Davis, Todd R. Callaway, and Steven C. Ricke 10 Finfish  Microbiota and Direct-Fed Microbial Applications in Aquaculture ������������������������������������������������������������������  249 Jacob W. Bledsoe and Brian C. Small 11 Practical  Applications of Probiotics in Beef Cattle Production ����������  301 Todd R. Callaway, O. Koyun, N. Corcionivoschi, J. J. Baloyi, C. Ateba, L. Stef, R. El Jeni, and D. Bu 12 Current  Status of Practical Applications: Probiotics in Dairy Cattle������������������������������������������������������������������������������������������  323 Rim El Jeni, Andrea Osorio-Doblado, Katie Feldmann, Jeferson Lourenco, Dengpan Bu, and Todd R. Callaway Index������������������������������������������������������������������������������������������������������������������  347

About the Editors

Todd R. Callaway received his BS degree in agriculture and his MS in animal and dairy science from the University of Georgia. He received his PhD in microbiology from Cornell University, with minors in biochemistry and animal science. Dr. Callaway served as a research microbiologist for the Agricultural Research Service of the US Department of Agriculture for 18 years in College Station, TX, including a brief stint as its national program leader. Todd served as a science fellow for the Foreign Agricultural Service of the US State Department and served as a scientific panel chair for the Joint FAO/WHO Expert Meetings on Microbiological Risk Assessment (JEMRA) for the Food and Agriculture Organization of the UN’s World Health Organization. Todd currently serves as the editor in chief for foodborne pathogens and disease. In 2017, Dr. Callaway returned to the University of Georgia, Department of Animal and Dairy Science, as a faculty member. His research program continues to focus on the structure of the gastrointestinal microbial ecosystem and on how this population impacts host animal health, physiology, growth efficiency, and food safety.

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About the Editors

Steven C. Ricke received his BS degree in agriculture and MS degree in ruminant nutrition at the University of Illinois and his PhD from the University of Wisconsin–Madison with a double major in animal science and bacteriology. Dr. Ricke was a member of the faculty at Texas A&M University in the Poultry Science Department from 1992 to 2005. He joined the University of Arkansas (UA) in 2005 to become the inaugural Donald “Buddy” Wray endowed chair in food safety as well as director of the UA Center for Food Safety. He was on the faculty in the Department of Food Science, and a member of the Cellular and Molecular Biology Faculty until 2020, when he joined his alma mater, the University of Wisconsin–Madison, WI.  Steve is currently the director for the Meat Science and Animal Biologics Discovery Program (MSABD) and serves as a Professor in the Department of Animal and Dairy Sciences. Dr. Ricke’s research program has long focused on understanding the virulence and pathogenic characteristics of foodborne Salmonellae and Campylobacter. Steve also has research experience in understanding how to utilize prebiotics and probiotics most effectively in poultry, swine, and ruminants.

Part I

The Gastrointestinal Tract of Food Animals and Impact of Feed Additives

Chapter 1

Commensal Gastrointestinal Microbiota as a Complex Interactive Consortia J. A. Patterson, Todd R. Callaway, and Steven C. Ricke

Abstract  The commensal microbial population of the gastrointestinal tract is crucial to host health and wellbeing, not only because the microbes degrade feedstuffs but also because they provide resistance against pathogen colonization, and these commensal microbes are involved in developmental programming and immune system development. The microbial population has been described as a functional organ system in the host, and this population outnumbers host cells by a factor of more than ten to one. The presence of a large number of microbial genes that are not found in the host genome means that the native microbial population is an accessory genome to the host animal, providing the ability to degrade feedstuffs and produce the essential nutrients (e.g., vitamins and cofactors) needed by other members of the microbial ecosystem and the host animal. More and more information has shed light on the involvement of the microbial population in immune development, gut health, host physiological status, and even mental health. The dynamic microbial population changes during aging, dietary shifts, and exposure to environmental stressors, and the ability of this population to attenuate these profound shifts increases the adaptability of the host animal and can affect feed efficiency and sustainability.

1.1 Introduction Upon birth, bacteria colonization of the host occurs almost immediately with primary entry points being the skin and mucosal surfaces of the gastrointestinal, respiratory, and urogenital tracts leading to colonization of complex microbial J. A. Patterson Department of Animal Sciences, Purdue University, West Lafayette, IN, USA T. R. Callaway Department of Animal and Dairy Sciences, University of Georgia, Athens, GA, USA S. C. Ricke (*) Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_1

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communities of beneficial bacteria to the host that would be considered as commensal in their behavior (Tlaskalová-Hogenová et al. 2004). The commensal microbiota in the intestinal tract are important to the host, not only in food digestion but also in reducing infection from pathogens by serving as barriers to pathogen colonization (Buffie and Pamer 2014; Abt and Pamer 2014). The commensal microbiota are engaged in the developmental programming and function of organ systems in adults. This is not surprising because there are ten times as many microbial cells as host cells and 100 times as many microbial genes (Gill et  al. 2006). The commensal microbiota could be considered together as an additional organ that influences not only functions in adults but also development in neonates (O’Hara and Shanahan 2006). The commensal microbiota are important components of the host animal’s genome. During and immediately after birth, the intestinal tract is colonized by a succession of bacteria. The presence of these bacteria is important for the functional development of the intestinal tract (angiogenesis, epithelial tissues, and the mucosal system), and more-recent data suggest that they play a role in the development and function of the brain and the hypothalamic–pituitary axis (HPA) throughout the host anima’s life span. From an ecological perspective, the intestinal tract could also be viewed as a major river running through a continent, originating in the headwaters and discharging after passing through the continent. The river ecosystem is dynamic and constantly changing and is influenced by the surrounding land given that the land is impacted by the river. The intestinal tract has major (rumen in ruminants, crop and proventriculus in birds) and minor (human, mouse) differences in stomach structure, which influence subsequent microbial ecosystems. There are major differences among bacterial species in the structure of the small intestine, cecum, and large intestine that also influence the dynamics of the microbial ecosystem. Individual differences in intestinal structure, pH, transit rate, water content, immune function, and the expression of molecules lining the epithelium influence the unique microbiota in individual animals. In this review, the role of gastrointestinal commensal bacteria in host development and overall health will be discussed, as will their interactions as a complex microbial community.

1.2 The Diversity of Microbial Communities in the Gastrointestinal Tract From a microbial ecology perspective, disturbances in ecosystems decrease microbial diversity and increase opportunities for foreign species to invade. For example, pasture soil may contain 3500–8800 bacterial species, whereas species diversity in arable land is around 140–350 species (Horner-Devine et  al. 2004; Xavier et  al. 2005). The luminal contents of the intestinal tract are constantly being disturbed, especially in the small intestine, and the number of bacteria and bacterial diversity are lower in the small intestine. However, estimates of bacterial diversity in the

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colon rarely exceed 1000 species. From a nutritional competition perspective, high diversity in an established ecosystem is thought to inhibit invasion by new species, whether they are pathogens or beneficial microorganisms. In environmental ecosystems, the low susceptibility to invasion of high-diversity communities is due to their low levels of available resources because a redundancy in the species’ use of resources reduces niche width. Disturbances in the ecosystem may allow invading species to overcome resource-dependent limitations to invasion (Tillman 2004; Xavier et al. 2005). In complex ecosystems, superior competitors for a nutrient may be limited by growth rate; thus, they may be unable to exploit all the available space, and inferior competitors can exploit these gaps if they have high growth rates (Amarasekare et al. 2004). The rumen microbial ecosystem is a classic example of a fine-tuned ecologically balanced consortium’s being partially controlled by the growth dynamics of individual members of the community and by host factors such as passage rate, dilution rate, and inhibitory physicochemical conditions such as drastic changes in pH or other dietary alterations, which can lead to rapid rumen bacterial cell lysis (Russell 1984; Wells and Russell 1996). Locations within the rumen ecosystem may also represent unique niches for specific groups of rumen bacteria. For example, on the basis of 16S rDNA microbiome analyses, Pinnell et al. (2022) detected significant differences in the diversity and community structure of microbial communities, such as rumen fluids, packs, and mucosae, and suggested that individual microenvironments existed independent of diet. Despite these differences, the overall metabolic balance in the rumen is retained to some extent thanks to the redundancy in function among multiple species and resilience and/or their capacity to recover from ecological disturbances in the rumen (Weimer 2015). Given the complexities of dietary substrates, ranging from cellulose and other fiber components in forages to grain supplements, the rumen microbial community would be expected to possess highly complex functionalities, ranging from primary polymer degraders to specialized substrate fermenters (Russell 1984). Cellulose degradation is conducted by a few rumen bacterial species, but the diversity of microorganisms that benefit from that primary hydrolysis increases when cross-feeding is taken into account (Wolin and Miller 1982a, b; Weimer 1998). Cross-feeding occurs when rumen noncellulolytic microorganisms such as Selenomonas ruminantium use some of the hydrolyzed cellulose products and intermediate end products such as succinate (Ricke et al. 1996). The interactions between cellulolytic bacteria can, in turn, be further influenced by the presence of noncellulolytic bacteria (Chen and Weimer 2001). Cross-feeding also includes rumen methanogens that can utilize the hydrogen generated from carbohydrate fermentation, and this results in interspecies hydrogen transfer (Wolin and Miller 1982a, b). Where most of this occurs in the rumen may be complex, as Pinnell et  al. (2022) detected a greater abundance of Methanobacteriaceae in the fluid phase of rumen contents. The intestinal tract contains a variety of ecosystems, and each exerts different ecological pressures on microbial colonization. Another example would be the microbial growth rate or metabolic activity of different sections of the intestinal tract. Although the number of bacteria and that of bacterial species are lower in the

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small intestine, if one calculates the ATP per bacterial cell in each location, the metabolic activity of the microbiota in the small intestine is ten-fold greater than that of the colon (Patterson, unpublished, adapted from Jensen and Jorgensen 1994). The conceptual framework of microbial ecology theory may help explain the different enterotypes discussed by Arumugam et  al. (2011) and Yin et  al. (2010). Additional concepts for host contributions to species/enterotype colonization (differential gene expression resulting in unique epithelial cell composition/secretions, mucosal immune status, etc.) need to be further developed to reach a more comprehensive understanding of host–microbiota ecological theory development.

1.3 Temporal Colonization of the Intestinal Tract The intestinal tract is sterile at birth and becomes colonized in a series of successional steps (Dominguez-Bello et al. 2011; Ley et al. 2006; Koenig et al. 2011; Lu et al. 2003; Yin et al. 2010). Facultative microorganisms rapidly colonize the intestinal tract, and as they modulate the nutritional and environmental (oxygen, pH, host gene expression) ecosystem of the intestinal tract, more anaerobic microorganisms sequentially colonize the intestinal tract (Dominguez-Bello et  al. 2011; Koenig et al. 2011; Ley et al. 2006; Wilkinson 2002). The early and rapid initial colonization helps protect against pathogen invasion (colonization resistance), but the climax microbial population may not become established for several years or even until the adolescent period in an animal (Marques et  al. 2010). Colonization is dependent on the microorganisms in the host animal’s environment, the host’s physiology, and the host animal’s response to the early colonizers. In adult animals, there is a gradient of oxygen from food and water consumption and a gradient from tissues’ entering the lumen that influences species composition along the digestive tract (Wilkinson 2002). There is an increase in total numbers of bacteria along the small intestinal tract, in the cecum, proximal, and distal large intestine, causing facultative microorganisms to make up < 0.01 to 1% of the total population. The ecosystems influence the types of microorganisms colonizing each ecosystem and are the sources of microorganisms that colonize subsequent intestinal ecosystems (see Rawls et al. 2006 and Yin et al. 2010 for a discussion on the impact of microbiota sources and hosts on microbial colonization). The stability of the intestinal microbiota also changes in elderly people (Claesson et al. 2011; Spor et al. 2011).

1.3.1 Postnatal Programming Information about fetal and postnatal programming is increasing, not only about behavior (Heijtz et al. 2011; Huang 2011; Li et al. 2009; Marques et al. 2010; Tarry-­ Adkins and Ozanne 2011) but also about the metabolic and immune functions (Badr and Mohany 2011; Leach and Mann 2011). One of the more detailed examples of

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postnatal programming interactions with microbiota was described by Hooper et al. (1999). They discussed the programmed expression of fucose on epithelial cell surfaces in germfree mice in early postnatal development and demonstrated that fucose expression in germfree mice lasted only briefly. However, in the presence of Bacteroidedes thetaiaotamicron, fucose expression expanded among epithelial cells and continued in the presence of B. thetaiotamicron. They also showed that B. thetaiotamicron secreted a signal molecule stimulating the expression of fucose, which the bacterium could use as a nutrient source. However, it would be naïve to assume that this was the only molecule in the intestinal tract with programmed expression, where subsequent regulation takes place in the presence of bacterial signals. Another example of the importance of early colonization by specific microbial populations is that children who develop allergies are colonized less frequently with bifidobacteria and enterococci but more frequently with Clostridium difficile, and there is a correlation between nonallergic children and SIgA levels. Early colonization with bifidobacterium species correlated with higher levels of SIgA in Swedish infants 1  month after birth, whereas there was a negative correlation between Bacteroides fragillis and TLR4, CCL4, and IL-6 expressions in peripheral mononuclear cells 12 months after birth (Sjögren et al. 2009). The initial inoculum is primarily thought to be bacteria from the mothers rectal/ vaginal microbiota, but other environmental sources may also be important. Tapiainen et al. (2006) showed that the gastrointestinal microbiota varied significantly over the first few days of life and varied between individuals. The fecal microbiota resembled that of both the mothers and their nurses 6 months after birth. Other factors influencing the microbiota include the mode of delivery, gestational age, antibiotic use, hospitalization, the surrounding environment, and maternal infections (Adlerberth and Wold 2009; Marques et al. 2010; Tanaka et al. 2009). We (Patterson, unpublished data) have shown that chickens raised intensively versus those raised on pasture carry Salmonella longer in the cecum but not the ileum. Yin et al. (2010) used two continuous culture inocula from adult birds or water to inoculate 1-day-old chicks. Both continuous culture inocula contained ~36% Bacteroidetes, 61% Firmicutes, and 3% Proteobacteria; however, one inoculum was characterized by much higher levels of Bacteroides fragilis, whereas the second inoculum contained much higher levels of Prevotgella albensis, Acidaminococcus, and Dorea. Over 15  days, the chicks developed significantly different microbial populations, where the latter treatment and water inoculum had more similar populations. Gene expression in ileal samples was also different between the three inocula. Thus, certain microbial populations inoculated early have lasting effects on the subsequent microbial populations. Early life exposure to microorganisms drives the expansion and development of immune cells and tissues, and the diversity and specific types of microorganisms at least partially influence the subsequent ability of the immune system to respond to allergens and infections (Bjorksten et al. 2001). The exposure of neonatal piglets to low- and high-hygiene environments showed a greater diversity of microbiota in piglets raised in low-hygiene environments, a slower accumulation of dendritic cells in the intestinal mucosa, and the differential production of IL-2 and IL-4 by mucosal

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and systemic T cells (Inman et al. 2010). Arumugam et al. (2011) have found three enterotypes among humans from different cultures characterized by high levels of either Bacteroides, Prevotella, or Ruminococcus species that differ in functional properties. Hydrogen disposal may also be a factor in enterotype development as the high Bacteroides enterotype is associated with higher levels of Desulfovibrio and the high Ruminococcus enterotype is associated with higher levels of Methanobrevibacter. The newer high-throughput molecular approaches may be able to identify other minor components of the microbiota that have important functions in the intestinal tract. Current information is not detailed enough to determine the specific host properties that dictate the different enterotypes or whether they may be influenced by host immune modulation (which may be influenced by early colonizers) and/or physiological factors such as transit time, dry matter content, or luminal pH. However, Spor et al. (2011) have indicated some host genes associated with specific microbiota.

1.4 Upsetting the Balance: The Effect of Stressors on the Intestinal Microbiota Although the gastrointestinal microbiota are relatively stable in adult animals, disturbances can occur that disrupt that ecological balance. Numerous stressors can come in contact with the gastrointestinal microbiota and lead to compositional and/ or metabolic perturbations in this balance and in turn gastrointestinal dysbiosis. Zaneveld et  al. (2017) proposed that gastrointestinal dysbiosis can essentially be characterized as a transitioning to an unstable gastrointestinal microbiome. Consequently, Zaneveld et al. (2017) concluded that the microbiomes of dysbiotic individuals vary much more than their healthy counterparts. Stressors that impact the gastrointestinal microbiota can come from a multitude of sources. Some of these may occur as dietary changes, such as the introduction of antibiotics, organic acids, or other compounds that are more generally inhibitory to groups of microorganisms (Jernberg et al. 2010; Dittoe et al. 2018; Bäumler and Sperandio 2016; Ricke et al. 2019, 2020; Abd El-Hack et al. 2022). Antibiotics can be particularly disruptive, and this can create ecological nutritional openings for pathogenic bacteria, which can, in turn, alter the gastrointestinal environment by inducing inflammation (Bäumler and Sperandio 2016). Other antimicrobials, such as bacteriophages, antimicrobial peptides, and bacteriocins, exhibit narrower spectra of antimicrobial activity and therefore are less likely to be disruptive to the general gastrointestinal population (Chou et al. 2022). Some stressors occur through host responses (Alverdy and Luo 2017). For example, it is well known that stress makes animals more susceptible to infection, and until recently, it was thought that stress hormones acting through the hypothalamic– pituitary axis (HPA) increased susceptibility by suppressing the immune system. It appears that catecholamines do increase the growth and expression of virulence

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genes in Gram-negative pathogenic bacteria (Freestone et al. 2008; Lyte 2004; Lyte et al. 2011). The central theses from this group are that the intestinal microbiota constitute an organ; that the microbial species composition influences host homeostasis and disease susceptibility; that the host’s nervous system (in conjunction with the immune system) influences the species composition; and that the microbiota possess their own nervous system (quorum sensing as well as the ability to sense and secrete a variety of signal compounds) (Lyte 2010). The massive release of norepinephrine caused by the administration of a neurotoxin has been shown to cause a several-log fold increase in E. coli within hours. (Lyte and Bailey 1997) and Bailey et al. (2010, 2011) have shown that mild stressor exposure disrupts the commensal microbial population and that infection levels were associated with the presence of specific microbial genera.

1.5 Upsetting the Balance: Lactic Acidosis and Rumen Microbiota Dietary stresses on the gastrointestinal tract can occur from multiple sources. A classic example is an abrupt change in diet. For example, lactic acidosis occurs in cattle that are rapidly switched from a forage diet to high-grain diet because this represents a drastic change in substrate availability for the fermenting rumen microbiota. Streptococcis bovis, which is normally a minor species in the rumen, has poor affinity for carbohydrates but can grow rapidly when carbohydrates are available and has been identified as a primary culprit in the series of events leading to the acidification of the rumen (Hungate et al. 1952; Jarvis et al. 2001; Herrera et al. 2009). S. bovis produces lactic acid, which rapidly decreases ruminal pH, inhibiting the normal dominant microbiota and eventually resulting in indigestion, feed intake reduction, and more-extreme clinical manifestations, such as parakeratosis, liver abscesses, and ultimately death (Slyter 1976; Russell and Hino 1985; Herrera et al. 2009; Hernández et al. 2014). Under normal diet conditions, S. bovis produces a mixture of fermentation acids (acetate, formate, and ethanol), but in the presence of excess carbohydrate and reduced pH, such as a rapid switch to a grain-based diet, S. bovis becomes homofermentative, producing exclusively lactate (Asanuma and Hino 2000; Herrera et al. 2009). This spirals into a perfect storm of rumen imbalance where lactate utilizers are unable to consume the excess lactate, coupled with their being sensitive to acidic pH and not being able to sufficiently decrease lactate levels, leading to further pH decreases and shifting to acid-resistant lactobacilli, which accelerates lactate production and the development of lactic acidosis in clinical outcomes (Asanuma and Hino 2002; Nagaraja and Titgemeyer 2006; Herrera et al. 2009). A comparison of cows’ undergoing induced subacute lactic acidosis with noninduced animals indicates that liquid- and solid-phase rumen microbiomes also differ (McCann et al. 2016). In addition, systemic inflammation can occur as Gram-negative bacteria are lysed, resulting in the release of endotoxins and

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lipopolysaccharides (Nagaraja and Titgemeyer 2006; Loor et al. 2016; Chen et al. 2019). Recovering the rumen microbiota is possible, as Brede et al. (2020) demonstrated with a rumen simulation technique (RUSITEC) in an in vitro subacute lactic acidosis model, where most of the microbial groups regained their initial abundance after subacute lactic acidosis was no longer present in the RUSITEC system. However, longer-term consequences can also occur. Wetzels et al. (2016) demonstrated that the bovine epimural bacterial microbiome was slower to recover to baseline levels than the lumen pH in ruminants experiencing a transient long-term subacute lactic acidosis induced by concentrate diets. Several factors influence the relationship between S. bovis, the rumen microbial population, and the development of rumen lactic acidosis. Certainly, the grain type and level of processing can influence the level of the digestibility of starch in the diet and its subsequent availability to the rumen microbiota (Kotarski et al. 1992). This variability can, in turn, influence which members of the rumen microbiota community are most likely to hydrolyze and ferment the available dietary starch (Kotarski et al. 1992). In addition, there are phenotypic and genetic differences in S. bovis strains that could contribute to the variability observed with diets (Russell and Robinson 1984; Jarvis et al. 2001). The responses of rumen lactate utilizers are also factors. For example, Megaspheara elsdenii, one of the primary lactate degraders, can be impacted by both lactate concentration and pH, where the sensitivity-to­pH decreases are especially influenced at the transcriptional level of metabolic genes (Chen et  al. 2019). Other factors may play a role as well. When Li et  al. (2017) separated lambs into low-risk (most cellulolytic bacteria) and high-risk (least cellulolytic bacteria) subacute lactic acidosis groups, they detected distinct rumen populations in the two groups, where the high-risk lambs exhibited lower ratios of ruminal pH and acetate to propionate, lower concentrations of acetate, and higher concentrations of lactate and propionate. It remains to be determined whether host selection of rumen microbial populations plays a role in susceptibility to lactic acidosis and whether specific genetic lineages of cattle or other ruminants correlates with this susceptibility. Development in high-throughput phenotyping and the ability to examine large data sets in livestock, as proposed by Koltes et al. (2019), may help answer this question when such data sets are compared with rumen microbiome, metagenomics, and metabolomic data.

1.6 Upsetting the Balance: Feed Withdrawal and Intestinal Microbiota Other dietary stress factors can be disruptive to the gastrointestinal tract. A fairly acute stress that can be experienced by an animal’s gastrointestinal tract is the removal of feed. Historically, one of the more dramatic management strategies for feed removal was the use of several days of complete feed withdrawal to induce a period of molting that effectively shuts down egg production and allows the laying

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hen to undergo reproductive rest and restoration (Park et al. 2004). However, while effective for molt induction, the removal of the layer diet for an extended period proved to be disruptive to the hen’s digestive tract and was discontinued by the layer industry (Ricke 2003, 2017). Durant et al. (1999) demonstrated that the removal of feed reduced lactobacilli in crops, resulting in a decrease in lactate production and an increase in pH. This effectively removed the microbial barrier that would have limited Salmonella Enteritidis establishment in the gastrointestinal tract and consequently led to infection in the reproductive tract and other organs. Further studies based on denatured gradient gel electrophoresis have revealed shifts in cecal and fecal populations as well as the cecal fermentation profiles of hens undergoing feedwithdrawal-induced molt compared to fully fed birds (Dunkley et al. 2007b). When S. enteritidis was introduced to these birds, regulatory virulence gene hilA was upregulated, and increased infection occurred (Dunkley et al. 2007a). Other farm animals do undergo feed withdrawal as a part of production practices, but for much shorter periods. In broiler production, birds are subjected to feed withdrawal for only a few hours prior to transport and delivery to the processing plant but can still experience increases in Salmonella establishment as well as microbiological changes in the gastrointestinal tract (Moran Jr. and Bilgili 1990; Corrier et al. 1999; Hinton et al. 2000a, b; Byrd et al. 2001). In beef cattle, feed removal, referred to as lairage, serves as a potential preventive method for reducing stress in animals before preslaughter by allowing animals to rest in holding pens at the plant before slaughter for a particular amount of time (Edwards-­Callaway and CalvoLorenzo 2020). When Welch et al. (2021) investigated the rumen after fasting during the preslaughter process, they detected changes in the rumen microbiota after fasting Angus steers for 24 h prior to slaughter. Matthews et al. (2019) showed that withholding food from cattle for 24 h reduced substrates for anaerobes, resulting in a decrease in rumen volatile fatty acid concentrations and an increase in rumen pH level. The lack of feed also significantly reduced rumen microbial diversity (Matthews et al. 2019). Even with the shorter feed withdrawal times in broilers and cattle, there appears to be sufficient disruption in the indigenous gastrointestinal microbiota to be detectable with microbiome sequencing. Whether this also lowers the barrier for foodborne pathogens to be competitive in what would otherwise be considered hostile environments in fully fed animals as occurs in poultry remains to be determined.

1.7 Development of Intestinal Microbiota in the Early Life of the Host The initial establishment of gastrointestinal bacteria in the host is influenced by multiple factors, and interaction with the host is a critical component. Thus, the picture that is emerging is that the sterile intestine is rapidly colonized by a succession of bacterial species and then slowly approaches its climax population with

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increasing numbers of and an increasing diversity of bacteria. The composition of this early microbiota has implications not only on the programming of the climax microbiota but also on the development of the intestinal epithelium, immune system, and brain, and this early developmental programming influences how these systems respond to stress and disease in adulthood. The data also suggest that although there are unique individual differences in microbial composition, the developmental and climax microbial populations may be manipulated to enhance animal wellbeing and resistance to stress and disease. The intestinal microbiota secrete signals that affect the epithelium, mucosal immune system and brain. In turn, the epithelium, mucosal immune system and brain influence the composition of the intestinal microbiota. The interactions between these systems during development and homeostasis dictate how these systems respond to stressors and infection (Fig. 1.1). More-recent data suggest that the early microbial colonizers influence the development of subsequent microbial populations, host development, and the host’s functions. There is increasing interest in the use of probiotics, prebiotics, and other dietary additions to improve animal health and wellbeing for food animals such as poultry (Rubio 2019). Although the efficacy of these dietary additions is variable, it

Fig. 1.1  Beneficial and pathogenic microorganisms secrete signal molecules for the molecule secretion and cytoskeleton rearrangement of epithelial cells; epithelial cells signal both luminal bacteria and mucosal immune cells, which in turn can signal the HPA axis; signals from the HPA axis also influence mucosal immune cells and epithelial cell function and can influence the microbiota in the lumen of the intestinal tract; red rectangles represent pathogenic bacteria, and other colored shapes represent the diversity of nonpathogenic bacteria with negative, neutral, or beneficial properties

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may be important to address offering these dietary additions shortly after birth (Bezirtzoglou and Stavropoulou 2011; Nava et al. 2005). There is evidence of this with the introduction of probiotic cultures to young chicks to prevent pathogen colonization. For example, when combinations of poultry microbiota were fed to young chicks as competitive exclusion cultures of Salmonella, Drolesky et  al. (1995) used scanning electron microscopy to demonstrate increased colonization within and between the crypts of the cecal mucosal epithelium in young chicks receiving the probiotic cocktail versus nonrecipients. They also observed increases in cecal volatile fatty acid concentrations and resistance to Salmonella colonization in the competitive exclusion cultures that were in parallel with a visual increase in cecal mucosal colonization. This type of impact on the early development of the gastrointestinal microbiota likely occurs with multiple feed additives. The introduction of microbiome sequencing and metabolomics should offer more-­comprehensive assessments to delineate more-subtle changes in the gastrointestinal microbiota as they develop in the presence of a particular feed additive and lead to subsequent influences on the host. Poultry offers an example of the opportunities to influence the early development of the gastrointestinal microbiota (Rubio 2019). Historically, in ovo vaccination for certain avian diseases was explored as a potential route for the delivery of certain vaccines to large numbers of birds (Peebles 2018). The ability to optimize the injection site and timing during incubation led to the automation and commercialization of in ovo administration as a practical approach to vaccinate large numbers of birds (Gildersleeve et al. 1993; Uni and Ferket 2003; Roto et al. 2016). As this approach developed, the concept of the in ovo introduction of different immunostimulants, hormones, live beneficial bacteria, prebiotics, and synbiotics received considerable attention (Kadam et al. 2013; Roto et al. 2016; Peebles 2018). Feeding certain nutrients such as vitamins, amino acids, peptides, and carbohydrates, among others, via an in ovo route has demonstrated that embryo development and posthatch performance could be improved (Kadam et al. 2013; Peebles 2018). There is evidence that the incubating egg can be exposed to bacterial contamination relatively early during incubation. Obviously, pathogens such as Salmonella Enteritidis can gain entry from an infected hen through transovarian transfer into the developing egg prior to laying, but eggs are exposed to other bacterial contaminants from the hen as well as the environment (Gantois et al. 2009; Ricke 2017; Gast et al. 2022; Ricke et al. 2022). Because early colonization may occur in the prehatch egg embryo, administering probiotics in ovo to serve as competitive exclusion cultures becomes intuitive (Roto et  al. 2016). In ovo application of probiotics has been extensively explored, where some probiotics have greater effects than others (Pender et al. 2017; Baldwin et al. 2018; Peebles 2018). Likewise, prebiotics administered in ovo might be expected to influence the development of the gastrointestinal tract of the hatching chick and further development as the bird matures posthatch (Roto et al. 2016). As more becomes understood on embryo development and the reproductive and intestinal tissues with the application of proteomics and transcriptomics, the interaction of the immune system, other host tissues, and exposure to intestinal bacteria can be further characterized (Rodrigues et al. 2020a, b; Overbey et al. 2021).

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1.8 Conclusions The understanding of the gastrointestinal tract in food animals has advanced tremendously in the past few decades with the introduction of genomic sequencing, metabolomics, proteomics, transcriptomics, and other technologies. Collectively, this array of omic methods offers an opportunity to develop a systemic appraisal of not only the gastrointestinal microbiota but also its interaction with the host animal. The ability to align metabolic functionality with the compositional profiles of gastrointestinal microbial communities can begin to provide the basis for developing more-effective modulation approaches by identifying specific microbiome targets. This may not always require microbial taxonomical shifts. According to, first, pure culture studies and, more recently, metabolic analyses of gastrointestinal communities, many of the individual members, in addition to the ability to use multiple substrates from incoming dietary materials, also possess more than one fermentation pathway, which can fluctuate depending on factors such as substrate availability. A further complexity is the level of metabolic crosstalk that occurs among members of the gastrointestinal community. In the future, the further development of metabolic flux analyses on gastrointestinal microbial ecosystems may be an important consideration for targeting modulation strategies. The ability to generate data with the multiple analytics tools that are now available for routine use has incredible potential for conducting true systematic assessments of gastrointestinal ecosystems. However, this introduces not only an overwhelming quantity of data but also complexities that have not necessarily been foreseen. Therefore, data analytics tools that can handle these large sets of data are now becoming critical research components. The field of bioinformatics has rapidly expanded and offers sophisticated computer programs and data processing pipelines that can synthesize data sets and corresponding analyses into biologically meaningful outputs for interpretation. This will be critical for efforts that aim to combine the interaction of the gastrointestinal microbiota with the array of host responses at the interface of the gastrointestinal host tissue with the respective microbial inhabitants. This includes immune responses, competition for nutrients, the host processing of microbial metabolites, and end products. This becomes even more complicated when host responses beyond the gastrointestinal system, such as the neural system, are considered. Finally, host neonatal development and gastrointestinal tract microbial impact on host programming offer new complexities to explore in the search for potential modulation strategies. In summary, the definition of a commensal gastrointestinal microorganism may still be associated with beneficial activities to the host, but the depth and the breadth of what would be considered “beneficial” may be evolving as more is understood.

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Brede M, Orton T, Pinior B, Roch F-F, Dzieciol M, Zwirzitz B, Wagner M, Breves G, Wetzels SU (2020) PacBio and Illumina MiSeq amplicon sequencing confirm full recovery of the bacterial community after subacute ruminal acidosis challenge in the RUSITEC system. Front Microbiol 11:1813. https://doi.org/10.3389/fmicb.2020.01813 Buffie CG, Pamer EG (2014) Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol 13:790–801. https://doi.org/10.1038/nri3535 Byrd JA, Hargis BM, Caldwell DJ, Bailey RH, Herron KL, McReynolds JL, Brewer RL, Anderson RC, Bischoff KM, Callaway TR, Kubena LF (2001) Effect of lactic acid administration in the drinking water during preslaughter feed withdrawal on Salmonella and Campylobacter contamination of broilers. Poult Sci 80:278–283 Chen J, Weimer PJ (2001) Competition among three predominant ruminal cellulolytic bacteria in the absence or presence of non-cellulolytic bacteria. Microbiology 147:21–30 Chen L, Shen Y, Wang C, Ding L, Zhao F, Wang M, Fu J, Wang H (2019) Megasphaera elsdenii lactate degradation pattern shifts in rumen acidosis models. Front Microbiol 10:162. https:// doi.org/10.3389/fmicb.2019.00162 Chou S, Zhang S, Guo H, Chang Y-F, Zhao W, Mou X (2022) Targeted antimicrobial agents as potential tools for modulating the gut microbiome. Front Microbiol 13:879207. https://doi. org/10.3389/fmicb.2022.879207 Claesson MJ, Cusack S, O’sullivan O, Green-Diniz R, de Weerd H, Flannery E, Marchesi JR, Falushy D, Dinan T, Fitzgerald G, Stanton C, van Sinderen D, O’Conner M, Harnedy N, O’Conner K, Henry C, O’Mahony D, Fitzgerald AP, Shanahan F, Twomey C, Hill C, Ross RP, O’Toole PW (2011) Composition, variability, and temporal stability of the intestinal microbiota of the elderly. PNAS 108:4586–4591 Corrier DE, Byrd JA, Hargis BM, Hume ME, Bailey RH, Stanker LH (1999) Presence of Salmonella in the crop and ceca of broiler chickens before and after preslaughter feed withdrawal. Poult Sci 78:45–49 Dittoe DK, Ricke SC, Kiess AS (2018) Organic acids and potential for modifying the avian gastrointestinal tract and reducing pathogens and disease. Front Vet Sci 5:216. https://doi. org/10.3389/fvets.2018.00216 Dominguez-Bello MG, Blaser MJ, Ley RE, Knight R (2011) Development of the human gastrointestinal microbiota and insights from high-throughput sequencing. Gastroenterology 140:1713–1719 Drolesky RE, Corrier DE, Nisbet DJ, DeLoach JR (1995) Colonization of cecal mucosal epithelium in chicks treated with a continuous flow culture of 29 characterized bacteria: confirmation by scanning electron microscopy. J Food Prot 58:837·842 Dunkley KD, McReynolds JL, Hume ME, Dunkley CS, Callaway TR, Kubena LF, Nisbet DJ, Ricke SC (2007a) Molting in Salmonella Enteritidis challenged laying hens fed alfalfa crumbles I. Salmonella Enteritidis colonization and virulence gene hilA response. Poult Sci 86:1633–1639 Dunkley KD, McReynolds JL, Hume ME, Dunkley CS, Callaway TR, Kubena LF, Nisbet DJ, Ricke SC (2007b) Molting in Salmonella Enteritidis challenged laying hens fed alfalfa crumbles II. Fermentation and microbial ecology response. Poult Sci 86:2101–2109 Durant JA, Corrier DE, Byrd JA, Stanker LH, Ricke SC (1999) Feed deprivation affects crop environment and modulates Salmonella enteritidis colonization and invasion of Leghorn hens. Appl Environ Microbiol 65:1919–1923 Edwards-Callaway LN, Calvo-Lorenzo MS (2020) Animal welfare in the U.S. slaughter industry—a focus on fed cattle. J Anim Sci 98:1–21. https://doi.org/10.1093/jas/skaa040 Freestone PPE, Sandrini SM, Haigh RD, Lyte M (2008) Microbial endocrinology: how stress influences susceptibility to infection. Trends Microbiol 16:55–64 Gantois I, Ducatelle R, Pasmans F, Haesebrouck F, Gast R, Humphrey TJ, Van Immerseel F (2009) Mechanisms of egg contamination by Salmonella Enteritidis. FEMS Microbiol Rev 33:718–738. https://doi.org/10.1111/j.1574-­6976.2008.00161.x

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Gast RK, Dittoe DK, Ricke SC (2022) Salmonella in eggs and egg-laying chickens: pathways to effective control. Crit Rev Microbiol. https://doi.org/10.1080/1040841X.2022.2156772 Gildersleeve RP, Hoyle M, Miles AM, Murray DL, Ricks A, Secrest MN, Williams CJ, Womack CL (1993) Developmental performance of an administration of Marek’s disease egg injection machine for vaccine. J Appl Poult Res 2:337–346 Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, Samuel BS, Gordon JI, Relman DA, Fraser-Liggett CM, Nelson KE (2006) Metagenomic analysis of the human distal gut microbiome. Science 312:1355–1359 Heijtz RD, Wang S, Anuar F, Qian Y, Björkholm B, Samuelsson A, Hibberd ML, Forssberg H, Pettersson S (2011) Normal gut microbiota modulates brain development and behavior. PNAS 108:3047–3052 Hernández J, Benedito JL, Abuelo A, Castillo C (2014) Ruminal acidosis in feedlot: from aetiology to prevention. Sci World J 2014:702572. https://doi.org/10.1155/2014/702572 Herrera P, Kwon YM, Maciorowski KG, Ricke SC (2009) Ecology and pathogenicity of gastrointestinal Streptococcus bovis. Anaerobe 15:44–54. https://doi.org/10.1016/j.anaerobe.2008.11.003 Hinton A, Buhr RJ, Ingram KD (2000a) Physical, chemical, and microbiological changes in the ceca of broiler chickens subjected to incremental feed withdrawal. Poult Sci 79:483–488 Hinton A, Buhr RJ, Ingram KD (2000b) Physical, chemical, and microbiological changes in the crop of broiler chickens subjected to incremental feed withdrawal. Poult Sci 79:212–218 Hooper LV, Xu J, Falk PG, Midtvedt T, Gordon JI (1999) A molecular sensor that allows a gut commensal to control its nutrient foundation in a competitive ecosystem. PNAS 96:9833–9838 Horner-Devine MC, Carney KM, Bohannan BJM (2004) An ecological perspective on bacterial biodiversity. Proc R Soc Lond B 271:113–122 Huang LT (2011) The link between perinatal glucocorticoids exposure and psychiatric disorders. Pediatr Res 69(5 Pt 2):19R–25R Hungate RE, Dougherty RW, Bryant MP, Cello RM (1952) Microbiological and physiological changes associated with acute indigestion in sheep. Cornell Vet 42:423–449 Inman CF, Haverson K, Konstantinov SR, Jones PH, Harris C, Smidt H, Miller B, Bailey M, Stokes C (2010) Rearing environment affects development of the immune system in neonates. Clin Exp Immunol 160:431–439 Jarvis GN, Kurtovic A, Hay AG, Russell JB (2001) The physiological and genetic diversity of bovine Streptococcus bovis strains. FEMS Microbiol Ecol 35:49–56 Jensen BB, Jorgensen H (1994) Effect of dietary fiber on microbial activity and microbial gas production in various regions of the gastrointestinal tract of pigs. Appl Environ Microbiol 60:1897–1904 Jernberg C, Löfmark S, Edlund C, Jansson JK (2010) Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology 156:3216–3223. https://doi.org/10.1099/ mic.0.040618-­0 Kadam MM, Barekatain MR, Bhanjac SK, Iji PA (2013) Prospects of in ovo feeding and nutrient supplementation for poultry: the science and commercial applications – a review. J Sci Food Agric 93:3654–3661. https://doi.org/10.1002/jsfa.6301 Koenig JE, Spor A, Scalfone N, Fricker AD, Stombaugh S, Knight R, Angenet LT, Lay RE (2011) Succession of microbial consortia in the developing infant gut microbiome. PNAS 108:4578–4585 Koltes JE, Col JB, Clemmens R, Dilger RN, Kramer LM, Lunney JK, McCue ME, McKay SD, Mateescu RG, Murdoch BM, Reuter R, Rexroad CE, Rosa GJM, Serão NVL, White SN, Woodward-Greene MJ, Worku M, Zhang H, Reecy JM (2019) A vision for development and utilization of high-throughput phenotyping and big data analytics in livestock. Front Genet 10:1197. https://doi.org/10.3389/fgene.2019.01197 Kotarski SF, Waniska RD, Thurn KK (1992) Starch hydrolysis by the ruminal microflora. J Nutr 122:178–190 Leach L, Mann GE (2011) Consequences of fetal programming for cardiovascular disease in adulthood. Microcirculation 18(4):253–255

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Ricke SC (2003) The gastrointestinal tract ecology of Salmonella Enteritidis colonization in molting hens. Poult Sci 82:1003–1007 Ricke SC (2017) Insights and challenges of Salmonella infections in laying hens. Curr Opin Food Sci 18:43–49. https://doi.org/10.1016/j.cofs.2017.10.012 Ricke SC, Martin SA, Nisbet DJ (1996) Ecology, metabolism, and genetics of ruminal selenomonads. Crit Rev Microbiol 22:27–65 Ricke SC, Richardson K, Dittoe DK (2019) Formaldehydes in feeds and interaction with the poultry gastrointestinal tract microbial community. Front Vet Sci 6:188. https://doi.org/10.3389/ fvets.2019.00188 Ricke SC, Dittoe DK, Richardson KE (2020) Formic acid as an antimicrobial for poultry production: a review. Front Vet Sci 7:563. https://doi.org/10.3389/fvets.2020.00563 Ricke SC, Dittoe DK, Olson EG (2022) Microbiome applications for laying hen performance and egg production. Poult Sci 101:101784. https://doi.org/10.1016/j.psj.2022.101784 Rodrigues DR, Wilson KM, Trombetta M, Briggs WN, Duff AF, Chasser KM, Bottje WG, Bielke L (2020a) A proteomic view of the cross-talk between early intestinal microbiota and poultry immune system. Front Physiol 11:20. https://doi.org/10.3389/fphys.2020.00020 Rodrigues DR, Winson E, Wilson KM, Briggs WN, Duff AF, Chasser KM, Bielke LR (2020b) Intestinal pioneer colonizers as drivers of ileal microbial composition and diversity of broiler chickens. Front Microbiol 10:2858. https://doi.org/10.3389/fmicb.2019.02858 Roto SM, Kwon YM, Ricke SC (2016) Applications of in ovo technique for the optimal development of the gastrointestinal tract and the potential influence on the establishment of its microbiome in poultry. Front Vet Sci 3:63. https://doi.org/10.3389/fvets.2016.00063 Rubio LA (2019) Possibilities of early life programming in broiler chickens via intestinal microbiota modulation. Poult Sci 98:695–706. https://doi.org/10.3382/ps/pey416 Russell JB (1984) Factors influencing competition and composition of the rumen bacterial flora. In: Gilchrist FMC, Mackie RI (eds) Herbivore nutrition in the subtropics and tropics. The Science Press (PTY) Ltd, Criaghall Russell JB, Hino T (1985) Regulation of lactate production in Streptococcus bovis: a spiraling effect that coontributes to rumen acidosis. J Dairy Sci 68:1712–1721 Russell JB, Robinson PH (1984) Compositions and characteristics of strains of Streptococcus bovis. J Dairy Sci 67:1525–1531 Sjögren YM, Tomicic S, Lundberg A, Böttcher MF, Björkstén B, Sverremark-Ekström E, Jenmalm MC (2009) Infulence of early gut microbiota on the maturation of childhood mucosal and systemic immune responses. Clin Exp Allergy 39:1842–1851 Slyter LL (1976) Influence of acidosis on rumen functuon. J Anim Sci 43:910–919 Spor A, Koren O, Ley RE (2011) Unravelling the effects of the environment and host genotype on the gut microbiome. Nat Rev Microbiol 9:279–290 Tanaka S, Kobayashi T, Songjinda P, Taeyama A, Tsucouchi M, Kiyohara C, Shirakawa T, Sonomoto K, Nakayama J (2009) Influence of antibiotic exposure in the early postnatal period on the development of intestinal microbiota. FEMS Immunol Med Microbiol 56:80–87 Tapiainen T, Ylitalo S, Eerola E, Uhari M (2006) Dynamics of gut colonization and sources of intestinal flora in healthy newborn infants. APMIS 114:812–817 Tarry-Adkins JL, Ozanne SE (2011) Mechanisms of early life programming: current knowledge and future directions. Am J Clin Nutr 94(suppl):1765S–1771S Tillman D (2004) Niche tradeoffs, neutrality, and community structure: a stochastic theory of resource competition, invasion, and community assembly. PNAS 101:10854–10861 Tlaskalová-Hogenová H, Štepánková R, Hudcovic T, Tucková L, Cukrowska B, Lodinová-­ Žádníková R, Kozáková H, Rossmann P, Bártová J, Sokol D, Funda DP, Borovská D, Reháková Z, Šinkora J, Hofman J, Drastich P, Kokešová A (2004) Commensal bacteria (normal microflora), mucosal immunity and chronic inflammatory and autoimmune diseases. Immunol Lett 93:97–108. https://doi.org/10.1016/j.imlet.2004.02.005 Uni Z, Ferket PR (2003) Enhancement of development of oviparous species by in ovo feeding. United States patent US 6592878 B2 (2003)

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Chapter 2

The Poultry Gastrointestinal Tract: An Overview of Microbial Ecology Steven C. Ricke, L. A. Wythe, and A. Scheaffer

Abstract  The poultry gastrointestinal tract is a complex organ that harbors a wide array of microorganisms. The poultry gastrointestinal tract comprises several compartments, including the crop, gizzard, proventriculus, small intestine, colon, and paired ceca. Each of these compartments differs to varying extents in physiological function and their respective roles in the digestion of diets. Not surprisingly, they also differ in the microbial communities that they harbor. With the introduction of 16S rDNA microbiome sequencing, the ability to identify and characterize individual members of the respective gastrointestinal microbial populations has markedly increased. The response of these microbial consortia to the expansive level of nutrients potentially available from complex diets fed to broilers and layers can be elucidated by identifying not only which indigenous microorganisms are involved but also their functional role in hydrolysis, fermentation, and interactions with other members of the microbial community. In addition, factors such as their interaction with the immune system are now becoming more apparent. This review covers the poultry gastrointestinal tract and includes a discussion on the activities and functions of the resident microbial populations.

2.1 Introduction Historically, the poultry gastrointestinal tract microbiota have been more of an indirect consideration for research efforts. Most of the interest has derived from attempting to identify undefined growth factors or determining the ability of the bird to

S. C. Ricke (*) · L. A. Wythe Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, USA e-mail: [email protected] A. Scheaffer SweetPro, Walhalla, ND, USA © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_2

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digest certain diets, such as high-fiber supplements (Coates et  al. 1968; Barnes 1979; Ricke et al. 2013). More recently, the introduction of feed additives such as probiotics and prebiotics to control foodborne pathogen colonization has led to a more comprehensive understanding of the gastrointestinal tract microbial population and their interactions with pathogens attempting to colonize the gastrointestinal tract (Clavijo and Flórez 2018). Much of this occurred as a result of the several decades of searching for probiotic strategies to control pathogens such as Salmonella and Campylobacter in both broilers and laying hens (Clavijo and Flórez 2018; Deng et al. 2020; Gast et al. 2022; Jeni et al. 2021a, b; Ricke 2017). In addition, the contribution of the indigenous gastrointestinal microbiota to overall gastrointestinal tract and bird health has become more apparent in both conventional and alternative poultry production systems (Rinttilä and Apajalahti 2013; Shi et al. 2019; Jeni et al. 2021a, b). Much of what is known about the poultry gastrointestinal tract has been derived from the microbial culture techniques available for isolation and further phenotypic characterization. The introduction of microbial culturing techniques adapted from rumen microbiology research developments enabled the cultivation of strict anaerobic bacteria, which led to the realization that anaerobic metabolism and fermentation were integral components of poultry gastrointestinal microbial ecology (Ricke and Pillai 1999; Ricke 2015). For example, organisms such as methanogens were identified as being present in the ceca of mature laying hens, and both organisms and methane production could be detected in young broilers (Saengkerdsub et al. 2006, 2007a, b). The presence of methanogens in the poultry ceca supports the concept that the establishment of an anaerobic environment in the chicken ceca occurs relatively early in the development of the gastrointestinal tract microbial community and likely affects the overall fermentation pathways and end products generated. The introduction of molecular techniques such as polymerase chain reaction assays has improved the ability to identify and quantify individual members of the poultry gastrointestinal microbial community. Most of this has evolved to track foodborne pathogens such as Salmonella and Campylobacter during and after establishment in the poultry gastrointestinal tract and to evaluate the effectiveness of intervention measures to limit pathogen establishment (Ricke et al. 2018, 2019). However, advances in sequencing technologies that allow for a more comprehensive characterization of entire microbial communities in food and animal samples have emerged (Ricke et al. 2017; Weinroth et al. 2022). Consequently, 16S rDNA microbiome and metagenomic analyses are now being used to characterize complex gastrointestinal microbial populations and metabolic functions in a wide range of animals, including poultry (Sergeant et al. 2014; Shi et al. 2019; Ricke and Rothrock Jr 2020; Weinroth et al. 2022). This review discusses the complexity of the poultry gastrointestinal tract (GIT) on the basis of some of the ongoing developments in microbiome characterization and how these GIT microbial consortia interface with the poultry host.

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2.2 The Poultry Gastrointestinal Tract: Anatomy and Physiology Avian gastrointestinal tract anatomy and physiology have been thoroughly reviewed in previous publications (Clench and Mathias 1995; Svihus 2011; Svihus et  al. 2013; Rodrigues and Choct 2018; Proszkowiec-Weglarz 2022). However, an understanding of gastrointestinal tract function and development is essential when discussing the corresponding microbial ecology of the various gastrointestinal compartments. Thus, the following presents a brief overview of gastrointestinal tract anatomy and physiology. The chicken GIT begins with the esophagus, where feed moves from the crop down through the proventriculus and gizzard for mechanical and chemical digestion and through the small intestines for further digestion and nutrient absorption and fermentation; digesta then exits through the lower colon and cloaca (Proszkowiec-Weglarz 2022). Because digesta is composed of solid, liquid, and semisoluble phases, these physical phases are not always moving in concert through the gastrointestinal tract, so various markers for quantifying the multiple phases have been developed for tracking in the gastrointestinal compartments (Svihus and Itani 2019; Rodrigues and Choct 2018). Peristaltic movement from the esophagus occurs rapidly prior to reaching the crop, but these movements are more regular in the distal esophageal region, as controlled by the fill in the gizzard (Turk 1982). The movement of a bolus into the crop is also further controlled by the fill in the gizzard. The esophagus and crop are essentially tubular organs, each with a mucosal layer consisting of an epithelial lining and smooth muscle and each with a circular and longitudinal muscle layer (Turk 1982; Proszkowiec-Weglarz 2022). Limited host digestion occurs within the crop; however, some carbohydrate digestion can occur through the production of amylase and thanks to bacterial fermentation (Turk 1982). Each of these depends on storage time: It has been shown that birds fed intermittently as opposed to ad libitum will increase the size and involvement of their crops (Svihus et al. 2010; Sacranie et al. 2017; Kristoffersen et al. 2021). The chicken stomach consists of two organs, namely the proventriculus and the gizzard, which perform separate but related functions in digestion. The proventriculus has a mucosal membrane with papillae projecting into the lumen; these papillae contain the opening of glands that secrete gastric juices containing hydrochloric acid and pepsin (Selander 1963; Turk 1982). After the bolus has been coated in these digestive juices, the material is forced into the gizzard. The gizzard has several distinct muscular regions, including a thin, longitudinal muscle and a thick, circular portion (Proszkowiec-Weglarz 2022; Turk 1982). The interior of the circular muscle contains a submucosa and a glandular mucosa, whose glands contain cells that secrete a thick cuticle that protects the internal lining from damage from digestive juices and during grinding (Turk 1982). The holding time in the proventriculus is estimated to be shorter than that in the gizzard. But because of the previously described converging peristaltic and antiperistaltic movements between the two organs, contributions to overall digestive activity are viewed as a combined effort

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coming from both organs (Svihus 2011; Proszkowiec-Weglarz 2022; Rodrigues and Choct 2018). Thus, while the proventriculus is the source of digestive enzymes, both mechanical and chemical breakdowns of ingested matter have been reported to occur in the gizzard (Svihus 2011). Once broken down, the bolus enters the small intestines, where nutrient absorption is initiated. The intestine consists of a serosal layer, a longitudinal and circular muscle layer, and a mucosal and submucosal layer. The duodenum is typically designated as the portion that loops around the pancreas, followed by the jejunum, which ends at the Meckel’s diverticulum, and finally the ileum, extending to the junction of the ceca and the colon (Turk 1982; Rodehutscord et al. 2012). The small intestine epithelium contains nutrient transporters, digestive enzymes, and hormones and contains limiting pathogens via the production of glycoproteins and defensins (Zhang et  al. 2019). Ducts from the liver, gall bladder, and pancreas release digestive enzymes to aid in the catabolism of nutrients that then pass through the lining. The villi within the small intestines decrease in thickness and then become shorter from the duodenum to the ileal-cecal junction (Turk 1982). The small intestine also plays a pivotal role in maintaining GIT health and function for chickens, including preventing the growth of harmful pathogens via a microbial and chemical barrier within the mucosal lining (Shang et al. 2018; Zhang et al. 2019). This mucosal layer within the small intestines is derived from goblet cell secretions and contains two layers: an outer layer providing a habitat for commensal bacteria and a sterile, inner layer formed from the expression of antimicrobial peptide β-defensin, immunoglobulin A, etc. (Turk 1982; Forder et  al. 2007; Hong et  al. 2012; Zhang et al. 2019). The total passage time of chicken digestion has been quantified at 3–4  hours, where passage rate marker compounds first appeared in excreta 1.6–2.6 hours after ingestion (Svihus and Itani 2019; Proszkowiec-Weglarz 2022). However, the aforementioned method more accurately describes the minimum passage rate, and this may not accurately describe the relationship between digesta passage and retention, leading to the suggestion that mean retention may be a better description of the rate of passage (Svihus and Itani 2019). Mean retention time is calculated by supplementing the diet with a marker for a limited time following a short feed withdrawal period, then collecting excreta in specific time intervals, and finally analyzing both the feed intake and the excreta for marker content (Svihus and Itani 2019). In turn, this method measures total tract retention time by quantifying the marker, and the mean retention time can be calculated (Svihus and Itani 2019). The mean retention time for poultry has been quantified as occurring between 5 and 9 hours, depending on the age of the bird, the nature of the ingesta, and the particle size (Proszkowiec-­ Weglarz 2022; Svihus and Itani 2019). Furthermore, the overall passage rate has been reported to be influenced by the genetics of the bird and has been attributed to potential changes in the proventriculus and the gizzard when comparing high- and low-digestion-efficiency genetic lines (Rougière and Carré 2010; Proszkowiec-­ Weglarz 2022). Residence times for digesta in the crop are 10–50  minutes, and 30–90  minutes are spent between the proventriculus and the gizzard (Ravindran

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2013). However, this time varied depending on management practices such as light regime, feed structure, and feeding frequency (Rodrigues and Choct 2018). A confounding aspect of understanding the dynamics of digesta residence time is antiperistaltic movement and the impact that it has on the passage rate of feed particles. Antiperistaltic movements transport digesta contrary to typical passage. It is known to occur in three main regions of the gastrointestinal tract: (1) the aforementioned grinding action of the gizzard forces particles back into the proventriculus, thus increasing their exposure to proventricular enzymes; (2) it moves from the small intestines back into the gastric region; and (3) the low-amplitude contractions of the intestinal lining force it from the large intestines and the cloaca to the ceca (Duke et al. 1972; Jimenez et al. 1994; Sacranie et al. 2009; Rodrigues and Choct 2018). The purpose of this reverse movement has been suggested to induce gizzard contractions to prolong the bolus’s exposure to enzymatic and mechanical digestion and continue the nutrient absorption of digesta to thus establish satiety in fasted birds (Rodrigues and Choct 2018). However, reflux may be harmful, depending on the bird’s general health, as the forcing of cecal contents back into the small intestine could have negative consequences in immunocompromised birds (Rodrigues and Choct 2018). For instance, commensal microorganisms residing in the hindgut could be introduced to more-antral regions of the gastrointestinal tract and become opportunistic pathogens, which can inhibit growth or lead to mortality (Sacranie et al. 2005; Rodrigues and Choct 2018). The remaining digesta subsequently passes through the ileocecal junction into the ceca, or it passes the junction to the colon to be excreted. The ceca are filled thanks to the converging peristaltic and antiperistaltic waves, filling only with fluid or very small particles, which is due to the morphology of the ileocecal junction (Proszkowiec-Weglarz 2022). The ceca are formed into three distinct areas, where the opening junction has a thicker muscular and mucosal layer with broad villi, likely to aid in the movement of digesta into the sacs (Turk 1982). These layers become thinner in the middle area of the ceca, and the epithelial lining becomes smooth at the apical area (Turk 1982). The ceca have the longest holding time of the intestinal tract, consisting of approximately 12 hours, but can remain for at least 48 hours (Turk 1982; Svihus et al. 2013; Svihus and Itani 2019). This varies from previously reported passage rates and mean retention times, and Liu et al. (2017) reported that markers took 4 hours before appearing ceca, suggesting that passage through the gastrointestinal tract is not necessarily influenced by cecal retention (Svihus and Itani 2019). Nonetheless, thanks to this longer holding time, the ceca have been shown to play roles in the microbial fermentation of carbohydrates; vitamin synthesis; water absorption; and cholesterol and nitrogen digestion and absorption (Jørgensen et al. 1996; Jamroz et al. 2002; McNab 1973; Coates et al. 1968; Tortuero et al. 1975; Goldstein 1989). The contents of the ceca are easily distinguishable from the contents of rectal feces, thanks to the increased viscosity of the solubilized particles that have been fermented (Proszkowiec-Weglarz 2022).

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2.3 Poultry Gastrointestinal Microbiota Poultry physiology and metabolism are highly influenced by bidirectional interactions with the associated microbiome as the bird matures (Stanley et  al. 2014; Swaggerty et al. 2019; Rychlik 2020; Dittoe et al. 2022). Although their life spans are considerably longer than that of broilers, this relationship between the microbiome and laying hen physiology are also interactive (Ricke et al. 2022). Furthermore, the microbiota are essential for a swathe of physiological processes, including nutrient acquisition, pathogen exclusion, and the development of the immune system (Shang et al. 2018; Swaggerty et al. 2019). Thus, detailed descriptions of the taxonomical ranges and the function of microorganisms inhabiting the poultry GIT, along with a description of the various methods of characterization, are necessary to better understand the relationship between the bird and its gastrointestinal microbiota (Rychlik 2020). As methodology has advanced, the development of protocols for sampling birds must be carefully considered to achieve an accurate representation of the poultry gastrointestinal ecosystem (Rychlik 2020; Weinroth et al. 2022). Likewise, advances in sequencing, the generation of large sets of data, and the application of bioinformatic analyses have led to refinements in the definition of what constitutes the microbiome (Berg et al. 2020). In general, the microbiome has been defined as the culmination of all microorganisms present and their genes, along with their functionality within the ecosystem (Ricke et  al. 2017; Rychlik 2020). Conversely, the gastrointestinal microbiota are considered the constituents comprising the GIT ecosystem community in broilers and laying hens (Rychlik 2020; Dittoe et al. 2022; Ricke et al. 2022).

2.4 Bacterial Ecology in the Poultry Gastrointestinal Tract The use of 16S rRNA gene sequencing has provided an opportunity to characterize the diversity and taxonomical distributions of the microbial populations throughout the poultry gastrointestinal tract in a more comprehensive fashion compared to the conventional culturing method. These bacterial populations perform specific metabolic functions that coincide with the region of the tract that they reside in; therefore, a description of the community members throughout the gastrointestinal tract is warranted. This is an important consideration because feed additives such as prebiotics may, depending on the structure (constituents/sugars, cross-linking, and branching), be uniquely metabolized in different poultry gastrointestinal tract compartments (Ricke 2018). Similarly, the resident gastrointestinal tract microbial populations in each of these gastrointestinal tract compartments may shift as the bird matures (Stanley et al. 2014; Rychlik 2020). In addition, when the compositional profiles of gastrointestinal tract microbiota appear relatively stable, metabolism can still be altered, depending on diets and other factors (Dittoe et al. 2022).

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It has been suggested that the different regions of the gastrointestinal tract could be considered separate ecosystems (van der Wielen et al. 2002; Stanley et al. 2014; Rychlik 2020). However, just as the various organs govern interconnected physiological functions, so too do the gastrointestinal tract microbiota that inhabit them (Stanley et al. 2014). Because of differences in age, sex, diet, genetics, feed components, housing, sampling, library preparation, and other factors, specifically defining the typical community profiles has proven difficult (Stanley et al. 2014). Other factors may play roles as well but remain even less known. For example, the contribution of the feed microbiome to the early development of the young chick gastrointestinal tract microbiota has not been elucidated but could be a contributor, depending on the feed type and the physical form, among other characteristics associated with feed processing—as suggested in a review by Olson et  al. (2022). Nonetheless, the gastrointestinal tract microbiota could certainly be impacted by the feed microbiota but also have other impacts in addition to this interaction. Overall, the dominant bacteria phyla reported in chickens include the Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes (Clavijo and Flórez 2018). However, Firmicutes are the predominant phylum in the crop, gizzard, small intestine, and cecum (Rehman et al. 2007; Qu et al. 2008; Danzeisen et al. 2011). Various Lactobacillus species have been shown to dominate the crop, proventriculus, and gizzard (van der Wielen et al. 2002; Rehman et al. 2007; Stanley et al. 2014; Rychlik 2020). Furthermore, these gastrointestinal tract sections have also been reported to harbor clostridia and lactobacilli (Feng et  al. 2010; Sekelja et  al. 2012). More recently, Adhikari and Kwon (2017) analyzed isolates on de Man, Rogosa, and Sharpe agar plates from the cecal and distal ileal lumen and mucosa samples and concluded that the respective Lactobacillus spp. were distinct, where each gastrointestinal tract section and location implying that functionality differences may be attributable to these distinct populations. Certainly, the presence of acid-tolerant taxa and taxa capable of fermentation is intuitive given the fermentation potential in the crop and the low pH in the proventriculus and the gizzard, as previously described. This is particularly reflected in the crop: Durant et  al. (1999) demonstrated that sustained feed withdrawal in mature laying hens reduced the lactobacilli populations, decreased lactate, and increased pH, leading to a crop environment that was less of a barrier to Salmonella Enteritidis colonization. Thanks to longer digesta residence times, microbial density and diversity are generally greatest in the cecum (Rehman et  al. 2007). Within the cecal pouches, bacteria exist at concentrations ranging from 1010 to 1011 cells/g of digesta (Qu et al. 2008; Danzeisen et al. 2011). Van der Wielen et al. (2002) described the microbiota composition development in the crop, duodenum, ileum, and cecum in broilers that occurred over 40 days. They concluded that early microbial compositional profiles became less similar as the birds matured, where all four sections were similar in the first 4 days of life and then differentiated by 7 days. By day 40, the crop and the duodenum shared little similarity to the cecum, while the ileum was similar to the duodenum and the ceca. Despite similarities and correlations, each gastrointestinal tract organ possessed its own microbiota compositional profile. Likewise, Lu et  al. (2003) reported similarities in the intestinal segments during the early days of development, but

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differentiation still occurred as the birds matured. Their group reported that Lactobacillus comprised over 68% of the microbiota constituents in the ileum, and different Lactobacillus species succeeded each other in dominating the microbiota as the birds matured. Culture-free insights into the cecal microbial profiles confirmed the dominant genera identified through extensive culturing methods but also identified taxa with limited similarities to culturable isolates (Barnes 1979; Mead 1989; Gong et  al. 2002; Zhu et al. 2002; Lu et al. 2003; Stanley et al. 2014). In turn, the aforementioned groups have reported various anaerobes within the Firmicutes phyla in relatively greater abundance, including Clostridiaceae, Bacteroidacea, Lactobacillus, and Proteobacteria, among others. The avian cecal microbiota are capable of at least partially hydrolyzing and fermenting feeds containing fibrous components such as beta-glucans, starch, nonstarch polysaccharides, and some of the more resistant fibers, depending on the avian species (Clench and Mathias 1995; Józefiak et al. 2004; Ricke 2018). In a series of in vitro and in vivo studies, it was shown that the layer hen cecal population was capable of fermenting and producing SCFA from a variety of high-fiber substrates, including alfalfa, soybean hull, beet pulp, wheat middlings, ground sorghum, and cottonseed meal (Dunkley et al. 2007a, b; Ricke et al. 2013). When cecal microbial populations were examined by using denatured gradient gel electrophoresis (DGGE), most of the substrates generated shifts in cecal microbiota when incubated anaerobically as cecal-inoculated cultures (Dunkley et al. 2007a). Ideally, analyzing shifts in GIT microbial populations over time by utilizing more-frequent sampling time points and greater bird numbers would be optimal to differentiate what could be relatively subtle changes. However, because invasive gastrointestinal tract sampling requiring the euthanasia of the birds is generally not practical during live production, the noninvasive collection of fecal samples has been used as a substitute. For example, the early work of Dunkley et al. (2007b) comparing laying hen cecal and fecal populations using DGGE noted that there were similar microbial populations and short chain fatty acid patterns especially in the later stages of the molting period and that fecal samples could be used to compare alfalfa-based molt diets with layers undergoing feed withdrawal. More recently, using direct 16S rRNA gene sequencing, Sekelja et al. (2012) concluded that the fecal microbiota comprised microbial populations originating from the gastrointestinal tract—where the small intestine, cecum, and colon contributed to clostridial phylogroups, whereas the lactobacilli phylogroup aligned with the crop and gizzard. On the basis of pyrosequencing, Stanley et al. (2015) concluded that while microbiota from fecal cloacal swabs were indicative of some shifts in cecal microbiota and were representative of the cecal microbial diversity, the cloacal swab microbiota were still quantitatively different from the cecal microbiome. Given the potential impact of feed additives on the development of the gastrointestinal tract microbiota, it will be important to devise standardized approaches for reconciling noninvasive sampling methods with shifts in gastrointestinal tract microbiota. This will require more direct comparisons between the different compartments of poultry

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gastrointestinal tract and fecal collections and involve not just microbiome characterization but also in-depth metabolomics to assess the functional comparisons.

2.5 Conclusions and Future Directions The introduction of advanced molecular technologies such as 16S rDNA microbiome sequencing and metagenomics has ushered in an era featuring a more in-depth understanding of complex microbial consortia and their respective ecosystems. This has also occurred with research directed toward understanding the poultry gastrointestinal ecosystem. This has led to an appreciation for the development of different poultry gastrointestinal populations not only as a function of the age of the bird as it matures but also the progressive differentiation of the respective microbial populations in the individual compartments of the poultry gastrointestinal tract. It remains to be determined how much influence these different microbial communities have on one another during the life span of the bird. In addition, further differences may occur in broilers compared with layer hens given their contrasting life spans. Breed differences within broilers and laying hens likely play more-prominent roles than has been initially realized. Obviously, a primary interest in gaining a better understanding of the poultry gastrointestinal tract is centered on efforts to modulate its composition and/or metabolic activities. Certainly, manipulating the poultry gastrointestinal tract to control the establishment of foodborne pathogens has been an important focus of research efforts. For example, much of the early work was based on applying specific probiotic cultures that could become established in the poultry gastrointestinal tract and serve as barriers either physically or through the generation of metabolites antagonistic to foodborne pathogens. More recently, it has become apparent that indigenous poultry gastrointestinal microorganisms are already present, which can potentially limit pathogen establishment. Consequently, the introduction of feed additives that favor their selection, such as prebiotics, have been examined as a means to create a gastrointestinal microbial ecology that is hostile to pathogens (Ricke 2018). Given the similarities between some probiotics and the indigenous poultry gastrointestinal microorganisms that are being supported by prebiotics, combining specific probiotics and prebiotics, referred to as synbiotics, has emerged as a strategy to potentially ensure a more consistent response. Molecular sequencing has also offered the opportunity to identify probiotic candidates from the indigenous poultry gastrointestinal microbial population, as suggested by Adhikari and Kwon (2017) in their characterization of Lactobacillus spp. in the intestinal tract. Microbiome analyses on the gastrointestinal microbial composition of poultry can reveal considerable information on the members of the microbial consortia. However, such information has limits. For example, only a proportional estimate is possible in terms of the individual microorganisms identified by 16S rDNA sequencing, and  quantitation requires other approaches (Ricke et  al. 2017). Estimating microbial viability versus simple identification also requires more than DNA

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isolation. Consequently, while culture techniques may not provide complete answers, these methods still have roles to play in the isolation of viable cultures for further characterization. However, microbial composition does not necessarily change in line with detectable responses, but metabolism and fermentation can still shift in response to a feed additive. This requires analyses on microbial population functionality. From an overall microbial community standpoint, the introduction of metagenomic sequencing offers an opportunity to further characterize genetic functionality within a microbial population. Ideally, coupling this with metabolomics will support a more complete assessment of the ecological and biochemical characteristics occurring in the poultry gastrointestinal tract. This in turn will generate larger data sets that will require computer programs that carry out more-sophisticated bioinformatic analyses to assemble the disparate information derived from these analyses. As these approaches develop, the opportunity to modulate the poultry gastrointestinal tract in a more predictable manner should become possible.

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Rychlik I (2020) Composition and function of chicken gut microbiota. Animals 10:103. https://doi. org/10.3390/ani10010103 Sacranie A, Iji P, Choct M (2005) Reflux of digesta and its implications for nutrient digestion and bird health. Paper presented at the Proceedings of the 17th Australian Poult Sci Symposium, Sydney, New South Wales, Australia, 7–9 February 2005 Sacranie A, Svihus B, Denstadli V, Iji P (2009) Reverse peristalsis in intermittent and ad libitum fed broiler chickens raised on diets of varying form and insoluble fiber content. Proceedings of 17th European Symposium on Poultry Nutrition, Edinburgh Sacranie A, Adiya X, Mydland LT, Svihus B (2017) Effect of intermittent feeding and oat hulls to improve phytase efficacy and digestive function in broiler chickens. Br Poult Sci 58:442–451. https://doi.org/10.1080/00071668.2017.1328550 Saengkerdsub S, Kim W-K, Anderson RC, Woodward CL, Nisbet DJ, Ricke SC (2006) Effects of nitrocompounds and feedstuffs on in vitro methane production in chicken cecal contents and rumen fluid. Anaerobe 12:85–92. https://doi.org/10.1016/j.anaerobe.2005.11.006 Saengkerdsub S, Anderson RC, Wilkinson HH, Kim W-K, Nisbet DJ, Ricke SC (2007a) Identification and quantification of methanogenic archaea in adult chicken ceca. Appl Environ Microbiol 73:353–356. https://doi.org/10.1128/AEM.01931-­06 Saengkerdsub S, Herrera P, Woodward CL, Anderson RC, Nisbet DJ, Ricke SC (2007b) Detection of methane and quantification of methanogenic archaea in faeces from young broiler chickens using real-time PCR.  Lett Appl Microbiol 45:629–634. https://doi. org/10.1111/j.1472-­765X.2007.02243.x Sekelja M, Rud I, Knutsen SH, Denstadli V, Westereng B, Næs T, Rudi K (2012) Abrupt temporal fluctuations in the chicken fecal microbiota are explained by its gastrointestinal origin. Appl Environ Microbiol 78:2941–2948. https://doi.org/10.1128/AEM.05391-­1 Selander U (1963) Fine structure of the oxyntic cell in the chicken proventriculus. Acta Anat (Basel) 55:299–310. https://doi.org/10.1159/000142480 Sergeant MJ, Constantinidou C, Cogan TA, Bedford MR, Penn CW, Pallen MJ (2014) Extensive microbial and functional diversity within the chicken cecal microbiome. PLoS One 9(3):e91941. https://doi.org/10.1371/journal.pone.0091941 Shang Y, Kumar S, Oakley B, Kim WK (2018) Chicken gut microbiota: importance and detection technology. Front Vet Sci 5:254. https://doi.org/10.3389/fvets.2018.00254 Shi Z, Rothrock MJ Jr, Ricke SC (2019) Applications of microbiome analyses in alternative poultry broiler production systems. Front Vet Sci 6:157. https://doi.org/10.3389/fvets.2019.00157 Stanley D, Hughes RJ, Moore RJ (2014) Microbiota of the chicken gastrointestinal tract: influence on health, productivity and disease. Appl Microbiol Biotechnol 98:4301–4310. https:// doi.org/10.1007/s00253-­014-­5646-­2 Stanley D, Geier MS, Chen H, Hughes RJ, Moore RJ (2015) Comparison of fecal and cecal microbiotas reveals qualitative similarities but quantitative differences. BMC Microbiol 15:51. https://doi.org/10.1186/s12866-­015-­0388-­6 Svihus B (2011) The gizzard: function, influence of diet structure and effects on nutrient availability. Worlds Poult Sci J 67:207–224. https://doi.org/10.1017/S0043933911000249 Svihus B, Itani K (2019) Intestinal passage and its relation to digestive processes. J Appl Poult Res 28:546–555. https://doi.org/10.3382/japr/pfy027 Svihus B, Sacranie A, Denstadli V, Choct M (2010) Nutrient utilization and functionality of the anterior digestive tract caused by intermittent feeding and inclusion of whole wheat in diets for broiler chickens. Poult Sci 89:2617–2625. https://doi.org/10.3382/ps.2010-­00743 Svihus B, Choct M, Classen HL (2013) Function and nutritional roles of the avian caeca: a review. Worlds Poult Sci J 69:249–264. https://doi.org/10.1017/s0043933913000287 Swaggerty CL, Callaway TR, Kogut MH, Piva A, Grilli E (2019) Modulation of the immune response to improve health and reduce foodborne pathogens in poultry. Microorganisms 7:65. https://doi.org/10.3390/microorganisms7030065 Tortuero F, Brenes A, Riopérez J (1975) The influence of intestinal (ceca) flora on serum and egg yolk cholesterol levels in laying hens. Poult Sci 54:1935–1938

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Chapter 3

Current Understanding of the Crosstalk Between Direct-Fed Microbials and Indigenous Microbiome in the Gastrointestinal Tract: Applications and Challenges in Food-Producing Animals Tao Ma and Le Luo Guan Abstract  Direct-fed microbials (DFMs) are defined as feed products containing the source of naturally existing microbes, which are considered as one of the promising alternatives to prophylactic antibiotics used in food-producing animals. The gastrointestinal tract (GIT) of animals harbors a complicated microbial ecosystem with a tremendous number of species and high density of microbes, which is collectively referred to as GIT microbiota or the GIT microbiome. Interacting with and/or altering the GIT microbiome has been proposed as one mode of the actions of DFMs, but this is still largely unspecified in food-producing animals. In this chapter, we focus on the most recent findings in core, mucosa-associated, and individualized microbiomes in food-producing animals, including swine, poultry, and ruminants. In addition, we summarize the potential challenges in the application of DFMs in food-producing animals from lacking a comprehensive understanding the GIT microbiome, the interactions between DFMs and the indigenous GIT microbiome, and the individuality of the GIT microbiome. Moreover, the directions for future investigations into DFM–GIT microbiome crosstalk are suggested, which may help us develop strategies to effective use DFMs in order to improve health and productivity in different food-producing animal species.

T. Ma Key Laboratory of Feed Biotechnology of the Ministry of Agriculture and Rural Affairs, Institute of Feed Research, Chinese Academy of Agricultural Sciences, Beijing, China Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada L. L. Guan (*) Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada e-mail: [email protected] © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_3

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3.1 Introduction A growing population, growing economies, and increasing urbanization are three key drivers of the increasing consumption of animal products (Makkar 2016). It is estimated that in 2050, the world population will increase from 6.8 billion to 9.7 billion, among which 70% will be in urban cities (Northoff 2016). Concomitantly, the consumption of meat and eggs on one hand dairy products on another is predicted to increase by 73% and 58%, respectively, worldwide by the year 2050 (McLeod 2011). In order to meet such demands for animal food products, strategies should be implemented to improve the growth and efficiency in food-producing animals. Antibiotics have been extensively applied in food animal production not only for the treatment of diseases but also for promoting growth and production efficiency (Marshall and Levy 2011). However, with the increasing concerns of the emergence and prevalence of antimicrobial-resistant pathogens (Hao et  al. 2014; Lekshmi et  al. 2017), the need to reduce the antimicrobial usage in food animal productions has become urgent. Many studies have been conducted to investigate replacements for antibiotics, among which direct-fed microbials (DFMs) have been considered as one of the promising alternatives (Buntyn et  al. 2016; Grant et  al. 2018). According to the US Food and Drug Administration, DFM is defined as a “feed product containing a source of live naturally existing microbes” (Brashears et al. 2005). DFMs have been used in the livestock industry for over 25 years, showing beneficial effects on feed utilization, health and production, and immune function (Buntyn et  al. 2016). The mechanisms of DFMs for host health and growth benefits are not fully understood but potentially include protecting nonpathogenic bacteria and thus limiting the colonization of pathogens (competitive exclusion), improving digestion and nutrient utilization, and stimulating immune function (Buntyn et al. 2016). Microbiota is a term that refers to the community of organisms living within a specific environment, while microbiome is a term that describes the whole genome/ genetic materials of the microbiota (Turnbaugh et al. 2007). The microbiome in the host gastrointestinal tract (GIT) comprises the collective genome of microbes, including bacteria, archaea, viruses, and eukaryotes (fungi and/or protozoa) (Taneja 2017). It was not until the development of culture-independent method that our knowledge about the GIT microbiome was extensively expanded in the past 10 years. Investigations into the microbiome residing in the GIT of food-producing animals (swine, poultry, and ruminants) is of particular interest as it is closely associated with not only animal growth/production efficiency but also animal health and animal wellbeing, where the latter two have recently been at the center of the public’s concerns (Gensollen et al. 2016). The modulatory effect of DFMs, mostly lactic acid bacteria (Lactobacillus, Enterococcus, and Bifidobacterium) and yeast (Saccharomyces cerevisiae and S. boulardii), on the GIT microbiome in swine (Barba-Vidal et al. 2018), poultry (Tellez et al. 2012), and ruminants (Uyeno et al. 2015) has been recently reviewed. Even with those studies, it is still unclear how DFMs interact with the GIT microbiome in different food-producing animal

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species, mainly because of our lack of knowledge of the GIT microbiome in these species and because most of studies are based on fecal samples. In this review, we focus on the most recent findings on the GIT microbiome (core/mucosa-associate/ individualized microbiome) in three major food-producing animals, namely swine, poultry, and ruminants, and discuss how they are barriers to the application of DFMs. Finally, we propose directions for future research into the use of DFMs to effectively improve health and productivity in different food-producing animal species from a gut microbiome perspective.

3.2 Recent Advances in Researching the GIT Microbiome of Food-Producing Animals 3.2.1 Core Microbiota 3.2.1.1 Taxonomic Core Microbiota in the GIT of Food-Producing Animals More and more studies have revealed a core GIT microbiota within each mammalian species, where core microbiota is defined as a fraction of microorganisms shared by most microbial assemblages among the populations associated with a habitat (Hamady and Knight 2009). The research on the functional aspects of the core microbiota has been emerging and has suggested that taxa in the core microbiota may play important roles in the functions of the microbial community (Shade and Handelsman 2012). Identifying a core microbiota is a prerequisite to defining what a “healthy” microbiome looks like for a particular habitat and for predicting microbiome responses to environmental perturbations (diet, use of antibiotics, and so on) (Shade and Handelsman 2012). In addition, understanding which members are core can provide insights into the manipulation of communities, such as through the use of DFMs, in order to achieve desired outcomes. According to the definition of core microbiota, the sample size should be considered one of the most important factors in determining a “true” core microbiota in the GIT of a specific animal species. The dominant taxa identified from one animal study or a few such studies may not necessarily be the “true” core members, because membership in the core microbiota would be expected to shrink upon the inclusion of successively larger numbers of animals (Weimer 2015). For example, Holman and Chénier (2014) reported that the most prevalent bacterial genera were Prevotella, followed by Treponema and then by Lactobacillus, in 94 fecal samples from piglets. Kim et al. (2015) reported that the most prevalent classified genus was Xylanibacter, followed by Lachnospiraceae and Prevotella, in 19 fecal samples from swine at various growth stages. However, when the results from those two studies and those from another ten studies on the fecal microbiome of pigs were summarized and subjected to meta-analysis, only five genera—including Prevotella, Clostridium, Alloprevotella, Ruminococcus, and the RC9 gut group—were found in 99% of all

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949 fecal samples (Holman et al. 2017), suggesting that those five genera may constitute the “true” core microbiota in swine fecal samples. Similarly, an analysis of 16,000 fecal samples collected from broiler chickens suggested that 52 taxa were present in all fecal samples, dominated mostly by Fusobacterium, Brevibacterium, Bacteroides, Clostridium, Faecalibacterium, and Lactobacillus (Oakley et al. 2013), which are considered broiler chickens’ core microbiota. According to the 16S rRNA gene sequencing of 742 rumen samples from 32 ruminant species from 35 countries, Henderson et al. (2015) reported that bacterial genera Prevotella, Butyrivibrio, and Ruminococcus or families of unclassified Lachnospiraceae, Ruminococcaceae, Bacteroidales, and Clostridiales existed in all samples, a result that was further confirmed by Li and Guan (2017) and Xue et al. (2018) in beef and dairy cattle, respectively. On recent study, based on 16S and 18S rRNA gene sequencing of rumen samples from 1061 dairy cattle, suggested that 39 core operational taxonomic units (OTUs), including Lachnospiraceae, Ruminococcus, Fibrobacter, and Succinovibrionaceae families, along with two fungi belonging to the genus Neocallimastix, are considered as taxononmic core microbiota (Wallace et al. 2019). These findings suggest that these bacteria taxa could be the core bacteriomes in the rumen of cattle, and such information is valuable in determining whether and how their population and/or functions are affected by DFMs. To date, the response of the GIT taxonomic core microbiota identified in swine (Holman et al. 2017), chicken (Oakley et al. 2013), and ruminants (Henderson et al. 2015; Wallace et al. 2019) to the supplementation of DFMs is not well understood, and future DFM trials should take this into account. However, the core microbiome in fecal samples identified in swine and chicken may not necessarily represent the core microbiome in the whole GIT given that recent studies have shown that fecal microbiota could be different from microbiota in the cecum of chicken (Stanley et al. 2015) and swine (Panasevich et al. 2018). In addition, it is reported that fecal microbiota are different from the microbiota in the small intestine (Malmuthuge et al. 2014) and the proximal hindgut in calves (Song et al. 2018). Because both the distribution of the GIT microbiome and its interaction with intestinal epithelium development occur in a site-specific manner (Sommer et al. 2015), more studies and analyses need to be conducted to investigate the core microbiome in different regions of the GIT of food-producing animals and how they might be affected by DFMs. In addition, even with the recent study on the composition of the intestinal mucosa-associated microbiome in newborn (Song et al. 2018; Ma et al. 2019a) and preweaning calves (Malmuthuge et al. 2015), there is still a lack of knowledge on the difference in taxonomic core microbiota among ruminant species and among the different regions of the lower gut of ruminants. More efforts are still needed to identify the region-specific taxonomic core microbiota in the small and large intestines of cattle, sheep, and goats so as to provide a basis for the effective use of DFMs to improve their health and productivity.

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3.2.1.2 Functional Core Microbiota in the GIT of Food-Producing Animals In addition to knowledge on the taxonomic composition of core microbiota in the GIT (“who are there”), it is also important to understand the collective functional traits of the core microbiome (“what are they doing”). Culture-based approaches allow researchers to investigate the functions of specific taxa. For example, Prevotella spp. and Ruminococcus spp., identified as core taxa in swine fecal samples (Holman et al. 2017) and rumen samples (Henderson et al. 2015), are capable of degrading plant hemicellulose (Dehority 1967; Coen and Dehority 1970) by producing polysaccharidases such as glucanase, mannanase, and xylanase (Flint and Bayer 2008). Faecalibacterium prausnitizii, identified as a core taxon in chicken feces (Oakley et al. 2013), is known as a butyrate-producing bacterium belonging to the Firmicutes phylum (Duncan et al. 2002). In addition, substantial crosstalk may take place among core taxa. For instance, Prevotella spp. produces acetate, which provides energy for butyrate-producing bacteria such as Butyrivibrio spp., Ruminococcus spp., and F. prausnitizii (Vital et  al. 2014). Given the beneficial effect of most known core taxa on GIT functions and GIT health, it is important that the use of DFMs is able to promote the prevalence of core taxa and their crosstalk, which in turn will enhance the growth and immunity of food-producing animals. However, it is not possible to characterize the functions of uncultured microorganisms or to illustrate the functions of all core taxa on the basis of taking a culture-­ dependent approach (Li et  al. 2018). For example, the function of the RC9 gut group, a core taxon recently identified in swine feces (Holman et  al. 2017) that belongs to the Rikenellaceae family on the basis of taking the 16S rRNA approach, is still not clear. To address this issue, metagenomic- and metatranscriptomics-based analyses should be applied to investigate the functional potentials and activities of the core microbiome because those approaches are able to capture the whole genomic and transcriptomic repertoire for both cultivable and uncultivable microorganisms (Vakhlu et al. 2008). Efforts have been made to identify the function of the core microbiome in the GIT of food-producing animals on the basis of using metagenomics/metatranscriptomics. For example, a metagenomics-based analysis suggested that Prevotella sp. CAG:604 contains genes that encode proteins involved in nutrient and energy metabolism, whose abundance increased in the cecal microbiome of pigs with low feed efficiency compared with those with high feed efficiency (Tan et  al. 2017). This reveals that increasing the particular core member could affect the functions of the microbiome, which may affect host phenotypes, such as feed efficiency in swine. More recently, Prevotellaceae was revealed to be the dominant acetate and propionate producer in the rumen of dairy cows, according to quantitative metatranscriptomics (Söllinger et  al. 2018). It is well known that these two volatile fatty acids contribute to cattle host energy metabolism (Bergman 1990), and thus, a shift in this core member may lead to a change in host energy metabolism and affect the health and performance of animals. More studies are needed to investigate the response of the core microbiome to DFMs by using advanced “feedomics” techniques (Sun and Guan 2018; Sun et al. 2019), in order to

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elucidate the potential mechanisms by which DFMs affect the GIT health and function of more-food-producing animal species.

3.2.2 Mucosa-Associated Versus Digesta-Associated Microbiomes Digesta samples rather than mucosa samples have been used most often in previous studies on the GIT microbiomes of food-producing animals. There are substantial differences between mucosa-associated and digesta-associated microbiomes. First, in contrast to the continuous flux of nutrients/digesta in the lumen, the mucosa is expected to show a stabler balance of nutrients and may therefore represent a selective criterion for certain bacterial species (Singh et al. 2013). A study comparing mucosa- and digesta-associated bacterial phylotypes in both chickens and preweaned calves has revealed a much greater richness in mucosa-associated bacterial phylotypes than in digesta-associated bacterial phylotypes, throughout the GIT (Malmuthuge et al. 2012, 2014). Second, mucosa-associated microorganisms can directly interact with the host and with pathogens, which are crucial in shaping the host immune system (Van den Abbeele et al. 2011). More importantly, one of the modes of the actions of DFMs is the regulation of host immune function (Buntyn et  al. 2016), and thus, the intensive crosstalk between DFMs and the mucosa-­ associated microbiome can be expected. Third, it has also been shown that mucosa-­ associated rather than digesta-associated bacterial profiles in ileum changed in response to dietary changes and the use of antibiotics in pigs (Levesque et al. 2012). It can therefore be speculated that the response to the use of DFMs can be different between the mucosa- and digesta-associated microbiomes in the GIT of food-­ producing animals. In this regard, more investigations into the changes in the mucosa-associated microbiome induced by DFMs in food-producing animals are warranted. Several studies have compared the difference between digesta- and mucosa-­ associated microbial profiles in the GIT of food-producing animals. For example, the mucosa-associated bacterial community was dominated by a significantly higher concentration of Firmicutes phylum (42.4%), whereas the digesta-associated community was dominated solely by this phylum (93.4%) in the ileum of 3-week-old calves (Malmuthuge et al. 2012). Megamonas and p-75-a5 were exclusively present in the mucosa-associated microbiota, whereas Streptococcus and Sarcina were exclusively present in the digesta-associated microbiota in the rumen of preweaned calves (Malmuthuge et al. 2014). In dairy cattle, the small intestine digesta samples presented a higher abundance of unclassified Enterobacteriaceae and lower abundance of Acinebacter compared with the corresponding mucosa samples. In the large intestine, unclassified Peptostreptococcaceae, Turicibacter, and Clostridium were dominant in the digesta, whereas Treponema and unclassified Ruminococcaceae were dominant in the mucosa (Mao et al. 2015). In addition to the difference in the

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relative abundance of specific taxa between the two sample types, the mucosa-­ associated microbiota was reported to have higher individual variation than the digesta-associated microbiota (Song et  al. 2018), suggesting that the mucosa-­ associated microbiome may not be as easily manipulated as the digesta-associated microbiome. A substantial difference between the microbiomes of the two types of gut environments can be inferred at even the lower taxonomic level, such as species and strain levels. Studies on the mucosa-associated microbiome in different GIT regions of food-­ producing animals (swine, poultry, and ruminant) over the past 10 years are summarized in Tables 3.1, 3.2, and 3.3. In general, for almost all animal species, Firmicutes is the most dominant phylum in the mucosa-associated microbiome in different GIT regions, whereas Proteobacteria is the dominant phylum in the small intestine (duodenum, ileum, and jejunum), and Bacteroidetes is the dominant phylum in the large intestine (colon and cecum) and feces. At the genus level, Lactobaicllus, Flexispira, Ruminococcus, Turicbacter, and Streptococcus (Munyaka et  al. 2016; Hooda et  al. 2016; Argüello et  al. 2018; Holman et  al. 2019) are Table 3.1  Summary of dominant taxa of mucosa-associated bacteria in the GIT of swine over the past 10 years Animal 28-day-old piglet

3-week-old piglet 28-day-old piglet

9-week-old pig 17-day-old piglet

4-week-old pig 21-day-old piglet 6-week-old pig

Sample Stomach Ileum Colon Ileum

Hypervariable region V1-V2

Dominant taxa Lactobacillus

Duodenum V4

Helicobacter, Lactobacillus Helicobacter, Prevotella Clostridium, Lactobacillus, Sarcina, Streptococcus Proteobacteria

Jejunum Ileum Cecum Colon Colon

V4

Proteobacteria Proteobacteria Proteobacteria Bacteroidetes, Firmicutes Prevotella, Roseburia

Ileum

V4

Firmicutes

Cecum Colon Ileum

V3-V4

Ileum

V1-V3

Proteobacteria Firmicutes, Bacteroidetes Lactobacillus, Flexispira, Ruminococcus Lactobacillus, Turicbacter

Ileum

V4

Lactobacillus, Streptococcus

Cecum

V1-V3

References Mann et al. (2014)

Levesque et al. (2014) Kelly et al. (2017)

Burrough et al. (2017) Munyaka et al. (2016)

Argüello et al. (2018) Hooda et al. (2016) Holman et al. (2019)

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Table 3.2  Summary of the dominant taxa of mucosa-associated bacteria in the GIT of poultry over the past 10 years Animal 1-day-old broiler 10- and 35-day-­ old broilers 1-day-old broiler

Hypervariable Sample region Jejunum V1-V3 Ileum

V1-V3

Jejunum V3-V5 Cecum

1-day-old broiler

Ileum

V1-V2

Cecum

1-day-old broiler

Ileum

V1-V3

Cecum 78-day-old broiler Ileum

V4

Dominant taxa Lactobacillus

References Stanley et al. (2012) Candidatus Arthromitus Wang et al. (2016) Lactobacillus Escherichia, Awad et al. (2016) Lactobacillus Escherichia, Anaerotruncus Lactobacillus Borda-Molina et al. (2016) Unclassified Lachnospiraceae, Unclassified Anaerotruncus Lactobacillus, Adhikari and Kwon Enterococcus, (2017) Citrobacter Lactobacillus, Enterococcus, Rhodococcus Wen et al. (2019)

dominant in ileum mucosa-associated microbiota, whereas Prevotella and Roseburia (Burrough et al. 2017) are dominant in the colon mucosa-associated microbiota of swine. In poultry, Rhodococcus and Lactobacillus are the dominant taxa associated with ileum mucosa (Borda-Molina et al. 2016; Wen et al. 2019), Escherichia and Lactobacillus are the dominant taxa associated with the jejunum mucosa (Awad et al. 2016), and Escherichia and Anaerotruncus are the dominant taxa associated with the cecum mucosa (Awad et al. 2016; Borda-Molina et al. 2016). In ruminants, Prevotella is the dominant genus associated with the rumen mucosa of both young calves (Malmuthuge et al. 2014) and dairy cows (Mao et al. 2015). Faecalibacterium was reported as dominant in the mucosa hindgut of young calves (Malmuthuge et al. 2014) and newborn calves (Song et al. 2018; Ma et al. 2019a). As major microbial fermentation products in the GIT, short-chain fatty acids (SCFAs) play key roles in protecting epithelial cells from inflammation (Hamer et al. 2008) and infection from enteric pathogens (Fukuda et al. 2011). Recent studies have revealed that SCFAs are correlated with certain microbial communities in the hindgut mucosa of young calves (Song et  al. 2018) and the ileum and colon mucosa of 2-day-old calves (Ma et al. 2019a). For example, the relative abundance of mucosa-associated Escherichia-Shigella in the hindgut is negatively correlated with acetate concentration in young calves (Song et al. 2018), which is expected given that acetate has been reported to inhibit the growth of E. coli (Fukuda et al. 2011). In addition, the molar proportion of acetate is negatively correlated with the

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Table 3.3  Summary of the dominant taxa of mucosa-associated bacteria in the GIT of ruminants over the past 10 years Animal Sample 3-week-old calf Rumen

Hypervariable region V1-V3

Ileum Jejunum Cecum Colon 5-year-old dairy Rumen cow Reticulum

V3-V4

Omasum

Abomasum Duodenum Jejunum

Ileum

Cecum

Colon

Rectum

Newborn, 7-day, 21-day, 41-day-old calf

Hindgut (cecum, colon, rectum)

V1-V3

Dominant taxa Prevotella, Bacteroides Burkholderia, Prevotella Burkholderia, Lactobacillus Prevotella, Faecalibacterium Prevotella, Faecalibacterium Prevotella, unclassified Ruminococcaceae Prevotella, unclassified Ruminococcaceae unclassified Ruminococcaceae, Prevotella unclassified Ruminococcaceae unclassified Enterobacteriaceae unclassified Enterobacteriaceae, Butyrivibrio unclassified Peptostreptococcaceae, unclassified Enterobacteriaceae unclassified Peptostreptococcaceae, unclassified Enterobacteriaceae unclassified Peptostreptococcaceae, Turibacter unclassified Peptostreptococcaceae, Turibacter, Clostridium Bacteroides, Escherichia-Shigella, Lactobacillus (newborn and 7-day-old); Bacteroides, Faecalibacterium, Blautia (21- and 42-day-old)

References Malmuthuge et al. (2014)

Mao et al. (2015)

Song et al. (2018)

(continued)

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Table 3.3 (continued) Animal 2–7-day-old calf

Sample Ileum

Hypervariable region V3-V4

Colon

2-day-old calf

Ileum

Colon

V1-V3

Dominant taxa Megamonas, Bifidobacterium Streptococcus, Ruminococcaceae UCG-005 Escherichia-Shigella, Nocardiopsis, Brevibacterium Escherichia-Shigella, Butyricicoccus, Streptococcus, Faecalibacterium

References Fomenky et al. (2018)

Ma et al. (2019a)

relative abundance of Subdoligranulum in the ileum mucosa, while that of acetate and of propionate are positively correlated with the relative abundance of Bacteroides in the colon mucosa of 2-day-old calves (Ma et  al. 2019a). Subdoligranulum is known to produce butyrate (Eeckhaut et al. 2011), which requires acetate as a key intermediate (De Vuyst and Leroy 2011). On the other hand, it is reported that acetate produced by colon mucosa-associated Bacteroides thetaiotaomicron is used by F. prausnitzii to produce butyrate in rats (Wrzosek et al. 2013). These results suggest potential crosstalk between lumen microbial metabolites and the mucosa-­ associated microbiome, which may be essential to maintaining normal GIT functions, by either inhibiting the prevalence of opportunistic pathogens or promoting the growth of beneficial bacteria. More studies are needed to illustrate how the mucosa-associated microbiome affects host immune function in a regional-specific manner in food-producing animals. Overall, the regional- and type-specific microbiomes throughout the whole GIT should be independently analyzed to better understand how those microbiomes interact with DFMs and host immune function in food-producing animals.

3.3 Challenges for the Application of DFMs in Food-Producing Animals 3.3.1 Lack of In-Depth Understanding of the GIT Microbiome Despite the efforts made by using the 16S rRNA gene sequencing technique to characterize regional- and type-specific features of microbiomes, it is still largely unknown which exact microbial species/strains exist in the specific site of the GIT in food-producing animals. It is suggested that only certain strains of E. coli, such

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as enterotoxigenic and Shiga-toxin-producing/enterohemorrhagic strains, are recognized as pathogenic (Russo and Johnson 2000). Although probiotics-based DFMs, including Lactobacillus, Lactococcus, and Bifidobacteria strains, were reported to be effective against the growth of pathogenic strains of E. coli, their effects differed (Fijan et  al. 2018). In addition, it is not clear which specific probiotics-­based DFM strain inhibits the growth of specific pathogenic strains. Consequently, a better understanding of the profiles of opportunistic pathogens/ beneficial bacteria at species or strain levels will enable the design of DFMs that have the best inhibitory/promoting effects on the specific pathogenic/beneficial species/strain in the GIT of food-producing animals. In addition to the comprehensive knowledge of “who are there,” there is also an urgent need to understand how DFMs affect the function of microbiomes because changes in microbial composition may not always lead to changes in function and vice versa. As suggested by Li et al. (2019a), although the rumen microbial composition was divergent among three cattle breeds, the difference in functional activity was less apparent, according to a metatranscriptomic analysis. On the contrary, Ma et al. (2019b) reported that light-intensity lamb grazing led to a change in microbial functional gene families but not in microbial taxonomic composition, indicating that the key level at which to address microbial responses to environmental perturbations (such as antibiotics/DFMs) may not be the taxonomic level but rather the functional gene/protein/metabolite level in food-producing animals. According to those findings, it is crucial to investigate how DFMs induce changes in the GIT microbiome at both the compositional and functional levels in order to understand the mode of action of DFMs in the GIT of food-producing animals. As the GIT microbiome changes dynamically over life spans, the response of the GIT microbiome to DFMs may be different at various growth stage of food-­ producing animals. For example, temporal changes in the epimural bacterial community have been reported in goat kids, where Proteobacteria was predominant during the first week of life and where Bacteroidetes and Firmicutes were predominant when the kids were older (Jiao et al. 2015). Bacteroides and Clostridium sensu stricto, the dominant genus on postnatal day 1, were replaced by Prevotella and Alloprevotella at 6 months in the small intestine of piglets (Liu et al. 2019). Those results indicate that the timing of using DFMs is crucial to effectively manipulating the GIT microbiome in a way that life-long health/production benefits are achieved. Although it has been recommended that probiotics should be provided during early life in pigs (Kenny et al. 2011), chickens (Rubio 2018), and calves (Malmuthuge et al. 2015), possibly because of the less-resilient and moreflexible GIT microbiome at this stage, the mechanism remains largely unknown. More efforts are needed to investigate how the GIT microbiome changes over time, especially during early life, to provide a basis for the effective use of DFMs in food-producing animals.

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3.3.2 Lack of Understanding of the Interaction Between DFMs and the GIT Microbiome Although, according to studies, DFMs were found to inhibit the growth of opportunistic pathogens and promote the growth of beneficial bacteria in the GIT of different food-producing animal species, as summarized by Ma et al. (2018), most of the data from such studies were obtained by targeting limited pathogenic organisms such as E. coli, Salmonella, Lactobacillus, and Bifidobacterium and ignoring the subtle influence of DFMs on other genera that are potentially beneficial/detrimental to the health of the GIT. In addition, the exact mechanism of how DFMs interact with the GIT microbiome and how DFM interactions in turn impact host health and growth in food-producing animals are still unclear. The effect of DFMs on opportunistic pathogens can be achieved by directly producing antibacterial substances such as bacteriocins and organic acids (Bermudez-Brito et  al. 2012), by making them compete for adhesion sites (Ohland and MacNaughton 2010), or by limiting their nutrients (Bajaj et al. 2015), while the promoting effect of DFMs on commensals may be mediated by indirectly modulating host immune responses (Famularo et al. 1997). For example, the supplementation of probiotics-based DFMs increased ileal mucosal Secretory immunoglobulin A (SIgA) concentration (Peng et al. 2016), the number of goblet cells, and neutral mucin production (Martínez et  al. 2016; Forte et al. 2018) in broilers, which is speculated to be associated with an increase in beneficial bacteria such as Lactobacillus in response to the DFMs. The exact mechanism through which DFMs exert inhibitory/promoting effects on specific opportunistic pathogen(s)/commensal(s) needs further investigation. In addition, although the majority of the studies reported positive effects of DFMs on the GIT microbiome, the results were not always consistent. On one hand, different strains or subspecies of a certain DFM, such as Bacillus subtilis, produce different sets of peptides (Fuchs et al. 2011; Grant et al. 2018), suggesting that different B. subtilis strains may interact differently with the GIT microbiome. On the other hand, the interactions between DFMs and the indigenous GIT microbiome can also be affected by animal characteristics (age, breed, physiological conditions, and metabolic conditions), experimental factors (long- or short-term treatment, the sample type, and the method of microbiome analysis), and DFM variables (the strain, dosage, and method of delivery). For example, Bacillus subtilis DSM 32315 was reported to increase the abundance of members of the Ruminococcaceae family in healthy broiler chickens (Bortoluzzi et al. 2019) but decrease its abundance in broiler chickens with necrotic enteritis (Whelan et  al. 2018). More studies are needed to investigate how a specific DFM strain/subspecies interacts with the indigenous GIT microbiome and modulates mucosal immune function in food-producing animals.

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3.3.3 Individualized Microbiomes Pose Challenges for Application of DFMs Many studies have suggested that humans and mice have highly individualized gut microbiomes (Smits et al. 2016; Zeevi et al. 2015; Johnson et al. 2019). However, studies on individualized GIT microbiomes in livestock animals are just emerging. After using the cultured-independent method (Polymerase chain reaction (PCR) with denaturing gradient gel electrophoresis (DGGE)), Li et al. (2009) reported that bacterial profiles differed among rumen samples collected from three cows fed the same diet. With the help of the sequencing technique, Jami and Mizrahi (2012) reported a 51% similarity in bacterial taxa across 16 rumen samples from lactating dairy cows, supporting the findings of Li et al. (2009). Using 750 rumen samples from dairy cows, Difford et al. (2018) further confirmed the individual variation in the composition of rumen microbiota. More recently, Malmuthuge et  al. (2019a) revealed high individual variation in the GIT (small intestine) metagenomes (composition and function) of neonatal calves. The highly individualized variation in microbiomes may explain the difference in response to a similar dietary intervention in many studies. For example, Zhou et al. (2018a) reported that shifts in rumen microbiota in response to a supplementation of brown seaweed differed across rams. One study suggested that humans display considerable person-to-person variation in gut microbiome composition, which caused probiotic-permissive or -resistant states, depending on the features of the respective microbiomes (Zmora et al. 2018). It can therefore be inferred that highly individualized microbiomes in livestock animals pose challenges for the application of DFMs, because some individuals (“responders”) may be more permissive to DFM colonization than others (“nonresponders”) are. In an attempt to discover which factors contribute to individualized gut microbiomes, Zhou et  al. (2018b) investigated how individual rumen microbiomes were altered and re-established after being emptied and then receiving exogenous content from donors. The results suggest that the rumen microbial re-establishment patterns and the overall microbial ecology at each stage were unique for individual animals after rumen transfaunation, highlighting the importance of considering host genetics, microbial functional genomics, and host fermentation/performance assessments when developing effective and selective microbial manipulation methods for improving animal feed efficiency (Zhou et al. 2018b). Metagenomic and metatranscriptomic analyses have suggested that the rumen microbial composition (metatranscriptomic level) and functional potentials (metagenomic level) are divergent among three breeds of beef cattle, indicating that host genetics and environmental factors work together to shape individualized rumen microbiomes and their functionality (Li et al. 2019a). Recently, some studies have reported that certain members of the GIT microbiome, which are closely associated with either methane emission (Roehe et al. 2016; Difford et al. 2018) or production efficiency (Li et al. 2019b), or both (Wallace et al. 2019), are heritable in cattle. For example, the relative abundance of Methanobrevibacter, an archaea genus that is predominant in the

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GIT of livestock animals (St-Pierre et al. 2015), had a significant heritability estimate (h2 = 0.22 Vg; Difford et al. 2018). In addition, it was suggested that five single nucleotide polymorphisms (SNPs) that were known quantitative trait loci for feed efficiency in cattle were found to be significantly associated with 14 rumen microbial taxa (Li et  al. 2019b). In total, 39 heritable core microbial OTUs associated with either methane emission or milk production efficiency from the rumens of 1016 dairy cows were identified, and they showed significant heritability estimates ranging from 0.2 to 0.6 Vg (Wallace et al. 2019). Those results suggest that more studies are required to further characterize the mechanisms of action for DFMs while taking into account different host genetic factors and environmental conditions.

3.4 Future Directions for Effective Use of DFMs in Food-Producing Animals Strong evidence has suggested that DFMs are promising alternatives to antibiotics, and thus, it can be expected that the use of DFMs will expand enormously in the future thanks to the increasing demand for animal protein. However, our current lack of understanding of the mechanisms of action may hamper the development and use of DFMs that effectively enhance host health productivity. To address those issues, multiple steps need to be taken to illustrate how DFMs interact with the GIT microbiome and whether/how these interactions potentially affect GIT function, health, and performance and the productivity of food-producing animals (Fig. 3.1). First, the response of the GIT microbiome to DFMs needs to be identified at not only the compositional level but also the functional level in food-producing animals. Although microbial taxonomy and microbial functions are often coupled because related taxa have similar functions, it is what microbes are doing, not who they are, that is finally important for an ecosystem (Inkpen et  al. 2017). In fact, it has been suggested that functional profiles are more conserved, relevant, and useful than the taxonomic profiles of an environmental microbiome (Franzosa et al. 2014; Louca et al. 2016). It can be speculated that taxonomic changes may not always be consistent with the functional changes in the GIT microbiome in response to DFMs in food-producing animals and that the functional changes may be more useful than taxonomic changes at illustrating how the GIT microbiome interacts with DFMs. Most current studies have focused on the changes in the taxonomic composition of the GIT microbiome in response to DFMs in food-producing animals by using the 16S rRNA gene sequencing technique (Ma et  al. 2018). As suggested by Sun and Guan (2018), feedomics-based approaches, such as metagenomics and metatranscriptomics, should also be applied to explore the genes and transcripts of the microbiome, which provides us with a comprehensive understanding of the changes in the composition, function, and activities of the GIT microbiome that are induced by DFMs in food-producing animals. A recent study has revealed a three-way

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Fig. 3.1  Steps for the effective use of direct-fed microbials (DFMs) in food-producing animals

interaction among rumen microbiota, host mRNAs, and microRNAs by using microbial metagenomics and rumen tissue transcriptomics, suggesting a potential role for bacteria-driven transcriptional regulation in early rumen development via microRNAs in neonatal calves (Malmuthuge et al. 2019b). Second, the interaction between DFMs and the GIT microbiome should be examined not only under healthy conditions for food-producing animals but also under disease/ stress conditions for them, because it has been suggested that certain DFMs exhibiting beneficial effects under normal physiological conditions may not exhibit similar effects or even detrimental effects on chickens under challenging/ stress conditions (Sohail et al. 2013), pigs (Zhu et al. 2014), and calves (Zhang et  al. 2016). The inconsistent effect of DFMs on food-producing animals is largely unknown, which may be due to the difference in GIT microbial profiles under various health conditions. In this regard, the GIT microbiome, especially the core microbiome, of animals under healthy/unhealthy conditions needs further identification, which can provide a basis for the precise screening and selection of DFM strains that effectively manipulate the GIT microbiome in a way that prevents or cures disease or promotes the growth and health of food-producing animals. Third, strategies are needed to ensure that the beneficial effects of DFMs are long lasting. In many cases, DFM strains appear to function only

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transiently in the community, and their effects are sustained only via daily supplementation (Weimer 2015). On the other hand, the GIT microbiome is more flexible and susceptible to dietary intervention in the early life than in the adult period of animals (Abecia et al. 2013), indicating that providing DFMs during early life could permit the establishment of early and life-long health benefits (Kenny et  al. 2011). A recent study has revealed that the supplementation of Lactobacillus rhamnosus GG-derived protein to neonatal mice (from d 1 to d 21) reduced their susceptibility to intestinal injury and colitis and promoted protective immune responses in the adult period (d 49) (Shen et  al. 2018). Further investigations are needed to determine the best time to use DFMs in food-producing animals to achieve long-lasting beneficial effects on their health and productivity. Fourth, compared with the numerous studies on monogastric animals, such as pigs and chickens, studies on ruminants are relatively limited. The ruminant digestive system is distinct from the monogastric one owing to its fourchambered stomach, of which rumen harbors a wealth of microbiomes that are able to ferment high-cellulose feedstuffs (Hungate 1966). The direct ruminal dosing or feeding of DFMs may fail to establish the introduced strains because of the intensive competition between them and the indigenous GIT microbiome, which is well adapted to ruminal conditions (Weimer 2015). More-intensive studies on the interactions between DFMs and the rumen microbiome are needed in order to develop DFMs that are able to adapt to the complicated and competitive rumen conditions and to effectively engineer the rumen for improved function. Meanwhile, as early life may represent a window of opportunity to effectively modulate the GIT microbiome composition, studies on manipulating lower-gut microbiomes, especially those in neonatal/young ruminants, which are characterized as pseudomonogastric (Baldwin et al. 2004), via DFMs should not be overlooked. Fifth, host genetic factors and interactions between the host and environmental factors should be considered when applying DFMs to food-producing animals. It has been suggested that environmental and host genetic factors may collectively shape the individuality of the GIT microbiome in mice (Benson et al. 2010). Recent studies have also revealed the effect of host genetic factors on individualized rumen microbiomes in cattle (Roehe et al. 2016; Difford et al. 2018; Zhou et al. 2018b; Li et al. 2019a, b; Wallace et al. 2019). However, it is reported that the GIT microbial community was largely independent of host genetics (represented by single-nucleic polymorphisms, or SNPs) in chickens (Wen et al. 2019), but heritable taxa were detected, and some of them are associated with SNPs in cattle (Li et al. 2019b; Wallace et al. 2019). That inconsistency indicates that the “key” environmental and host genetic factors that shape an individualized GIT microbiome may exist and need to be identified. In this regard, more-­comprehensive studies are needed to investigate how genetic factors (such as breed and sex) and environmental factors (such as barn and diet) contribute to the differences in the GIT microbiomes of individual hosts and how such differences affect the efficacy of using DFMs in food-producing animals.

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3.5 Conclusion More and more studies have shown the beneficial effects of DFMs on growth performance and health in food-producing animals. Although the specific mechanisms that explain the improvement in health and performance from the use of DFMs are not clear, the potential interaction between DFMs and the GIT microbiome may be largely responsible for the beneficial effects. However, our current knowledge about the interactions between DFMs and the GIT microbiome is still limited, hampering the effective use of DFMs in food-producing animals. The composition and the function of core/individualized microbiomes and how host genetic factors affect the use of DFMs remain largely unknown. Therefore, more efforts should be made to investigate how the GIT microbiome interacts with a supplementation of DFMs in a strain-specific or host-specific manner in food-producing animals. With the help of advanced feedomics-based approaches, a clear understanding of the mechanisms governing DFM effects on animal health and performance can be expected, which should in turn help us to develop specific strategies to effectively apply DFMs in different food-producing animal species.

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Chapter 4

Advancements in Poultry Nutrition and Genetics, the Role of Antibiotic Growth Promoters, and the Introduction of Feed Additive Alternatives L. A. Wythe, D. K. Dittoe, and Steven C. Ricke Abstract  The commercial poultry industry has made tremendous strides over the past decades, where its scientific advancements have translated into optimized economics and production efficiency. These changes have led to a vertically integrated industry that is highly organized from the hatchery to the final poultry retail products. Much of this improvement can be attributed to nutritional discoveries and advances in poultry genetics. Both have led to faster-growing and more-efficient uniform birds in the production cycle. As a part of that progress, historically, antibiotic growth promoters were extensively used to promote gastrointestinal health and reduce disease, among other benefits, some of which were less defined. However, because of public health concerns, antibiotic growth promoters have been mostly phased out of poultry production, creating a demand for alternative feed additives that can contribute to some of these benefits. This review discusses the developments in poultry nutrition and genetics, the introduction and eventual phasing out of antibiotic growth promoters, and the rationale for using alternative feed additives.

4.1 Introduction One of the significant milestones for the poultry industry was the introduction of antibiotic growth promoters (AGPs) to the supply chain (Jones and Ricke 2003; Dibner and Richards 2005). By including AGPs prophylactically at subclinical levels, the industry found that bird pathogen prevalence decreased and that growth performance was improved (Castanon 2007). The main hypotheses for this improved growth included stimulating intestinal vitamin synthesis, decreasing microbial L. A. Wythe · S. C. Ricke (*) Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, USA e-mail: [email protected] D. K. Dittoe Department of Animal Science, University of Wyoming, Laramie, WY, USA © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_4

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competition for nutrients, and inhibiting pathogens (Economou and Gousia 2015; Huyghebaert et al. 2011; Ricke et al. 2012). Likewise, the basis for the prophylactic administration of veterinary-based antibiotics to food animals has been attributed to enhancing production, improving feed conversion, and treating diseases (Beyene 2016). However, a movement away from their use in food production has emerged and become established as a policy. Regulations have been implemented in the European Union since 2006 (European Commission 2005). In 2017, the US Food and Drug Administration (FDA) removed all growth-promotion clearances for medically important antibiotics, and those administered in the feed for disease control became classified as veterinary feed directive drugs (Smith 2019). Part of this concern is related to the appearance of antibiotic-resistant foodborne pathogens such as Salmonella, Listeria, and Campylobacter, which are associated with food animal production and processing and which present public health challenges (Marshall and Levy 2011; Ricke et al. 2012; Jarvis et al. 2015; Ricke and Calo 2015; Yang et al. 2019a, b). There is a global concern for the appearance of antibiotic residues in food, animal meat, and egg products related to such factors as improper antibiotic usage, failure to adhere to the appropriate withdrawal period, and the potential increased usage of antibiotics in low-income countries that are shifting to intensive animal production systems (Beyene 2016; Rana et al. 2019; Hedman et al. 2020). Concerns are not limited to food animals but rather also includes the impact of waste materials potentially containing antibiotic-resistant pathogens that ultimately enter groundwater, surface water, and land applications of animal wastes such as poultry litter (Roe and Pillai 2003; Yang et al. 2019a). Therefore, US federal regulatory agencies are highly engaged in the examination and use of antibiotics in the food animal industry. For example, both the US FDA and the US Department of Agriculture (USDA) have conducted extensive research, surveillance programs, and compliance actions to develop detection methods for antibiotic residues and monitor tissues residues in poultry products (Donoghue 2003). Understanding the motivation for implementing AGPs in the poultry industry requires a historical context of the development of the modern commercial poultry industry and how this became possible. The poultry industry has become a major agriculture sector in the United States, where the yearly consumption per capita has increased by over 20 pounds from 2000 to 2019 (US Poultry and Egg 2022; National Chicken Council 2021). Within 50  years, the US broiler industry has evolved to become highly efficient and vertically integrated (National Chicken Council 2021). Both market demands and scientific advancements in nutrition and genetics have contributed to this remarkable rise in poultry production. This review aims to provide a historical evaluation of the nutritional and genetic advancements that led to the poultry industry’s utilizing AGPs, the subsequent phasing out of their use, and the rationale for using feed additive alternatives.

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4.2 Broiler Performance and Genetics Current poultry diets contain precise formulations of macro- and micronutrients such that modern genetic lines can reach their optimized growth potential; however, improved nutrition accounts for only approximately 15% of the changes in broiler performance since the 1950s (Havenstein et al. 2003; Dittoe et al. 2020). Instead, genetics accounts for the remaining improvement (Havenstein et  al. 2003). The broiler industry continues to demand faster-growth and more-efficient birds, and breeder operations have responded by selecting progeny for improved performance and feed efficiency (Tixier-Boichard et al. 2012; Dittoe et al. 2020). In turn, growth occurs faster with less feed intake, causing younger, heavier birds to reach the processing line, thus decreasing overhead costs per unit of meat (Tixier-Boichard et al. 2012; Dittoe et al. 2020). Chickens were initially kept for egg production instead of solely for meat production (Daniel et al. 2011; Roto et al. 2015; Dittoe et al. 2020). However, layers have been bred to be smaller and more feed efficient while selecting for egg quality and egg number, including shell quality and average egg weight (Anderson et al. 2013). The layer industry has continued to evolve, introducing battery cages in the 1930s to move hens from the ground and offering several advantages, such as cleaner eggs, labor reduction, more-uniform egg production, decreased competition among birds, and minimal fecal contamination of feed and water, among others (Kidd and Anderson 2019). While more-significant numbers of eggs were produced, specific challenges, such as revising the nutritional formulation, had to be developed to replace the dietary needs met by their scavenging behavior (Kidd and Anderson 2019). By the 1980s, Technical advances in housing efficiency led to the multitier cage and automated egg systems (Kidd and Anderson 2019). More recently, thanks to pressure from animal welfare concerns, the layer industry has returned to cage-free practices and aviary systems to accommodate these issues for housing layers (Anderson 2009; Mench et al. 2011). However, the impact of these systems on issues such as food safety and bird health is still being discussed (Holt et  al. 2011; Holt 2021). Meanwhile, because of diverging needs, the broiler industry was motivated to genetically select different traits in their birds. The winning bird of the Chicken of Tomorrow Contest in 1974 grew to 5.7 pounds by 7 weeks and 5 days, while the winning bird of 1949 grew to the same weight by 13 weeks and 2 days (Gordy 1974; Dittoe et al. 2020). The practice of crossing breeds led to the development of a cross of a Cornish gamebird female with a White Plymouth Rock male that boasted a broader breast with greater potential for breast meat development (Skinner 1974; Dittoe et al. 2020). Similarly, the application of quantitative genetics from the early 1950s spurred the development of commercial breeder operations, allowing for the performance improvements needed for the broiler industry to reach the present commercial levels. Zuidhof et al. (2014) pointed out that much of the early genetic selection in broilers was based on economically driven attributes and consumer shifts in market demand and included metrics such as body weight, feed

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consumption, feed conversion ratio, and yield. To illustrate this, they compared heritage broiler genetic lines representative of those from 1957 or 1978 with those from a 2005 commercial broiler genetic line (Zuidhof et al. 2014). They concluded that by 2005, there was a 400% increase in broiler growth and a 50% reduction in feed conversion ratio (Zuidhof et al. 2014). In more-recent times, the emergence of next-generation sequencing (NGS) has led to an array of applications, from the whole-genome sequencing (WGS) of microorganisms, including foodborne pathogens, to the WGS of the livestock genome and the application of an omic approach to animal agriculture. This has been coupled with the need for high-throughput phenotyping and the management of large data sets for animal agriculture (Koltes et al. 2019). In turn, the understanding of the evolution of the avian genome and the subsequent emergence of domesticated chickens has occurred, including potential insights into evolutionary traits that may have been selected in response to production environment requirements (Burt 2002; Jarvis et al. 2014; Lawal et al. 2018). Similarly, transcriptomic analyses and other molecular techniques, such as polymerase chain reaction (PCR) assays, have been used to describe various physiological parameters, including skeletal muscle development through coding and noncoding RNA (Li et al. 2012); potential traits underlying growth-related and meat quality–related phenotypes (Yuan et al. 2018; Teng et al. 2019; Allais et al. 2019; Yang et al. 2021; Guan et al. 2022); and egg weights, ovaries, and the genetic regulation of follicle development (Liu et al. 2018; Zhou et al. 2020; Overbey et al. 2021). A vital component of these advances has been identifying housekeeping genes involved in maintaining levels of basal cellular function that are sufficiently stable to serve as internal baseline controls for quantifying tissue gene expression by using quantitative PCR (Hasanpur et  al. 2022). Transcriptomics has also been used to identify potential genetic markers for resistance to Salmonella Enteritidis and S. Gallinarum infections (Matulova et al. 2012; Psifidi et al. 2018). As detailed understandings of genetic information continue to improve, methods to select or improve broiler lines are expected to continue, especially as various biotechnology industries expand (Tizard et al. 2019). Of these biotechnological advancements, gene-editing tools, such as clustered regularly interspaced short palindromic repeats (CRISPR), may address many of the growth-related and pathogen-based issues that occur in the poultry industry (Tizard et al. 2019; Khwatenge and Nahashon 2021). The opportunity to employ some of these genetic approaches during the embryonic development of the chick is now being considered (Liu et al. 2020; Kanakachari et al. 2022).

4.3 Nutritional Advancements in the Poultry Industry The first complete broiler feed was developed in 1925 by the Beacon Milling Company, followed by a coccidiosis control mash diet by 1929, altering the landscape of poultry feed and nutrition (Sawyer 1971; Dittoe et al. 2020). Following the introduction of a protein-inadequate but high-energy poultry diet at the end of World

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War II, the calorie–protein ratio and metabolizable energy (ME) content were evaluated in broiler diets, and research continued toward correcting for zero nitrogen-­ retention ME (AMEn) (Fraps et al. 1940; Sawyer 1971; Elwinger et al. 2016; Dittoe et al. 2020). Finally, true metabolizable energy (TME) was described by Sibbald in 1976, paving the way for nutritional studies to shift their emphasis from macronutrients to micronutrients (Dittoe et al. 2020). It was not until the Third World Poultry Congress (1927) that the poultry industry initiated a discussion on protein requirements, despite the first use of the term in 1834 (Elwinger et  al. 2016). Subsequently, the National Academy of Sciences’ National Research Council (NRC) published the first Nutrient Requirements of Poultry over a half-century ago (1954). The publication described the current understanding of crude protein needs and the requirements for the essential amino acids for starting chicks, poults, and laying hens (NRC 1954). In addition, amino acid contents were listed for various feed ingredients. However, variations can occur within plant and animal feedstuffs, depending on the regional location, soil and farm qualities, climate, and other factors. In tandem with protein and energy needs, mineral requirements have been extensively researched in the poultry industry, especially for fast-growing broilers. Minerals and mineral salts, such as calcium, sodium chloride, and phosphorous, are associated with skeletal formation, cofactors or structural components of hormones and enzymes, metabolic pathways, and osmotic balance and pH balance (Elwinger et al. 2016). Zinc has been explored as a mineral for supplementation in broilers and as a feed additive to induce molt in laying hens (Park et al. 2004). Additionally, Ca, P, and carbonate play roles in the eggshell formation and embryo development in layers and breeders. The general importance of minerals in animal diets, particularly NaCl, was reportedly acknowledged before the twentieth century. However, their specific roles in metabolism and growth have been characterized only since the 1920s and 1930s (Georgievskii 1981). The increased availability of radioactive isotopic tracers made it possible to study the role of minerals in detail. Thus, the ability to follow migration and distribution within organisms and understand the inherent biochemical importance in host metabolism and development has occurred within the past 50 years (Georgievskii 1981). Throughout an organism’s life span, bones continually release and reabsorb calcium and phosphorous to accommodate the needs throughout the rest of the body. Furthermore, dietary Ca and P are concurrently evaluated because deficiencies or excesses in one mineral lead to a clinical expression for the other mineral (Al-Masri 1995). Currently, the Ca:P ratio is estimated at 1:1–2:1  in fast-growing broilers but is assumed to be lower in slower-­ growing meat birds (Matuszewski et al. 2020). Despite advancements in Ca and P needs, there are still general misunderstandings of the necessary levels required in the diet, especially because the NRC requirements have not been updated since 1994 (Applegate and Angel 2014). By the time of the 1994 publication, phytases and available P were only beginning to be fully understood from a nutritional standpoint, and the delayed update has had negative consequences for environmental levels of phosphorous and been potentially detrimental to skeletal development in fast-growing broilers (Applegate and Angel 2014;

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Elwinger et al. 2016). Because poultry evolved for active flight, with a quintessential adaptive trait including low volumes of bone marrow and pneumatic bones, the fast-growing nature of modern broilers has led to increases in formative anomalies (Matuszewski et  al. 2020). Indeed, in an examination between a fast-growing genetic line versus a heritage line, Williams et al. (2000) reported that fast-growing genetic lines exhibited less mineralization and greater porosity in cortical bones than slow growers, and thus serving as 20-year-old evidence for needing an update to the dietary requirements published almost 30 years ago. Of the significant macro- and micronutrients, the reluctant acceptance of the “vitamin hypothesis” propelled nutrition’s irrevocable role in human medicine and animal agriculture forward (McDowell 1989a). With the “vitamin hypothesis” came the understanding that disease could have nutritional origins, moving away from the germ theory of all diseases (McDowell 1989a). In 1881, Swiss biochemist N. Lunin reported that animals failed to thrive on diets composed only of purified proteins, carbohydrates, fats, water, and salt and proposed the need for natural foods such as milk, which may contain quantities of unknown substances that are essential to life (McDowell 1989a). Subsequently, vitamins were first proposed by Casimir Funk in 1912, using the term to describe the amine structure of thiamin. The term has since evolved to describe the class of active organic compounds essential to various metabolic pathways throughout biological life. Vitamin A was the first described vitamin in 1913, and the remaining vitamins were identified by the 1940s, cobalamin (B12) closing out the discoveries in 1948 (Elwinger et  al. 2016; Semba 2012; DeLuca 1974). However, the complete characterization of the compounds continued into the 1970s, and poultry, rats, and dairy cattle were important research models used for these discoveries (Elwinger et al. 2016; Semba 2012; DeLuca 1974). The history of B12 begins with the 1824 description of fatal pernicious anemia in humans and the suggestion that it may be related to a digestive tract disorder (McDowell 1989b). In 1926, it was reported that 120–240 g/day of the oral ingestion of raw liver would alleviate this disease, suggesting the existence of an unknown factor within the liver and leading to 20  years of research activity to isolate and concentrate the substance (McDowell 1989b). Of the numerous attempts to describe and use this substance, the most notable was when Dr. William Bosworth Castle observed that a combination of an “intrinsic factor” within gastric juices and an “extrinsic factor” within beef muscle might be lacking in his anemia patients, and thus, he used his own stomach to process and regurgitate raw beef patties to test on his unknowing patients (Castle and Locke 1928; Castle 1929; Castle and Townsend 1929; Castle et al. 1930). Ultimately, both factors were isolated, and Castle reported that the extrinsic factor was identical to the newly discovered cobalamin in 1948 (Strauss and Castle 1933). Alternatively, no similar clinical presentations for B12 deficiency in animals occur in humans. Instead, B12 became recognized through attempts to raise swine and poultry on all-vegetable diets, resulting in poor performance. A similar recognition came by 1926: Liver extract and other animal-origin products stimulated growth (McDowell 1989b). The still-unknown compound, identified as animal protein factor (APF), was eventually identified as vitamin B12 and is considered one of

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the most significant advances in poultry nutrition (Rickes et al. 1948; Smith et al. 1952; Dittoe et al. 2020). The finding occurred in tandem with the continued explosive economic growth of the poultry industry, allowing for the maximization of body weight gain at a younger age. Poultry nutrition continues to be refined as dietary requirements become more established. Indeed, comparative genomics and nutrition advances should lead to further progress (Klasing 2005). However, as Klasing (2005) pointed out, avian species are nutritional specialists capable of consuming complex diets. The introduction of pasture flock or free-range production systems has added to the realization that poultry broilers and layers are capable of consuming a relatively wide range of diets, including insects and forages (Sossidou et al. 2015; Ricke and Rothrock Jr 2020; Ricke 2021). In conventional and free-range poultry production, rising feed costs have likely driven some more-recent interest into exotic feed additives such as insect meal and other nontraditional feed supplements (Biasato et al. 2018; Józefiak et al. 2020). Insect-derived feedstuffs offer a lower environmental footprint, minimal competitiveness with human food, and the positive modulation of the gastrointestinal tract (GIT) microbiota by their respective contents of chitins, lipids, and antimicrobial peptides (Biasato et al. 2018; Józefiak et al. 2020). For example, black soldier larvae are being explored as potential replacements for corn, soybean, and fishmeal-based diets for laying hens and broilers (Heuel et al. 2021; Nassar et al. 2023; Noviadi et al. 2023). Another development that advances poultry nutrition is the introduction of in vitro assays that allow for the high-throughput screening of protein and amino acid bioavailability (Ravindran and Bryden 1999). Amino acid availability, in particular, has become an important consideration as supplementation with crystalline amino acids to achieve the optimal amino acid balance has become routine. In response to this, genetically modified auxotrophic intestinal Escherichia coli amino acid bioassays that use the microorganism’s extent of growth as an indicator of specific amino acid availability have been developed (Erickson et al. 2002; Froelich Jr and Ricke 2005; Chalova et al. 2009, 2010). As evidence of the bioassays’ utility, Chalova et al. (2007) demonstrated that the E. coli response was comparable to the corresponding chick bioassay for lysine availability from several poultry protein supplements. These microbial assays have the advantage of allowing for the screening of individual amino acid availability within a protein matrix of a particular poultry feedstuff without having to conduct chick bioassays. Knowing this offers the opportunity for the more-precise supplementation of required amino acids such as lysine and methionine and avoids excessive nitrogen emissions due to oversupplementation (Erickson et al. 2002; Kim et al. 2006). As these in vitro assays become further refined, the entire spectrum of amino acids and other nutrients could be assayed for availability assessment.

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4.4 Feed Additives As previously described, poultry nutrition is based on fine-tuned nutritional components met through nutritional feed ingredients. Feed additives have historically been classified as feed ingredients that do not necessarily satisfy nutrient roles but instead induce a desired response in the animal, such as growth performance (Hutjens 1991; Pandey et al. 2019). Similarly, feed additives such as feed enzymes can also be specifically designed to improve the nutritive quality of feed or animal health and performance (Cowieson and Kluenter 2019; Pandey et  al. 2019). The bans and restrictions on AGPs intensified the search for alternative feed additives that approximate the benefits associated with antibiotics, and thus inevitably, comparisons have been made to antibiotic attributes (Applegate et  al. 2010; Yadav and Jha 2019). Therefore, the history and the mode of action of AGPs and of feed additives will be discussed in the following sections.

4.5 Antibiotic Growth Promoters Although penicillin was discovered in 1928 by Alexander Fleming, it would take until the 1940s for a sufficient quantity of penicillin to be validated for treating illness (Jones and Ricke 2003). In 1935, Prontosil, the first drug proven effective against Gram-positive bacteria, was marketed by Bayer, eventually marketing it for veterinary use in animals in 1938 (Kirchhelle 2018). Subsequently, gramicidin and penicillin were tested and used in the 1940s to treat mastitis outbreaks in dairy cattle to battle milk production issues during the Second World War (Kirchhelle 2018). Moore et al. (1946) were the first to include antibiotics in chicken rearing, demonstrating an increase in weight gain due to this inclusion, and by 1948, Merck released the first antibiotic, an anticoccidial sulfaquinoxaline, officially licensed for routine inclusion in poultry feed. As the global political climate shifted from world wars to cold wars, capitalist and noncapitalist systems both began relying heavily on animal production exports as means of international competition, and antibiotics became increasingly popular for decreasing labor costs and disease prevalence, thus increasing yields (Kirchhelle 2018). Subsequently, small-scale farming operations could spend less time caring for individual animals, thus allowing for the animal agricultural industry to evolve toward confined animal feeding operations (CAFOs) that employed herd-health techniques with a greater number of animals. Antibiotics soon became commonly used as antibiotic growth promotors (AGPs) to prevent the risk of illness and promote growth in broilers in CAFOs. Numerous hypotheses have been formed to explain how AGPs alter an animal’s ability to grow more efficiently. Most of these have revolved around interactions with the GIT microbial populations, including (1) a reduction in the total microbial density; (2) promoting a favorable microbial balance and subsequently decreasing the risk of infection; (3) a reduction in potentially toxic bacterial metabolites such

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as amines, phenols, ammonia, and indoles; and (4) better nutrient absorption thanks to a thinner epithelial lining in the intestines (Gaskins et al. 2002). More specifically, Gaskins et  al. (2002) described the difference in the upper small intestinal microbiota in swine as being dominated by acid-tolerant taxa such as lactobacilli and streptococci, the lower small intestines and the large intestines becoming more ecologically diverse because digesta moves more slowly throughout the tract. In turn, the upper small intestinal microbiota competes with the host for energy sources and amino acids, where as much as 6% of the net energy is lost to bacterial competition (Hedde and Lindsey 1986; Vervaeke et al. 1979; Cowieson 2022). Of course, poultry GIT physiology and microbial inhabitants vary compared to mammalian species, but germ-free (GF) models suggest a similar story. Coates et al. (1963) compared GF chicks to chicks raised in a conventional (CV) setting, simultaneously comparing evaluations of using sterile feed against those of using nonsterile feed, both with and without the inclusion of penicillin. All the GF chicks exhibited improved growth over the CV chicks. However, there was no difference between the GF chicks fed penicillin and those not provided the antibiotic. Alternatively, they reported improved growth in the CV chicks when fed penicillin with either a sterilized diet or a nonsterilized diet. The improved growth in birds raised in a GF environment not enhanced with antibiotics served as early evidence for AGPs’ eliciting a growth-promoting effect via an interaction with GIT microorganisms. Indeed, multiple early research efforts comparing GF poultry and CV poultry verified this growth improvement, where the caveat of these diets was meeting the specific needs of the GF intestinal physiology (Cowieson 2022; Forbes 1959). Modern molecular and sequencing methods have allowed for the greater elucidation of the potential effects that AGPs have on the GIT microbiome. Current analytical approaches can characterize changes in community structure and define the genetic and metabolic changes that occur thanks to AGP supplementation. Robinson et al. (2019) explored the effects of various classes of AGPs on the cecal community structure of 14-day-old broilers. The analysis utilized the following antibiotics: The cyclic peptide antibiotic bacitracin (BMD), which functions by inhibiting bacterial cell wall synthesis; tylosin, a macrolide; virginiamycin, a streptogramin, which inhibits protein synthesis in Gram-positive bacteria; and the polyether ionophores monensin and salinomycin, which target coccidia and Gram-positive bacteria with their corresponding effects on uncoupling ion gradients in bacterial cell membranes (Broom 2017; Butaye et al. 2003). Robinson et al. (2019) reported decreased evenness with the use of BMD, tylosin, and virginiamycin, where only tylosin resulted in a significant reduction in evenness. However, there was increased evenness after the supplementation of both ionophores (Robinson et al. 2019). Alternatively, all AGPs decreased richness, but only tylosin and both ionophores were significant. When both classes of AGPs were compared, only the ionophores significantly affected alpha diversity. The reported beta diversity analyses revealed that all AGPs were significantly different in Bray– Curtis dissimilarity. The Jaccard similarity index values were not different between the birds fed the control and those treated with tylosin (Robinson et al. 2019). The reported taxonomical analyses revealed specific differential effects depending on

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the AGP type, where 898 OTUs were regulated by at least one AGP, but only 59 taxa were impacted by all five. Of the 59 taxa, several were upregulated through AGP supplementation: members of the Escherichia/Shigella, Blautia, and Clostridium XIVa genera and a member of an undescribed Clostridiales order. Alternatively, Robinson et al. (2019) reported members of the Clostridium XIVb and Lactobacillus genera as downregulated. The group concluded that their results indicated a tendency for AGPs to enrich butyrate- and lactic-acid-producing bacteria while reducing bile salt hydrolase producers such as Lactobacillus, which may lead to enhanced metabolism and the increased utilization of dietary components. Indeed, as previously mentioned, Gaskins et  al. (2002) reported growth-suppressing metabolites produced by Streptococcus and Lactobacillus in swine studies and that AGPs reduce the abundance of these taxa in the small intestines. However, Robinson et al. (2019) reported the upregulation of Streptococcus in their cecal evaluations. Further elucidating the effects on various Gram-positive bacteria should be continued by using ileal and cecal microbiota analyses, and repeated measures within blocks may determine the community structural changes as birds mature beyond the age of 14 days. Zou et al. (2022) compared 60 broilers raised on corn-soybean meal diets with those raised on wheat-based diets, each in the presence or absence of the AGP bacitracin, to determine their ages and diets, the GIT sampling site, and the AGP effects on the taxonomical and metabolic effects of the GIT microbiome through 16S rRNA gene sequencing and metatranscriptomics. The researchers reported greater influence on the taxonomical diversity throughout the GIT owing to the sampling site and age over diet or AGP use. However, the diet was still more impactful than AGP use was. A weighted UniFrac PCA analysis revealed that diet affected diversity in the gizzard on days 10, 24, and 40, while AGPs had no effect. The diet and age interaction was significant on day 24 in gizzard diversity. In the duodenum, the diet was significant on day 10, while AGP supplementation was significant on day 10 and day 40. The effect of diet was significant on the microbial compositional profiles on day 10 in the jejunum, and AGP supplementation had no effect. Within the ileum, the effect of diet was significant on days 10, 24, and 40, while AGP was again significant only on day 10. Cecal compositional profiles were affected by diet on days 24 and 40 but only on day 40 for AGP supplementation. Differences occurring between age and sampling sites are not necessarily surprising given that both factors have been previously reported as important in describing the GIT microbiota because the physiology significantly varies from the beak to the colon and because the microbiome changes as birds mature (Pan and Yu 2014; Stanley et al. 2014; Xiao et al. 2017; Ocejo et al. 2019; Richards-Rios et al. 2020; Rychlik 2020). For instance, Ocejo et al. (2019) characterized the cecal microbiota in broilers through 16S amplicon sequencing. Ocejo et al. (2019) reported Shannon and Simpson values as the lowest when birds were 3 days old and the highest at 14 days, followed by a decrease on days 29 and 42. Similarly, Bray–Curtis principal coordinate analysis (PCoA) plots revealed apparent separations in diversity across time, where compositional profiles on day 3 were fully separated from the remaining sampling days; however, the day-28 compositional profiles were in line with those distributed between the day-14 and day-42 compositional profiles (Ocejo

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et al. 2019). The relative abundances of the top 15 families also varied across days, some families increasing or decreasing across time and some taxa increasing between days 14 and 28 and then decreasing again by day 42 (Ocejo et al. 2019). These fluctuations suggest competitiveness among taxa. Competitiveness among individual members of the GIT microbial community can be detected in microbial taxa differences and metabolic functionality. For example, Zou et  al. (2022) reported that AGPs disrupted community organization by potentially altering the influential taxa that promote the exclusion of other taxa, particularly through regulating energy-production metabolic pathways. Lactobacillacea were reported to dominate the active glycolysis enzyme expression in corn-based diets. At the same time, Lachnospiracea, Clostridiaceae, and Enterobacteriaceae were observed to dominate glycolytic expressions in the wheat-­ based diets on day 24, and glycolytic expression overall was increased when AGPs were used (Zou et al. 2022). However, these patterns did not continue through day 40. Furthermore, similarly high representations of Lactobacillacea and Lachnospiraceae per each diet on day 24 exhibited differential enzyme expression in purine synthesis, where the corn-based diets were restricted to salvage pathways that became more limited by day 40. However, with the addition of AGPs, Zou et al. (2022) reported the reduced representation of the Lactobacillacea expressing purine synthesis pathways in the corn-based diets at day 24, suggesting a complex relationship between purine biosynthesis and potential stress responses due to AGP supplementation. Likewise, Yang et al. (2019) previously reported an interaction between purine biosynthesis and antibiotic lethality as discovered through machine learning with E. coli mutants. The machine-learning approach yielded pathway mechanisms such that the relative contributions of each pathway to the lethal mechanism of AGPs could be quantified. The group analyzed E. coli mutants deficient in various ribonucleotide synthases and mutases and reported increased lethality among the mutants when exposed to gentamycin. Furthermore, biochemical supplementation with purine biosynthesis substrates decreased lethality (Zou et al. 2022). Despite the overarching benefits on broiler growth and health, the US poultry industry has begun turning away from the use of AGPs as a direct response to public concern over antibiotic resistance in foodborne pathogens and in other human medical areas (Aarestrup 2015; Broom 2017; Van Boeckel et al. 2017; Dittoe et al. 2018, 2020). In response to an antibiotic-resistant Salmonella Typhimurium outbreak in the United Kingdom, the Swann Committee was appointed to identify potential resistance in pathogens (Doeschate and Raine 2006). In 1969, the Swann Committee ultimately published the following recommendation: The AGPs to be allowed for use in animal feed must have limited application in human medicine (Doeschate and Raine 2006). Sweden banned AGPs in 1985, the first country to do so, and the United Kingdom adopted the Swann Committee’s recommendation by 1998 (Doeschate and Raine 2006; House of Lords 1998). After joining the European Union in 1995, Sweden encouraged the remaining members to ban AGPs (Doeschate and Raine 2006). The United States soon adopted the National Antimicrobial Resistance Monitoring System to monitor antimicrobial resistance in bacteria

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(1996), and the World Health Organization and the Economic and Social Community of the European Union deemed AGPs as a public health concern because of the potential for AGP resistance (1997) (Castanon 2007; Jones and Ricke 2003). With the implementation of Regulation 1831/2003, all AGPs were officially banned in the European Union as of January 1, 2006 (Castanon 2007). Poultry products have been linked to Salmonella and Campylobacter infections that are resistant to multiple antibiotics, including fluoroquinolones, gentamicin, streptomycin, tetracyclines, sulfonamides, and some β-lactam antibiotics (Economou and Gousia 2015; Ricke and Calo 2015; Dittoe et al. 2018; Yang et al. 2019b). However, rates of increase in antibiotic resistance have also been reported for the antibiotics not used in agriculture (Economou and Gousia 2015). Nonetheless, the US poultry industry has moved toward phasing out AGPs to satisfy US consumer concerns and to meet exportation requirements (Dittoe et al. 2018; Yadav and Jha 2019). In response to phasing AGPs out, however, the intersection of poultry health and poultry performance has reached the forefront of the industry and academic research efforts to discover viable alternatives to AGPs. The necessary optimization of growth and efficiency, coupled with the now-limited options for minimizing infection, has now reached the forefront of the poultry industry, thus leading to the need to find suitable feed additive replacements for AGPs.

4.6 Alternatives to Antibiotic Growth Promotors Diet has a defining impact on GIT microbiota composition and affects growth performance. Therefore, feed additive alternatives that improve growth performance are at the forefront of research. Given the proposed mechanisms of AGPs, additives that modulate the microbiota and GIT health and immunity are the most likely candidates for replacements. Furthermore, the main components of the diet, such as its grain source, can influence the type of feed additives that will have the most significant impact (Huyghebaert et al. 2011). The effect of the main dietary components is particularly evident in those grain components that elicit prebiotic-like properties, such as the bran fraction (Ricke 2018). As more becomes known about the GIT microbial responses to complex feed sources, the GIT modulation impact will likely be relatively elaborate (Zhuang et al. 2017; Ricke 2018). Various alternatives continue to be evaluated in academia and industry, all with various modes of action. These include biological and chemical interventions that vary in functionality and their manner of improving GIT and modulating microbiota taxonomic composition and metabolism. Biological agents can consist of exogenous enzymes, probiotics, and prebiotics, while chemical agents can include acidifiers and phytochemicals (Ricke 2003, 2018; Applegate et  al. 2010; Clavijo and Flórez 2018; Dittoe et al. 2018; Cowieson and Kluenter 2019). Additives can also be categorized according to their intended impact on the animal, such as growth-­ promotion, GIT modulation, pathogen prevention, and other less-characterized but potentially influential factors (Pandey et al. 2019).

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When targeting foodborne pathogen prevention in poultry, feed additives can be employed through two general strategies: using them as antimicrobial agents so that indigenous GIT pathogens are inhibited or removed, such as with antibiotics, organic acids, formaldehyde, bacteriophages, and bacteriocins (Joerger 2003; Ricke 2003; Sirsat et al. 2009; Clavijo and Flórez 2018; Dittoe et al. 2018; Ricke 2018; Ricke et al. 2019, 2020a), or introducing additives that alter the microbiota composition in a way that generates a GIT microbial environment hostile to initial pathogen colonization, which is especially important while the bird is young (Ricke et al. 2020b; Ricke 2021). The optimized control of foodborne pathogens in the poultry GIT may entail a multiple-hurdle approach involving agents such as bacteriophages to reduce already-colonized pathogens, followed by a feed additive such as a prebiotic or a probiotic that prevents future pathogen colonization. Probiotics and prebiotics are composed of a wide range of biological additives with differing modes of action that, in general, elicit beneficial responses in both growth performance and GIT development (Torres-Rodriguez et  al. 2007; Sohail et al. 2010; Ashraf et al. 2013; Li et al. 2016; Ricke 2018; Yadav and Jha 2019). Probiotics have evolved over the years, starting from undefined cultures, to fully defined and identified mixed cultures, to single cultures such as Lactobacillus species and Bacillus species that became more commonly used (Ricke and Saengkerdsub 2015; Clavijo and Flórez 2018). Prebiotic classification and their use in poultry have also evolved over the years, starting with well-defined carbohydrate polymers such as fructooligosaccharides, but now, more-complex sources are being considered as possessing prebiotic-like activities (Ricke 2015, 2018; Gibson et al. 2017; Zhuang et al. 2017). Another group of additives, yeast fermentation culture products, uses prebiotic fibers fermented by either yeasts or bacteria, resulting in a product that includes bioavailable nutrients, prebiotics, and fermentation metabolites (Roto et al. 2015). Depending on the drying and sterilization processes, yeast fermentate products can be further delineated into synbiotics and postbiotics.

4.7 Conclusions and Future Directions Because of the increased movement toward the removal of antibiotics from poultry rearing, the industry has been tasked with identifying alternatives that elicit similar responses to antibiotic growth promoters while promoting the birds’ health and welfare (Cervantes 2015). Antibiotics have been used because of their ability to improve weight gain by reducing infections by modulating the GIT and the GIT microbiota, thus reducing competition with the host for nutrients, enhancing nutrient digestibility, stimulating the immune system, and thinning the intestinal wall (Huyghebaert et  al. 2011). Exact replications of these beneficial responses with nonantibiotics remains a challenge partly because some of the impacts attributed to antibiotics are not always well identified mechanistically and partly because alternative feed additives either represent different chemical structures or are biological agents such as probiotics or bacteriophages, which behave differently.

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Not surprisingly, given the need to replace AGPs, a swathe of feed amendments are continually being explored as potential alternatives for AGPs (Van Immerseel et  al. 2009; Clavijo and Flórez 2018; Pandey et  al. 2019; Perricone et  al. 2022). However, the mechanisms of action on both the host and microbiota have not been fully elucidated, thus suggesting the need for continued research. Previous research has compared growth performance and GIT sampling throughout the life span of the bird but typically provides only singular responses from microbiota compositional profiles, particularly at the end of the life span (Roto et al. 2017; Nelson et al. 2020; Liu et al. 2021). As parts of such investigations, some comparisons with antibiotic treatments are warranted to determine whether the alternative feed additive can approximate the corresponding antibiotic treatment and how microbial antibiotic resistance is impacted. In addition, research that analyzes microbiota development through 16S rRNA gene sequencing by utilizing repeated sampling methods over the bird’s life cycle could help describe how an alternative feed additive impacts microbiota development in tandem with growth performance and GIT development.

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Chapter 5

Prebiotics with Plant and Microbial Origins Celeste Alexander, Ching-Yen Lin, Brittany M. Vester Boler, George C. Fahey Jr., and Kelly S. Swanson

Abstract  As we have begun to accept the use of probiotic approaches to replace the benefits of antimicrobials in animal production, we also should include prebiotics in animal rations in forms that may support the activity of the host microbiota in an economically feasible manner. While currently established prebiotics are carbohydrate based, prebiotics may include noncarbohydrate and nonfood substrates, with applications in animal production. One approach that has exciting possibilities is to include feedstuffs that naturally contain prebiotic compounds or properties to selectively provide resident microorganisms a competitive advantage that confer a health benefit to the host. Many phytochemical and bioactive substrates (e.g., organic acids) are capable of modulating the gastrointestinal microbiome composition and activity, providing a health benefit to the host, but they are not classified as prebiotics, because they are not selectively utilized by host microorganisms. This chapter discusses the potential of selecting specific feedstuffs as prebiotic approaches to manipulating the respective microbial populations of the guts of food animals, pets, and humans.

C. Alexander · C.-Y. Lin Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA B. M. Vester Boler Nestlé Purina North America, St. Louis, MO, USA G. C. FaheyJr. Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA K. S. Swanson (*) Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_5

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5.1 Introduction The food industry is constantly shifting focus on the basis of what is most important to the consumer. Currently, public interest is directed toward products that are marketed as providing health benefits. Such products are touted as either having health-­ promoting or disease-preventing effects. Because of the increased demand, there is a growing interest in research that helps to identify new products that may lead to health benefits and help food companies make accurate claims on their products. One area that has garnered substantial public interest is the modulation of the gastrointestinal microbiome via prebiotics. The concept of prebiotics was first introduced in 1995 by Gibson and Roberfroid, who defined them as “non-digestible food ingredients that beneficially affect the host by selectively stimulating the growth and/or activity of one or a limited number of bacterial species already resident in the colon” (Gibson and Roberfroid 1995). At that time, the microbiota were studied by using primarily culture-based methods, and bifidobacteria and lactobacilli were the primary organisms targeted in prebiotic feeding studies. Over time, DNA-based techniques, namely 16S rRNA gene sequencing, that allowed for a far more comprehensive analysis and understanding of the gastrointestinal microbiome were developed (Holscher 2017). In 2017, the International Scientific Association for Probiotics and Prebiotics (ISAPP) released an expert consensus statement with an updated definition of prebiotics: “substrates that are selectively utilized by host microorganisms conferring a health benefit” (Gibson et al. 2017). This definition no longer states that a prebiotic selectively stimulates the growth of specific bacterial species but rather that the selective utilization of these compounds by resident microorganisms must confer a health benefit to the host. Additionally, although all the currently established prebiotics are carbohydrate based, this updated definition expands the concept of prebiotics to include possible noncarbohydrate and nonfood substrates and includes applications in animals. Importantly, the classification of a substrate as a prebiotic depends on the target host. Additionally, many exogenous substrates are capable of modulating microbiome composition and providing a health benefit to the host, but they are not classified as prebiotics, because they are not selectively utilized by host microorganisms (Gibson et  al. 2017). Such substrates include antibiotics, minerals, vitamins, and bacteriophages.

5.2 Nondigestible Oligosaccharides and Fermentation Currently, all the established prebiotics are carbohydrate based and fall into the category of nondigestible oligosaccharides (NDO). Oligosaccharides are low-­ molecular-­weight carbohydrates with a low degree of polymerization (DP) or chain length. They are either 2–20 monosaccharide units or no greater than 10 monosaccharide units, depending on the official definition used (IUB-IUPAC 1982; Food and Drug Administration 1993). These prebiotic oligosaccharides are not able to be

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digested by the host, because the anomeric carbon atom has a configuration making the osidic bond resistant to mammalian enzymes. Microorganisms are capable of hydrolyzing these prebiotics through a large family of enzymes that are not produced by mammals, thus fulfilling the “selective utilization by host microorganisms” requirement (Lombard et al. 2014; Alexander et al. 2019). Because all the current established prebiotics are NDO, much of the focus on potential mechanisms of action is on microbial fermentation and the production of fermentative end products. Briefly, the process of fermentation involves the hydrolysis of NDO, or other fermentable carbohydrates, into their constituent sugars, which are then fermented to produce short-chain fatty acids (SCFA) and H2 and CO2 gases. Greater DP and branching are associated with sustained fermentation throughout the large intestine, while nondigestible carbohydrates that are shorter and less branched are fermented more rapidly and proximally (Holscher 2017; Alexander et al. 2019; Hernot et al. 2009). The anatomical structure of the gastrointestinal tract (GIT) also greatly influences the location of fermentation (i.e., pre- or postgastric) (Cummings and Macfarlane 1991). SCFA produced from the fermentation of NDO prebiotics provide energy sources for both host growth and microbial growth and for a variety of systemic physiological effects (Holscher 2017; Koh et  al. 2016). Once absorbed, SCFA are either metabolized by the colonocyte for energy or released into portal circulation for use by other tissues. Butyrate is preferentially used by colonocytes for energy and regulates their proliferation and differentiation (Wong et al. 2006).

5.3 Health Benefits and Industrial Use of Prebiotics Many health benefits associated with prebiotics stem from the production of SCFA, which, in addition to providing energy to the host and resident bacteria, promote bile acid excretion and reduce GI luminal pH to directly limit pathogen growth and enhance mineral absorption. SCFA also activate several G-protein-coupled receptors and act as histone deacetylase inhibitors to regulate gene expression, stimulate hormone and gut peptide synthesis, and initiate signal transduction pathways in the gut and peripheral tissues. These actions result in a multitude of effects on gastrointestinal health and systemic inflammation and metabolism, such as improved gut barrier function, increased glucose utilization, and reduced cholesterol synthesis (Alexander et al. 2019). Therefore, in both humans and animals, prebiotic consumption has been associated with reduced risks and symptoms of many metabolic and inflammatory diseases, including inflammatory and infectious bowel diseases, cardiovascular diseases, colorectal cancer (CRC), obesity, and diabetes (Alexander et  al. 2019; Kasubuchi et  al. 2015; Deng et  al. 2013; Markowiak and Ślizewska 2018). Prebiotics have also been shown to alleviate constipation, reduce the risk of infection and diarrhea, increase satiety, modulate lipid metabolism and endogenous cholesterol synthesis, treat hepatic encephalopathy, and improve immune responses (Swennen et al. 2006; Mussatto and Mancilha 2007; Marteau 2001; Kaur and Gupta

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2002; Jenkins et al. 1999; Kelly-Quagliana et al. 2003; Manning and Gibson 2004; Meyer 2015). Many prebiotics also modulate gastrointestinal microbiota and are well known for increasing the abundance of potentially beneficial bifidobacteria and lactobacilli. Prebiotics are popular food additives largely because of their low caloric values and abilities to elicit a variety of beneficial physiological effects. However, prebiotics have many uses in the food industry beyond their systemic health properties. Prebiotics are water soluble and sweet tasting; however, the sweetness decreases with increasing DP. These ingredients can aid in water binding and gelling capacity, which can potentially decrease the amount of fat required in food products (Roberfroid and Slavin 2000). They have been used in food products to add bulk, mask the taste of artificial sweeteners, and improve mouth feel due to their viscosity (Mussatto and Mancilha 2007; Crittenden and Playne 1996). NDO prebiotics are also generally recognized as safe (GRAS) by the US Food and Drug Administration and can therefore be added to products meant for human and animal consumption. Additionally, thanks to being heat resistant, prebiotics remain intact during baking processes and can therefore be incorporated into a wide variety of food products (Panesar et al. 2013). Prebiotics generally lead to only transient side effects when consumed in large doses; however, what constitutes a large dose is person/animal dependent. Side effects of NDO prebiotics can include severe flatulence, intestinal discomfort, and osmotic diarrhea (Pedersen et  al. 1997; Cummings et  al. 2001; Juskiewicz and Zduńczyk 2002). To date, the only definitively established prebiotics are three NDO: fructans (which include fructooligosaccharides (FOS), oligofructose, and inulin), galactooligosaccharides (GOS), and lactulose. Several other NDO are candidate prebiotics because there is a large body of evidence suggesting they meet the requirements of a prebiotic, but no definitive statement on them has been made. Such NDO include lactosucrose, isomaltooligosaccharides (IMO), xylooligosaccharides (XOS), polydextrose (PDX), and bovine- and human-milk oligosaccharides (BMO and HMO). While other carbohydrate-based and noncarbohydrate-based compounds may have prebiotic potential, either limited research is available or current data are conflicting, which do not allow them to be classified as prebiotics. The remainder of this chapter will describe the manufacturing processes and key health benefits of established prebiotics as well as other candidate carbohydrate- and noncarbohydrate-­ based prebiotics.

5.4 Methods of Manufacture There are three main manufacturing processes to obtain prebiotics: direct extraction from a naturally occurring source, the controlled enzymatic hydrolysis of high-DP polysaccharides into lower-DP oligosaccharides, and enzymatic-catalyzed synthesis via microbial action on simple sugars (Panesar et  al. 2013; Grizard and Barthomeuf 1999). These processes use various chemical reactions, defined in

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Table 5.1  Definitions of some processing terms Term Hydrolysis

Definition The cleaving of a molecule into two parts with the addition of a molecule of water Extraction The separation of compounds according to their solubility in two types of liquids (usually water and an organic solvent) Isomerization The transformation of one molecule into a different one with the same molecular formula but with a different structure Transglycosylation The transfer of a sugar residue from one glycoside to another

Table 5.1, and will be described in greater detail below. Common dietary sources of prebiotics include chicory roots, soybeans, garlic, onions, barley, Jerusalem artichokes, asparagus, and rye.

5.5 Established Prebiotics 5.5.1 Fructans Fructans include inulin-type and levan-type oligosaccharides. Inulin-type fructans have β-2,1-D fructofuranosyl units, are found in plants and synthesized by fungi, and have a DP value of 2–70. Levan-type fructans have β-6,2-D fructofuranosyl units, are found in plants and synthesized by bacteria, and have a DP > 30. Fructans naturally occur in plants such as chicory, Jerusalem artichoke, dahlia, salsify, gobo, onion, garlic, leek, and wheat byproducts and serve as energy sources for these plants. Only inulin-type fructans are proven prebiotics (Roberfroid et al. 1998). Inulin is manufactured through direct hot-water extraction from natural sources, mainly chicory root (De Bruyn et al. 1992). It is composed of β(2-1) linkages of glucose and fructose [GpyFn: α-D-glucopyranosyl-(β-D-­ fructofuranosyl)n  −  1—D-fructofuranoside] or only fructose [FpyFn: β-D-­ fructopyranosyl-(α-D-fructofuranosyl)n  −  1- D-fructofuranoside] (Roberfroid and Delzenne 1998). Between 2 and 70 units of fructose may be present in native inulin, and it has an average a DP of 10–20. Inulin comprises 15%–20% of chicory root fresh weight, and 55% of oligosaccharides have a DP of 2–19, 28% a DP of 20–40, and 17% a DP of > 40. It comprises 17–20% of Jerusalem artichoke fresh weight, and 74% of oligosaccharides have a DP of 2–19, 20% a DP of 20–40, and 6% a DP of > 40 (Van Loo et al. 1995). After the extraction of native inulin, the product then either undergoes industrial physical separation of long-chain fructans (De Leenheer 2007) or is partially hydrolyzed by endoinulinase to produce short-chain oligosaccharides, mainly oligofructose (Fig.  5.1). Oligofructose produced from inulin with a terminating glucose molecule is specifically called an FOS. FOS and oligofructose may contain longer-­ chain fructans (Crittenden and Playne 1996) and have DP between 2 and 10, with

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Fig. 5.1  Commercial production of inulin-type fructans from extraction of natural sources, partial enzymatic hydrolysis, or enzymatic synthesis from sucrose

an average of 5 (Roberfroid and Delzenne 1998). Alternatively, short-chain FOS (scFOS) can be synthetically produced through the transfructosylation of sucrose by using the β-fructofuranosidase enzyme (Crittenden and Playne 1996) from Aureobasidium pullulans (Yun 1996; Yoshikawa et al. 2008) or Aspergillus niger (Park and Almeida 1991). Further, scFOS contain 2–4 fructosyl units with a terminal glucose unit and an average DP of 3.5 (Roberfroid and Delzenne 1998). Synthetic FOS contain only GpyFn oligomers. These products may contain free glucose, fructose, and sucrose, which can be removed via chromatographic procedures to increase the purity of the final product. A large amount of starting material is needed to achieve efficient transglycosylation (Park and Almeida 1991). Inulin and FOS are perhaps the best established prebiotics (Roberfroid 2007) and the most extensively studied. In humans, inulin and FOS have been shown to improve glycemic control and mineral absorption, reduce circulating cholesterol concentrations and systemic inflammation, reduce cancer risk, improve gastrointestinal function, and modulate the gastrointestinal microbiota (Holscher 2017; Alexander et al. 2019; Kaur and Gupta 2002). In animals such as swine, poultry, cattle, and companion animals, these prebiotics have been shown to enhance growth, reduce blood cholesterol concentrations and insulin resistance, reduce enteric pathogens, improve immune function, and modulate gastrointestinal microbiome composition (Markowiak and Ślizewska 2018; Swanson et  al. 2002; Respondek et al. 2008).

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5.5.2 Galactooligosaccharides GOS are produced from lactose (Fig. 5.2) and are polymers of galactose units with a terminal glucose. The monomeric units are linked by a mixture of β-1,4 and β-1,6 bonds. Lactose undergoes transglycosylation from β-galactosidase enzymes, either galactosyltransferases or galactohydrolases. The types of GOS produced are dependent on the type of β-galactosidases used and on processing conditions (Sabater et  al. 2019). Galactosyltransferases move a galactose unit from the donor to the receptor molecule, forming a glycosidic bond. While the production of GOS is relatively efficient, galactosyltransferase enzymes are difficult to isolate, and their needing sugar nucleotides as substrates makes them cost-prohibitive to industry. Galactohydrolase enzymes, while more readily available, lack the stereoselectivity of galactosyltransferases (Tzortzis and Vulevic 2009). These enzymes are commonly derived from Aspergillus oryzae and Streptococcus thermophilus, which form β-1,6 bonds, or Bacillus circulans and Cryptococcus laurentii, which form β-1,4 bonds (Sako et al. 1999). Recent work has shown that dairy propionibacteria are also capable of synthesizing GOS (Sabater et al. 2019). During production, approximately 55% of the starting lactose is converted to GOS.  The GOS produced are mostly trisaccharides (namely 4′-galactosyllactose and 6′-galactosyllactose) and longer-chain oligosaccharides with 4 or more monosaccharide units. Generally, 80% of the oligosaccharides formed are trisaccharides (Playne and Crittenden 2004). Other products present at the end of the reaction include lactose, galactose, and glucose disaccharides and transgalactosylated disaccharides (Sako et  al. 1999). These transgalactosylated disaccharides have similar properties to longer-chain GOS (Ito et al. 1993). The commercial production of GOS often utilizes highly concentrated lactose from bovine milk whey (Mussatto and Mancilha 2007). Commercial GOS products

Fig. 5.2  Commercial production of lactose-derived prebiotics via tranglycosylation to produce galactooligosaccharides, alkali isomerization to produce lactulose, or tranglycosylation with sucrose to produce lactosucrose

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are typically made in batch systems for simplicity; however, this method is the least efficient, and most of the enzyme added to the initial reaction is lost. Continuous systems have been proposed to cut production costs by using ultrafiltration to retain soluble enzymes via enzyme immobilization (Tzortzis and Vulevic 2009). During batch reactions, multiple enzymes may be added at the initial reaction or in sequence during the reaction. The mixture is heated to facilitate lactose solubilization and drive the formation of oligosaccharides over the hydrolysis of lactose into monosaccharides (Playne and Crittenden 2004). Unreacted products may be removed by using chromatography, although lactose has been noted to be difficult to remove and leads to a loss of GOS. Furthermore, the product is decolorized, demineralized, and concentrated into a syrup or powder form. By maintaining strict production conditions, a very consistent product can be developed; however, all the final products are mixtures of various GOS products (Playne and Crittenden 2004). GOS stimulate an increase in bifidobacteria and lactobacilli abundance in the gastrointestinal microbiome (Ito et al. 1990; Bouhnik et al. 1997; Moro et al. 2002). Additionally, in clinical trials, GOS have been shown to reduce appetite, curb the glycemic response, decrease markers of inflammation, improve symptoms of irritable bowel syndrome, improve the symptoms and duration of common colds and flus, and increase mineral absorption (Alexander et al. 2019; Paganini et al. 2017; Vulevic et  al. 2015; Morel et  al. 2015; Wilson and Whelan 2017; Hughes et  al. 2011). In animals, GOS have been shown to improve gut function, enhance growth, and modulate immune responses (Nawaz et al. 2018; Tian et al. 2018).

5.5.3 Lactulose Lactulose, like GOS, is produced from lactose (Fig. 5.2). It is formed through the alkali isomerization of the glucose moiety of lactose to fructose, making it a combination of fructose and galactose. The resulting disaccharide contains β-1,4 linkages and is therefore not digested by mammalian enzymes. To manufacture lactulose, lactose is mixed with an alkali (e.g., sodium hydroxide), and a catalyst may be added (Playne and Crittenden 2004). The mixture is then heated to facilitate isomerization. The unreacted lactose is removed, and the product is pasteurized and then concentrated into syrups, powders, or crystals. Commercial lactulose can be expensive to produce because traditional methods result in only a 20–30% yield and require expensive purification techniques. Recent advances have shown that using recyclable sodium aluminate as a catalyst can provide a maximum yield of ~85% lactulose following isomerization (Wang et al. 2017). Lactulose can also be generated enzymatically from fructose and galactose by using a β-galactosidase (Meyer 2015). Lactulose is known to have prebiotic effects and may be used in that capacity or as a low-calorie sweetener (Crittenden and Playne 1996). Lactulose is classified as a proven prebiotic because of the extensive published human database, despite the fact that its use as a food supplement is limited (Roberfroid 2008). Most lactulose

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(90%), however, is used pharmaceutically as a laxative and for hepatic encephalopathy to reduce blood ammonia concentrations. Key animal and human studies indicate that it is fermented in the large bowel, can selectively stimulate bifidobacteria and lactobacilli populations (Terada et al. 1993; Ballongue et al. 1992; Tuohy et al. 2002), and may also be able to enhance calcium absorption (van den Heuvel et al. 1999). Lactulose has also been shown to enhance growth and intestinal morphology in broiler chickens (Calik and Ergün 2015). While further research would help clarify additional health benefits, lactulose is considered a proven prebiotic (Roberfroid 2007; Roberfroid 2008).

5.6 Candidate Prebiotics While the previously described NDO are considered prebiotics, several other carbohydrates have been shown to elicit prebiotic effects, though they have not yet been formally declared as prebiotics. Included in this category are some polysaccharides, such as polydextrose. Interestingly, most polysaccharides with prebiotic potential can be consumed in higher doses than NDO can without adverse side effects, such as intestinal discomfort and excessive flatulence (Crittenden 2006). This is due largely to the higher DP, resulting in a more sustained fermentation pattern throughout the length of the colon rather than rapid and more-proximal fermentation, as is common with NDO. Candidate prebiotics include lactosucrose, IMO, XOS, polydextrose, and BMO/HMO.

5.6.1 Lactosucrose Lactosucrose is a trisaccharide produced from lactose and sucrose in a reversible reaction (Fig. 5.2). The fructosyl moiety of sucrose forms a β-2,1 glycosidic bond to the glucose residue of lactose to create lactosucrose. This is carried out by transglycosylation via a β-fructofuranosidase enzyme that produces a nonreducing oligosaccharide (Hara et al. 1994). This enzyme can also hydrolyze sucrose (Mussatto and Mancilha 2007). Therefore, in a batch system, with an equimolar initial ratio, there is only a yield of 52% lactosucrose (Kawase et al. 2001). The cleanup of this product is complicated and includes decolorization, filtration, concentration, purification, filtration, deionization, and concentration (Playne and Crittenden 2004). Lactosucrose resists digestion by human enzymes, and it has been noted to be bifidogenic, enhance calcium absorption, limit body fat accumulation, decrease serum cholesterol concentrations, and enhance gastrointestinal immunoglobulin A production in a limited number of human and rodent trials (Kumemura et al. 1992; Ohkusa et al. 1995; Mu et al. 2013). Further research is needed to obtain a comprehensive understanding of the health benefits elicited by lactosucrose consumption.

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5.6.2 Isomaltooligosaccharides IMO consist of glucose monomers with α-1,6 glucosidic bonds (Fig. 5.3). While the food industry uses commercially produced material, IMO occur naturally in miso, soy sauce, sake, and honey. The commercial production of IMO is a twostage process that begins with starch as the starting material. Starch is first hydrolyzed with α-amylase and pullulanase to make a liquefied starch product. β-amylase hydrolyzes the liquefied starch into maltose, then the transglucosidase activity of α-glucosidase produces IMO with a maximal final concentration of 40% in the total mixture (Crittenden 2006; Casci and Rastall 2006). Unreacted glucose (approximately 40% of the final mixture) is then removed, and the product is concentrated. IMO have been used to improve laxation and lower blood cholesterol concentrations in elderly people and in patients undergoing hemodialysis (Mussatto and Mancilha 2007; Yen et al. 2011). They have also been shown to increase bifidobacteria and lactobacilli counts in humans (Yen et al. 2011). In weaned pigs and broiler chickens, IMO have been shown to enhance growth performance and immune function (Wang et al. 2016; Zhang et al. 2003). While these data indicate that IMO have potential as prebiotics, to date, limited data are available to classify them as prebiotics.

5.6.3 Xylooligosaccharides XOS consist of chains of xylose molecules with β-1,4 linkages. They are naturally occurring oligosaccharides found in honey, bamboo shoots, fruits, vegetables, and milk (Vázquez et al. 2000). An XOS also can be made by breaking down the polysaccharide xylan, a major component of hemicelluloses. Commercial production is conducted through the enzymatic hydrolysis of primarily corn cobs but also straws, hardwoods, bagasse, hulls, and bran by using endo-β-1,4-xylanase (Fig. 5.4). Using enzymes with low exoxylanase and/or β-xylosidase activity is prudent to minimize the production of xylose. Xylanases are produced by Trichoderma reesei, T. harzianum, T. viride, T. koningii, and T. longibrachiatum (Casci and Rastall 2006; Chen

Fig. 5.3  Commercial production of isomaltooligosaccharides, a two-stage process: The first stage hydrolyzes starch into a liquefied product; in the second stage, soluble starch undergoes transglycosylation into isomaltooligosaccharides

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Fig. 5.4  Commercial production of xylooligosaccharides, which are most commonly from corn cobs, but they can also be extracted from hardwood; xylooligosaccharides are extracted by hydrolyzing xylans in the starting material by using endo-1,4-β-xylanase

et al. 1997). Other methods of extracting XOS include the chemical fractionation of material to isolate xylan with further enzymatic hydrolysis and the hydrolytic degradation of xylan by steam, water, or diluted mineral acid solutions (Vázquez et al. 2000). The chains produced through extraction in all these processes include xylobiose, xylotriose, and xylotetraose (Hopkins et al. 1998). Prior to cleaning, the solution contains approximately 60–70% XOS (Playne and Crittenden 2004). After production, xylose and other compounds are then removed via ultrapurification and reverse osmosis (Crittenden and Playne 1996) to create a product generally containing 70% or 95% oligosaccharides (Xylooligo 70  and Xylooligo  95) (Playne and Crittenden 2004). Data indicate that XOS are bifidogenic (Okazaki et al. 1990; Campbell et al. 1997; Broekaert et al. 2011). XOS have also been shown to normalize stool consistency, increase laxation frequency, reduce serum cholesterol and triglyceride concentrations, reduce fasting glucose and HbA1c concentrations, and alter immune cell populations and responsiveness in humans and rodents (Alexander et  al. 2019; Broekaert et  al. 2011; Childs et  al. 2014). In broiler chickens, XOS increased weight gain and antibody titers (Zhenping et al. 2013).

5.6.4 Polydextrose PDX is a polysaccharide formed through an acid-catalyzed vacuum thermal polymerization of glucose and may contain small amounts of sorbitol and citric acid that has an average DP of 12 but can range from 2 to 120 (Stowell 2009; Li 2010; do Carmo et  al. 2016). It is a highly branched compound containing predominantly β-1,6 linkages and α and β-1,2, -1,3, and -1,4 linkages. PDX does not have a sweet taste, and it is used to replace fat and sucrose in food products, as a humectant, and to provide mouth feel and bulk to food products (do Carmo et al. 2016; Murphy 2001). It is well documented that it resists enzymatic hydrolysis by mammalian enzymes (Achour et  al. 1994; Fava et  al. 2007). Both animal and human studies report that approximately 30–50% of PDX is fermented in the large bowel (Achour et al. 1994). In vitro studies indicate that PDX enhances butyrate and other short-chain fatty acid production (Stowell 2010). The results from many clinical and rodent trials suggest that PDX leads to selective increases in beneficial bacteria, including

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Bifidobacterium, Lactobacillus, and Faecalibacterium spp. and that it is also capable of increasing mineral absorption, decreasing intestinal oxidative stress, modulating immune responses, curbing the glycemic response, and reducing bowel transit time (do Carmo et al. 2016; Jie et al. 2000).

5.6.5 Bovine- and Human-Milk Oligosaccharides BMO and HMO constitute a family of diverse carbohydrates composed of many monosaccharides and are unique to bovine milk and human milk. HMO and BMO are composed of five monosaccharides: glucose (Glc), galactose (Gal), N-acetylglucosamine (GlcNAc), fucose (Fuc), and N-acetylneuraminic acid (Neu5Ac) (Aldredge et al. 2013; Bode 2012). All HMO contain lactose at the reducing end, which can be elongated by the addition of β-1,3- or β-1,6-linked units. Lactose or the oligosaccharide chain can be fucosylated in α-1,2, α-1,3, or α-1,4 linkages and/or sialylated in α-2,3 or α-2,6 linkages (Bode 2012). Oligosaccharides can be purified from milk through many variations of solid phase extraction (SPE), but recently, an improved method using graphitized carbon-SPE has been validated (Robinson et al. 2018). HMO quantity and composition in milk varies greatly among women—over 100 HMO have been identified—and within the same woman over the course of lactation (Davis et al. 2017). Oligosaccharides have also been identified in feline milk samples and canine milk samples, where feline milk had higher concentrations. Feline milk oligosaccharides (MO) are similar to HMO, where the majority of the oligosaccharides are fucosylated rather than sialylated. Although feline MO and canine MO are found in greater concentrations than those in bovine milk, these concentrations are still relatively low compared to those in human milk (Swanson et al. 2019). MO are most abundant in human milk and have been shown to provide a wide variety of developmental health benefits to infants beyond their bifidogenic properties. Specifically, HMO have been shown to be critical for the development of the infant gut barrier and microbiome and for the establishment of proper immune functions. They also help to prevent pathogen adhesion to the gut epithelial layer and upregulate the expression of genes related to carbohydrate metabolism (Davis et al. 2017; Akkerman et al. 2018). Thus, HMO are often touted as the “original prebiotic.”

5.7 Prospective Carbohydrate-Based Prebiotics Several carbohydrate-based compounds show some evidence of prebiotic effects, but more research is needed to fully elucidate these properties. As mentioned previously, some longer-chain carbohydrate sources, not just NDO, may also have prebiotic capabilities. These prospective prebiotic carbohydrates are listed in Table 5.2.

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Table 5.2  Prospective carbohydrate-based prebiotics Arabinoxylan-oligosaccharides β-glucans Chitooligosaccharides Cyclodextrins Gentiooligosaccharides Germinated barley foodstuffs Glucooligosaccharides Glucuronic acids Gums

Konjac glucomannans Lactose Mannanoligosaccharides Oligodextrans Oligosaccharides from melobiose Pectins Resistant starches and dextrins Soybean oligosaccharides Sugar alcohols

Some prospective carbohydrate-based prebiotics of interest include resistant starches and dextrins, β-glucans and arabinoxylan-oligosaccharides (AXOS), and mannanoligosaccharides (MOS).

5.7.1 Resistant Starches and Dextrins Not all dietary starch is hydrolyzed and absorbed by the host, because some starch is resistant to host enzymatic hydrolysis. This fraction is called resistant starch (RS). How much starch reaches the large bowel and its ability to be fermented depend on its source and structure. RS are classified into one of four categories: (1) RS1— physically inaccessible starch (e.g., starch in whole grains); (2) RS2—granular starch (e.g., starch in green bananas or uncooked potatoes); (3) RS3—retrograded starch (e.g., starch in cooked and then cooled foods resulting in gelatinization); or (4) chemically modified starch (e.g., esterified starch) (Brown 1996). RS can also be heated and treated with enzymes to produce resistant dextrins, which are smaller, indigestible polysaccharides (Mukai et  al. 2017). Though resistant to enzymatic hydrolysis, RS and resistant dextrins are still homopolysaccharides consisting of α-1,4- and α-1,6-linked glucose units (Mukai et al. 2017; Ma and Boye 2018). Research on the prebiotic effects of RS has focused primarily on RS2 and RS3, which are noted to have prebiotic capabilities in animals and humans (Ma and Boye 2018; Silvi et al. 1999; Wang et al. 2002; Dongowski et al. 2005; Jacobasch et al. 2006; Beloshapka et al. 2014; Rahat-Rozenbloom et al. 2017; Bouhnik et al. 2004). RS has been reported in several studies to increase bifidobacteria and/or lactobacilli populations (Silvi et al. 1999; Wang et al. 2002; Dongowski et al. 2005; Jacobasch et al. 2006; Kleessen et al. 1997), along with increases in SCFA, especially butyrate (Brown et al. 1997). RS and resistant dextrin have also been shown to curb the glycemic response, reduce markers of inflammation, and promote weight loss in humans (Alexander et  al. 2019; Mukai et  al. 2017; Aliasgharzadeh et  al. 2015). Although RS is not digested by mammalian enzymes and can be fermented by host microorganisms, the critical question remaining as to its prebiotic potential is its selectivity, as many other bacterial species are amylolytic (Crittenden 2006).

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5.7.2  β-Glucans and Arabinoxylan-oligosaccharides Polysaccharides are beginning to receive more attention as potential prebiotics. Furthermore, the use of whole grains in the food industry has markedly increased. Whole grains have been investigated, as have oligosaccharides that can be obtained through breakdown of polysaccharides by glyconases (Mussatto and Mancilha 2007). The best studied whole grain components include β-glucans and AXOS, which are fermented in the gastrointestinal tract. Wheat bran extract is also rich in AXOS. In vitro studies indicate that β-glucans are not well fermented by bifidobacteria or lactobacilli (Crittenden et al. 2002). AXOS, however, may have bifidogenic effects and may be of particular use as they are more slowly and sustainably fermented than most NDO are (Alexander et al. 2019; Broekaert et al. 2011; Karppinen et al. 2000). β-glucans and AXOS have been heavily studied both as purified supplements and in whole grain interventions. It has been well documented that β-glucans elicit cholesterol-­lowering effects that may also be related to their fermentation and production of SCFA, although these effects are due largely to their ability to increase bile acid excretion levels (Alexander et al. 2019). In clinical trials, β-glucans and AXOS have been shown to improve markers of gut health and inflammation, curb the glycemic response, and reduce colonic and serum ammonia concentrations that may elicit anticarcinogenic effects (Alexander et al. 2019; Broekaert et al. 2011). Whole grains and their components clearly have potential prebiotic effects, but more research remains to be conducted on their fermentative capabilities and bacterial selectivity.

5.7.3 Mannanoligosaccharides MOS are linked to serine and threonine residues on protein moieties and are extracted from the cell walls of yeast, predominantly Saccharomyces cerevisiae. Because of the demand for MOS in feed production and the demand for Saccharomyces cerevisiae in the food, medical, and biotechnological industries, recent research has identified other yeasts isolated from food products that are rich in MOS (Gupta et al. 2018). MOS are composed of mannose units linked by α-1,2, α-1,3, and α-1,6 glycosidic bonds. Mannan-binding protein complexes are isolated from cell walls via either copper complexation fractionation or Cetavlon fractionation. Following isolation, the mannoproteins undergo β-elimination to release the oligosaccharides from the amino acid residues (Nakajima and Ballou 1974). MOS can also be derived from yeast mannans through acetolysis and gel filtration (Lee and Ballou 1965). In the feed industry, MOS are increasingly used as potential replacements for growth antibiotics, particularly in poultry (Fritts and Waldroup 2009; Abudabos and Yehia 2013; Benites et al. 2008). In dogs, MOS have been demonstrated to influence

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immune function and decrease fecal putrefactive compounds (Swanson et al. 2002). In mice, MOS have also been shown to modulate systemic immune responses, but they did not improve diet-induced obesity or glucose intolerance (Hoving et  al. 2018). Additional research is needed to fully elucidate the prebiotic effects of MOS supplementation.

5.8 Prospective Noncarbohydrate Prebiotics The 2017 ISAPP definition of prebiotics expands the concept of prebiotics to include possible noncarbohydrate and nonfood substrates. Some noncarbohydrates that could be classified as prebiotics include phenolic compounds (e.g., polyphenols) and polyunsaturated fatty acids (PUFA). Polyphenols have been shown both in  vitro and in  vivo to increase bifidobacteria, lactobacilli, and Akkermansia muciniphila counts and exert antimicrobial effects on potentially harmful bacteria (Anhê et  al. 2015; Rodríguez-Costa et  al. 2018; Duda-Chodak et  al. 2015). Polyphenols have also been shown to prevent weight gain in association with increases in bifidobacteria and lactobacilli in rodent models (Anhê et  al. 2015). Some bacteria, particularly bifidobacteria, lactobacilli, and Faecalibacterium spp., are capable of metabolizing PUFAs into conjugated linoleic acid (CLA) and conjugated linolenic acid (CLnA). CLA and CLnA activate some nuclear receptors and are subsequently able to influence host metabolic processes (Druart et al. 2014). In fact, supplementation with CLA has been shown to exert its own prebiotic effect on Bacteroidetes and Akkermansia muciniphila and to increase the expression of gastric leptin, a hormone involved in satiety (Chaplin et al. 2015). To date, however, limited research is available on the prebiotic nature of these compounds.

5.9 Conclusions Three carbohydrates have been declared to meet all the requirements of the prebiotic definition: inulin-type fructans, galactooligosaccharides, and lactulose. All three prebiotics are manufactured in a unique manner but have a common characteristic in that all need a large amount of starting substrate to produce the end product. Relatively consistent final products for use by humans and animals result from the manufacturing process. Several other nondigestible oligosaccharides show substantial results for their prebiotic potential, but they have not yet been formally established as prebiotics. Some prebiotics with promising results include lactosucrose, isomaltooligosaccharides, xylooligosaccharides, mannanoligosaccharides, and bovine- and human-milk oligosaccharides. Finally, additional carbohydrate-based and even noncarbohydrate-­ based compounds may have prebiotic effects when fed to animals and humans. However, more research defining their prebiotic potential is needed.

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Sabater C, Fara A, Palacios J et  al (2019) Synthesis of prebiotic galactooligosaccharides from lactose and lactulose by dairy propionibacteria. Food Microbiol 77:93–105. https://doi. org/10.1016/j.fm.2018.08.014 Sako T, Matsumoto K, Tanaka R (1999) Recent progress on research and applications of non-­ digestible galacto-oligosaccharides. Int Dairy J 9:69–80. https://doi.org/10.2135/cropsci197 5.0011183x001500030020x Silvi S, Rumney CJ, Cresci A, Rowland IR (1999) Resistant starch modifies gut microflora and microbial metabolism in human flora-associated rats inoculated with faeces from Italian and UK donors. J Appl Microbiol 86:521–530. https://doi.org/10.1046/j.1365-­2672.1999.00696.x Stowell J (2009) Polydextrose. In: Cho S, Samuel P (eds) Fiber ingredients: food applications and health benefits. CRC Press, Boca Raton, pp 174–206 Stowell JD (2010) Prebiotic potential of polydextrose. In: Charalampopoulos D, Rastall RA (eds) Prebiotics and probiotics science and technology. Springer, New York, pp 337–352 Swanson KS, Grieshop CM, Flickinger EA et al (2002) Supplemental fructooligosaccharides and mannanoligosaccharides influence immune function, ileal and total tract nutrient digestibilities, microbial populations and concentrations of protein catabolites in the large bowel of dogs. J Nutr 132:980–989. https://doi.org/10.1093/jn/132.5.980 Swanson KS, Goonatilleke E, Wong M et al (2019) High-throughput glycomics analyses reveal unique oligosaccharide profiles of canine and feline milk samples. In: Proc 2019 AAVN Clin Nutr Res Symp Swennen K, Courtin CM, Delcour JA (2006) Non-digestible oligosaccharides with prebiotic properties. Crit Rev Food Sci Nutr 46:459–471. https://doi.org/10.1080/10408390500215746 Terada A, Hara H, Kato S et al (1993) Effect of lactosucrose (4G-beta-D-galactosylsucrose) on fecal flora and fecal putrefactive products of cats. J Vet Med Sci 55:291–295 Tian S, Wang J, Yu H et al (2018) Effects of galacto-oligosaccharides on growth and gut function of newborn suckling piglets. J Anim Sci Biotechnol 9:75. https://doi.org/10.1186/ s40104-­018-­0290-­9 Tuohy KM, Klinder A, Gibson GR et al (2002) A human volunteer study to determine the prebiotic effects of lactulose powder on human colonic microbiota. Microb Ecol Health Dis 14. https:// doi.org/10.3402/mehd.v14i3.8234 Tzortzis G, Vulevic J (2009) Galacto-oligosaccharide prebiotics. In: Charalampopoulos D, Rastall RA (eds) Prebiotics and probiotics science and technology. Springer, New York, pp 207–244 van den Heuvel EGHM, Muijs T, van Dokkum W, Schaafsma G (1999) Lactulose stimulates calcium absorption in postmenopausal women dose-dependently. J Bone Miner Res 14:1211–1216. https://doi.org/10.1007/0-­306-­47466-­2_136 Van Loo J, Coussement P, De Leenheer L et al (1995) On the presence of inulin and oligofructose as natural ingredients in the western diet. Crit Rev Food Sci Nutr 35:525–552. https://doi. org/10.1080/10408399509527714 Vázquez MJ, Alonso JL, Domínguez H, Parajó JC (2000) Xylooligosaccharides: manufacture and applications. Trends Food Sci Technol 11:387–393. https://doi.org/10.1016/ S0924-­2244(01)00031-­0 Vulevic J, Juric A, Walton GE et al (2015) Influence of galacto-oligosaccharide mixture (B-GOS) on gut microbiota, immune parameters and metabonomics in elderly persons. Br J Nutr 114:586–595. https://doi.org/10.1017/S0007114515001889 Wang X, Brown IL, Khaled D et al (2002) Manipulation of colonic bacteria and volatile fatty acid production by dietary high amylose maize (amylomaize) starch granules. J Appl Microbiol 93:390–397. https://doi.org/10.1046/j.1365-­2672.2002.01704.x Wang XX, Song PX, Wu H et al (2016) Effects of graded levels of isomaltooligosaccharides on the performance, immune function and intestinal status of weaned pigs. Asian Australas J Anim Sci 29:250–256. https://doi.org/10.5713/ajas.15.0194 Wang M, Gasmalla MAA, Admassu Tessema H et al (2017) Lactulose production from efficient isomerization of lactose catalyzed by recyclable sodium aluminate. Food Chem 233:151–158. https://doi.org/10.1016/j.foodchem.2017.04.080

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Chapter 6

Prospects for Prebiotic and Postbiotic Applications in Poultry Steven C. Ricke, L. A. Wythe, E. G. Olson, and A. Scheaffer

Abstract  The opportunities to modulate the gastrointestinal tract of poultry have dramatically increased over the past few years. Research efforts have focused on different feed additives that can influence the gastrointestinal microbiota and lead to potential improvements in growth performance in broilers and egg production in laying hens. The diet, including feed additives, provides the ecosystem in which the gastrointestinal tract (GIT) microbial community metabolizes and ferments. These communities include a wide variety of microorganisms that collectively represent multiple fermentation pathways. As more is understood about the poultry GIT thanks to 16S rRNA gene-sequencing microbiome characterization, developing more-effective feed additives has become possible. Among these additives are prebiotics, which include a relatively diverse array of compounds and can include various beta-glucans and related compounds that are substrates for gastrointestinal bacteria that are considered beneficial to the host. Postbiotics include yeast fermentation products that consist of nonviable or residual yeast cells and the subsequent cell wall components, including mannanoligosaccharides (MOSs) and fermentation metabolites. In addition, the fermented cereal grain substrate that supported yeast growth and fermentation can generate multiple prebiotic fiber types, depending on the initial grain source. These products have grown in the poultry industry thanks to their potential antipathogenic and health-promoting effects. This review overviews select prebiotics and postbiotics examined for poultry utilization and food safety.

S. C. Ricke (*) · L. A. Wythe · E. G. Olson Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, USA e-mail: [email protected] A. Scheaffer SweetPro, Walhalla, ND, USA © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_6

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6.1 Introduction Because of the emphasis on the removal of antibiotics from poultry rearing, the industry has become more focused on identifying alternatives that elicit similar responses to antibiotic growth promoters while promoting the birds’ health and welfare (Jones and Ricke 2003; Dibner and Richards 2005; Huyghebaert et al. 2011; Cervantes 2015). In addition, the impetus to develop alternative feed additives has received further support thanks to the emergence of poultry production systems such as organic and pasture flock operations that include antibiotic-free management as part of the production system (Diaz-Sanchez et al. 2015; Ricke and Rothrock Jr 2020; Jeni et al. 2021; Abd El-Hack et al. 2022). Collectively, these trends have accelerated the investigation into alternative feed additives that can accomplish some of the beneficial outcomes associated with antibiotics. Alternative feed additive candidates have been extensively researched, developed for practical utilization, and commercially promoted. While commercial applications have become relatively common, the beneficial outcomes are not always consistent. This inconsistency has many reasons and is due to intentions for identifying and developing a particular alternative candidate. For example, focusing on minimizing foodborne pathogen establishment in the gastrointestinal tract (GIT) does not necessarily translate to an overall performance improvement, whether broiler growth and efficiency or optimal egg production in layer hens. This phenomenon is unsurprising given that alternative feed additives vary in structure, possess different mechanisms of action and bacterial targets, and may have multiple functionalities. Prominent examples of this complexity are prebiotics and postbiotics. This review discusses the different types of prebiotics and postbiotics and their impacts on poultry performance and foodborne pathogen control.

6.2 Prebiotics: General Concepts As initially defined by Gibson and Roberfroid (1995), prebiotics are “non-digestible food ingredients that beneficially affect the host by selectively stimulating the growth and activity of one or a limited number of bacteria in the colon, improving health.” This class of additives is typically composed of fibers derived from various grain sources, and an updated definition defines them as able to resist digestion within an acidic and enzymatic gastric environment while subsequently resisting absorption by their host (Roberfroid 2007). Instead, the additives are fermentable by GIT microorganisms, thus stimulating the growth of beneficial, health-promoting bacteria, such as Lactobacillus and Bifidobacterium (Roberfroid 2007). According to the initial definitions of prebiotics, definitive sources were generally limited to fructooligosaccharides (FOSs), galactooligosaccharide (GOSs), xylooligosaccharides (XOSs), and mannanoligosaccharides (MOSs) because they possessed the typical characteristics of being indigestible by the poultry GIT and being

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fermentable by Lactobacillus and Bifidobacterium (Patterson and Burkholder 2003; Ricke 2015, 2018, 2021; Ricke et al. 2020). In this way, specific metabolic pathways were described in these bacterial species for producing short-chain fatty acids (SCFAs) that are associated with the GIT and overall host health. However, with the technological advancements in next-generation sequencing and amplified understandings of the complexities of GIT microbial populations and their subsequent genetic and metabolic potential, other nutritional substances have received consideration after being defined as prebiotics (Hutkins et al. 2016; Gibson et al. 2017; Ricke 2018, 2021; Ricke et al. 2020). Microbiome analyses have increased the list of GIT microbial species that could respond to prebiotic supplementation. The microbial metabolism of dietary polysaccharides is very complex. It involves a broad range of microorganisms, such that fermentation via a single bacterial species, such as Lactobacillus or Bifidobacterium, does not adequately describe a nutritional component’s ability to beneficially modulate the GIT microbiome (Gibson et al. 2017). This complexity is due in part to the metabolic cross-feeding that occurs among the GIT microbial consortia, as opposed to targeting only select species, thus becoming a significant contribution to an overall prebiotic effect (Scott et  al. 2013; Hutkins et  al. 2016; Gibson et  al. 2017). Consequently, prebiotics elicit direct and indirect impacts on the GIT microbial community. The initial fermentation of the prospective prebiotic compounds results in metabolites and degraded products that other members of the GIT microbial population can utilize. In turn, the prebiotic definition has become more complex, potentially including resistant starches, cereal grain components, polyphenols, and other less-defined sources as prebiotic candidates (Bird et al. 2010; Zhuang et al. 2017; Ricke 2018; Delzenne et al. 2020; Nazzaro et al. 2020). In addition, this relationship is further complicated by the realization that different microbial species populate different regions of the poultry GIT and respond variably to incoming dietary substrates, depending on their hydrolysis and fermentation capabilities. For example, the upper poultry GIT harbors a higher abundance of the lactic acid bacterial (LAB) population. The microbial members of the upper GIT compartments are likely to ferment prebiotic compounds differently than does the lower GIT, which possesses a diverse anaerobic microbial population with a myriad of enzymatic and fermentation capabilities. Using metagenomic profiling, Sergeant et al. (2014) identified numerous encoded polysaccharide- and oligosaccharide-degrading enzymes in poultry ceca, which appeared to be in coordination with a polysaccharide degradation system that included sugar transport, sugar utilization, and multiple SCFA fermentation pathways.

6.3 Fructooligosaccharides Fructooligosaccharides (FOSs) are fermented by several Bifidobacteria and Lactobacillus species (Kaplan and Hutkins 2004; Fig. 6.1). FOSs have also been suggested as being modulators of the poultry GIT microbiota (Ricke 2015, 2018,

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Fig. 6.1  Prebiotics such as fructooligosaccharides, xylooligosaccharides, and galactooligosaccharides originate from various sources, such as hemicellulose, plant xylan, cereal grains, lettuce, and onions; prebiotic supplementation in poultry production has shown an increase in microbial fermentation in the GIT, resulting in the production of short-chain fatty acids (SCFAs) and improved GIT health. (The figure was created with BioRender)

2021). For instance, using 16S rRNA gene sequencing on microbiomes, Kumar et  al. (2019) detected ileal microbiota responses in broilers supplemented with FOSs. Utilizing in vitro cecal models incubated with FOSs and alfalfas, Donalson et al. (2007, 2008a) detected shifts in the cecal microbiota and differences in SCFA production. These findings suggest that in addition to LAB and Bifidobacteria, other GIT microbiota may be able to utilize FOSs as substrates. The FOS-supported increase in SCFA concentrations also inhibited the in vitro growth of Salmonella and cecal colonization in laying hens (Donalson et al. 2007, 2008a, b; Bailey et al. 1991). However, caveats to FOS supplementation include certain pathogenic bacteria that can also utilize fermentative pathways, which can rapidly lead to a subsequent pH decrease, mucosal inflammation, or damage in the intestinal epithelial lining (Wu et al. 1999; Ten Bruggencate et al. 2004). Interest in probiotic/FOS prebiotic combinations has also increased thanks to their potential applications in poultry production. Because some Bifidobacterium, and LAB that ferment, FOS are also probiotic candidates, combinations of probiotic bacteria and FOS would be possible feed additives. Such combinations are called synbiotics (SYNs) (Adebola et  al. 2014; Hamasalim 2016; Markowiak and Śliżewska 2018; Kariyawasam et al. 2020). Such combinations are strain and species dependent in that the prebiotic must be matched with an appropriate probiotic candidate to use the latter as a substrate (Rastall et al. 2005; Saminathan et al. 2011). Summarizing the use of SYN feed additives in animal nutrition, Markowiak and Śliżewska (2018) suggested that a SYN candidate should meet all the requirements

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of probiotics and prebiotics. For instance, the purity of FOSs can be an issue because some probiotics can use only the monosaccharides of the crude FOS preparations (Fan et al. 2021). Lactobacillus spp. have been used as probiotic candidates for SYN combinations with FOSs as feed additives in poultry, and numerous studies have shown beneficial effects on poultry performance and pathogen effects. For example, by combining FOSs with Lactobacillus plantarum and introducing the combination to broilers, Ding et al. (2019) observed an increase in cecal SCFA levels and the alleviation of the jejunal damage caused by E. coli O78—leading to reduced mortalities for pathogen-­challenged broilers. Luoma et al. (2017) demonstrated that a commercial SYN composed of Bifidobacterium animalis, Enterococcus faecium, Lactobacillus reuteri, and Pediococcus acidilactici with FOSs decreased the cecal load in laying hens challenged with Salmonella Enteritidis regardless of their vaccination status. Mohammed et al. (2019) tested the efficacy of this same commercial SYN to alleviate heat stress in broilers. In addition to regulating physiological stress responses and improving antioxidant statuses, they reported lower cecal levels of E. coli in the heat-stressed birds and increased levels of Bifidobacterium and Lactobacillus spp. but not Enterococcus spp. These findings reinforce the claim that prebiotics can affect a broad range of GIT microbiota associated with metabolic cross-feeding; such a combination of prebiotics and probiotics may have contributed to the observed host benefits in the abovementioned studies. Other probiotic–FOS combinations besides LAB have also been explored. For example, Obianwuna et  al. (2023) reported that the combination of Clostridium butyricum and FOSs enhanced layer hen egg quality, amino acid digestibility, jejunal morphology, and physiological responses. Using spore formers such as Clostridium in combination with FOSs helps the probiotic to survive the low-pH GIT environments and generate SCFAs (Obianwuna et al. 2023). Thanks to their ability to withstand stresses encountered during feed manufacturing, the most common spore-forming probiotics used in the poultry industry are Bacillus spp. (Ricke and Saengkerdsub 2015; Abd El-Hack et al. 2020). Li et al. (2008) fed a combination of 0.3% FOSs with 0.1% B. subtilis to newly hatched broilers over 6 weeks. They concluded that FOSs and B. subtilis as single treatments or the FOS–B. subtilis combination improved the growth performance and reduced diarrhea in treated birds compared to control birds. However, the combination appeared to be the most effective in reducing cecal E. coli, Salmonella, and total aerobes while increasing Lactobacillus populations in treated birds versus control birds and compared to those given single treatments.

6.4 Galactooligosaccharides Galactooligosaccharides (GOSs) consist of galactose, which can differ in the branching level, chain length, and type of glycosyl linkages (Fig.  6.1). They can occur as either α-GOS or β-GOS, although β-GOS is the primary focus for prebiotic

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applications (Mei et al. 2022). Milk is a common natural source of GOSs, but few other natural sources exist for natural extraction. GOSs can be produced from the hydrolysis of polysaccharides and chemical or enzymatic synthesis (Mei et  al. 2022). Enzymatic synthesis, from lactose via a glycosyl transfer of one or more D-galactosyl units onto a chain of galactose units, represents the most commonly used method to produce GOSs (Crittenden and Playne 1996; Mahoney 1998; Boon et al. 2000; Tzortzis et al. 2005; Macfarlane et al. 2008; Mei et al. 2022). The transgalactosylation reaction is carried out by β-galactosidase by using lactose as the substrate. While several bacteria and fungi possess the enzyme, GOS β linkages can differ depending on the organism (Ambrogi et al. 2021; Mei et al. 2022). More so, the GOS level of polymerization can range from two to eight monomers and varies with the source, lactose concentration, substrate composition, and reaction conditions, among other factors (Macfarlane et al. 2008; Mei et al. 2022). As a prebiotic, GOSs have been associated with the selective stimulation of organisms such as Bifidobacteria and lactobacilli, leading to the fermentation and generation of end products such as lactate and SCFAs that create a GIT environment hostile to pathogens (Gomes and Malcata 1999; Rastall and Maitin 2002; Tzortzis et al. 2005; Macfarlane et al. 2008; Saminathan et al. 2011; Alloui et al. 2013; Mei et al. 2022). Other intestinal bacteria may also be involved in GOS metabolism. For example, Cheng et  al. (2017) fed mice a combination of inulin and GOS over 3 weeks. Analyses of the fecal samples via 16S rDNA sequencing revealed that while there was a detectable increase in the proportion of Bifidobacterium thanks to the GOS-inulin combination, this increase was relatively small. However, using a single prebiotic supplement, they observed a significant increase in Bacteroides spp., a decrease in Alloprevotella, and an overall decrease in fecal microbial diversity. The authors concluded that combinations of oligosaccharides and fiber would provide optimal strategies to promote stable intestinal microbiota and prevent the dominance of specific bacterial populations that can arise from using a single prebiotic supplement. GOSs have also been examined as potential prebiotics in poultry. Park et  al. (2017c) compared FOSs, GOSs, and plum fiber treatments with a control diet fed to pasture flock broilers that received the diet in phases, namely starter, grower, and finisher, during the 6 weeks. Cecal samples were used for 16S rDNA microbiome analyses. Overall, each treatment uniquely affected cecal microbial diversity at the family taxonomic level, where Halomonadaceae and Alcaligenaceae were detected only in the GOS-fed birds. At the same time, Blautia was detected only in the FOS-­ fed birds, but Eubacterium and Alcaligenaceae genera were present only in the GOS birds. Park et al. (2017c) also found that prebiotics did not affect Campylobacter. However, its occurrence may align with Alistipes and Lactobacillus intestinalis; thus, these taxa could serve as potential indicators of Campylobacter. Only limited studies have examined GOSs as prebiotics for controlling Campylobacter (Kim et al. 2019). Flaujac Lafontaine et al. (2020) reported that GOS supplementation improved body weight gain at 35 days of age, impacted intestinal architecture and intestinal and cecal innate responses, and led to shifts in the cecal microbiota but did not reduce or prevent the colonization of C. jejuni. Further research is needed to

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determine various combinations of feed additives, such as probiotics and prebiotics, with other approaches that may be more effective in limiting Campylobacter establishment. A possible approach might entail the use of Campylobacter-specific phage to reduce the initial levels of Campylobacter, followed by combinations of prebiotics and probiotics to prevent further colonization (Kim et al. 2019; Deng et al. 2020; Olson et al. 2022).

6.5 Xylooligosaccharides Xylooligosaccharides (XOSs) each contain a beta-1,4 xylose backbone, with a reducing end series of xylose, rhamnose, and galacturonic acids, along with acetyl and (methyl)glucuronic acid side groups, and they are considered among the most abundant carbohydrate polymers in hemicellulose fractions (Limayen and Ricke 2012; Wierzbicki et al. 2019; Fig. 6.1). In woody biomass and cereal grains, XOSs are major noncellulosic carbohydrate polymer constituents, and arabinoxylans are the highest among all polysaccharides, except for starch in some cereal grains (Zhuang et al. 2017; Wierzbicki et al. 2019; Garutti et al. 2022). Most polysaccharides associated with cereal grains have high molecular weights and can increase GIT viscosity (Zhuang et al. 2017). The viscosity increases because soluble fibers absorb water in the GIT, increasing in bulk, which can impede nutrient absorption (Tiwari et al. 2020). These changes can cause an increase in villus cell loss with negative consequences for digestibility and nutrient use in the GIT (Tiwari et al. 2020). Consequently, from a practical standpoint, some types of further processing are warranted, such as extrusion, chemical modification, or enzyme hydrolysis, to decrease the water-holding capacity of these large polysaccharides (Zhuang et al. 2017). The employment of feed-grade enzymes to generate fermentable oligosaccharides, as well as other GIT benefits, has become a vital component of improving overall nutritional management in poultry (Ravindran 2013; Cowieson and Kluenter 2019; Abd El-Hack et al. 2022). Because of the poor GIT health associated with feeding intact arabinoxylan polymers to poultry and other monogastric animal species, xylanases are often used to generate nutrients and smaller carbohydrate fragments (Tiwari et al. 2020). Xylanases have been shown to increase the nutritional availability of feedstuffs high in xylan and generate prebiotic oligosaccharides as a function of enzyme hydrolysis (Broekaert et al. 2011; Lee et al. 2017; Morgan et al. 2020; Tiwari et al. 2020). Combining feed-grade enzymes with cereal grain xylans showed an increase in soluble and available substrates for GIT fermentation, which potentially altered the GIT microbial population and shifted their fermentation activities (Ricke 2018; Cowieson and Kluenter 2019). For example, Lee et al. (2017) fed wheat diets with or without xylanase to broilers over 42 days. They detected an increase in arabinose and xylose in the ileum and decreased viscosity in the xylanase-­supplemented birds at all ages, which led them to suggest that arabinoxylan enzymatic hydrolysis was occurring. In the 21-day-old birds, cecal levels of

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xylose and arabinose decreased in xylanase-supplemented birds. By day 42, an increase in Bifidobacterium spp. was accompanied by increases in acetic acid and butyric acid and a decrease in lactic acid. These findings suggest that the hydrolyzed products of arabinoxylans could serve as prebiotic substrates that selectively support beneficial bacteria such as Bifidobacterium spp. in the lower GIT. Several studies have supported the claim that when XOSs and arabinose-­ substituted XOSs (AXOSs) can reach the hindgut, either directly from the diet or after exposure to feed enzymes, they can be selectively fermented by beneficial microorganisms, including Lactobacillus and Bifidobacterium, leading to an increase in SCFAs, such as butyrate, in broilers and laying hens (Courtin et al. 2008; De Maesschalck et al. 2015; Lee et al. 2017; Ding et al. 2018; Morgan et al. 2019; Bautil et al. 2020). The direct supplementation of XOSs and AXOSs has provided evidence of improving bird health by increasing immune cells in the GIT, increasing cecal weights and villi lengths, improving nutrient utilization, and modulating GIT microbiota composition (Courtin et al. 2008; De Maesschalck et al. 2015; Pourabedin et al. 2015, 2016; Samanta et al. 2017; Yuan et al. 2018; Morgan et al. 2019; Bautil et al. 2020). The GIT’s microbial response can be complex. De Maesschalck et al. (2015) fed XOSs and a wheat-rye diet to broilers. They detected increased Clostridium cluster XIVa and Anaerostipes butyraticus levels in the ceca and increased lactobacilli, particularly Lactobacillus crispatus, in the colon of the XOS-­ fed birds. The increased levels of butyrate accompanied an increase in the cecal populations. More so, on the basis of in vitro incubations, the authors suggested that the fermentation of XOSs by L. cripsatus results in lactate that serves as a substrate for A. butyraticus for butyrate production. As more is understood about the complexities of poultry GIT microbial populations, multiple cross-feeding events among the microbial community members in response to prebiotics will likely be detected. It would not be surprising if the degree of complexity in the prebiotic substrates parallels the complexity of the GIT microbial community’s response and amplifies the number of cross-feeding events that would involve additional divergent members of the microbial community.

6.6 Yeast Cell Wall Components: Prebiotics/Microbiota Yeast cell wall (YCW) components can serve as prebiotic and “prebiotic-like” additives (Roto et al. 2015; Santovito et al. 2018). Yeast cell walls contain polysaccharides and proteins, where the polysaccharides comprise anywhere from 75% to 90% of the cell wall (Nguyen et al. 1998; Kogan and Kocher 2007). These polysaccharides include mannans, glucans, and chitins, where α-D-mannans and β-D-glucans are the most abundant (Korolenko et al. 2019). In S. cerevisiae, the proportions of mannans and glucans are equal, but this is not necessarily true for all species (Nguyen et  al. 1998). Most of the protein within the cell wall is also covalently linked to the mannan (Nguyen et al. 1998). Mannans are the general name given to glycoproteins, typically represented as linear polymers of mannose residues. Yeast

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mannans consist of an α(1–6)-linked backbone with α(1–2)- and α(1–3)-linked branches (Libjaková et  al. 2007; Orlean 2012). Alternatively, glucans are D-glucopyranosyl-based polysaccharides and are formed by the covalent bond between (1 → 3)-β-D-glucan and (1 → 6)-β-D-glucan (Jacob and Pescatore 2017). Finally, chitins are made up of N-acetylglucosamine and found in lower concentrations in the cell wall (1%–2% of the cell wall dry weight), where they are interconnected with the β(1 → 3)-glucans and mannoproteins via β(1 → 6)-glucan linkages and is believed to provide structural support to the yeast cell wall (Kollár et al. 1995, 1997; Orlean 2012).

6.6.1 Chitins Chitins are available from yeast cells and within the exoskeletons of insects and some crustaceans. Insects, in particular, have received increasing interest as food sources for human consumption and as potential feed additives for broilers (Imathiu 2020; Józefiak et al. 2020). When Józefiak et al. (2020) fed Tenebrio molitor and Zophobas morio to broilers, the authors observed an increase in the relative amount of Lactobacillus, represented by Lactobacillus agilis, the Bifidobacteriaceae family, especially Bifidobacterium pseudolongum, and the Clostridia class in ceca. However, improving GIT health and microbial diversity may not correlate with enhanced performance in birds. Hossain and Blair (2007) reported that the ability of broilers to digest chitin protein from the crustacean shell improved serum cholesterol and triglycerides but not the carcass yield. Whether these responses also occur for chitin in YCWs remains to be determined and depends to some extent on how much YCW chitin composition differs from other chitin sources.

6.6.2  β-glucans β-glucans have become subjects of increased research for potential feed additives because of their beneficial effects on animal health. β-glucans can bind mycotoxins, pathogenic bacteria, and host macrophages (Stier et al. 2014; Teng and Kim 2018; Korolenko et al. 2019; Hernández-Ramírez et al. 2021; Papp et al. 2021). The active binding of mycotoxins may occur in the live bird GIT, illustrated by Hernández-­ Ramírez et al. (2021). The authors demonstrated that feeding YCW to broilers alleviated some intestinal epithelium damage in broilers when the birds consumed aflatoxin, decreasing the intestinal permeability associated with aflatoxin. More so, goblet cell density and villus height and depth increased in the YCW-supplemented group compared with the control birds. Several studies have shown improved immunological function when poultry are fed β-glucans (Teng and Kim 2018). Such improvement can occur with other treatments that interact with the immune system. The shifts in ileal microbiota and the

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expression of immune responses by autolyzed yeast supplementation can improve bird performance. For example, Bortoluzzi et al. (2018) fed an autolyzed yeast supplement to broilers receiving a live coccidia vaccine. The authors observed the downregulation of TLR-4 expression and a decrease in ileal Lactobacillus in 8-day-­ old birds compared to the control birds—which were supplemented with zinc bacitracin—which showed an increase in Enterococcus populations. The authors showed that zinc bacitracin and 0.4% autolyzed yeast supplements improved overall feed-conversion ratios. The use of the yeast supplements exhibited an improved feed-conversion ratio and an upregulation of IL-1β in 21-day-old birds. YCWs can also stimulate the immune system in the presence of nonpathogenic antigens. For example, Alizadeh et al. (2016) reported that broilers that received sheep red blood cells and bovine serum albumen as nonpathogenic immunogens and fed YCWs showed increased levels of Th2 cytokines IL-10, IL-4, and IL-13 gene expression compared with the birds fed the control diet with no antibiotic and showed improved total antibody production compared with the birds receiving virginiamycin. They concluded that YCWs possessed immune adjuvant-like properties that enhanced broilers’ Th2 cell-mediated and humoral immune responses.

6.6.3 Mannans Mannanoligosaccharides (MOSs) are active components within the yeast cell wall that can serve as feed additives, potentially benefiting poultry performance and health (Teng and Kim 2018). Supplementations of MOSs in poultry, farm animals, and companion animals demonstrate improvements in performance and feed efficiency and decreases in mortality (Hooge 2004; Spring et  al. 2015). MOSs have been proven to limit pathogen colonization in the GIT, particularly species that express type 1 fimbriae, overall improve the integrity of the intestinal mucosa, and modulate immune activity (Spring et al. 2015; Santovito et al. 2018; Teng and Kim 2018). For example, Spring et  al. (2000) demonstrated that MOSs decreased Salmonella cecal colonization in young broiler chicks challenged with either S. Typhimurium or S. Dublin without altering the cecal levels of lactobacilli, enterococci, anaerobic bacteria, lactates, SCFAs, or pH. While MOSs are known to bind to specifically Gram-negative pathogens, evidence suggests that MOSs can also bind to some Gram-positive pathogens, such as Clostridium perfringens, reducing its viability (Santovito et al. 2018, 2019).

6.7 Yeast Fermentation Products as Postbiotics Yeast offers an ultimate one-stop postbiotic supplementation, including yeast as a probiotic, lysed YCW components that serve as prebiotic molecules, and the resultant fermentation metabolites that comprise the final product. Yeast fermentation

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products (YFPs) are generated by inoculating live yeasts onto a specific growth media, typically some combination of cereal grains, and subsequently allowing them to ferment to produce ethanol (Perricone et al. 2022). The growth culture is subsequently dried, which destroys most yeast cells and leaves dead and autolyzed yeast cells, releasing YCW components (Perricone et al. 2022). Aside from ethanol, the remaining biomass and residual metabolites are available for consumption by the host when added to feed. YFPs can deliver the combined benefits of yeast-based feed additives, depending on the harvest process. Various yeast species can ferment 5- and 6-carbon sugar molecules into ethanol through anaerobic respiration (Pronk et al. 1996). For simplicity, this review focuses on hexoses, such as glucose metabolism. Extracellular enzymes can break oligosaccharides into mono- and disaccharides (Barnett 1981). Disaccharides can then be transported into the cell through a proton symport, while monosaccharides may be involved in either a proton symport or facilitated diffusion (Barnett 1981). Hexoses are subsequently broken down through the Embden–Meyerhof–Parnas (EMP) pathway to be converted to pyruvate, but other pathways may also be utilized, depending on the species (Pronk et al. 1996). In the EMP pathway, the initial hexose is isomerized and phosphorylated through enzymes and adenosine triphosphate (ATP), and the resulting 1,6-­bisphosphate is cleaved into two 3-carbon sugars. These 3-carbon sugars are oxidated and phosphorylated, producing ATP and eventually pyruvate, which can be continued through aerobic or anaerobic respiration. Anaerobic respiration converts pyruvate into ethanol through the respective enzymes, namely pyruvate dehydrogenase and alcohol dehydrogenase, to produce ethanol and CO2. This process does not produce additional ATP but instead recycles the nicotine adenine dinucleotide (NAD+) used during glycolysis, which allows for additional ATP production without oxygen (Pfeiffer and Morley 2014). In addition to ethanol fermentation, yeasts can generate a wide variety of metabolites that possess properties that could have various effects on food and hosts, including enzymes, lipids, carotenoids and other vitamins, volatile flavor compounds and organic acids, extracellular polysaccharides, and several other compounds (Buzzini and Vaughn-Martini 2006). Many yeast species can produce carotenoids, including β-carotene, which can be metabolized into vitamin A (Buzzini and Vaughn-Martini 2006). While S. cerevisiae cannot produce carotenoids, it can be engineered to express the pathway to produce β-carotene (Yamano et  al. 1994). Yeasts can produce additional vitamins such as L-ascorbic acid, D-erythroascorbic acid, and ergosterol. D-erythroascorbic acid is synthesized by S. cerevisiae and can be converted into L-ascorbic acid or vitamin C, depending on the available substrates (Hancock et al. 2000). Similarly, ergosterol, a precursor to vitamin D2 and cortisone, is in the yeast cell membrane and is responsible for its structure, permeability, fluidity, and enzymatic activity within the membrane (Parks and Casey 1995; Shang et al. 2006). Despite the knowledge of the array of metabolic substrates generated thanks to yeast fermentation that may remain in yeast fermentation products, the exact metabolites and modes of action have yet to be entirely deduced (Perricone et al. 2022). Nonetheless, yeast fermentate products have a suggested effect on improving growth performance and modulating GIT microbiota (Perricone et al. 2022).

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According to a series of studies characterizing the poultry GIT microbiota, it appears that the stability of the microbiota is at least partially related to age. Thus, stabilizing the microbiota earlier could protect the bird from pathogen colonization (Stanley et  al. 2014; Clavijo and Flórez 2018; Rychlik 2020; Dittoe et  al. 2022). Furthermore, identifying at a younger age which microbiota compositional profiles maximize the benefits from the residential microorganisms that are ultimately present, along with their fermentative metabolites, should optimize bird health and performance (Rinttilä and Apajalahti 2013). In vitro evidence and in  vivo evidence suggest that YFPs influence microbial diversity in poultry, including broilers, turkeys, and layers, and might allow the microbiota diversity to stabilize at an earlier age and might limit pathogen establishment (GuyardNicodème et al. 2016; Park et al. 2017a, b; Zhen et al. 2019; Sun et al. 2020; Liu et al. 2021; Feye et al. 2021; Nelson et al. 2018, 2020). One overall observation based on the cecal in vitro studies was that some adaptation period of the cecal inoculum with the yeast fermentate was required to achieve the maximum inhibition of pathogen growth (Rubinelli et al. 2016; Park et al. 2017a; Feye et al. 2021). Without the adaptation of the cecal microbiota, yeast fermentates were less inhibitory, suggesting that some metabolism of the yeast metabolites was required to achieve an inhibitory cecal environment to the respective pathogen. Park et  al. (2017a) also concluded that the age of the birds from which the cecal inocula originated was essential for in vitro–based efficacy studies. The method needed to determine the critical adaptation of the GIT microbiota for in  vivo studies still needs to be explored. Likewise, determining the bird’s age when the yeast fermentate modulation of the GIT is effective could be a factor in evaluating the relative efficacy of different fermentate sources. Additional specific bird growth and production responses are presented in Table 6.1 and GIT microbial profiles and modulations after exposures to YFPs are presented in Table 6.2—as selected examples from the wide range of impacts of yeast fermentates on poultry. More-recent discussions involving applications of YFPs, and similar feed additives, have centered on refining their classifications. Terms such as postbiotic, SYN, para-probiotic, bacterial lysates, and more, have been used to describe the same Table 6.1  Performance effects from yeast fermentate supplementation, from selected studies Model Breeder layers Broilers Broilers Broilers Broilers

Effect Improved egg quality, increased fertilization, hatching rate, and healthy chick rate Increased Average Daily Gain (ADG) and Average Daily Feed Intake (ADFI); improved Feed Conversion Ratio (FCR) Improved ADG in grower phase; improved Feed:Gain (F:G) over 42 days Increased Feed Intake (FI) and Body Weight (BW); decreased FCR Improved FCR; improved stress parameters equally to antibiotics

References Liu et al. (2021) Sun et al. (2020) Zhen et al. (2019) Roto et al. (2017) Nelson et al. (2018)

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Table 6.2  Effects on GIT microbiota composition from yeast fermentate supplementation, from selected studies Model Breeder layers Broilers Broilers, in vitro Broilers

Organ Effect Ileum Increased Lactobacilli and decreased Romboutsia Ceca Increased Faecalibacterium; altered taxonomical distributions Ceca Decreased C. jejuni; altered alpha and beta diversity; altered taxonomical distributions Ceca Increased Ruminococcus, Clostridiales, Bacteroides, Propionibacterium, and Bifidobacterium

Turkeys, in vitro Broilers

Ceca

Broilers

Ceca

Broilers, in vitro

Ceca

Ceca

Decreased Salmonella; diversity sustained compared to the control Decreased Salmonella against the control but variable against antibiotics at each sampling point No difference in diversity or taxonomical distribution at d 42 Decreased Salmonella; increased SCFA production

Method 16S rDNA 16S rDNA 16S rDNA

Denatured Gradient Gel Electrophoresis and 16S rDNA 16S rDNA 16S rDNA

16S rDNA Gas chromatography

References Liu et al. (2021) Sun et al. (2020) Feye et al. (2020) Zhen et al. (2019)

Feye et al. (2021) Roto et al. (2017) Nelson et al. (2020) Rubinelli et al. (2016)

products; similarly, several classifications have been used for single products (Salminen et al. 2021). SYN includes live cultures with prebiotics, which increase the chances of the probiotics’ survival in the GIT (Yang et al. 2009; Gaggìa et al. 2010). As discussed previously, bacterial probiotics, such as Bifidobacterium and Lactobacillus, can be provided with FOSs, lactitol, or inulin so that the specific substrates required for the probiotics to thrive are readily available (Yang et  al. 2009; Sharma et al. 2018). However, storage and handling issues could potentially risk the live cultures’ viability before inclusion in feed. Salminen et al. (2021), in their recent consensus statement, defined postbiotics as the “preparation of inanimate microorganisms and/or their components that confers a health benefit on the host.” Microorganisms and the matrix they have been grown in are deactivated, and the resulting product can benefit health. Therefore, yeast-derived culture products that undergo an adequate heating and drying step, such that all the yeast cells that are inactivated can be described as postbiotics. Alternatively, products with culturable yeast are considered SYN additives. The inherent stability of postbiotics, as opposed to probiotics, is an essential driving factor in the interest in the products. Despite this interest, the current understanding of yeast-derived postbiotics’ actual mechanisms of action remains limited (Reuben et al. 2021). Nonetheless, residual yeast, cereal grain biomass, and fermentation metabolites can  beneficially affect poultry growth and development.

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6.8 Conclusions and Future Directions A host of feed amendments are continually being explored as potential alternatives for antibiotic growth promoters, and the current review provides only an overview of prebiotics and postbiotics. Traditional prebiotics such as FOSs, XOSs, and MOSs have been extensively studied and assessed for their utility and for commercial applications in poultry. Although the application of pre- and postbiotics has focused on pathogen reduction, recent efforts have examined the GIT microbial ecology, growth performance, egg production, and physiological parameters necessary for the bird’s health. Much of the current knowledge has become possible with new-­ generation sequencings, such as 16S rDNA microbiome sequencing, and other tools that assess the system’s function, such as proteomics, transcriptomics, and metabolomics. The emergence of sophisticated bioinformatic data analytics has hastened the ability to interpret large databases. The challenge is to merge these disparate data sets into coherent interpretations of the biologically relevant responses that can be used to model and design practical applications for the poultry industry. Enough evidence suggests that yeast-derived products, such as probiotics, prebiotic cell components, and fermentation products, can enhance poultry development. YFPs appear to have beneficial effects on growth performance, possibly due to their potential to modulate GIT microbiota. However, the mechanisms of action on both the host and microbiota have yet to be fully elucidated, thus suggesting the need for continued research. Part of this is due to the complexity of the yeast products. For example, yeast fermentations of various cereal grains can lead to the production of a multitude of metabolites that possess postbiotic properties and, along with the higher concentrations of nutrients in the postfermentation grains, can lead to improved performance (Roto et al. 2015; Yasar and Yegen 2017; Zhuang et al. 2017; Perricone et al. 2022). Depending on the fermentation recovery process, residual yeast cells containing MOSs may remain which are  known to bind to pathogens such as Salmonella preventing attachment and subsequent colonization of the GIT (Baurhoo et al. 2009; Teng and Kim 2018). Previous research has compared growth performance and GIT sampling throughout the lifespan of the bird but typically provides only singular responses of microbiota compositional profiles, particularly at the end of the lifespan, as seen in several studies (Roto et al. 2017; Nelson et al. 2020; Liu et  al. 2021). Future research that analyzes microbiota development through 16S rRNA gene sequencing by utilizing repeated sampling methods such as daily cecal dropping could help describe how prebiotics affect microbiota development in tandem with growth performance and GIT development. However, more-­ comprehensive research must be conducted to determine whether cecal droppings sufficiently represent the GIT microbiota during the bird’s lifespan. The same applies to fecal collections and identifying the contributions of the different poultry GIT compartments. This review did not focus in detail on yeast-derived products and their specific inhibitory effects on foodborne pathogens, but previous evidence suggests their inclusion inhibits Salmonella and Campylobacter (Table 6.2; Rubinelli et al. 2016;

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Roto et  al. 2017; Feye et  al. 2020, 2021). Even though preharvest practices can impact food safety, more information is needed to learn the relationship between feed additives and carcass microbiota compositional profiles. The farm and the processing environment play inherent roles in the bacterial populations in the final product. However, connections between the dietary introduction of microorganisms have yet to be extensively explored. In the future, controlled studies will be necessary to explore the relationships between feed, feed additives, and final carcass microbiota compositional profiles. There could be at least some semblance of a potential continuum from a live bird to a poultry carcass of some microorganisms originating from the live bird. Establishing these relationships could factor into projecting shelf life as a function of processing plant contributions to the carcass microbial ecology and those members of the carcass microbiota originating from the bird before processing.

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Part II

Probiotics: Current Status and Future Challenges of Practical Applications

Chapter 7

Probiotics in Poultry Preharvest Food Safety: Historical Developments and Current Prospects A. V. S. Perumalla, L. A. Wythe, and Steven C. Ricke

Abstract  In the United States, the consumption of chicken and turkey continues to increase, and exports now constitute major sources of revenue for the poultry industry. With the increase in consumer demand for poultry products, there has been a shift in the dynamics of poultry production. With these significant changes, effective strategies for intervention are required to maintain the food safety of these products to protect public health. In recent years, there have been growing concerns about antibiotic resistance, the prohibition of growth promoters, and consumer demand for antibiotic-free or “chemical-free” produce. Such factors are critical in identifying potentially safe and alternative strategies for bird production. In this context, considering the use of probiotics in poultry production would be prudent given that food safety remains a contemporary issue. Their implementation has great potential in delivering promising results by reducing the intestinal pathogenic load and thereby reducing the subsequent contamination in poultry production. Several mechanisms of action have been proposed, including resistance to colonization, competitive exclusion, the production of toxic and inhibitory compounds, competition for nutrients, and stimulating the immune system. Probiotics also offer potential host-protective health effects and bird-growth benefits by modulating gut microbiota. This review focuses on gastrointestinal microbial ecology, beneficial effects, the mechanisms of action of probiotics, and the impact of probiotics on poultry preharvest food safety.

A. V. S. Perumalla Hill’s Pet Nutrition, Topeka, KS, USA L. A. Wythe · S. C. Ricke (*) Meat Science and Animal Biologics Discovery Program, Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_7

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7.1 Introduction Foodborne illness and its implications on the food industry and to the general public is a concern, and its impact could be reduced by establishing effective, novel interventions to enhance food safety in a “farm to fork” approach (Oliver et al. 2009). Conventionally, the majority of the efforts in controlling foodborne pathogens have had a postharvest focus; however, limiting the spread of foodborne pathogens prior to harvest (as they are reservoirs/asymptomatic carriers of several foodborne pathogens) continues to garner interest and focus among food safety researchers, policymakers, government officials (FSIS/USDA), and consumers (Tuohy et  al. 2005; Choct 2009; FSIS/USDA 2010; Ricke 2021; USDA-FSIS 2023). Preharvest food safety is now being considered equally essential to protect the food supply because not only can foodborne pathogens originate from birds entering slaughter, but cross-­ contamination may occur with workers or machinery in the processing environment or by direct contact with feces or digesta from the intestinal tract (Corry et al. 2002; Rasschaert et al. 2006, 2008; O’Bryan et al. 2022).

7.2 Foodborne Pathogens Associated with Poultry Foodborne diseases continue to have major public impacts on millions of people and cost several billion dollars in the United States (CDC 2009; Scallan et al. 2011; Painter et al. 2013). A majority of these foodborne illnesses/outbreaks have been linked to contaminated poultry products or contact with food animals, waste, and enteric pathogens in poultry (Doyle and Erickson 2006; Chai et al. 2017; Yang et al. 2019a; Ricke 2021; O’Bryan et  al. 2022). The foodborne pathogens transmitted mainly through raw and processed poultry products are Salmonella and Campylobacter (Park et al. 2008; Finstad et al. 2012; Chai et al. 2017; Rajan et al. 2017; Yang et al. 2019b; Ricke 2021; O’Bryan et al. 2022). In addition to the common bacterial pathogens, zoonotic parasitic infestations such as Trichinella spiralis and Toxoplasma gondii can pose health risks to consumers (Gebreyes et al. 2008). Salmonellosis remains one of most commonly reported foodborne disease associated with the consumption of meat, poultry, eggs, milk, and seafood in the United States (Vugia et al. 2007, 2009; Scallan et al. 2011; Painter et al. 2013). Every year in the United States, there continues to be over a million cases of salmonellosis that lead to hospitalizations and deaths (Voetsch et al. 2004; Scallan et al. 2011; Painter et  al. 2013). Farm animal products, such as chicken (broiler meat and eggs) and turkey products, represent major reservoirs of Salmonella and can also act as asymptomatic carriers in the absence of clinical disease (Finstad et al. 2012; Chai et al. 2017; Ricke 2017; Gast et al. 2022; O’Bryan et al. 2022). Poultry remains a primary source of salmonellosis, accounting for 25% of the outbreaks and is a critical concern nationally and internationally as poultry consumption increases globally, and the United States exports one-third of the world’s poultry supply (USDA 2007a, b;

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Chai et  al. 2017). Factors such as age, Salmonella serotype and initial challenge dose level, stress, the presence of feed additives (antimicrobials and anticoccidials), survival through the low pH of the crop, competition with gut microbiota, and the presence of compatible colonization sites influence the susceptibility of poultry to Salmonella colonization (Bailey 1988; Foley et al. 2011, 2013). Campylobacter jejuni is one of the major foodborne agents associated with diarrhea and gastroenteritis and possesses antibiotic resistance genes, so it continues to represent a major concern to the poultry industry (Altekruse et al. 1999; Newell and Fearnly 2003; Yang et al. 2019b). Historically, the prevalence of Campylobacter in the United States was reported to be 32–53% in poultry (Miller and Mandrell 2005). Since 2005, Campylobacter is still considered a major foodborne disease-causing organism and has only become an even-more-critical public health concern. In the European Union, broiler meat and products caused 24.2% of the total foodborne campylobacteriosis outbreaks in 2017 (European Food Safety Authority 2018; Deng et  al. 2020). Consequently, campylobacteriosis has been designated by the European Food Safety Authority as one of the most reported foodborne diseases since 2005, representing 70% of the human zoonoses in the European Union (European Food Safety Authority 2020; Olson et al. 2022). This is partly because Campylobacter has evolved and adapted to colonize in the intestine of poultry as a member of the gastrointestinal tract (GIT) microbial population, which in turn can pose serious public health hazards (Heuer et al. 2001; Newell and Davison 2003; Indikova et al. 2015; Deng et al. 2020). Collectively, the continuing public health concerns reaffirm and further emphasize the importance and demand for effective control strategies and interventions to produce wholesome food products in all phases of poultry production, from live bird production to retail.

7.3 Preharvest Control Strategies Developing interventions that have the potential to substantially reduce pathogens in the live animal can improve food security and safety (Loneragan and Brashears 2005; Ricke and Jones 2010; Callaway and Ricke 2012). A wide range of intervention strategies have been developed to reduce the burden of foodborne pathogens in poultry, including the genetic selection of animals that are resistant to colonization, sanitation practices, additives (feed or water), and biological treatments that directly or indirectly inactivate the pathogen within the host (Doyle and Erickson 2006). However, the use of antibiotics and chemotherapeutics in prophylactic doses for prolonged periods led to concerns across the world about cross resistance and multiple antibiotic resistances among foodborne pathogens, including Campylobacter and Salmonella (Ricke and Calo 2015; Lekshmi et  al. 2017; Yang et  al. 2019a). Furthermore, the use of antibiotics as growth promoters in feed to reduce pathogens impacted the export of meat and poultry products to European countries (EC 2001, 2003). Consequently, there has been a transition by the Food and Drug Administration Center for Veterinary Medicine to veterinary oversight, beyond feed management,

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for medically important antimicrobials that had previously been used in food animals for performance and production applications (Guidance for Industry #213; Food and Drug Administration 2013; Yang et al. 2019a). This in turn has generated interest in the development of novel, innovative, and safe alternatives for poultry and other food animals that would boost natural defense mechanisms, and it includes interventions such as the acidification of feed by organic acids, essential oils, bacteriophages, probiotic organisms, and prebiotic compounds, among others (Patterson and Burkholder 2003; Oliver et al. 2009; Ricke and Jones 2010; Hume 2011; Calo et al. 2015; Dittoe et al. 2018; Ricke 2018). The ultimate objective in the food animal industry is to minimize the risk of antibiotic resistance while maintaining production efficiency and cost. In addition to food safety issues, high protein prices and environmental concerns have caused the poultry industry to consider the adoption of feed supplements such as probiotics that would positively influence bird performance by modulating gut microbiota (Tuohy et al. 2005).

7.4 Chicken GIT Microbiota The chicken gut (also referred as digestive tract or GIT) begins with the mouth and ends at the cloaca, with several important organs and functions (such as the esophagus, crop, proventriculus (true stomach), gizzard/ventriculus, small intestine, ceca, large intestine) along the tract. According to microbiota dynamics and their colonization perspective, the poultry intestine can be divided into three parts: (a) the duodenum and the small intestine, where bacteria numbers are relatively low (less than 108/g), (b) the ceca, the major site of bacterial colonization and microbial fermentation (1011 to 1012/g; wet weight), (c) and the large intestine (Barnes 1972; Barnes et al. 1972). The GIT and its associated tissues in poultry during hatching time are relatively sterile and underdeveloped (Cressman 2009). However, as the chick or poult grows, the GIT provides the required conditions for bacterial colonization, including attachment sites, optimal pH, substrate/nutrients, and waste removal. At this developmental stage, healthy broilers exhibit significant changes such as increased villi volume (three- to fivefold) between day 2 and day 14 and crypt depth (two- to threefold by day 14), along with more rapid proportional weight increases in GIT tissues when compared to total body mass (Uni et al. 1998). Similar increases have also been observed in poults, though not to the same extent (Uni et al. 1999). The development and the subsequent function of the normal GIT microbiota of poultry have been extensively studied in specific pathogen-free (SPF) chickens, which should be unbiased thanks to the absence of competitive microbiota. The use of SPF birds is advantageous compared with using conventionally raised chickens in that there is no risk of additional infectious agents, such as viruses and parasites, that may be in the latter (Coloe et al. 1984). In the same study on the development of the normal GIT microbiota in SPF chickens, no bacteria were detected at hatching (day 1); the development of significant levels—108 colony-forming units (CFUs)

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per gram (CFU/g)—of facultative anaerobes such as fecal streptococci and coliforms occurred by day 3; and Proteus spp. (greater than 107 CFU/g) accompanied them by day 7 in the cecum. In poultry, the major sites of colonization by gut microbiota in the GIT are the crop, proventriculus, gizzard, small intestine, colon, and ceca (Chichlowski et al. 2007a; Gaskins et al. 2002; Heczko et al. 2000; Rastall 2004). Normal GIT microbiota and representative bacteria in various parts of the healthy chicken GIT are presented in Table 7.1. In the proximal part of the intestine (the crop, gizzard, and proventriculus), there are usually low numbers of anaerobic bacteria owing to the presence of oxygen, low luminal pH, and hydrochloric acid originating from the proventriculus (Rastall 2004). In spite of these unfavorable conditions, Lactobacilli can still survive in the chicken crop thanks to surface receptors on Lactobacilli that have the ability to adhere to the squamous epithelial cells of the crop to be retained in high numbers (107 to 108) (Fuller 2001) and exhibit stable, persistent, and host-­ specific adhesion effects (Fuller 1973). Consequently, the predominance of Lactobacilli in the crop results in the production of lactic acid, which can significantly reduce Escherichia coli and Salmonella during contamination (Fuller 1977; Durant et al. 1999, 2000). The microbial colonization of the poultry GIT starts with microbial contact from the eggshell, feed, and other environmental sources immediately after hatching (Cressman 2009). Normal microbiota colonize the GIT beginning with the early posthatch period, develop a biological association with the host, and can have a significant impact on the uptake and utilization of energy and nutrients (Choct et al. 1996; Smits et  al. 1997; Apajalahti and Bedford 2000; Torok et  al. 2007). The Table 7.1  GIT microbiota of the chicken, with predominant microbiota observed in primary gastrointestinal sections

Densitya GIT section pHa (CFU/g) Crop, 3.0–6.0 103 to 105 gizzard, and duodenum Small 6.5–7.5 108 to 109 intestine

Ceca

7.0–7.5 1010 to 1012

Representative gut microbiotab Lactobacilli, coliforms, and Streptococci

Indigenous microbiota with potential probiotic properties Acid-tolerant Lactobacilli

Facultative anaerobes (Lactobacilli, Lactobacilli Streptococci, and Enterobacteria), anaerobes (Bifidobacterium spp., Bacteroides spp., and Clostridia spp.), Eubacterium, and Coliforms Facultative anaerobes (Streptococci, Bifidobacterium Coliforms, and Proteus), obligate anaerobes (Clostridium), Eubacterium, Bacteroides, Lactobacillus, and Methanobrevibacter woesei

Adapted from Chandrasekhar (2009) Barnes et  al. (1972), Coloe et  al. (1984), Fuller (2001), Chichlowski et  al. (2007b), and Saengkerdsub et al. (2007a) a

b

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development of the small intestinal microbiota is observed as starting within the first 2 weeks after hatch until several weeks after hatch (Ochi et al. 1964; Smith 1965; Smirnov et al. 2006). Immediately after hatching, there is evidence that bacteria, particularly Streptococci and Enterobacteria, initially multiply in the ceca and then spread throughout the alimentary tract within 24 h (Smith 1965). Lactobacilli can become established by day 3, while the Streptococci and Enterobacteria slowly decline in the GIT, except in the ceca (Barnes et  al. 1972). By 2  weeks of age, Lactobacilli became the predominant genus in the microbiota with occasional Streptococci and Enterobacteria in the duodenum, and lower portions of the small intestine (Barnes et al. 1972). In the cecum, Bifidobacterium became established as predominant microbiota by 30 days (Ochi et al. 1964). More-recent evidence, based on real-time PCR analyses of feces from 3- to 12-day-old broilers, also indicates the presence of methanogens in these young birds (Saengkerdsub et al. 2007b). In adult birds, most of these methanogens have been identified as Methanobrevibacter woesei (Saengkerdsub et  al. 2007a). Overall, the composition of the microbiota undergoes major changes during the time of hatch, and the anaerobic microbial community becomes established, which requires significant amounts of substrates such as carbohydrates (Apajalahti et al. 2002). The diverse microbial community profile that thus developed over time was historically identified through molecular techniques such as denatured gradient gel electrophoresis (DGGE), % G (guanine) + C (cytosine) profiling, and 16S rDNA gene sequencing (Ricke and Pillai 1999; Apajalahti et al. 2002; Gong et al. 2002; Hanning and Ricke 2011; Holben et al. 2002; Zhu et al. 2002). In studies based on a combination of % G + C profiling, 16 S rDNA gene sequencing, and using certain criteria as described by Maidak et al. (1999), the following was concluded: (1) Only 10% of the GIT bacteria were previously known bacterial species, (2) 35% represented previously unknown species within a known bacterial genus; (3) and the remaining 55% represented bacteria for which even the genus was completely unknown. In total, 640 species and 140 bacterial genera have been tentatively identified in the chicken GIT (Apajalahti et al. 2004). In the past few years, the application of rDNA microbiome sequencing and metagenomics analyses has led to a much more comprehensive examination of these respective broiler and laying hen GIT populations (Sergeant et al. 2014; Stanley et al. 2014; Ricke et al. 2017; Dittoe et al. 2022; Ricke et al. 2022; Weinroth et al. 2022). Collectively, microbiome studies have revealed that microbial diversity is relatively slight among the various GIT compartments in young birds but becomes magnified as the birds age, leading Stanley et al. (2014) to suggest that young birds represent the most likely target of opportunity for GIT modulation. However, this will require extensive baseline GIT microbiome information to detect whether modulation occurs. In addition, the impact of the feed microbiome on the GIT microbial development of the young bird may need to be considered as well (Olson et al. 2022). The microbial community profile in the chicken GIT is influenced chiefly by the diet (grain base) and the age of the bird (Barnes et al. 1972). Apajalahati and Bedford (2000) studied the effect of grains (wheat, corn, or rye) on the microbial community profile and concluded that the incorporation of rye in the diet increased the

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abundance of bacteria, with a 35–40% G + C content, when compared to wheat and corn. While this study did not identify individual bacteria, the authors did conclude that incorporation of diets with corn favored low % G + C microorganisms (such as Clostridia and Campylobacter); whereas the wheat-based diets favored higher-­ percentage G + C microorganisms (such as Propionibacteria and Bifidobacteria). In addition to diets, the processing of grains also had significant effects because different processed diets favored different bacteria in the GIT of chickens regardless of whether the dietary mix originated from the same raw material (Apajalahti et al. 2001). Furthermore, anaerobes and Lactobacilli were found to be significantly lower in the gizzards of broilers fed sorghum and wheat-based diets when compared to broilers raised on barley- and maize-based diets (Shakouri et al. 2008). Similar differences were observed in the cecum, whereas in the ileum, there was no effect of grains on the anaerobic and Lactobacilli populations (Shakouri et  al. 2008). Supplementating diets with fats and the sources of those fats have been observed to influence microbiota structure (Knarreborg et  al. 2002; Dänicke et  al. 1999). Knarreborg et  al. (2002) studied the effects of animal-derived fats and those of plant-derived fats on the microbiota within the ileum of broilers (14–21 days) and reported that the source of dietary fat significantly altered the viable populations of Clostridium perfringens, while Lactobacilli species were not affected. Dänicke et al. (1999) demonstrated that broilers fed diets with beef tallow had significantly more Gram-positive cocci in the crop, jejunum, and ileum (1.18, 1.05, 1.36, and 2.10 CFU/log10 higher) at day 16 compared with those fed diets with soybean oil. Enterobacter was substantially higher in the crop and duodenum (1.05 and 1.30 CFU/log10 higher respectively) in birds fed with soybean oil, and the total number of anaerobes did not substantially vary across intestinal segments because of the source of fat.

7.4.1 Microbiota Changes in Adult Chickens The age of the bird can also influence colonization and susceptibility to infectious agents in the GIT (Corrier et al. 1999; Apajalahti et al. 2004). Even though GIT microbiota in the normal adult chicken constitute sufficient microbial complexity and are relatively resistant to enteric pathogens, stress-associated conditions can make the host susceptible to pathogen infection and colonization (Ricke 2003b; Ricke et al. 2004; Dunkley et al. 2007a, b, d, 2009; Norberg et al. 2010). Feed withdrawal was historically followed as the standard practice to induce molting and is a current practice in broilers prior to shipping to clear fecal content in the GIT and reduce the potential fecal contamination of carcasses (Ricke 2003b; Appleby et al. 2004; Park et  al. 2008; Doyle and Erickson 2006). Although this practice has reduced the number of carcasses with fecal contamination, it can significantly increase the Salmonella and Campylobacter populations in broiler crops (May and Lott 1990; Ramirez et al. 1997; Byrd et al. 1998). Artificial molting in laying hens by withdrawing feed can increase intestinal shedding and the dissemination of

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Salmonella Enteritidis  to internal organs (ceca, spleen, liver, and ovary), thus potentially increasing the public health incidence and people’s susceptibility to salmonellosis through contaminated eggs (Holt et al. 1995; Corrier et al. 1997; Durant et al. 1999; Ricke 2003b; Dunkley et al. 2007c, 2009). This can be due to decreases and shifts in beneficial microbiota and their host-protective activities, such as microbial fermentation to produce volatile fatty acids (VFAs) in the host’s GIT (Ricke 2003a; Ricke et al. 2004; Dunkley et al. 2007d, 2009). In adult birds, there is increasing evidence that providing substrates for fermentation is sufficient to retain protective GIT microbiota that will minimize colonization by foodborne pathogens such as Salmonella (Ricke 2003b; Dunkley et  al. 2009; Norberg et al. 2010; Ricke et al. 2013a; Ricke 2017; Gast et al. 2022). In layers, feeding alternative low-energy molt-induction diets that are rich in fermentable dietary fiber such as alfalfa have been successfully used to produce short-chain fatty acids (SCFAs) in the cecum, thereby reducing the colonization of S. Enteritidis and retaining beneficial microbiota (Ricke 2003a; Woodward et al. 2005; Dunkley et al. 2007d, 2009; Norberg et al. 2010; Ricke et al. 2013a; Ricke 2017). Feeding alfalfa crumble diets to laying hens reduced the colonization of S. enteriditis via various mechanisms, including reducing the virulence expression of the Salmonella virulence gene regulator hilA response compared to the feed withdrawal hilA levels associated with stress (Dunkley et  al. 2007c) and increasing the production of SCFAs, which may also limit Salmonella (Dunkley et  al. 2007d). Furthermore, feeding alfalfa diets to chickens favorably influenced some of their physiological metabolites and stress indicators, such as total protein, uric acid, calcium, triglyceride concentration levels, heterophil to lymphocyte ratios, and α-1-acid glycoprotein (AGP) levels that accompany feed-withdrawal-stress conditions (Dunkley et  al. 2007a, b). In addition, alternative diet regimes containing wheat middlings have been successfully used as molt inducers to limit Salmonella colonization (Seo et al. 2001). Similarly, glucose-based treatments and their commercial products, such as D-glucose polymer (maltodextrin) with added salts and vitamins, can reduce the microbial load of S. Typhimurium (in the crop) or Campylobacter infection (Hinton et al. 2000; Northcutt et al. 2003). The addition of zinc acetate (10,000 ppm) in laying hen diets has been shown to reduce S. Enteritidis colonization in the crop during induced molt, but it depends on the zinc concentration (Moore et  al. 2004; Park et al. 2008). Furthermore, the incorporation of carbon substrates such as lactose into drinking water with a feed-withdrawal molt has been shown to improve resistance to S. Enteritidis colonization by enhancing the fermentative cecal population without dietary intervention (Corrier et al. 1997). In broilers, feeding alternative diets consisting of semisynthetic ingredients during the last 72  hours before slaughter yielded less feed intake and lower live weights (0.24% less per hour) compared with the yields of broilers subjected to feed withdrawal, thereby decreasing the gut contents that would ultimately be involved in the contamination of the carcasses during evisceration (Nijdam et al. 2006).

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7.5 Probiotics In Greek, probiotic means “for life” (Gibson and Fuller 2000) and is defined as “a dietary supplement of living bacteria that exhibits beneficial effects in the host through its effect in the intestinal tract” (Roberfroid 2000). Probiotic supplementation is a strategy that promotes the growth of beneficial microorganisms that are competitive with or antagonistic to foodborne pathogens. Conceptually, this implies the establishment of microbial niches in the gut that prevent the colonization of pathogenic bacteria.

7.5.1 Historical Background For centuries, microorganisms have been used in food processing, such as fermented dairy and meat products (Johnson and Steele 2007; Ricke et al. 2013b). Metchinkoff (1907) proposed that “the dependence of the intestinal microbes on the food makes it possible to adopt measures to modify the flora in our bodies and to replace the harmful microbes by useful microbes.” The consumption of dairy foods such as fermented milk, buttermilk, and yogurt is associated with health benefits and longevity in Bulgarian peasant populations, and the scientific reasons for their beneficial effects have also been proposed (Metchnikoff 1908). The term probiotics was defined by Parker (1974) as “organisms and substances that contribute to intestinal microbial balance.” Fuller (1989) attempted to refine the definition of probiotic as a “live microbial feed supplement which beneficially affects the host animal by improving its intestinal microbial balance.” In later years, there were several attempts to further modify the definition of probiotics by including products and microorganisms or their preparations, proposing the phrase “alteration of microflora” over enhancing the beneficial effects of microbiota and by redefining the term indigenous microbiota (Havenaar and Huis In’t Veld 1992; Salminen et al. 1996; Schaafsma 1996).

7.5.2 Regulatory Considerations of Probiotics In the United States, probiotics used as feed supplements are required to possess generally recognized as safe (GRAS) status, which is regulated by the US Food and Drug Administration. Feed supplements claiming to contain probiotic bacteria must cite the name of the exact taxonomical species of probiotic to avoid misidentification. Manufacturers should also provide the “best-before” date of the product featuring recommended storage conditions, and the strength of the probiotic should match that declared on the label, with a maximum deviation of one or two logarithmic units (Czinn and Blanchard 2009).

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While there are numerous advantages of using probiotic feed supplements, their usage is often associated with adverse side effects, unreliability, and unconfirmed clinical significance (Przyrembel 2001). In 2002, to ensure the equality, safety, reliability, and appropriate usage of the product, the Food and Agricultural Organization (FAO) formulated guidelines that led to the development of operating standards (Reid 2005). An overview of guidelines for evaluating commercial probiotics, including labeling requirements, is presented in Table  7.2. Furthermore, these guidelines and recommendations were considered essential to identify and accurately define the health benefits claimed by the probiotics (FAO/WHO 2002). Given the numerous probiotics on the current market claiming various health benefits, they should be selected and used according to the appropriate criteria as discussed in the following section. Table 7.2  Overview of labeling guidelines/information and selection criteria that should be followed for commercial probiotic feed or supplements (the International Probiotic Association and the World Health Organization) (Dash 2009; Przyrembel 2001; Reid 2005) Step Approach 1 Identification and confirmation of probiotics 2

3

4

5

Determination & validation of probiotic stability

Points of consideration Genus, species, and strain identification through genotype and phenotype methods

References Wang et al. (2002), Gardiner et al. (2002), and Burton et al. (2003) Reid et al. (1987) and Conway et al. (1987)

In vitro tests should be performed to confirm the ability to adhere surfaces, inhibit the growth and attachment of pathogens, resist environmental stress, etc. Safety of probiotics Validation of newly introduced probiotics Marteau (2002) and their safety through in vitro tests, lab animal–feeding trials, and genomic sequencing Efficacy of probiotic Evaluation of the health benefits incurred Reid (2005) on the host health by probiotic usage and comparison with a placebo trial Health claims and Involves labeling guidelines and specific Dash (2009) labeling health claims: the genus, species, and functionality of the strain on the label Strength of the probiotic strain (CFU/mL or g) in the product Serving size and effective dose of probiotic Total servings per container Proven health claims (scientific research validation) Storage conditions Manufacturer’s name and contact address Manufacturer’s lot number and the expiration date

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Table 7.3  Ideal characteristics of optimal probiotics Characteristic Are nonpathogenic and nontoxic and have host origin Are resistant and persistent against stress, processing and storage, and gastric acid and bile Provide suitable adherence factors to attach in intestinal epithelium or mucus and compete for binding sites Produce toxic conditions and antimicrobial/ inhibitory compounds (VFAs, low pH, and bacteriocins etc.) Stimulate/modulate host immune system Alter microbial activities by demonstrating microbial antagonism Are genetically stable and viable at high populations

References Lan et al. (2003) Rastall (2004) Chichlowski et al. (2007a) Saavedra (1995) Saavedra et al. (1994) Gibson et al. (1997)

7.5.3 Selection Criteria of Probiotic Strains Identifying appropriate probiotic strains to achieve maximum beneficial effects in the host is a challenging task. The ideal characteristics for an optimal probiotic are presented in Table 7.3. The selection of suitable probiotic strains is influenced by factors such as the colonizing ability of the microbiota in the gut, their resistance to antibacterial factors such as hydrochloric acid in the proventriculus and gizzard, bile acids in the small intestine and VFAs in the ceca, stability and safety, and the ability to produce antibacterial compounds. Proper criteria as discussed in the previous section (Table 7.2) should be followed for safety, production, administration, application, survival, and colonization in the host (Dash 2009).

7.6 Potential Mechanisms of Action of Probiotics in Poultry Ever since the concept of probiotics was introduced, there has been a drastic change in the perspectives on the composition, knowledge of the GIT microbiota (both obligate and facultative anaerobes), and their mechanisms of action in the intended host. Microorganisms in the poultry host are present as diverse and complex communities that depend on one another and their environment, in contrast to the general opinion that they are independent from surrounding bacteria (Nisbet 2002; Apajalahti et al. 2004; Ricke et al. 2004; Stanley et al. 2014). Most of the bacteria have certain growth requirements, still not completely identified, which are satisfied by their natural habitats and other synergistic bacterial species living in the same community (Nisbet et al. 1996a, b; Apajalahti et al. 2004; Dittoe et al. 2022). The introduction of probiotic microbiota into the host gut should lead to the formation of a complex ecosystem and the generation of additional microbial interactions among the gut microbiota (Guillot 2009). However, these interactions should be balanced and well-established biological defenses against pathogenic organisms.

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There are several mechanisms of action through which probiotics can act in the host. Some of the proposed mechanisms are discussed in the following subsections.

7.6.1 Immune System Stimulation Probiotics are known to interact with the immune system of poultry (Kim and Lillehoj 2019). Several studies have demonstrated the effect of probiotics on the systemic immunity of the host. Incorporating probiotics into the animal diet can stimulate the immune system via the production of immunogenic compounds and by mediating the downregulation of specific signaling pathways (Fuller 1975; Havenaar and Spanhaak 1994; Schiffrin et  al. 1995; Yurong et  al. 2005). Consequently, stimulated immunity can be manifested by enhancing macrophage activity; systemic antibody response through the enhanced immunoglobulin (Ig) production of IgG, IgM, and interferons; IgA levels at mucosal surfaces; and the expression of various pro- and anti-inflammatory cytokines. The administration of probiotics can also lead to increased IgA levels in the lumen-, IgA-, IgM-, and IgG-producing cells and increased T cells in the cecal tonsils (Yurong et al. 2005). Similarly, probiotic administration has been shown to increase natural antibodies against several antigens in both the gut and serums (Haghighi et  al. 2006). Furthermore, the administration of probiotics in chickens has been demonstrated to elicit significant increases in the oxidative burst and degranulation of heterophils (Farnell et al. 2006).

7.6.2 Competitive Exclusion (CE) The initial concept of competitive exclusion (CE) was based on the Metchinkoff principle (1907). Competitive exclusion refers to the physical blocking of intestinal pathogens by probiotic bacteria thanks to their ability to colonize niches within the intestinal tract, such as intestinal villi and colonic crypts (Duggan et  al. 2002). Nurmi and Rantala (1973) and Rantala and Nurmi (1973) successfully demonstrated that chicks (1–2 days old) developed resistance to Salmonella infantis colonization when they were inoculated with a suspension of “gut contents” from healthy adult roosters. This mechanism was referred to as competitive exclusion (CE) by Lloyd et al. (1974) and first applied to poultry. This study initiated worldwide research into finding potential CE cultures (Pivnick and Nurmi 1982). Competitive exclusion application introduces a nonpathogenic bacterial culture (single or several strains through oral administration) to the intestinal tract of food animals to reduce the colonization or populations of pathogenic bacteria in the GIT (Nurmi et al. 1992; Steer et al. 2000). The exact mechanisms by which the probiotic bacteria prevent the colonization of pathogens are typically considered organism specific. Lactobacillus plantarum

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induces the transcription and excretion of the mucins MUC2 and MUC3 from goblet cells and thus inhibits the adherence of enteropathogenic Escherichia coli (EPEC) to the intestinal surface (Fooks and Gibson 2002). Other mechanisms include changes in the physical microenvironment of the intestinal tract by preventing pathogenic bacteria or competing with them for nutrients, growth, and function (Cummings and Macfarlane 1997) and the production of small antimicrobial molecules such as VFAs, lactic acid, or bacteriocins (Kohler et al. 2002). The selection of CE microbiota (especially cecal microbiota) depends on their ability to ferment specific carbohydrates in the form of dietary lactose and mannose or other compounds to produce protective compounds such as VFAs that in turn reduce the number of pathogenic microorganisms in the GIT (Oyofo et al. 1989a, b, c; Hinton Jr et al. 1992; Nisbet et al. 1993; Ricke 2003a). In addition, the availability of growth-limiting amino acids such as serine, the oxidation–reduction potential, and the level of anaerobiosis in the cecum can all play important roles in reducing the number of nonindigenous intestinal organisms in the host (Goren et al. 1984; Nisbet et al. 1993; Ha et al. 1994, 1995; Nisbet et al. 1994; Ricke et al. 2004).

7.6.3 Alter the Intestinal pH Probiotic microorganisms in the intestine produce organic acid end products such as VFAs and lactic acid (Gibson 1999). These weak organic acids reduce the pH so that they will potentially create unfavorable conditions to the survival of pathogenic bacteria such as E. coli and Salmonella (Ricke 2003a; Marteau et  al. 2004; Van Immerseel et  al. 2006; Van Immerseel et  al. 2010). Volatile fatty acids absorbed from the colon serve two purposes: to stimulate water and electrolyte absorption and to provide energy from the bacterial fermentation (Marteau et al. 2004). In addition, VFAs are also involved in the hepatic regulation of lipids and carbohydrates that can serve as energy substrates to vital organs of the host, such as the heart, kidney, brain, and muscle (Meghrous et al. 1990).

7.6.4 Colonizing Ability Probiotic bacteria can colonize three areas in the GIT, namely the small intestinal epithelial  surface, the cecal epithelial surface, and the colonic epithelial surfaces (Yamauchi and Snel 2000). In general, there are at least six microenvironment niches for each of the aforementioned areas: the digesta, the surface enterocytes, the cecum and colon, the mucus blanket, and the epithelial surface (Chichlowski et al. 2007a). Probiotic bacteria such as Lactobacillus and Enterococcus can colonize the GIT of axenic (no microbiota) and gnotoxenic (consisting of specific or known microbiota) chickens (Guillot 1998). However, spores of Bacillus cannot colonize the gut in axenic and gnotobiotic animals and are referred to as transients. The

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colonizing ability is measured by colony-forming units (CFUs), and in poultry, this process begins at the beak and progresses distally to the colon (Simon et al. 2004). Factors influencing successful probiotic colonization include the type of probiotic strain and host specificity, the stability of probiotic strain, the dose and the frequency of administration, health and nutrition statuses, age, stress, and the genetics of the host (Mason et al. 2005). The first step In the colonization of probiotic bacteria is their attachment to the plasmalemma of the enterocyte so that they can resist the subsequent actions for removal from the GIT through peristalsis and the mixing of the digesta and mucus layer (Chichlowski et al. 2007a). Lactobacilli that originate from ingested food or are shed from epithelial surfaces in poultry can permeate the entire digestive tract (Henriksson et al. 1991; Servin and Coconnier 2003). The ultimate beneficial effect of probiotic bacterial colonization is to prevent the adherence of pathogenic bacteria. Briandet et al. (1999) reported that Bifidobacteria and Lactobacilli produced a dose-dependent inhibition of the adherence of enterotoxigenic E. coli (ETEC), EPEC, and S. Typhimurium. In vitro techniques such as microbial adhesion to solvents (MATS) can be used to estimate the affinity of the bacterial cells to polar and nonpolar solvents (Wadstrom et al. 1987). Bomba et al. (2002) demonstrated that hydrophobic interactions are more predominant than hydrophilic interactions in bacterial attachment to intestinal epithelial cells. However, Lactobacilli possess a strong affinity for polar solvents (maximum at pH 7), which suggests that it has an inclination toward hydrophilic associations with cellular surfaces (Huang and Adams 2003). The dietary inclusion of polyunsaturated fatty acids (PUFAs) can affect the attachment sites for the GIT microbiota by modulating the chemical composition of fatty acids in the intestinal wall and thus altering its hydrophobicity (Fooks and Gibson 2002). Probiotic bacteria such as Lactobacillus and Bifidobacterium reduce the oxidation–reduction potential in the gut and provide a favorable environment for colonization (Cummings and Macfarlane 1997).

7.6.5 Maintenance of Epithelial Barrier Integrity Probiotic bacteria have been reported to enhance the maintenance and function of the epithelial barrier (Madsen et al. 2001), and these functions are believed to be carried out through two major mechanisms. In the first mechanism, probiotics increase the basal luminal mucin content through the upregulation of mucin (specifically MUC2) gene expression (Caballero-Franco et al. 2007) and may increase the growth and maturation of goblet cells through metabolites produced from intestinal bacterial fermentation (Chichlowski et al. 2007b). In vitro studies involving Lactobacillus have also demonstrated an increase in the production of mucin (Montalto et al. 2004). This secreted mucin serves as a “mucous blanket” and is made of numerous small associated proteins, glycoproteins, lipids, and glycolipids (Caballero-Franco et  al. 2007). Furthermore, it contains soluble receptors that

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recognize specific adhesion proteins that in turn facilitate bacterial attachment (Chichlowski et al. 2007b). The second mechanism in which probiotic strains may be involved is in altering the permeability of tight junctions (Zonula occludens) to strengthen the biological barrier in the intestinal wall (Shen et al. 2006). These tight junctions form an unbroken, continuous barrier that prevents infectious bacterial entrance and penetration by large molecules of digesta (Chichlowski et al. 2007b). The permeability function of tight junctions is modulated by zonulin, a molecule that is involved in the movements of fluids, macromolecules, and leukocytes from blood streams flowing to and from the intestinal lumen (Shen et al. 2006). Buts et al. (2002) reported on the protective effect of Lactobacillus on zonulin after in vitro treatment with nonsteroidal inflammatory drug administration. Shen et al. (2006) demonstrated that more-intact epithelial cell tight junctions occur after probiotic treatment. However, the exact mechanisms responsible for this observation were not clear in this study.

7.7 Applications of Probiotics in Poultry Preharvest Food Safety 7.7.1 Introduction Probiotics have been extensively examined for the control of foodborne pathogens in poultry. Most of the focus has been directed toward Salmonella, but interest in administering probiotics to limit Campylobacter has recently increased (Santini et al. 2010; Deng et al. 2020). In addition to the food safety attributes of probiotics, their attributes that can improve GIT health and performance are also important. Because poultry production has become more diverse as organic and alternative production systems have become more common, probiotics can offer an acceptable means in these systems for maintaining GIT health and limiting pathogens (Jeni et al. 2021). The most common microorganisms that have been explored as probiotic bacterial candidates are species from genera such as Lactobacillus, Streptococcus, Bacillus, Bifidobacterium, and Lactococcus and certain yeasts such as Saccharomyces species (Roto et  al. 2015; Ricke and Saengkerdsub 2015; Krysiak et  al. 2021). Currently, probiotic bacteria are selected and designed such that they can withstand feed-manufacturing processes, or they are administered by other means, such as through drinking water (Ricke and Saengkerdsub 2015; Krysiak et al. 2021).

7.7.2 Bacteria The supplementation of bacterial probiotics for poultry dates back as far as the 1970s, when undefined cultures were first identified as possessing anti-Salmonella competive exclusion capabilities (Nurmi and Rantala 1973; Rantala and Nurmi

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1973; Bailey 1988; Nurmi et al. 1992). Probiotics included as feed supplements, including those fed to poultry, are referred to as direct-fed microbials (DFMs). Although many sources consider them essentially the same as probiotics, DFMs specifically confer an effect to animal performance, while probiotics exert benefits outside of just increasing growth responses (Abd El-Hack et  al. 2020; Jha et  al. 2019). In order for a bacterium to fulfill the criteria as a functional probiotic, the bacteria must exhibit certain traits, such as being an indigenous inhabitant of the GIT, the ability to withstand gastric juices and bile salts, and the ability to adhere to the epithelial lining in the GIT and confer benefits to the host (Patterson and Burkholder 2003). Importantly, the bacteria must also be able to withstand unfavorable processing and storage conditions (Patterson and Burkholder 2003). To further qualify themselves as valid replacements for antibiotic growth promoters, probiotics used in poultry have been shown to elicit several beneficial responses, including being antagonistic to pathogens in the GIT, stimulating growth in broilers, improving host immunity, reducing GIT disease, and enhancing egg production in layers (Anadón et al. 2006; Guyard-Nicodème et al. 2016; Al-Khalaifa et al. 2019; Peralta-­ Sánchez et al. 2019; Shini et al. 2020; Qamar et al. 2020). As discussed in detail in the previous section, bacterial probiotics interact with pathogens through antagonistic actions such as secreting products, including combinations of bacteriocins, organic acids, and hydrogen peroxide, among others (Abd Al-Fatah 2020). They also participate in CE by competing with other bacteria for adherence to the intestinal mucosal membrane to sequester nutrients from the luminal contents (Patterson and Burkholder 2003; Abd Al-Fatah 2020). The method for identifying the specific nutrients that probiotics compete directly against pathogens for remains somewhat unknown, although certain amino acids appear to be potential targets (Ha et  al. 1994, 1995). There is likely a wide range of nutrients that would dictate competitive interactions, but this would depend on the specific metabolic capabilities of a particular probiotic species and on its substrate preferences. Probiotics also lower GIT pH through the production of VFAs and other organic acids, the latter of which can inhibit pathogens such as Salmonella and E. coli (Ricke 2003a; Van Immerseel et al. 2006; Khan and Naz 2013; Dittoe et al. 2018; Abd Al-Fatah 2020). However, pathogens do possess acid-tolerance mechanisms that can enable them to withstand exposure to certain acids (Ricke 2003a). Probiotic supplementation has been extensively investigated for growth performance effects. Jin et al. (1998) reported that Lactobacillus increased body weight and the feed-to-gain ratio. In a more recent study, L. salivarius and L. reuteri improved intestinal architecture and nutrient absorption (Awad et  al. 2010). In a broiler field trial, Timmerman et al. (2006) reported a slight increase in the broiler productivity index in response to the administration of seven chicken-specific Lactobacillus strains, according to daily gain, feed efficiency, and mortality. Timmerman et al. (2006) also reported decreased mortality from pathogen infection. More-recent studies continue to show the benefits of multistrain probiotics: not only promoting growth performance but effectively limiting the establishment of foodborne pathogens such as Campylobacter and Salmonella (Hume 2011; Clavijo

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and Flórez 2018; Deng et al. 2020). However, other studies have shown no effect on growth performance but did detect a positive impact on the serum IgM concentration and cell-mediated immunity, or multistrain probiotics altered the GIT microbiota (Olnood et al. 2015; Fathi et al. 2017). There has been a trend toward the development of single-species probiotic cultures for poultry that possess specific properties that make them more amenable to practical commercial management systems. A particular interest in spore-forming bacteria, especially Bacillus for animal agriculture, has developed thanks to their thermotolerance and the sustained viability of their spores, which allow them to undergo long-term storage prior to administration in the spore state as probiotics (Ricke and Saengkerdsub 2015; Abd El-Hack et al. 2020). This is attractive because Bacillus spores can be incorporated into feed mill operations due to their ability to withstand thermal processing (Abd El-Hack et al. 2020). Despite the relative stability of the spore, once ingested as a probiotic, it appears to still stimulate the immune system and germinate into vegetative cells in the GIT (Ricke and Saengkerdsub 2015). Spore formers can reproduce and survive even in environments that contain limited nutrients (Abd El-Hack et al. 2020). In both chickens and turkeys, Bacillus-­ based probiotics have been reported to limit the colonization of several pathogenic bacteria, including Clostridium perfringens, E. coli, and Salmonella (Ricke and Saengkerdsub 2015). Other properties, such as the ability to produce an array of extracellular enzymes, may offer additional benefits to Bacillus-based probiotics for poultry nutrition (Ricke and Saengkerdsub 2015).

7.7.3 Yeasts Viable yeasts and yeast products have been promoted for use in the animal feed industry for several years, particularly in ruminant nutrition (Roto et al. 2015). In poultry production, Saccharomyces cerevisiae has been used as the most common yeast-based probiotic (Ahiwe et al. 2021). Numerous benefits have been attributed to S. cerevisiae, both as viable yeast cells and as nonviable hydrolyzed yeast products, including amino acid and vitamin production; an array of enzymes; cell wall components that exhibit prebiotic properties, including mannans, beta-glucans, and chitins; and metabolism-generated fermentates with postbiotic characteristics (Roto et al. 2015; Ahiwe et al. 2021). However, factors such as how yeast cells are produced must be considered when assessing probiotic efficacy in broilers. For example, Sun et  al. (2020) concluded that yeast cells allowed to ferment for different 12-hour interval incubation times (12–60  hours) elicited different responses in broiler feed-conversion rates and altered cecal microbial populations according to 16S rDNA microbiome analyses and cecal metabolite profiles identified with gas chromatography mass spectrometry. Given this array of cellular characteristics, it is not surprising that when fed to broilers, yeast probiotics elicit multiple probiotic activities, including GIT microbiota modulation, immune system stimulation,

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growth performance improvement, and GIT digestion enhancement (Ahiwe et al. 2021). This is also reflected in limiting foodborne pathogen control in broilers. For example, when Massacci et al. (2019) supplemented broiler diets with a S. cerevisiae boulardii culture, they observed that the yeast probiotic not only positively affected the intestinal histology and bird performance but also increased the proportion of GIT bacteria considered beneficial while reducing the level fecal Campylobacter. Liu et al. (2021) also saw proportional shifts to ileal Bacilli and Lactobacilli in aged breeder layers fed a yeast culture supplement that corresponded with improvements in egg quality and hatchability as well as enhanced ileal crude fat digestibility.

7.7.4 Probiotics and Poultry Management Numerous studies have been conducted and have highlighted the beneficial effects of using probiotic feed supplements to enhance the performance of and stimulate the immune responses in poultry (Table  7.4). In general, food animals are often exposed to stress from physiological (age, health status), nutritional (dietary changes), psychological (transportation, housing changes), and environmental (climate, management) factors. This may lead to dysfunction and an increase in the permeability of intestinal protective barriers, which often results in changes in intestinal microbial composition (e.g., a decrease in Bifidobacteria and Lactobacilli) and an increase in susceptibility to enteric pathogens (Si et al. 2004). Although probiotic organisms such as Pediococcus and Saccharomyces are less commonly used in animal feeds, they can modulate the establishment of lymphocyte populations and IgA secretions in the gut and reduce translocation to mesenteric lymph nodes, after an ETEC infection (Lessard et al. 2009). Poultry management practices such as high stocking densities, transportation, and nutritional imbalances or regimens may predispose the host to stress that would ultimately affect the host’s immune system and the colonization of pathogenic bacteria in the gut and lead to potential food safety issues (Virden and Kidd 2009). The supplementation of probiotics in poultry diets has been considered an effective tool to maintain a healthy intestinal microbiota, thereby improving growth performance and reducing the intestinal pathogens (Jin et  al. 1996). Factors affecting the functionalities or efficacies of probiotic supplementation include the route of administration (vent, feed, or water) and the stage of the host  life cycle (Timmerman et  al. 2006). Probiotic supplementations can be administered through powders, liquid suspensions, or sprays in feed or in water or through in ovo methods where the shell membrane of the air cell is inoculated with the probiotic culture after 18 days of incubation for early gut colonization (Fuller 2001; Roto et al. 2016).

Super-BioLicks

Star-Lab company, Clarksdale, MO, USA Leuconostoc spp. (107 CFU/g), Pichia spp. Nippon Formular (107 CFU/g and Bacillus subtilis 105 CFU/g) Feed, Mfg, Japan

PremaLac

Lactobacillus acidophilus, L. casei, Bifidobacterium, Enterococcus faecium

Lactobacillus reuteri, Enterococcus faecium, Biomin, Bifidobacterium animalis, Pediococcus Herzogenburg, acidilactici, Lactobacillus salivarius Austria (2 × 1012 CFU/kg)

BIOMIN Poultry5star

Company Biomin, Herzogenburg, Austria

Active components Enterococcus, Pediococcus, Lactobacillus, Bifidobacterium (probiotic), fructooligosaccharides (prebiotic)

Commercial product Poultry Star

Increase in body weight and growth performance by inducing hypertrophy in intestinal villi and epithelial cells

Beneficial effects in the host Inhibition of pathogens (S. Enteritidis, S. Typhimurium, S. Choleraesuis, C. jejuni, E. coli, and Cl. perfringens) Immunological activity, VFA production, stability against acids and bile salts Growth-promoting effect Modulation of the composition and activities of the cecal microflora Higher specific microbial glycolytic enzyme activities (α-galactosidase and β-galactosidase) compared with the controls Increased body weight of broilers (0–21 days old)

Table 7.4  List of commercial probiotics on the market, with the probiotic cultures and their beneficial effects

(continued)

Khambualai et al. (2010)

Pour and Kermanshahi (2010)

Mountzouris et al. (2007)

References Sterzo et al. (2007) and Mountzouris et al. (2010)

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15 facultative anaerobic bacteria and 14 obligate anaerobic bacteria (Competitive exclusion culture, 107 CFU/g)

2.3 × 108 CFU/g each of Bacillus licheniformis and Bacillus subtilis spores

Lactobacillus casei and L. bulgaricus (~107 CFU/mL) L. bulgaricus (3), L. fermentum (3), L. casei (2), L. cellobiosus (2), L. helveticus (1)a

PREEMPT

BioPlus 2B

Histostat-50

Floramax (FM-B11)

Active components Lactic acid bacterial strain Pediococcus acidilactici (107 CFU/g)

Commercial product Bactocell

Table 7.4 (continued) Beneficial effects in the host Enhanced immune system stimulation and function Significant increase in antibody production against Newcastle disease virus (relative increase in bursa of Fabricius, spleen, and thymus) Protection from Salmonella MSBioscience, colonization by competitive Madison, WI, exclusion and increasing the USA. cecal propionic acid concentration Chr. Hansen A/S, Improved live body weight, feed-conversion ratio, and Horsholm, antibody response to Newcastle Denmark disease virus Alpharma, Fort Increase in body weight and Lee, NJ performance Pacific Vet Group, Increased weight gain in poults Effective in treating clinical USA IVS-Wynco LLC, enteritis caused by Salmonella Senftenberg when used along Springdale, AR with therapeutic antibiotic regimes

Company Lallemand Animal Health Company, France

Higgins et al. (2005)

Higgins et al. (2005)

Rahimi (2009)

Corrier et al. (1995a, b), Nisbet et al. (1996a, b), and Martin et al. (2000)

References Alkhalf et al. (2010)

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Bactocell + Lactose or Myco (Mannoseoligosaccharides)

Protexin

Toyocerin

Commercial product

Company

Beneficial effects in the host Reduced S. Enteritidis colonization in the cecum of neonatal chicks (1 day old) owing to phagocytic action of macrophages Reduced the incidence of S. Typhimurium (60–70%) and that of S. Enteritidis (89–95%) in day-of-hatch broilers Bacillus cereus var. toyoi (109 viable Lohmann Animal Increased performance spores/g of product) Health Int., ME, (fattening) in broilers and turkeys USA 7 strains of bacteria (L. plantarum, L. Improved laying performance Probiotics delbrueckii subsp. Bulgaricus, L. International Ltd, (egg production and shell acidophilus, L. rhamnosus, B. bifidum, S. weight) in Japanese quails UK salivarius subsp. Thermophilus, E. faecium; (Coturnix japonica). 1010 CFU/kg each) and two yeasts (A. oryza, Immunomodulatory effect (increase in avian influenza C. pintolopesii; 109 CFU/kg) viral antibodies) Lactic acid bacterial strain, Pediococcus Bactocell, lactose, and Myco Lallemand acidilactici (107 CFU/g) improved feed-conversion ratio Animal Health Company, France (FCR): 3.2%, 0.5%, and 1.6%, respectively Bactocell + lactose improved Myco Probyn FCR by 4.2% International, USA Bactocell + Myco improved FCR by 5.34%

Active components

(continued)

El-Banna et al. (2010)

Ayasan et al. (2005) Ghafoor et al. (2005)

Jadamus et al. (2000)

Higgins et al. (2007a)

References Higgins et al. (2007b, 2008)

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a

The number in the parentheses denotes the number of isolates in the probiotic culture

Aviguard

NUTRA-GLO

Alltech, Inc, Dried Streptococcus faecium and L. acidophilus, yeast culture (live S. cerevisiae, Kentucky, USA A. niger), dried tridhoderma viride fermentation extract (beta glucan) L. acidophilus fermentation product Sunrise Supply, LLC, Ohio, USA Freeze-dried competitive exclusion culture Schering-Plough, derived from healthy, pathogen-free birds UK

Lacto-Sacc/Lacto-Sacc Farm pak 2X

Company Chr. Hansen A/S, Horsholm, Denmark

Active components Minimum of 3.2 × 109 (CFU/g) Bacillus subtilis (CH201) and Bacillus lichenioformis (CH200)

Commercial product BioPlus 2B (BP)

Table 7.4 (continued) References Mahdavi et al. (2005), Dizaji and Piromohammadi (2009), Šabatková et al. (2008) Zeweil et al. (2006)

Improved growth rates, feed conversion, and egg production Hofacre et al. (1998) Reduced mortality, gross lesions, and performance losses Reynolds (1998) inflicted by the necrotic enteritis Nakamura et al. (2002) infection in broilers Reduced Salmonella colonization without affecting normal antibody response Significantly reduced colonization by multiresistant pathogenic E. coli

Improved egg production, egg mass/hen/day, egg weight, and feed-conversion ratio in broilers

Beneficial effects in the host Increased feed conversion, weight gain Significant increase in goblet cell numbers

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7.7.5 Role of Probiotics: Beneficial Effects Probiotic bacteria such as Lactobacilli and Bifidobacteria have been identified in poultry; they modulate the immune system of the host by stimulating different subsets of the immune system to produce cytokines (Christensen et al. 2002; Lammers et al. 2003; Maassen et al. 2000). Dalloul et al. (2003a, b) demonstrated that probiotic administration results in the secretion of cytokines and changes in the lymphoid cells in the chicken GIT, which may ultimately provide immunity against Eimeria acervulina. However, a precise understanding of the effect of probiotics on the induction of systemic antibody response is not well established (Haghighi et  al. 2006). The beneficial effects of probiotic supplementation in poultry are attributed mainly to CE, which has demonstrated protection against the colonization of Salmonella, Campylobacter jejuni, pathogenic E. coli, and Clostridium perfringens in chicks (Nisbet 2002; Schneitz 2005). The use of Lactobacillus as a probiotic nutritional and health supplement is an increasing trend in the poultry industry because it modulates the immune system of the host and increases overall performance, including the growth rate, the feed-­ conversion ratio, and meat quality (Kalavathy et al. 2003; Mountzouris et al. 2007). The addition of Lactobacillus successfully lowered the mortality rate caused by necrotic enteritis in 1-day-old chicks (Hofacre et  al. 2003). Lactobacillus-­ supplemented poultry diets also significantly reduced S. enteritidis recovery in neonatal chicks (Higgins et  al. 2007a, 2008). Other probiotic bacteria, such as the spore-forming Bacillus cereus var. toyo and B. subtilis, suppressed the persistence and colonization of S. enteriditis and C. perfringens (La Ragione and Woodward 2003). Broiler chicks fed a mixture of probiotics (L. acidophilus, L. casei, Bifidobacterium thermophilus, and E. faecium) had reduced C. jejuni populations (Willis and Reid 2008).

7.7.6 Commercial Probiotic Supplements Currently, there are numerous commercial probiotic supplements consisting of beneficial microorganisms alone or combinations featuring fermentable carbohydrates (prebiotic compounds) available on the market (Table 7.4). Probiotic microorganisms such as Lactobacillus spp., Enterococcus spp., Pediococcus spp., and Bacillus spp. are commonly found in the commercial supplements where Lactobacillus spp. are the predominant group. Several studies have been conducted on Lactobacilli species–based commercial probiotics (Floramax (FM-B11), Histostat-50, and Nutra-Glo) in poultry (Higgins et al. 2005, 2007a, b, 2008). The dietary supplementation of Lactobacilli spp. in poults (7 days old) led to an increase in weight gain for the poults (an increase of at least 18  g on day 21) and effectively treated the clinical enteritis caused by S. Senftenberg when combined with therapeutic antibiotic regimes (penicillin,

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roxarsone, and neomycin) (Higgins et al. 2005). Furthermore, incorporating probiotic cultures of Lactobacilli spp. in 1-day-old broiler chicks reduced the incidence and colonization of S. Enteritidis and S. Typhimurium because of the phagocytic action of macrophages (Higgins et al. 2007b, 2008). Probiotic supplements containing Bacillus spp. (BioPlus 2B, toyocerin) have shown growth-enhancing activities (live weight, feed-conversion ratio, and fattening) in broilers and turkeys and an increased antibody response to Newcastle disease virus in broilers (Jadamus et al. 2000; Mahdavi et al. 2005; Šabatková et al. 2008; Dizaji and Piromohammadi 2009; Rahimi 2009). The dietary supplementation of the lactic acid strain Pediococcus acidilacti (Bactocell) reportedly stimulated the immune function of broiler chicks and thus significantly increased antibody levels against Newcastle disease virus (Alkhalf et al. 2010). Administering commercial probiotic supplements according to competitive exclusion (Aviguard) also significantly reduced the colonization of multiresistant pathogenic E. coli and Salmonella in broilers (Reynolds 1998; Nakamura et al. 2002). Several commercial supplements on the market (Poultry Star, PremaLac, PREEMPT, and Protexin) contain mixed, defined, and characterized probiotic cultures. They have been reported to confer diverse benefits to the poultry host, such as host-protective effects from enteric pathogens (immune stimulation, increased VFA production, reduced colonization, and competitive exclusion) and overall growth performance activities (improved body weight and feed-conversion ratios) (Ayasan et  al. 2005; Sterzo et  al. 2007; Mountzouris et  al. 2007; Pour and Kermanshahi 2010). Mountzouris et al. (2007) reported that a mixed, defined probiotic culture (Biomin Poultry Star) exhibited modulated composition and activities of cecal microbiota, and it displayed higher specific microbial glycolytic enzymatic activity in broilers. In addition to these beneficial effects, some commercial probiotics are well known to protect birds from Salmonella colonization by preventing Salmonella establishment in the ceca after probiotic (PREEMPT) administration (Corrier et al. 1995a, b; Nisbet et al. 1996a, b; Martin et al. 2000). Furthermore, commercial probiotics consisting of yeasts and beneficial bacteria (Protexin, Lacto-Sacc, or Lacto-­ Sacc Farm pak 2X) have been shown to improve laying performance factors, such as egg production, egg weight, feed-conversion ratios (Ayasan et al. 2005; Zeweil et al. 2006), and immune-modulatory activities against avian influenza, in broilers (Ghafoor et al. 2005). The dietary supplementation of probiotics with prebiotic compounds is also known to elicit several health benefits in poultry. EL-Banna et al. (2010) reported that feed-conversion rates improved by 4.2%, or they improved by 5.34% when the probiotic (Bactocell) was supplemented with lactose or Myco (mannoseoligosachharide) in 1-day-old broiler chicks. Furthermore, these combinations (probiotic and prebiotic) also inhibited enteric pathogens such as S. enteriditis, S. Typhimurium, S. Choleraesuis, C. jejuni, and E. coli (Sterzo et al. 2007; McReynolds et al. 2009).

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7.7.7 Probiotics’ Inconsistent Responses In spite of numerous reported health benefits in poultry, inconsistent effects have been observed following probiotic administration (Turner et al. 2001). These inconsistent responses are similar or comparable to the effects observed following the administration of conventional antimicrobials. Furthermore, the results available from the literature on probiotic treatments have often appeared to be contradictory. This may be due to variation in the target pathogen, dietary supplementation, and duration of use. Disregarding the environmental and stress statuses of the animals, the experimental settings also explain the inconsistent results. Factors such as the production environment (cleanliness, history of diseases in the farm, health status) (Catala-Gregori et al. 2007), the source of the probiotic, the number of viable cells in the probiotic and their consistency, their survivability and metabolic capacity in the host gut, the probiotic’s host specificity, the influence of feed processing (e.g., steam conditioning and pelleting) on survivability of the probiotic in the final prepared diet, and differences in the experimental conditions can play important roles in the observed effective responses to the administration of probiotics (Taherpour et al. 2009). The use of probiotics can sometimes also pose adverse effects, especially when those probiotics competitively exclude other indigenous beneficial microbiota with the newly introduced probiotic culture (Edens 2003). Probiotics often cause transitory alterations in the indigenous GIT microbiota, especially when large numbers of probiotic bacteria are introduced (Edens and Pierce 2010).

7.8 Future Directions A comprehensive knowledge base needs to be established on the metabolites responsible for the effect of probiotics on the host immune system’s responses to pathogenic bacteria. Considerable work remains to be done to determine the mechanisms of action and the optimum dose of the probiotics. This includes not only elucidating the mechanism of action but also developing an understanding of the interactions in the host and host responsiveness to probiotics. Genetic evaluations of probiotic and GIT microbiota would help in the selection of appropriate probiotic supplements. The application of molecular and metabolomic approaches, in conjunction with advanced bioinformatic tools such as machine learning to identify and evaluate the microbial communities and their growth requirements, is likely to elicit new microbial responses that benefit the host (Ricke et al. 2017; Dittoe et al. 2022). Applying in-depth analytical bioinformatic techniques can be of great value in understanding the bacteria–diet interactions and the roles of different probiotic bacteria in animal health. These technological approaches would allow the advancement of therapeutic treatments in poultry management systems and enhance the birds’ nutrition through a modified feed formulation to optimize growth and gut health. Identification tools combining microbiome 16S rDNA gene sequencing and

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metagenomics with metabolomics can further increase the ability to ensure validation before, during, and after application (Ricke et  al. 2017; Ricke 2018; Dittoe et al. 2022; Weinroth et al. 2022). A combination of probiotics and naturally occurring components such as prebiotics, nonspecific substrates, plant extracts, and microbial metabolites that act synergistically to improve host health would be more appealing and may yield a new dimension in using probiotics in the sphere of safe food practices. The beneficial effects of probiotics can be further enhanced by selecting more-efficient strains or combinations of microorganisms, through gene manipulation, or by combining probiotics and naturally occurring, synergistically acting compounds such as prebiotics (Bomba et al. 2006). Synbiotics are nutritional supplements which contains a mixture of prebiotics and probiotics that function synergistically (Gibson and Roberfroid 1995). Adding prebiotics to animal feed would further increase the efficiency of probiotic culture preparations by improving the survival of probiotic bacteria throughout the upper intestinal tract and thereby inducing beneficial effects (Roberfroid 1998; Suskovic et al. 2001; Ricke 2018). The findings of the majority of earlier studies concerned with the beneficial effects of probiotics have been difficult to interpret for one or few of the following reasons: no statistical interpretations of experimental results, poor experimental protocols, and the undetermined validity and viability of the probiotic strain (Simon et al. 2001; Jadamus et al. 2000). Henceforth, a comprehensive and clearly defined experimental protocol, along with a valid statistical analysis, should be in place to better apply the results from future research studies.

7.9 Conclusions The major focus of this review was the summation of probiotic beneficial effects and their impact on poultry preharvest food safety and changes in poultry gut dynamics. These changes may include stimulating the immune system and modulating the intestinal architecture with metabolic and physiological adjustments. A critical understanding both of the interrelationship between GIT physiology and microbiology and of its effect on the host immune system is important in the selection of probiotics. The dietary supplementation of probiotics in poultry production has reduced the potential use of antibiotics and other growth promoters and therefore could be viewed as potentially safe for growth promotion. Furthermore, probiotics could improve preharvest food safety by reducing the enteric pathogen load. Nonetheless, none of these alternative strategies/products will be sufficient to control the impact of foodborne pathogens or effective under a wide variety of conditions unless more is understood about specific mechanisms and their respective relationships with the avian host. Acknowledgments  This review was previously supported by a USDA Food Safety Consortium grant and USDA-NIFSI grant number 406-2008-51110 to Steven C. Ricke.

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Chapter 8

Probiotics and Prebiotics: Application to Pets Ching-Yen Lin, Celeste Alexander, Brittany M. Vester Boler, George C. Fahey Jr., and Kelly S. Swanson

Abstract  Probiotics and prebiotics are marketed in the human food sector as being beneficial to gut health. As is often the case, this led to prebiotic and probiotic use in the pet food and supplement markets. There is limited oversight for these products; thus, their application in a clinical setting remains limited. Despite this, research on this topic is continuing to increase, and more outcomes on gut health are being evaluated. Overall, many of the probiotics and prebiotics evaluated in dogs and cats have been shown to have positive effects on gastrointestinal and immune health, and some have reduced potentially pathogenic bacterial species in the large bowel, without adverse effects on nutrient digestibility. Further research is needed, especially on animals in diseased states, to determine effective dosages of supplementation and to evaluate synbiotics (prebiotic and probiotic mixtures).

8.1 Introduction The companion animal industry continues its robust growth with a global market value of approximately USD 125 billion for pet food and pet care products, pet food making up over 73% of the market. Market growth is driven, in part, by an increase in pet guardianship, the humanization of pets by their guardians, and the increased popularity of commercially produced pet foods (Higgins 2007). As more people treat their pets as family members, the sale of pet foods and supplements with proven health benefits steadily increases. Many people also expect functional ingredients with specific benefits be included in pet diets and supplements. Ingredients C.-Y. Lin · C. Alexander Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA B. M. Vester Boler Nestlé Purina North America, St. Louis, MO, USA G. C. Fahey Jr. · K. S. Swanson (*) Department of Animal Sciences, University of Illinois, Urbana, IL, USA e-mail: [email protected] © Springer Nature Switzerland AG 2023 T. R. Callaway, S. C. Ricke (eds.), Direct-Fed Microbials and Prebiotics for Animals, https://doi.org/10.1007/978-3-031-40512-9_8

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intended for supporting healthy digestion, including probiotics and prebiotics, are very popular in both pets and people. Probiotics are defined as “living microorganisms that,  when administered in adequate amounts, confer a health benefit on the host” (Hill et al. 2014), while a prebiotic is defined as “a substrate that is selectively utilized by host microorganisms conferring a health benefit” (Gibson et al. 2017). Both probiotics and prebiotics could play major roles in the development of new pet food products now and in the future thanks to several factors. Many pet guardians are particularly concerned about their pet’s health, which drives their demand for high-quality foods, especially those containing functional ingredients already marketed to humans. Probiotics and prebiotics have been reported to impact a number of biomarkers of health status in humans and animal models with minimal side effects, thereby making them ideal functional ingredients to address health concerns in pets. This is aided by the fact that probiotic- and prebiotic-containing products also are being advertised for human consumption, so guardians recognize these ingredients. Additionally, more niche diets may be formulated to appeal to consumers demanding high-quality, human-grade ingredients. This chapter intends to provide a comprehensive review of the probiotic and prebiotic research that has been conducted to date in dogs and cats. Several outcome variables have been measured to test the efficacy of these compounds in pet animals, but relative to the research reported on rodents, humans, livestock, and poultry, much less research is available on this topic for pets than for many other animal species.

8.2 Probiotics 8.2.1 Application of Probiotics in the Pet Industry Many probiotic studies using dogs or cats have reported the ability of the probiotic to survive in the gastrointestinal (GI) tract. Of these studies, many were prospective studies to determine the potential effects of different bacterial strains. Furthermore, very little information is available on the dosage that is most appropriate or efficacious for each bacterial species. A difficulty with creating pet foods that contain probiotic strains is the fact that most pet foods marketed today are in kibble or moist (canned) form. In order to create a kibble, ingredients must be extruded, which uses high heat (up to 250  °C) and pressure (up to 25  mPa) for short periods of time (1–2 min) to cook the starches and proteins in the food (Cheftel 1986). All canned moist diets undergo retort, which uses high heat (121.1 °C) to sterilize the product (Hendriks et al. 1999). Both processes (extrusion and retort) kill bacteria in the food and would be expected to kill any probiotic strains. Therefore, probiotics must be added after extrusion in order for the bacteria to survive; however, addition to diets after canning is not possible. A further hindrance of adding probiotics is that most pet foods now have a guaranteed shelf life of 12–24 months. Many probiotics may not be viable for this length of time while remaining efficacious. Therefore, sufficient testing should be performed so that label guarantees are valid throughout the

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entire shelf life of the product. Because of these limitations, probiotics often are included as supplements and not within the diet matrix itself. While there are some pet foods on the market that claim to contain probiotics, the ability of companies to produce diets that are shelf stable is suspect. Weese and Arroyo (2003) evaluated 19 commercial pet foods claiming to contain probiotics (13 for dogs, six for cats). All the diets were purchased from pet food retailers and tested prior to the indicated expiration date. None of the diets tested contained all organisms listed on the ingredient label. Ten of the 19 (53%) diets contained at least one microorganism listed on the ingredient label in the diet when tested. Five (26%) products had no probiotic bacteria. The diets tested contained between 0 and 1.8 × 105 colony-forming units (CFU) per gram (CFU/g), but it is unknown whether this was the intended dose or whether it was due to decreases during storage. Furthermore, some diets listed bacterial fermentation products on the label without listing the bacteria itself as an ingredient and yet still claimed to contain a probiotic (Weese and Arroyo 2003). The testing of supplements has been similar to that of complete and balanced pet diets. Label claims were tested on 13 probiotic supplements (five for human use, eight for veterinary use; Weese 2002). Only a few of these supplements, especially those marketed for veterinary use (three out of eight), provided the exact bacterial species included in the supplement or at the concentration declared on the label. Furthermore, all of the veterinary products contained less than 2% of the bacterial concentrations listed on the label, with the highest actual concentration measured at 1.6 × 108 CFU. The author suggests that dosage is below those known to elicit a response in humans (i.e., 1 × 109 to 1 × 1010 CFU; Weese 2002) and is also below the dosage used in much of the published dog and cat literature. Further testing of 44 human and veterinary product labels indicated striking issues with mislabeling (Weese 2003). Many of the products intended for both human and veterinary use contained misspelled (18%) or misidentified (35%) bacterial species or listed nonexistent (4%) bacterial species, and none stated on the expiration date the number of organisms that should be present. This clearly indicates that more needs to be done to ensure proper ingredient labeling, oversee claims, and meet the guidelines for probiotic inclusion in supplements and pet foods.

8.2.2 Probiotic Evaluation In Vitro Probiotic evaluation in vitro may be used as a preliminary evaluation tool to provide a better understanding of the potential of probiotic strains. To date, much of the research has focused on isolating potential probiotic strains and evaluating their ability to survive in the upper GI tract and their mucus adhesion capabilities. The ability of a probiotic to survive in the gut is often measured in vitro through tests of bile acid tolerance and pH tolerance. Mucus adhesion is often determined as a measure of the potential of a probiotic to attach to and colonize within the GI tract. Attachment is important because bacteria that adhere to the mucus are in close contact with immune cells and, therefore, may be able to modulate the immune

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system and have antimicrobial activity toward potentially pathogenic bacterial species. Lactic acid bacteria have been the most commonly studied probiotics in vitro for application to pets. Several strains of lactobacilli, including L. rhamnosus GG (human commercial strain), L. johnsonii La1 (human commercial strain), L. casei Shirota (human commercial strain), L. pentosus UK1A (isolated from dog feces), L. pentosus SK2A (isolated from dog jejunal chyme), Bifidobacterium lactis Bb12 (human commercial strain), and Enterococcus faecium (animal commercial strains), were evaluated in vitro by using dog jejunal chyme as inoculum (Rinkinen et al. 2000). L. rhamnosus adhered to canine mucus better than all other bacterial strains tested. Pretreatment with jejunal chyme to simulate digestion limited the adherence of all the bacterial species, but three of the human-origin bacterial species, namely L. johnsonii (0% change), L. casei (0% change), and B. lactis (~53% decrease), were able to maintain more adhesion than the other human strains and all strains isolated from dogs were. Further studies evaluated isolated bacterial strains of canine origin on their ability to survive and adhere to the mucus in the GI tract. Strompfová et  al. (2006) evaluated canine-derived L. fermentum AD1 both in vitro and in vivo. In vitro, it was noted that 86% of the probiotic survived at a pH of 3 for 3 h, and 75.4% survived in the presence of 1% bile for 24 h. Approximately 2% of all bacteria adhered to canine mucus and 2.7% to human mucus. In vivo, it was noted that fecal enterococci and lactobacilli species increased, but no changes were noted for E. coli or Staphylococcus spp. after 7 days of administration (109 CFU/mL) in healthy dogs (Strompfová et al. 2006). Other canine-derived lactobacilli spp., including L. fermentum VET9A, L. plantarum VET14A, and L. rhamnosus VET16A, have been shown to adhere to canine mucus in vitro (1.4–10.1% adhesion) (Grześkowiak et al. 2014). However, the adhesion capabilities varied among process conditions, such as the pretreatment methods and the growth media. The ability of lactobacilli spp. to survive in the presence of bile salts appears to be highly variable. Canine-derived strains of L. reuteri grew faster (3.17 h vs. 5.30 h) in broth containing bile compared to L. acidophilus and, therefore, are more resistant to bile (McCoy and Gilliland 2007). There were two L. reuteri strains (X-27 and X-18), however, that were able to tolerate bile salts, inhibit S. typhimurium, and produce reuterin, an antimicrobial substance. The adhesion capabilities of these strains were not determined in that study. Kim et al. (2016) noted that L. reuteri BCLR-42 and L. plantarum BCLP-51 derived from canine feces were able to survive at pH 3 and exposure to 0.2% bile and that they had antimicrobial activity against select Gram-negative and Gram-­ positive bacteria. Other canine-derived  lactobacilli spp., specifically L. murinus strains (LbP2, LbP6, and LbP10), were also shown to withstand a pH of 3.5 (a 50% reduction for the most tolerant strain) and exposure to 0.3% bile salts (a 27% reduction for the most tolerant strain), have antimicrobial activity against E. coli and C. perfringens strains (inhibitions zones between 10 and 17  mm), and adhere to mucus (5–16% adhesion; Perelemuter et al. 2008). Enterococci strains of canine origin (six strains) have been evaluated as potential probiotics (Strompfová et al. 2004). Between 72% and 98% of the total population

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of the selected strains were able to survive exposure to 1% bile salts, and between 76% and 87% were able to survive a pH of 3. Percentage adherence to canine mucus ranged from 4% to 11%. Most strains (75%) produced bacteriocin-like inhibitory substances against select Gram-positive bacteria. However, the question of safety regarding E. faecium probiotics has been raised (Rinkinen et al. 2003). E. faecium strains M74 and SF273 enhanced the adhesion of Campylobacter jejuni to canine mucus by 135% and 206%, respectively. If this occurred in  vivo, dogs could be considered potential carriers of C. jejuni, which can cause infections in humans. In addition to researching their abilities to adhere to and to survive in the GI tract, some researchers have begun to evaluate the ability of probiotics to affect the health outcomes of dogs and cats. Duodenal samples from dogs with intestinal inflammation due to chronic enteropathies were used to evaluate the ability of a probiotic to decrease inflammation (Sauter et al. 2005). A lactobacilli cocktail (two L. acidophilus strains (NCC2628 and NCC2766) and one L. johnsonii strain (NCC2767)) increased (approximately a 76% increase compared to the controls) the mRNA expression of the anti-inflammatory cytokine IL-10 and thereby decreased the ratio of pro-inflammatory cytokines (TNFα, IFN-γ, and IL-12p40) to the anti-­ inflammatory cytokine IL-10. L. reuteri BCLR-42 and L. plantarum BCLP-51 were shown to enhance phagocytic ability and the oxidative burst of canine granulocytes (Kim et al. 2016). Urinary oxalate stone formation is a common clinical problem in dogs and cats, and there is no current method of dissolving the stones. Several bifidobacteria and lactobacilli were evaluated for their ability to degrade ammonium oxalate (Murphy et al. 2009). None of the bifidobacteria, but some select strains of lactobacilli, were able to degrade oxalate. L. animalis and L. murinus were shown to have oxalate-­ degradation capabilities, where L. animalis resulted in a 27–68% reduction (compared to the controls) and L. murinus resulted in a 41–72% reduction (compared to the controls) in urinary oxalate. The in  vitro studies described above provide preliminary evidence that some strains of bacteria may have beneficial effects in dogs and cats. The abilities of these strains to withstand exposure to bile salts and low pH and to adhere to canine mucus indicate that they would likely survive the upper GI tract of the animal and reach the large bowel. Furthermore, these studies indicate that the use of probiotics in disease states may improve health biomarkers.

8.2.3 Probiotic Use in Dogs and Cats Probiotic use in pets was reviewed and summarized previously by Vester Boler and Fahey (2009; Table 8.1). Recent studies (2009–present) and research not reviewed previously by Vester Boler and Fahey (2009) are the focus of this chapter and are described in detail in Table 8.2. The most common microbial species evaluated and utilized as probiotics in pets include L. acidophilus and E. faecium. While a moderate number of studies to date have evaluated probiotic use in dogs, limited studies have been conducted in cats.

Nutrient digestibility Growth Fecal characteristics Fecal microbiota

Presence of probiotic after feeding Fecal colonization of probiotic

Pasupathy et al. (2001)

Weese and Anderson (2002)

References Biourge et al. (1998)

Outcome variables quantified Fecal bacilli concentrations during and after removal of treatment Nutrient digestibility

32 healthy adult beagles n = 4 for control and group 4 treatments n = 8 for groups 1, 2, and 3 treatments

4 mongrel puppies (age = 10 wk; BW = 5.3 kg)

Animals/treatment (age, initial BW) 5 female dogs (age = 5–10 yr; average BW = 24 ± 3 kg)

Dietary information; time on treatment RCCI M25, Royal Canin, Aimargues, France Chemical composition: 25% CP 12% crude fat 6.5% CF Time on treatment: 0–7 d delay of appearance; 3 wk disappearance study Basal diet: 33% CP 13% crude fat 4% CF Time on treatment: 9 wk Unknown diet Time on treatment: 5d Control: no supplementation Group 1: 1 × 109 CFU Group 2: 1 × 1010 CFU Group 3: 5 × 1010 CFU Group 4: 5 × 1011 CFU L. rhamnosus strain GG (LGG)

2 ml of 1 × 107 CFU/mLl Lactobacillus acidophilus

Probiotic dose (source) 1.5 × 108 CFU/g diet of Bacillus CIP 5832 (Paciflor, Pasteur Institute)

LGG present after 24 h in dogs in groups 2 (25%), 3 (50%), and 4 (100%) LGG present in 1 dog after 72 h of removal ↑ Fecal LGG levels in group 4 (~129%)**

↑ Fecal lactobacilli counts (11%)** ↑ Coliform counts (8%)* ↓ CF digestion (16%)*

Major findings No changes in nutrient digestibility Bacillus spp. present in feces within 24 h No detection of Bacillus after 3 d after removal of probiotic treatment

Table 8.1  In vivo experiments summarized in Vester and Fahey (2009), listed in chronological order, reporting the effects of probiotics on cats and dogs

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Baillon et al. (2004)

Vahjen and Männer (2003)

References Benyacoub et al. (2003)

Animals/treatment (age, initial BW) 7 puppies (age = 8 wk)

Dietary information; time on treatment Basal diet: Friskies Alpo Complete dry dog food; Nestle Purina Petcare (Glendale, CA) Chemical composition: 22% CP 10% crude fat Time on treatment: 44 wk 12 dogs (average age = 4.6 Basal diet fed to Salmonella spp., maintain BW ± 2.6 yr; average Campylobacter spp., Fed a dry or canned BW = 30.7 ± 20.5 kg) and Clostridium spp. commercial diet population counts Time on treatment: 18 d Basal diet fed to Presence in fecal matter 15 adult dogs (average age = 7.1 ± 2.5 yr; average maintain Fecal microbiota BW BW = 28.8 ± 4.0 kg) WBC analysis Chemical Serum biochemical composition: profile 33% CP 20% crude fat 3% CF Time on treatment: 4 wk

Outcome variables quantified Fecal IgA Plasma IgG and IgA Blood lymphocytes

↓ Clostridium spp. in 10/12 dogs**

2 g/dog (9.2 × 109 CFU) E. faecium (NCIB 10415, Enteroferm)

(continued)

7.1 × 106 CFU/g of L. Presence detected in feces, acidophilus (DSM 13241) disappeared after 2 wk of cessation ↓ Fecal clostridia spp. (approximately 83%)** ↑ Serum IgG (18%) ** ↓ Erythrocyte fragility (45%) and nitric oxide (281%) ** ↑ RBC count (9%) and hematocrit (11%)** ↑ WBC count (6%)* and monocyte number (53%) ** ↓ B cell counts (20%)*

Major findings ↑ Fecal IgA (~50%)* ↑ Plasma IgA wk 18–56 (~50%)** ↑ Response to CDV vaccination ↑ CDV-specific IgA (~50%) and IgG (~97%) ↑ Proportion of mature B cells (39% wk 31; 73% wk 44)** ↑ MHCII molecule surface expression in monocytes (62%)**

Probiotic dose (source) Control: no supplementation Test: 5 × 108 CFU/d Enterococcus faecium (strain NCIMB10415; SF68; Cerbios-Pharma, Barbengo, Switzerland)

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Marshall-­ Jones et al. (2006)

Marciňáková et al. (2006)

References Manninen et al. (2006)

Animals/treatment (age, initial BW) 5 fistulated beagles (age = 4–8 yr)

Dietary information; time on treatment Basal diet Chemical composition: 23% CP 13% crude fat 3% fiber Time on treatment: 7d Fed to maintain BW Basal diet not indicated Time on treatment: 7d

Probiotic dose (source) 1.4–5.9 × 107 CFU/mL/d mixture of lactic acid bacteria (LAB) L. fermentum LAB8, L. salivarius LAB9, Weissella confusa LAB10, L. rhamnosus LAB11, L. mucosae LAB12 1 × 109 CFU/mL 2–3 mL administered, depending on BW of dog Enterococcous faecium strain EE3

Major findings LAB detected in jejunal chyme 7 d after cessation, no LAB in chyme Reduced indigenous LAB in 4/5 dogs

Colonization and survival of probiotic Blood lipids, proteins, and cholesterol

11 dogs (age = 2–7 yr)

↓ Blood lipids in 8/11 dogs ↓ Total protein in blood of 6/11 dogs ↓ Pseudomonas-like spp.** Survival of E. faecium EE3 3 mo after cessation of probiotic 15 adult domestic shorthair Fed to maintain BW 4.1 × 109 CFU/kg diet L. Fecal quality ↓ Bacterial culture of clostridia Basal diet not cats Fecal bacterial acidophilus (DSM 13241) (9.5%),** coliforms (14%),** and (average age = 4.5 ± 0.4 yr; indicated populations (FISH Daily intake between enterococci (31%)** 8 average BW = 3.6 ± 1.1 kg) Time on treatment: 1.2 × 10  CFU and 2.8 enumeration), pH, ↓ Fecal pH (2%)** 4.5 wk ammonia, and hydrogen × 108 CFU ↑ Lactobacillus spp. (4%),** L. sulfide concentrations acidophilus (0.47 log/g WBC count baseline vs. 7.25 log/g Serum biochemical treatment)** analysis ↓ Enterococcus faecalis (66%)** Serum IgA, IgM, and ↑ Fluorescence intensity of IgG granulocytes (30%)** ↓ Plasma endotoxin concentrations (> 250 U/mL baseline vs. < 50 U/mL treatment)**

Outcome variables quantified Presence in jejunal chyme DGGE

Table 8.1 (continued)

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Strompfová et al. (2006)

References Sauter et al. (2006)

Animals/treatment (age, initial BW) 10 dogs for placebo, 11 test dogs diagnosed with food-responsive diarrhea (average age = 28 ± 4 mo)

15 healthy adult dogs Fecal microbiota Blood total protein, total (age = 0.5–3 yr of age) lipid, cholesterol, glucose, aminotransferase, and urea

Outcome variables quantified Duodenal and colonic cytokine gene expression Fecal microbiota

Dietary information; time on treatment Basal dietelimination diet with novel protein source: PurinaR Canine LA (limited antigen) diet (St. Louis, MO) Chemical composition: 28% CP 17% crude fat 2% CF Time on treatment: 4 wk Basal diet provided at 20 g/kg BW APORT Ideal Adult (Tekro s.r.o., Žitňany, Slovakia) Time on treatment: 7d ↑ Enterococcus spp. (25%)** ↑ Lactobacillus spp. (55%)** ↑ Total blood proteins (21%)** and total lipids (33%)** ↓ Blood glucose (11%)**

3 mL (1 × 109 CFU/mL) L. fermentum AD1

(continued)

Major findings ↓ Duodenal IL-10 mRNA levels (38%)* ↑ Total Lactobacillus spp. (29%)*

Probiotic dose (source) 1 g/d probiotic cocktail (1 × 1010 CFU) Probiotic cocktail 2 L. acidophilus strains (NCC2628, NCC2766) 1 L. johnsonii strain (NCC2767)

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Biagi et al. (2007)

References Veir et al. (2007)

Outcome variables quantified Fecal microbiota Fecal C. perfringens enterotoxins and C. difficile toxin A or B CBC, serum biochemical profiles, nonspecific immune response Fecal, sera, and saliva IgG and IgA Serum FHV-1- specific IgG, FHV-1-specific IgA, FCV-specific IgG, and FPV-specific IgG Fecal microbial populations

Table 8.1 (continued)

9 adult dogs

Animals/treatment (age, initial BW) 10 kittens (age = 7 wk)

Basal diet not indicated Time on treatment: 10 d

Dietary information; time on treatment Basal diets chicken and rice dry kitten growth formula Time on treatment: 20 wk

Major findings E. faecium detected in 7/9 treated kittens ↑ CD4+ lymphocytes (~36%)**

Increased lactobacilli fecal counts (108%)***

Probiotic dose (source) 0.25–0.28 g (5 × 108 CFU/d) of dry probiotic powder E. faecium SF68 (NCIMB10415, LBC ME5 PET, Cerbios-­ Pharma SA, Switzerland)

0.5 g (1 x 109 CFU/g) freeze dried probiotic, L. animalis LA4

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Animals/treatment (age, initial BW) 6 adult German shorthair pointers with nonspecific dietary sensitivity (age = 4.5 yr; average BW = 30.8 ± 2.0 kg)

Dietary information; time on treatment Dry kibble diet Chemical composition: Control diet 27.2% CP 8.8% crude fat 2.0% CF Probiotic diet 28.1% CP 8.8% crude fat 1.8% CF Time on treatment: 12 wk Probiotic dose (source) L. acidophilus DSM 13,241 (6 × 106 CFU/g dry dog food) Added after extrusion

Major findings Improved frequency of defecation (~70% 1–2 defecations per d on probiotic vs. 50% 1–2 defecations per d without probiotic), fecal consistency (~70% fecal score 3 (ideal) vs. ~45% fecal score 3 no probiotic), and fecal DM (11.8%)** Numerical increases in lactobacilli (6.2%) and bifidobacteria (6.6%) Numerical decreases in C. perfringens (4%) and Escherichia spp. (1.4%)

BCS body condition score, BW body weight, CBC complete blood count, CDV canine distemper virus, CF crude fiber, CFU colony-forming unit, CP crude protein, d day, DGGE denaturing gradient gel electrophoresis, DM dry matter, FCV feline calicivirus, FHV feline herpes virus, FISH fluorescence in situ hybridization, FPV feline panleukopenia virus, IgA immunoglobulin A, IgG immunoglobulin G, IgM immunoglobulin M, IL-5 interleukin- 5, IL-10 interleukin-­10, LAB lactic acid bacteria, LGG Lactobacillus rhamnosus strain GG, mo month, RBC red blood cell, TDF total dietary fiber, WBC white blood cell, wk week, yr year * p  7 yr; BW = 2.2 to 4 kg)

Dietary information; time on treatment Experimental dry kibble diets Chemical composition: 29% CP 37% crude fat 1% CF Time on treatment: 3 wk A commercial diet (Obesity Veterinary Diet, Royal Canin, France) fed to promote weight loss Chemical composition: 34% CP 10% crude fat 19.8% TDF 1% scFOS Time on treatment: Until ideal BCS obtained (5 out of 9)

Major findings OF: ↑ Fecal moisture (6%)* ↑ DM fecal output (27%)* ↑ Fecal N excretion (36%)* ↓ Urinary N excretion (48%)* ↑ Fecal bacterial N (% of N intake; 125%)* 1% scFOS in control No effect of scFOS supplementation on leptin, insulin, ghrelin, or glucose diet Control diet + 2% scFOS (Beghin-Meiji Industrie, France)

Prebiotic dose (source) 0% supplementation 3.11% OF (Raftilose, Orafti, Belgium), DMB

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Dietary information; time on treatment Hill’s Prescription Diet d/d: Rice and Duck Chemical composition: 17% CP 14% crude fat 4.0% TDF Time on treatment: 14 d

Experimental dry kibble diets Chemical composition: 32.7% CP 23.5% crude fat Time on treatment: 10 d

Animals/treatment (age, initial BW) 5 purpose-bred adult dogs (average age = 3.7 yr; average BW = 28.9 kg)

7 adult dogs

Outcome variables References quantified Spears et al. Food intake (2005) Apparent ileal and total tract nutrient digestibility values Fecal microbiota Fecal characteristics

Vanhoutte Fecal microbiota et al. (2005) population banding patterns (DGGE)

Baseline 4.5 g/d of oligofructose 5.6 g/d of inulin

Prebiotic dose (source) No supplement 2 g of high-­ molecular-­weight pullulan 4 g of high-molecular-­ weight pullulan 2 g of γ-cyclodextrin 4 g of γ-cyclodextrin

(continued)

Major findings Linear ↓ in food intake (352 g control versus 305 g on 4 g/d of treatment) with increasing γ-cyclodextrin* Linear ↑ in ileal bifidobacteria (9.46 CFU/g of feces DM in control vs. 10.12 CFU/g of feces DM) and lactobacilli (9.12 CFU/g of feces DM in control vs. 10.02 CFU/g of feces DM on 4 g/d of treatment) with increasing pullulan* Quadratic effect of ileal bifidobacteria (control: 9.46, 2 g/d: 10.20, 4 g/d: 9.83 CFU/g of feces DM) and lactobacilli (control: 9.12, 2 g/d: 10.11, 4 g/d: 9.42 CFU/g of feces DM) due to increasing γ-cyclodextrin* ↑ γ-cyclodextrin quadratically decreased fecal Clostridium perfringens (control: 9.75, 2 g/d: 9.44, 4 g/d: 9.76 CFU/g of feces DM)** ↑ Streptococcus lutetiensis

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Outcome variables References quantified Gouveia Number of et al. (2006) leukocytes, neutrophils, and lymphocytes Fecal enteropathogenic bacteria Verlinden Nutrient digestibility et al. (2006) Fecal characteristics Hematology Serum and fecal IgA, IgG, IgE, and IgM

Table 8.3 (continued) Dietary information; time on treatment Unknown diets Time on treatment: 10 d

Hydrolyzed protein diet (Hill’s z/d ultra, allergen-free); intact protein source (Hill’s d/d with duck and rice) Chemical composition: Hydrolyzed protein 18% CP 3% TDF Intact protein 14% CP 5% TDF Time on treatment: 21 d

Animals/treatment (age, initial BW) 8 dogs (age: 2–6 mo of age) with gastroenteritis

4 adult beagles (age: 2–11 yr; BW = 6–15 kg)

0% supplementation 3% inulin (Raftifeed Rips, DP 2–60; Orafti, Tienen, Belgium)

Prebiotic dose (source) 0 g of supplementation 2 g of MOS (Bio-Mos, Alltech, Nicholasville, KY)

↓ Fecal DM (12%)** ↓ Apparent CP digestibility in intact protein + inulin diet (4.6%)** ↑ Estimated bacterial protein content in feces (% fecal DM, 16%; and % CP intake, 33%) in intact protein + inulin diet**

Major findings Elimination of E. coli in 85.71% of animals

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Animals/treatment (age, initial BW) 8 primiparous female beagles (BW = 10–12 kg)

6 hound-cross puppies (age = 12 wk)

Outcome variables References quantified Adogony Mammary, nasal, and et al. (2007) blood immunoglobulin concentrations Diarrhea incidence in puppies

Apanavicius Food intake et al. (2007) GI tract histopathology Body temperature after infection Ileal and colonic nutrient and ion transport Fecal microbiota

Dietary information; time on treatment Control diet: 31% CP 16% crude fat 7.8% TDF 0.12% scFOS Test diet: 30% CP 15% Crude fat 6.6% TDF 0.91% scFOS Time on treatment: Gestation d 35 through weaning Control diet: 32% CP 19% fat 3% TDF scFOS diet: 32% CP 19% fat 3% TDF Inulin diet: 30% CP 19% fat 5% TDF Time on treatment: 14 d 0% supplementation 1% scFOS 1% inulin

Prebiotic dose (source) 0% supplementation 1% scFOS (Profeed, Beghin-Meiji, France)

(continued)

scFOS and inulin: ↓ Change in food intake following infection (26%)** ↓ Enterocyte sloughing severity (9%)** Maintenance of ileal Na + − dependent glucose transport (400% ↓ in control, no change in supplemented puppies)** Inulin diet: ↑ change from baseline in fecal acetate (control: −37.7 μmol/g vs. inulin 85.5 μmol/g) and SCFA concentrations (control: −53.5 μmol/g vs. inulin: 145.5 μmol/g)** ↑ Change in fecal lactobacilli concentrations (7%)**

Major findings ↑ IgM in colostrum and milk (40%)** ↑ Blood IgM concentrations (60%)* ↑ Bordetella bronchiseptica–specific IgM immune response in puppies from dams fed scFOS*

8  Probiotics and Prebiotics: Application to Pets 205

References Middelbos et al. (2007a)

Outcome variables quantified Nutrient digestibility Fecal microbiota Fecal fermentative end products Immunological indices

Table 8.3 (continued)

Animals/treatment (age, initial BW) 6 purpose-bred adult female dogs (age = 4.5 yr; BW = 23 kg)

Dietary information; time on treatment Control: no supplemental fermentable carbohydrate Control + 2.5% cellulose Control + 2.5% beet pulp Control + 1.0% cellulose + 1.5% scFOS Control + 1.0% cellulose + 1.2% scFOS + 0.3% YCW Control + 1.0% cellulose + 0.9% scFOS + 0.6% YCW Time on treatment: 14 d

Prebiotic dose (source) scFOS (Nutraflora P-95, GTC Nutrition, Golden, CO) YCW (Safmannan, LeSaffre Yeast Corp., Milwaukee, WI)

Major findings Supplemented diets: ↓ CP digestibility (15%)** ↑ Fecal bifidobacteria concentrations (14%)** ↑ Fecal lactobacilli concentrations (8%)* ↑ Fecal butyrate concentrations (67%)**

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Outcome variables quantified Apparent ileal and total tract nutrient digestibility Serum of IgA, IgM, and IgG Fecal microbiota

8 obese beagle dogs (average age = 6.5 yr; average BW = 12.8 ± 1.3 kg)

Animals/treatment (age, initial BW) 5 purpose-bred adult female dogs (age = 4 yr; BW = 23 kg)

Experimental dry kibble diets Chemical composition: 29.4% CP 18.6% fat Time on treatment: 6 wk

Dietary information; time on treatment Experimental dry kibble diets Chemical composition: 30% CP 21% crude fat 4% TDF Time on treatment: 14 d

1% w/w of DM intake (Profeed, Beghin-­ Meiji, Marckolsheim, France)

Prebiotic dose (source) 0 g supplementation 0.07 g YCW/d 0.35 g YCW/d 0.63 g YCW/d 0.91 g YCW/d (Safmannan, Lesaffre Yeast Corporation, Milwaukee, WI) Major findings ↑ Ileal nutrient digestibility (10% DM, 11% CP)* Linear ↓ in monocyte counts (control containing 1000/μL vs. 0.65% supplementation containing 700/μL)** Linear ↓ in fecal E. coli populations (control containing 9.1 CFU/g of fecal DM vs. 0.65% supplementation containing 8.2 CFU/g of fecal DM**) ↑ Rate of glucose infusion (7.8 vs. 4.7 mg/kg/min)** ↑ Adipose tissue UCP 2 gene expression (~39%)** ↑ Adipose tissue CPT1 gene expression (~32%)*

BCFA branched-chain fatty acid, BW body weight, CF crude fiber, CFU colony-forming unit, CP crude protein, CGM corn gluten meal, d day, DAPA diaminopimelic acid, DM dry matter, DMI dry matter intake, FOS fructooligosaccharide, GE gross energy, GM greaves meal, GOS α-glucooligosaccharide, IgA immunoglobulin A, IgG immunoglobulin G, IMO isomaltooligosaccharide, MBM meat and bone meal, MD maltodextrin-like oligosaccharide, mo month, MOS mannanoligosaccharide, YCW yeast cell wall, N nitrogen, OF oligofructose, PBM poultry byproduct meal, SBM soybean meal, SCFA short-chain fatty acid, scFOS short-chain fructooligosaccharide, TDF total dietary fiber, PM poultry meal, TGOS transgalactooligosaccharide, wk week, XOS xylooligosaccharide, yr year * p