# Interaction between threonine and glycine at low dietary crude protein and the effect on production performance, meat quality and plasma metabolites in broiler chickens

William Lambert, Marc Rovers, Jan Ensink, Sophie Tesseraud, Etienne Corrent, Loek de Lange, Laura Star

► To cite this version:

William Lambert, Marc Rovers, Jan Ensink, Sophie Tesseraud, Etienne Corrent, et al.. Interaction between threonine and glycine at low dietary crude protein and the effect on production performance, meat quality and plasma metabolites in broiler chickens. 20. European Symposium on Poultry Nutrition (ESPN), Aug 2015, Prague, France., 615 p., 2015, Full papers. 20th European Symposium on Poultry Nutrition (ESPN). hal-01607182

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**20th European Symposium on Poultry Nutrition**

24–27 August 2015 | Prague, Czech Republic

FULL PAPERS

20th European Symposium on Poultry Nutrition (ESPN)

Organised by

The Working Group 2: Nutrition of the European Federation of Branches
of the World's Poultry Science Association (WPSA)

and

The Czech Branch of the WPSA
## CONTENT

<table><tr><td>PLENARY LECTURES</td><td>4</td></tr><tr><td>Protein digestion re-visited by proteomics</td><td>4</td></tr><tr><td><u>M. J. Duclos, E. Recoules, S. Réhault-Godbert, M. Lessire, A. Narcy, and I. Gabriel</u></td><td></td></tr><tr><td>Relevance of gut microbiota for digestion</td><td>7</td></tr><tr><td><u>J. Zentek, F. Goodarzi Boroojeni, and W. Vahjen</u></td><td></td></tr><tr><td>Development of the gut associated immune system</td><td>12</td></tr><tr><td><u>B. Kaspers, S. Lettmann, and S. Roell</u></td><td></td></tr><tr><td>Relevance of glycine in low protein broiler feeds</td><td>16</td></tr><tr><td><u>W. Siegert and M. Rodehutscord</u></td><td></td></tr><tr><td>Revisiting Amino Acid Nutrition</td><td>25</td></tr><tr><td><u>P. Belloir, M. Lessire, C. Berri, W. Lambert, E. Corrent, and S. Tesseraud</u></td><td></td></tr><tr><td>The nutritional value of yellow lupin (Lupinus luteus) for broilers</td><td>33</td></tr><tr><td><u>S. Kaczmarek, M. Hejdysz, and A. Rutkowski</u></td><td></td></tr><tr><td>Evaluation of a Lys to Arg antagonism in low crude protein diets for broiler chickens</td><td>35</td></tr><tr><td><u>K. Schedle, R. Leitgeb, J. Bartelt, and E. Corrent</u></td><td></td></tr><tr><td>Fiber in poultry nutrition: Bonus or burden?</td><td>38</td></tr><tr><td><u>S. de Vries</u></td><td></td></tr><tr><td>Comparative interests and limits of metabolizable energy and net energy for evaluating poultry and pig feeds</td><td>46</td></tr><tr><td><u>J. Noblet</u></td><td></td></tr><tr><td>Evaluating the energy content of ingredients in poultry diets – An update</td><td>55</td></tr><tr><td><u>G. G. Mateos, L. Cámara, B. Saldaña, P. Guzmán, and R. Lázaro</u></td><td></td></tr><tr><td>Impact of feed mycotoxins on performance and health of poultry</td><td>63</td></tr><tr><td><u>S. Dänicke</u></td><td></td></tr><tr><td>How to feed layers until 100 weeks? – A practical approach</td><td>68</td></tr><tr><td><u>R. Pottgueter</u></td><td></td></tr><tr><td>Insects as poultry feed</td><td>73</td></tr><tr><td><u>D. Józefiak and R. M. Engberg</u></td><td></td></tr><tr><td>Imprinting – pre/post hatch as a nutritional tool</td><td>80</td></tr><tr><td><u>R. Angel, F. Escribano, Y. Noy, and C. Ashwell</u></td><td></td></tr><tr><td>Improving broiler performance through breeder nutritional management</td><td>88</td></tr><tr><td><u>M. J. Zuidhof</u></td><td></td></tr><tr><td>Nutritional solutions to improve broiler uniformity</td><td>96</td></tr><tr><td><u>R. M. Gous</u></td><td></td></tr><tr><td>Nutritional requirements and feeding management of meat type ducks</td><td>104</td></tr><tr><td><u>E. Baéza</u></td><td></td></tr><tr><td>Nutritional Determinants for Gut Health and Litter Characteristics in Turkeys</td><td>115</td></tr><tr><td><u>J. L. Grimes</u></td><td></td></tr><tr><td>Differences in amino acid and phosphorus digestibility between broiler chickens, turkeys and ducks</td><td>121</td></tr><tr><td><u>M. Rodehutscord</u></td><td></td></tr><tr><td>SHORT ORAL PRESENTATIONS</td><td>127</td></tr><tr><td>POSTER PRESENTATIONS</td><td>152</td></tr><tr><td>Additives</td><td>152</td></tr><tr><td>Feed enzymes</td><td>296</td></tr><tr><td>Feed raw materials</td><td>391</td></tr><tr><td>Mineral nutrition</td><td>452</td></tr><tr><td>Protein and amino acids nutrition</td><td>498</td></tr><tr><td>Other topics</td><td>549</td></tr></table>
# PLENARY LECTURES

## PROTEIN DIGESTION RE-VISITED BY PROTEOMICS

M. J. Duclos, E. Recoules, S. Réhault-Godbert, M. Lessire, A. Narcy, I. Gabriel

INRA UR 0083 Recherches Avicoles, 37380, Nouzilly, France; Michel.Duclos@tours.inra.fr

### Abstract

Further understanding of the mechanisms underlying protein digestion by poultry species is a prerequisite for a more efficient use of diverse protein rich feedstuffs. In this respect, proteomics methods are valuable tools, which can be applied to the feedstuffs or their digestion products. Basically, they rely on the combination of separation techniques (gel based or gel free) with mass spectrometry (MS) based identification, both of which have tremendously progressed in the last two decades and have also benefited of the increasing availability of sequence databases and bioinformatics. A number of studies applied to food products highlighted the power of these methodologies to identify the diversity of proteins in foodstuffs, of their digestion products in vitro or in vivo, and of undigested terminal products, including peptides with functional activities. Data about relevant feedstuffs and their digestion by poultry, or other livestock species, are still scarce. This paper reviews published data and ongoing research and perspectives arising from these.

**Keywords:** poultry, nutrition, broiler, protein

### Introduction

Feed is the main contributor to economic and environmental costs of poultry production schemes. This applies in particular to the protein fraction of the diet, as fast growing broilers require high amount of protein in their diet, with optimal amino-acid profiles. They usually perform best when fed diets based on corn and soybean meal whose composition and nutrient availability are well known and relatively constant, and which are classically used for the breeder's selection schemes. Depending on the global and local contexts of the feedstuff production and markets, legislation, and consumer's demand, broiler producers consider incorporating alternative protein sources, with a lesser digestibility of the nitrous fraction, a suboptimal amino acid availability, which may reduce the performances. Although numerous alternatives have been tested and for a long time now, only few studies considered the actual mechanisms of protein digestion. This paper intends to review the available literature in poultry and other livestock species, and to consider how the advent of proteomics opens new perspectives for a better understanding of protein digestion and its future optimisation through the combination of alternative feedstuffs, improved technological process and incorporation of additives in the diets.

### The principle of proteomics and its application in the food/feed sector

Proteomics is a global approach of the set of proteins present in a biological sample. It usually relies on the extraction of the proteins from the sample, their separation using gel based (1D or 2D SDS PAGE) or gel free (HPLC: reverse phase, ion exchange or size exclusion chromatography) methods, protein digestion, followed by mass spectrometry analysis. Depending on the mass spectrometer used the obtained data are protein or peptides molecular masses, or information on amino acid sequence. The interpretation depends on the quality of the available protein database in the biological organism where the sample originate. Further information can be obtained in a recent review article by Cunsulo et al, 2014. Proteomics has been applied to the study of food or feed protein digestion, and the terminology "protein digestomics" has been put forward by Picariello et al, 2013. These authors identified a growing activity in this field since the year 2000. Samples range from undigested food (feed) to digestion products collected in vitro (static or dynamic models) or in vivo (gastro intestinal tract contents). It is a valuable tool to understand how proteins are digested (or not) along the digestive tract, and to identify the host proteins involved in this process. The power of the methodology relies on the availability of protein (or genomic) sequence data from the organism providing the food (feed) stuff and the host. A further step of integration is the classification of proteins using Gene Ontology terms to appreciate the major biological processes involved.

Illustrations on the power of proteomics in the food sector are available in the review by Cunsulo et al, 2014, and allow to speculate on future perspectives for the feed sector. Protein profiling can be used as a way to assess food quality. Examples are available for wheat and for milk. As wheat is also an important feedstuff, it is worth mentioning that the identification of high molecular weight gluten subunits has been cited as a method for the identification of wheat varie-
ties, whether for quality assessment or authentication (Cunsulo et al, 2014). The identification of protein modifications has been cited as a way to evaluate the consequences of food processing and storage conditions (Cunsulo et al, 2014).

Peptidomics (Dallas et al, 2015), an adaptation designed for the identification of peptides, has also been used to detect digestion products and especially those having functional roles. Soybean, sunflower, cereals, maize and algae proteins have been cited as sources of such bioactive peptides, which could also benefit livestock's performances and health (see review by Cunsulo et al, 2014).

## Studies on protein digestion in animals, including broilers

The European Union, which is largely dependent upon importation of proteins for animal feeding has long considered alternative feedstuffs from home-grown species (see review by Crévieu-Gabriel, 1999). Pea is rich in proteins (18 – 30 %) and in lysine, thus being a good complement to cereals. It can be incorporated to poultry diets up to 10 % without adverse effects on performances and meat quality, although the digestibility of N is lower than for soybean meal based diets. The apparent faecal digestibility of N lies between 67 and 83 % (Carré & Conan, 1989, cited by Crévieu-Gabriel, 1999), lower than in pig. An experimental approach has been conducted to identify the mechanisms underlying digestion of pea proteins in broilers. The globulin fraction was observed to be well digested (87 %), despite its globular structure and low solubility. The combination of polyacrylamide gel electrophoresis and immunoblotting (IB) with antibodies directed against specific pea proteins allowed to obtain important results. Undigested polypeptide fractions of albumin (PA2), lectin and legumin were detected at the terminal ileum (Crévieu et al, 1997a and Gabriel et al, 2008). An endogenous protein of MW 57 kDa also accumulated in the ileum of birds fed pea or N free diet (Crévieu et al, 1997 a and b).

As a first example of using proteomics for feed digestion by monogastrics, Le Gall et al (2005) conducted a study in pigs fed diets incorporating different pea cultivars. Ileal proteins were separated by 1D gel electrophoresis and subsequently identified by immunoblotting or by LC-MS-MS. The MS-MS strategy was found appropriate to identify endogenous protein losses while immunoblotting was more suited to the detection and identification of dietary proteins. This might have resulted from the limited amount of protein sequences available for pea at the time. The endogenous protein losses corresponding to porcine enzymes and to antibodies varied between pea cultivars, which the authors linked to their relative fibre contents.

In an ongoing study (Recoules et al, 2015), protein digestion was followed in 21 day-old broilers fed semi-synthetic diets based on a single protein source (S: soybean meal, R: rapeseed meal, P: pea or C: corn DDGS). The soluble fractions of jejunal contents were analysed by 1D gel electrophoresis and LC-MS-MS, allowing for the identification of proteins with molecular weights between 15 and 75 kDa. Five bands (25, 26, 27, 36 and 55 kDa) were present in all samples, regardless of the protein source. The proteomics approach allowed identifying a number of chicken functional proteins, with a high proportion involved in digestive processes (protein digestion, carbohydrate metabolism, nucleic acid metabolism or intestinal homeostasis). Of the 59 chicken proteins identified, 18 were found in all diets, while 15 were diets specific (12 for S, 3 for P), suggesting a specific induction in response to the diet. These proteins, or fragments, were detectable in all common bands, where they were also mixed with plant proteins, and not only the 57 kDa, which likely corresponded to the 55 kDa band by Crévieu et al, 1997 as endogenous, by collecting samples from birds fed a N free diet. For the pea based diet, two specific bands of 16 and 24 kDa were identified and contained pea proteins with equal or lower theoretical MW: lectin, legumin and Bowman Birk Inhibitor (BBI), a trypsin inhibitor. This suggested that these proteins were hardly degraded. The observations concerning lectin and legumin were consistent with those made by Crévieu et al, 1997 and Gabriel et al, 2008, in chickens or Le Gall et al, 2005 in pigs, for lectin, using IB with specific antibodies. Similarly, soybean or rapeseed derived proteins were detected in samples collected from birds fed the corresponding diets. By contrast, no residual product was detected in the Corn DDGS based diet. As the corn protein database is the most documented, and assuming that technical problems such as extraction and solubilisation of proteins from different materials can be ruled out, this would suggest that corn proteins are highly digestible. By contrast, the occurrence of indigestible products may be underestimated in feedstuffs originating from species where data are scarce. Indeed, available protein sequences were about 3700 for Pisum (Pea), 18500 for Brassica (Rapessed), 105000 for Glycine (Soybean) and 175000 for Zea (Corn).
Conclusions and perspectives

The available and coming data show the interest of proteomics for a better characterisation of feedstuffs and for under-
standing the mechanisms underlying protein digestion. The following outcomes may be expected:

- A more detailed description of the products of digestion of plant proteins in the different parts of the digestive tract and their kinetic of appearance, the identification of resistant proteins or peptides, the understanding of their interaction with endogenous proteins.

- A better identification of endogenous proteins: i.e. a full list of enzymatic activities in the GI tract of the chicken, including the evaluation of the activity, by zymography for example. This will be completed by genomics studies for the identification of the expressed genes, thanks to the relatively rich genomics databanks in the Gallus gallus species.

- The obtained knowledge may ultimately lead to innovations for improving protein digestion, such as selection of more adapted cultivars, development of new feed processing schemes, or addition of appropriate additives.

- In a longer term, the feed sector could benefit from new ideas coming from the food sector. For example, the identification of bioactive peptides in raw materials could contribute to combine improved animal health and reduced medicinal inputs.

Literature

CREVIEU, I., B. CARRE, A-M. CHAGNEAU, L. QUILIEN, J. GUEGUEN, S. BEROT., 1997 : Identification of resistant pea proteins (Pisum sativum L) in the digestive tract of chickens. J. Agric. Food Chem. **45**, 1295-1300.

CREVIEU, I., B. CARRE, A-M. CHAGNEAU, J. GUEGUEN, J-P.MELCION., 1997 : Effect of particle size of pea (Pisum sativum L) flours on the digestion of their proteins in the digestive tract of broilers. J. Sci. Food Agric. **75**, 217-226.

CREVIEU-GABRIEL, I., 1999 : Digestion des protéines végétales chez les monogastriques. Exemple des protéines de pois. INRA Prod. Anim. **12**, 147-161.

CUNSOLO, V., V. MUCCILLI, R. SALETTI, S. FOTI., 2014. Mass spectrometry in food proteomics: a tutorial. J. Mass. Spectrom. **49**: 789-784.

DALLAS, D.C., A. GUERRERO, E.A. PARKER, R.C. ROBINSON, J. GAN, J.B. GERMAN, D. BARLE, C.B. LEBRILLA., 2015. Current peptidomics: Applications, purification, identification, quantification and functional analysis. Proteomics. **15**: 1026-1038.

GABRIEL, I., L. QUILIEN, CASSECUELLE, F., JUIN, H., LESSIRE, M., SEVE, B., DUC, G., BURSTIN, J., 2008. Variation in seed protein digestion of different pea (Pisum sativum L.) genotypes by cecectomized broiler chickens: 2. Relation between in vivo protein digestibility and pea seed characteristics, and identification of resistant pea polypeptides. Livestock Sci. **113**, 262-273

LE GALL, M., L. QUILIEN, J. GUEGUEN, H. ROGNIAUX, B. SEVE., 2005. Identification of dietary and endogenous ileal protein losses in pigs by immunoblotting and mass spectrometry. J. Nutr. **135**: 1215-1222.

PICARIELLO, G., G. MAMONE, C. NITRIDE, F. ADDEO, P. FERRANTI., 2013. Protein digestomics: Integrated platforms to study food-protein digestion and derived functional and active peptides. Trends in Analytical Chemistry. **52**: 120-134.

RECOULES, E., H. SABBOH-JOURDAN, A. NARCY, M. LESSIRE, G. HARICHAUX, M. DUCLOS, S. REHAULT-GODBERT., 2015. Identification of protein fractions in digesta of broilers fed with different protein sources. Poster ID 106 in Proceedings of ESPN 2015.
# RELEVANCE OF GUT MICROBIOTA FOR DIGESTION

**Jürgen Zentek, Farshad Goodarzi Boroojeni, Wilfried Vahjen**

Institute of Animal Nutrition, Freie Universität Berlin, Königin-Luise-Straße 49, 14195 Berlin, Germany;
juergen.zentek@fu-berlin.de

## Summary

Microbes contribute to the digestive process in chicken. Bacterial fermentation of non-digestible carbohydrates and dietary fibre helps to generate energy for the host. Thus, microbial fermentation can be considered as trophic factor especially when high fibre ingredients and by-products are used. Protein fermentation yields a spectrum of undesirable metabolic products such as ammonia that can have negative effects on animal health and performance. However, the impact on the host is not yet clear and deserves more in depth work in chicken. Fat digestion is affected by microbial activities in the small intestine, especially bacteria with the ability to deconjugate bile acids can reduce the apparent digestibility of fat in the small intestine. Besides the gross composition of the diet, minor components such as amino acids and other feed additives have been shown to affect the microbial composition, metabolic activity and may impact animal health. Manipulation of the intestinal microbiota and optimizing the interaction with the host organism is a promising scientific field to improve animal performance, health and well-being. This is of high interest as the use of antibiotics should be as far as possible minimized in chicken production.

**Key words:** microbiota, digestion, fermentation, health, performance

## Introduction

The intestinal microbiota has important functions in the digestive process in all animal species including humans. This was intensively studied in ruminants, but it became clear that monogastric animals such as poultry have a highly diverse microbial colonisation of the gastrointestinal tract (Waite and Taylor 2014) which is of utmost importance for the digestive process, animal health and finally also well-being. Ideally, nutrition has to support the "best possible fitness in a given environment" (Rinttilä and Apajalahti 2013). Concentration, diversity and metabolic activity of the intestinal microbiota increase significantly from the upper to the lower gastrointestinal tract (Rehman et al. 2007). Studies in humans and many other species show that the intestinal microbiota affects and supports the digestive process, but it is also interacting in various ways with the host organism (Tellez et al. 2006). This interaction has on the one hand trophic functions; on the other hand, the intestinal microorganisms also widely affect the gastrointestinal epithelium, the intermediary nutrient metabolism and play a vital role for the immune system. While the understanding of the importance of the intestinal microbiota is constantly evolving, it has become clear that animal health and wellbeing are supported by a balanced microbial composition. This condition is often referred to as "eubiosis". An undesirable status of the microbial system would be a "dysbiosis", which could be described as atypical composition and/or metabolic activity of the intestinal microbiota. Dysbioses can pave the way for gastrointestinal disorders, and may prepare the colonisation by pathogens or pathogens, as the colonization resistance can be adversely affected (Klis and Lensing 2007). In this overview, the composition of the gastrointestinal microbiota and their metabolic activity will be discussed in the context of nutritional interactions. It has to be emphasised, that the interpretation of studies and the comparison of different findings is complicated by methodological factors. Many of the available data comes from traditional cultural microbiological studies, on the other hand, in recent years almost all the work is based on molecular methods, allowing deeper insights into a very complex ecosystem with genetic, age and spatial related particularities, and exogenous factors. Nutritional impact seems to be of utmost importance for the intestinal microbial-host relation and has a high potential to modify animal health and performance.

## Colonisation of the avian gastrointestinal tract with microorganisms

The intestinal microbiota and its diversity is subjected to age effects in broilers (Lu et al. 2003). The crop is the first storage organ for ingested feed and is colonised intensively with microorganisms, especially lactobacilli (Collado and Sanz 2007). Consequently, microbial fermentation activity is already high, which manifests in an intensive formation of lactic acid and other short-chain fatty acids. In addition to lactobacilli, which were detected in high concentrations, enterobacteria, enterococci and anaerobic bacteria (clostridia, bacteroides, bifidobacteria) have been determined more or less regularly (Rehman et al. 2007). Physiologically it can be assumed that the microbial fermentation in the crop results in a first fermentative digestion of feed compounds (Goodarzi Boroojeni et al. 2014). Furthermore, the formation of organic acids could be a first barrier against environmental bacteria (Rehman et al. 2008). A selection process with the
reduction of acid intolerant bacteria can be assumed. There are only few systematic studies on dietary influences on the microbial colonisation and metabolic activity in the crop. The glandular stomach has very low pH values, and thus is of paramount importance for nutrient digestion, especially the hydrolysis of proteins. Despite the relatively low pH value, comparatively high concentrations of lactobacilli, enterococci and lactose-negative enterobacteria have been determined. In addition, *Escherichia coli* and coliform bacteria occur in higher concentrations (Rehman et al. 2007). To what extent this is resident bacteria or bacteria that originate from the digesta flow out of the crop, is not yet clearly established. Also, few studies on the microbial metabolites in the gizzard have been published (Goodarzi Boroojeni et al. 2014). In poultry, the microbial density of the small intestine is subject to strong fluctuations. In proximo-distal direction, an increasing diversity of the microbiota and higher bacterial numbers have been determined. Low concentrations of microorganisms are likely to be more favourable for the efficiency of the digestive processes in the small intestine, because the host-microbiota competition for nutrients is lower. In the duodenum, relatively low pH values, and the high inflow of bile and pancreatic secretions are of critical importance as regulatory factors, reducing the microbial density. In the distal small intestine, total bacterial counts are 7-9 log/g digesta (Rehman et al. 2007). Mostly lactobacilli, enterobacteriaceae and enterococci have been determined. The microbial metabolites show amazing variations between individual studies: it was found that the levels of lactic acid can reach 10-53 µmol/g, the concentrations of short chain fatty acids are given with 4-47 µmol/g. Acetic acid is dominating, propionic and butyric acid were found more irregularly (Rehman et al. 2007). The caecum has an intense microbial colonisation and is considered as anaerobic fermentation chamber. Recent studies show a significant microbial diversity (Choi et al. 2014), where anaerobic bacteria predominate in contrast to the upper gastrointestinal tract. The fermentation activity is clearly different to the small intestine. The total concentrations of short chain fatty acids are higher and acetic, propionic and butyric acid are predominant, while lactic acid occurs in low concentrations only (Rehman et al. 2007). The microbial colonisation of the hindgut has similarities to the caecum.

## Nutrition and intestinal microbiota

The gastrointestinal microbiota is subject to influences from the production technology, the feed composition, wherein both, the nutrient profile and the components used are of importance, and feed additives. The availability of feed is important, as fasting leads to a significant restructuring of the intestinal microbiota with increasing levels of enterobacteria (Holt et al. 2006, Moore and Holt 2006). At the same time, a significant reduction of microbial diversity was observed (Hinton et al. 2000, Thompson et al. 2008). The underlying reasons are the change in the substrate supply and stress-dependent effects. Strong influences of feed particle size have been described. Pelleted finely ground diets induced higher concentrations of volatile fatty acids in the crop and in the caecum (Huang et al. 2006). Feeding whole-wheat grains induced higher concentrations of volatile fatty acids in the crop of broilers (Bjerrum et al. 2005). Both, in broilers and laying hens feed structure has a significant impact on the microbial metabolic activity in the crop and in the gizzard. Apparently, a coarser structure stimulates a higher motor and secretory activity. This goes hand in hand with higher weights of the gizzard, the pancreas and the small intestine in animals fed with coarse diets. Under these conditions, a decrease in microbial colonisation of the small intestine was observed. Fermented liquid feed with high levels of lactobacilli has been shown to have a positive impact on the colonisation of the gut with *Salmonella* (Heres et al. 2003). Pelleting and thermal conditioning treatments of feed improve the hygiene of feed, can alter the chemical and physical characteristics of feed ingredients and affect the nutrient digestion and availability. The knowledge on the impact in microbial colonisation and metabolic activity of the gastrointestinal microbiota in chicken is limited, however, available data indicate only moderate effects (Goodarzi Boroojeni et al. 2014).

Carbohydrates have a strong impact on the intestinal microbiota as they and their hydrolysis products can serve as nutritional substrate for microbes and due to their hydration ability affect intestinal viscosity. Fermentable carbohydrates can be metabolised by lactic acid bacteria and thus can be useful to reduce enterobacteria during periods of feed withdrawal (Hinton et al. 2002). Non-starch polysaccharides affect the viscosity of the digesta and thus the substrate availability for the intestinal microbiota. The relevant carbohydrates comprise (1,3;1,4)-β-glucans and arabinoxylans, which have a high water binding capacity and can be readily degraded by microorganisms. Administration of diets containing high levels of non-starch polysaccharides also results in an increase in the transit time as well as in reduced nutrient absorption. This can stimulate the growth of specific microorganisms in the small intestine. Corresponding studies have shown that an increased viscosity of the digesta in the small intestine is accompanied by increased levels of *Clostridium perfringens* (Branton et al. 1997), *Campylobacter* (Fernandez et al. 2000) and spirochetes (Phillips et al. 2004). Administration of viscous diets with wheat instead of corn is at an increased risk. The impact of viscosity enhancing ingredients seems to be affected by the parasite status of birds. Carboxymethyl cellulose, as a viscosity-enhancing additive, had
less pronounced effects in birds infected with coccidia compared to non infected controls (Waldenstedt et al. 2000). The data allow the conclusion, that carbohydrates affect the intestinal microbiota and vice versa, and support the host by providing substrates being useable for energy generation. Viscous types of carbohydrates seem to be at higher risk to have negative impact on health and performance.

The role of different dietary fibre sources has not been widely studied in chicken. The microbiota can under certain conditions improve energy availability from fibre rich feedstuffs (Hegde et al. 1982, Muramatsu et al. 1991). Carboxymethylcellulose as jellying fibre source interfered with digestive processes in the upper intestinal tract and increased the concentrations of clostridia, lactobacilli and *Bacteroides* (Smits et al. 1998). Cellulose and wood shaving had different effects on the intestinal microbiota and obviously, this is also dependent on the particle length of the fibre sources (Amerah et al. 2009). Increasing dietary fibre in combination with coarse grinding has been shown to be useful for stimulating microbial diversity, leading to improved colonisation resistance against *Salmonella* (Santos et al. 2007, Escarcha et al. 2012). Pine shavings showed some protective efficacy in chicken challenged with *Salmonella* (Branton et al. 1997).

The protein supply may have a significant impact on the intestinal microbiota, both qualitatively and quantitatively. High protein diets increase the concentrations of proteolytic bacteria, especially clostridia. From the viewpoint of animal health, it is interesting in the context that there seems to be a link between the intestinal concentrations of *Clostridium perfringens* and the protein supply. Fishmeal is at higher risk compared to soya meal (Drew et al. 2004). Next to the protein itself, in particular the protein quality seems to be significant. The administration of feed with animal derived proteins led to a sharp increase in the concentrations of *Clostridium perfringens* and necrotic lesions in the intestinal mucosa. The amino acid methionine resulted in a reduction of the clostridia counts (Dahiya et al. 2007). In contrast, glycine caused an increase (Wilkie et al. 2005). In this respect, clear evidence is arising from these studies that the intestinal microbiota of the gastrointestinal tract is subject to strong effects by the protein composition, and that this can cause significant repercussions for animal health. Adjusting protein supply and amino acid profiles can be considered as essential to achieve optimal performance and to control the intestinal formation of metabolites such as ammonia and biogenic amines from protein fermentation, that are generally considered as detrimental (Rehman et al. 2009).

Fat intake seems to have a minor impact on the intestinal microbiota, although it could be shown that certain polysaturated fatty acids (Jozefiak et al. 2014) and medium chain fatty acids can reduce microbial concentrations including *Campylobacter* (van Gerwe et al. 2010, van der Hoeven-Hangoor et al. 2013). Bacterial bile acid deconjugation can interfere with the fat digestion in the small intestine (Knarreborg et al. 2003, Knarreborg et al. 2004). This aspect would deserve clearly more research to study the impact of fat concentration and qualitative aspects of different dietary fat qualities.

Many feed additives have an effect on the intestinal microbiota and thus influence on the digestive process. Corresponding effects are important under the terms of common feeding practice, also for *Salmonella* control (Totton et al. 2012). In practical terms, organic short and medium chain fatty acids, their salts, pre- and probiotics, enzymes and phytogenic additives have been widely studied with variable but generally positive effects (Huyghebaert et al. 2011). Relation to the intestinal microbiota is variable, but an impact on microbial concentrations and metabolic activity seem to be of utmost importance for performance enhancement and health effects, that have often been reported.

## Conclusion

The gastrointestinal microbiota is of utmost importance for feed digestion and supports the host by providing energy yielding substrates from non or low digestible feed compounds. On the other hand, it generates potentially harmful metabolites from undigested proteins, and the importance for animal health and performance has not yet been fully addressed in poultry. New technological developments for assessing intestinal microbiology will help to foster the understanding of the role of the microbiota for nutrient utilisation, host physiology and finally animal health and well-being.
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# DEVELOPMENT OF THE GUT ASSOCIATED IMMUNE SYSTEM

Bernd Kaspers, Sarah Lettmann and Susanne Roell

Department for Veterinary Sciences, Institute for Animal Physiology, University of Munich, Germany; Kaspers@lmu.de

## Introduction

The mucosal surface of the gut is a fascinating structure. A single epithelial barrier separates the intestinal content from the body. The intestinal content does not only consist of digested feed but harbors a highly complex microflora called the microbiome. Consisting of bacteria, fungi and archaea and some poorly defined viruses the microbiome has been estimated to be made up of more than 1000 different species collectively representing more than 100-fold more cells than the vertebrate host itself. The microbiota is well known for its capability to digest plant products which otherwise were inaccessible for the vertebrate as a nutrient source. However, research in recent years has demonstrated that the microbiome affects not only metabolic processes but also the development and function of the immune system (Belkaid and Hand 2014). Conversely, the composition of the microbiome seems to be modulated by the immune system. This cross-talk between the bacterial flora, the intestinal epithelium and the immune system has become a research focus in immunology over the last 10 years. Immunologists have used germ free mouse models, gnotobiotic mice and mice treated with antibiotics to get completely sterile animals or mice with a defined microbiome. This work has led to a wealth of information in mouse models (Kamada and others 2013) while knowledge in humans and domestic animal species is still highly limited.

## The avian immune system

The avian immune system is largely similar to its mammalian counterpart, even though some striking differences are found such as the absence of lymph nodes and the presence of a unique organ for B-lymphocyte development only existing in birds named the bursa of Fabricius (Schat and others 2014). Two major arms of the immune system have been defined which are called the innate and the adaptive immune system. The innate immune system provides a rapid response to pathogenic challenge while the adaptive immune system is responsible for sustained pathogen control and immunological memory. Both systems are made up of cellular and soluble components some of which have been known for a long time including macrophages and heterophils, complement components, and antibodies. Others have been characterized more recently in mice but are still poorly defined in birds (e.g. T-lymphocyte subsets or innate lymphoid cells). The two arms of the immune system closely interact with each other to provide adequate protection and communicate with each other through cell surface molecules and soluble factors collectively called cytokines. Cytokines play a critical role in the regulation of immune response to pathogens, vaccination, in immuno-regulation, and in the control of inflammation. Since the initial publication of the chicken genome significant progress has been made in avian immunology. Genomic data provides sequence information for genes involved in immuno-regulation and the function of the well-defined lymphoid tissues of the spleen, thymus, and the bursa of Fabricius. In contrast, mucosal tissues of the lung, reproductive tract, and the gut are less well understood.

## Development of the gut associated innate immune system of chickens

Using immunohistology, holistic gene expression analysis, and functional assays we have investigated the development of the gut immune system from hatch to seven weeks of age in both broilers and layers. Macrophages are readily found in large numbers from the day of hatch throughout the gut. Their number increases in parallel with gut growth (Figure 1). Macrophages are located in the lamina propria and are thus well positioned to rapidly detect invading pathogens or epithelial damage. Studies in Salmonella enterica infection models of day old chicks have revealed that these macrophages are fully functional and respond to pathogen invasion with the secretion of inflammatory cytokines and chemokines to attract more phagocytes into the mucosal tissue which help to clear the infection. Within hours of infection the chemokines interleukin-8 (IL-8) and CCL-16 are produced. They attract heterophils and macrophages from the blood, respectively. In addition, effector cytokines regulating the anti-microbial response such as interferon-γ have been detected by RT-PCR. Thus macrophages and other components of the innate immune system are present and functional at hatch when the bird first encounters microbial organisms in its environment.
<figure><img src="image_2.png" /></figure>

Figure 1: Immunohistological staining of macrophages in the caecum of layer chickens at different ages. Macrophages are found in the lamina propria but not in the epithelium.

In addition to the cellular components of the innate immune system, soluble components are found early after hatch. These include several acute-phase molecules of the pentraxin family and anti-microbial peptides of the defensin family (Cuperus and others 2013), which have been demonstrated by RT-PCR analysis. However, their functional role in the avian intestine has not been studied due to the lack of appropriate animal models deficient on one or several of these factors. From work in mice it has become clear that anti-microbial peptides are produced by epithelial cells of the crypts called paneth-cells and are secreted into the mucus layer. Bacteria invading the mucus barrier get in contact with these factors and are efficiently lysed. Most authors agree that paneth-cells (Nile and others 2004) are absent in chickens and even though defensin specific mRNA is found in gut tissue samples it is largely unclear where they are produced and which mechanisms elicit their synthesis and secretion.

## Development of the gut associated adaptive immune system of chickens

While the innate immune system seems to be functional at hatch the components of the adaptive immune system are absent at that time point. Developmental studies have shown that B-lymphocytes, the producers of antibodies, start to emigrate from the bursa of Fabricius around hatch. Similarly, emigration of T-lymphocytes from the thymus starts shortly before hatch but major waves of cell migration are only observed days after hatch (Ratcliffe 2006). Importantly, both populations of lymphocytes are rare in the gut tissue during the first two weeks after hatch (Figure 2). Subsequently, more and more lymphocytes colonize the mucosal tissues and formation of lymphoid aggregates is found. Lymphocytes can be demonstrated in the lamina propria and in the epithelium as intra-epithelial lymphocytes. The latter population is made up of T-cells specialized in the control of virally infected cells. They are called cytotoxic T-lymphocytes (CTL) and are characterized by the expression of the cell surface protein CD8. T-helper cells (expressing the CD4 molecule) are more restricted to the lamina propria and are found in close proximity to lymphoid aggregates. B-lymphocytes start to colonize the gut at nearly the same time. They form organized lymphoid structures called Payer's patches and caecal tonsils.

Studies performed more than 50 years ago with birds raised under germ free conditions have shown that bacterial colonization has a significant influence on the maturation of the gut associated immune system (Thorbecke and others 1957) This observation has been confirmed recently in germ free mouse models and in our own studies with germ free chickens. To investigate the role of the microbiota, we hatched groups of birds which were maintained sterile or received one (*E.coli* Nissle) or a mixture of four strains of bacteria (*E.coli*, Lactobacillus, Enterococcus, Clostridium). These birds were compared with chickens housed under SPF conditions.

Even in the complete absence of microbiota the innate immune system (as far as investigated) developed normally. No difference was observed with regards to colonization by macrophages and micro-array studies showed undisturbed expression patterns for several genes of the innate immune system. In striking contrast, the development of the adaptive immune system was strongly impaired. B-cells were absent in the lamina propria of four weeks old birds despite normal B-cell development in the bursa of Fabricius. B-cell regions of the caecal tonsils were hugely underdeveloped and did not contain germinal centers (Figure 3), which are essential for the production of IgA and IgY antibodies. Consequently, IgA production was absent in germ free birds in the gut and in the serum (Figure 4). A similar picture was observed in the T-cell system with the absence of both CD4+ and CD8+ T-cells in germ free animals. Colonization with *E.coli* alone did not revert the histological picture but lead to the production of IgA in serum. These antibodies were, to a large extend, *E.coli* specific. Birds colonized with four bacterial strains showed significant maturation of the adaptive immune system in the gut. This was most pronounced in the caecal tonsils were germinal centers formation and IgA production was observed.
<figure><img src="image_3.png" /><figcaption>Figure 2: Immunohistological staining of B-cells, CD8+ and CD4+ T-cells in the caecum of layer chickens at different ages. Small numbers of lymphocytes are found during the first two weeks of age but colonization progresses rapidly thereafter. At three weeks formation of lymphoid aggregates is observed.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Figure 3: Immunohistological staining of B-cells in the caecal tonsils of layer chickens raised under germ free, gnotobiotic or SPF conditions. The absence of a microbiota (germ free) lead to a highly underdeveloped structure of the caecal tonsil. This phenotype was only partially reverted in birds mono-colonized (E.coli). Colonization with four strains further supported maturation and induced the formation of few and small germinal centers in comparison with the SPF controls.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4: Immunoglobulin A levels in the serum of germ free, gnotobiotic and SPF (conventional) birds (n=5). Note the complete absence of IgA in birds without a microbiom.</figcaption></figure>

The described observations were further supported by our gene expression analysis. Comparison of micro-array data from germ free and SPF birds showed higher expression of a large number of genes associated with immune function and developmental processes in SPF chickens. Most strikingly, genes known to be critical in B-cell maturation were found to be far less abundant in germ free birds reflecting the phenotype observed by immune-histology. AID, an enzyme essential for immunoglobulin class switching from IgM to IgA and IgY was weakly expressed in germ free birds but significantly higher expressed in mono-reconstituted chickens. A further increase was detectable in tetra-reconstituted animals which showed expression levels equivalent to SPF birds.

## Conclusion

The development of the gut immune system is controlled by both genetic and environmental factors. The innate immune system develops early in ontogeny and is present at hatch and thereby able to protect birds during the critical phase of sudden encounter with microbes after hatch. Its subsequent development is not strongly influenced by the microbiota but it becomes strongly activated in response to pathogen invasion. In contrast, development of the adaptive immune system is significantly influenced by bacterial colonization of the gut. Absence of a microbiom leads to severe developmental defects with a lack of B- and T-lymphocytes in the gut mucosa and the absence of antibody formation. Our studies strongly indicate that full maturation of the gut immune system requires a complex flora. However, the precise composition of an optimal flora is still unknown. Under natural conditions hatchlings get in immediate contact with the maternal flora while birds hatched under commercial poultry production conditions are hatched essentially sterile. It is still unclear how these conditions influence the development of the mucosal immune system, the capability to control pathogenic microorganisms, and animal health and welfare. Interestingly, mouse studies have shown that nutrients and fermentation products also influence the functional status of the mucosal immune system either directly or through mediators secreted by the epithelial cells. The role of the epithelium, the mucus barrier, and macro- and micro-nutrients on the avian immune system has not been investigated to date but should be considered in future studies.

## References

* BELKAID Y., HAND TIMOTHY W. (2014). Role of the Microbiota in Immunity and Inflammation. Cell **157**, 121-141.

* CUPERUS T., COORENS M., VAN DIJK A., HAAGSMAN H.P. (2013). Avian host defense peptides. Dev Comp Immunol **41**, 352-69.

* KAMADA N., SEO S.U., CHEN G.Y., NUNEZ G. (2013). Role of the gut microbiota in immunity and inflammatory disease. Nat Rev Immunol **13**, 321-35.

* NILE C.J., TOWNES C.L., MICHAILIDIS G., HIRST B.H., HALL J. (2004). Identification of chicken lysozyme g2 and its expression in the intestine. Cell Mol Life Sci **61**, 2760-6.

* RATCLIFFE M.J. (2006). Antibodies, immunoglobulin genes and the bursa of Fabricius in chicken B cell development. Dev Comp Immunol **30**, 101-18.

* SCHAT K.A., KASPERS B., KAISER P. (2014). *Avian Immunology*. (Elsevier).

* THORBECKE G.J., GORDON H.A., WOSTMAN B., WAGNER M., REYNIERS J.A. (1957). Lymphoid Tissue and Serum Gamma Globulin in Young Germfree Chickens. The Journal of Infectious Diseases **101**, 237-251.
# RELEVANCE OF GLYCINE IN LOW PROTEIN BROILER FEEDS

Wolfgang Siegert and Markus Rodehutscord

Institute of Animal Science, University of Hohenheim, 70599, Stuttgart, Germany; inst450@uni-hohenheim.de

## Summary

Lowering the crude protein (CP) content of broiler diets is an effective tool for decreasing N emission related to meat production and for decreasing costs by more efficient use protein in feedstuff. Maintaining an adequate concentration of essential amino acids (AA) in diets was previously shown to be a successful tool for reducing the CP concentration to a certain extent without negative effects on growth of broilers.

Considering nonessential AA as a sum of nonspecific nonessential AA in diets with a CP concentration below 20% has not consistently achieved growth performance of currently common CP concentrations of 21 to 22% of broilers at the age of 1 to 21 days post hatch. Consideration of the requirement for specific nonessential AA is necessary. Increasing the concentration of glycine in diets enables a CP reduction below 20% without compromising growth and feed efficiency. Feather development, skin strength and fat digestibility are also affected by glycine deficiency. It is generally accepted that on a molar basis serine is equally effective in meeting the functions of glycine. Therefore, glycine and serine should be assessed together by evaluating the response to glycine equivalents (Glyequi) as the sum of glycine and the molar equivalent of serine. The extent of responses to dietary Glyequi is inconsistent in literature. Consideration of factors influencing the response to Glyequi is necessary. The dietary concentration of cysteine has an influence on the response to Glyequi because the conversion of cysteine from methionine requires serine. Glyequi sparing effects have been shown for threonine and choline which can be metabolized to glycine endogenously.

Because the concentration of Glyequi in vegetable protein sources varies only little, altering the Glyequi concentration independent from the CP concentration is hardly feasible. Usage of some animal byproducts, or free glycine or L-serine would overcome this problem but those ingredients currently are not approved in the European Union.

## Introduction

The increasing demand for meat and other animal products and concomitant limitation of land for cropping results in a shortage of protein-rich feedstuff to be expected. Consequences of increased crop prices have been shown to especially affect affordability of food in developing countries (FAZENI and STEINMÜLLER, 2011).

The excretion of nitrogenous compounds can have negative effects on the environment because the excreted N can be dispersed into water, soil and air. Nitrogen contained in manure can be applied as fertilizer, but in too high amounts it risks N leakage into the groundwater (VERSTEGEN and JONGBLOED, 2003). Ammonia emissions have been associated with a number of harmful effects on the environment, which include soil acidification, eutrophication, formation of fine particulates, and secondary emissions of nitrous oxide (MARTÍNEZ-LAGOS et al., 2013). In addition, high ammonia levels in the animal house can affect human and animal health as well as the acceptance of livestock farming by the public due to unpleasant odors (ANEJA et al., 2009). Ambient temperature and manure characteristics like pH and moisture have an influence on ammonia emissions, but total excretion of N by livestock is most determining (LIU et al., 2007; NAMROUD et al., 2008).

Excretion of N in parts is inevitable because of characteristics of feed, such as digestibility of nitrogenous compounds, or due to metabolic processes leading to formation of substances which are subject to urinary excretion (BERG et al., 2007; RODEHUTSCORD, 2008). However, reduction of N excretion by using highly digestible feed ingredients and adjusting the supply of nitrogenous compounds to the requirement of the animal is accomplishable (BAKER, 2009) and often done.

Experiments, however, showed that low protein diets may have undesirable effects on performance of farm animals and carcass quality although the requirement of essential AA was met. Various potential reasons have been suggested to explain the undesirable effects of low protein diets (AFTAB et al., 2006). Glycine plays a special role in feeding low protein dies in poultry and the role of glycine has been better understood recently.

This contribution in the first part summarizes relevant approaches being discussed to overcome negative consequences of lowering CP concentrations in broiler diets. The physiological background and current state of research concerning the importance of glycine in low CP broiler nutrition is presented in the second part.
# Approaches of lowering crude protein concentrations in broiler diets

## Optimal ratio of essential amino acids

It is often discussed that the optimal ratio of essential AA might be different between standard and low CP diets and therefore represent one possible reason for diminished growth when low CP diets are fed to broilers. Low CP diets supplemented with free amino acids to raise the level of all essential AA failed to achieve growth performance as with standard CP diets (e.g. DESCHEPPER and DEGROOTE, 1995; JIANG et al., 2005; BREGENDAHL et al., 2002). In other studies combinations of some essential AA were varied with the result of improving growth performance partially but without fully overcoming the impaired growth induced by a low CP diet (e.g. HUSSEIN et al., 2001; NAMROUD et al., 2008; 2010; SI et al., 2004a; b). Interactive effects of some essential AA with nutrients reduced along with CP reduction such as nonessential AA may also have led to differences in growth. Such interactive effects have been mentioned e.g. for glycine and arginine by AKINDE (2014), and for glycine and threonine by CORZO et al. (2005).

## Utilization of supplemented free amino acids compared to peptide-bound amino acids

Different utilization of supplemented free AA compared to peptide-bound AA in the metabolism of animals has often been suspected (e.g. NAMROUD et al., 2008). Differences are conceivable because peptides and free AA are absorbed via different transport mechanisms. An imbalance between AA in the systemic circulation as a consequence of faster passage of free AA through the intestinal wall might occur and lead to an increased amount of certain AA catabolized in the enterocytes (WU, 2009). Studies investigating different proportions of peptides and free AA without basically varying dietary AA concentrations in feed of farm animals in general are rare and not available for poultry. Recent investigations from our institute found no differences in N efficiency when AA from soy protein isolate were substituted with free AA (SIEGERT et al., 2015a). It appears likely that potential differences are less pronounced in poultry than in other farm animals that are not fed with continuous access to feed because the crop portions the feed delivered to the subsequent digestive tract. This may reduce concentration peaks of certain AA in the systemic circulation.

## Consideration of nonspecific nonessential amino acids

In literature, the effect of nonspecific nonessential AA was evaluated by varying either the ratio of the sum of the concentrations of essential AA to the sum of the concentrations of nonessential AA or by altering the sum of the concentrations of nonessential AA. These ways of proceeding could not reproducibly prevent undesirable effects of low CP diets. To give examples: When added to low CP diets, mixtures of free aspartic acid and glutamic acid (BREGENDAHL et al., 2002; LECLERCQ et al., 1994) and a mixture of free aspartic acid, glutamic acid and alanine (NIESS et al., 2003) had no effect on growth performance. However, mixtures of free glutamic acid and glycine (DESCHEPPER and DEGROOTE, 1995; NAMROUD et al., 2008; 2010) and tyrosine and serine (THORNTON et al., 2006) increased performance, but not to the level of diets with standard CP concentrations.

Consideration of nonspecific nonessential AA probably is not sufficient because an unlimited interconversion of nonessential AA is necessary. Results of the aforementioned studies suggest that adequate supply of specific nonessential AA is important for prevention of decline in growth performance of broilers fed diets with low CP concentrations.

## Specific nonessential amino acids

Studies aiming to increase nonessential AA nitrogen by adding free glutamic acid failed to prevent growth depression caused by feeding low CP diets (amongst others HUSSEIN et al., 2001; KERR and KIDD, 1999). CORZO et al. (2005) and DEAN et al. (2006) found that diets with 18 and 16.2% CP, respectively, supplemented with glycine to the level of 22% CP control diet caused no difference in growth and feed efficiency compared to the control diet. In both studies free aspartic acid, glutamic acid, alanine and proline failed to overcome negative effects of the low CP diet. PARR and SUMMERS (1991) also reported no difference in growth between a diet with 20% CP supplemented with glycine and a diet with 23% CP and additionally disproved similar effects of free glutamic acid, alanine and aspartic acid. Other studies showed a growth promoting effect of free glycine added to low CP diets (amongst others CORZO et al., 2004; JIANG et al., 2005; SCHUTTE et al., 1997).

Since a few decades the gain to feed ratio (G:F) in broiler production continuously increased and this caused specific nonessential AA becoming increasingly relevant. This can in part be explained by the increasing probability that not enough metabolic precursors for the respective AA are available or because endogenous metabolic processes are too slow (AFTAB et al., 2006; BERRES et al., 2010). The potential of glycine to increase growth has been known for decades (ALMQUIST and MECCHI, 1940). Since publication of the study of DEAN et al. (2006), it is broadly accepted that
a deficiency of dietary glycine is one factor limiting reduction of CP concentration in broiler diets and that glycine is the first-limiting nonessential AA (OSPINA-ROJAS et al., 2012). WAGUESPACK et al. (2009) described glycine as the fourth-limiting of all proteinogenic AA after methionine, lysine, and threonine in a diet based on corn and soybean meal for broilers from 1 to 18 days post-hatch. OSPINA-ROJAS et al. (2014) described valine and glycine as equally limiting after methionine, lysine, and threonine in a corn-soybean meal-based diet for broilers from 1 to 21 days post-hatch.

## Relationship between glycine and serine

Glycine can be metabolized from serine by splitting the hydroxymethyl group of serine. This reaction can be reversed by adding CH₃ from tetrahydrofolic acid (VELIŠEK and CEJPEK, 2006). For poultry, it is generally assumed that the inter-conversion of glycine and serine is not limited in metabolism (AKRABAWI and KRATZER, 1968; SUGAHARA and KANDATSU, 1976) and therefore usually they are assessed together.

As currently common practice, most authors including NRC (1994) take the analogue effect of dietary glycine and serine as the sum of both AA (Gly+Ser) into account, neglecting the fact that serine only has the same effect as glycine on an equimolar basis. DEAN et al. (2006) proposed to describe the physiological value of a diet by calculating the glycine equivalent (Glyequi) as the sum of the concentration of glycine and the molar equivalent of Ser:

$$ \text{Glyequi (g/kg)} = \text{glycine (g/kg)} + [0.7143 \times \text{serine (g/kg)}] $$

where 0.7143 is the ratio of the molar weight between glycine and serine.

The Glyequi appears more appropriate than the currently common Gly+Ser unit; the advantage of rendering the physiological value of diets more precisely should justify the additional calculation effort.

## Physiological functions of glycine and serine

As any other proteinogenic AA, glycine and serine are incorporated in proteins. Whole body accretion of glycine and serine in broilers from d 8 to d 21 was determined between 7.8 and 11.4 g glycine accretion and between 4.2 and 5.5 g serine/16 g N accretion(FATUFE et al., 2004; FATUFE and RODEHUTSCORD, 2005). The lack of a side chain of glycine causes some physical characteristics like size, imparting charge, and hydrophobicity. These features allow for a possible accommodation in the hydrophobic interior of proteins which causes flexibility in the folding of proteins with a propensity to form helices and causes versatility in the structure of receptor sites as well as flexibility for active sites of enzymes (HALL, 1998).

### Proteins incorporating glycine and serine

**Collagen and elastin:** The proteins richest in glycine are collagen and elastin, where glycine is incorporated at every third position in the primary structure. In broiler slaughter processing, low skin strength due low collagen content in consequence of low dietary supply with glycine can have economic implications (CHRISTENSEN et al., 1994).

**Keratin:** Keratin is rich in both glycine and serine. In avian species, keratin is mainly present in feathers and claws. Feather development of birds fed with glycine deficient diets is impaired (ROBEL, 1977).

**Mucin:** Mucin proteins are rich in serine because serine provides attachment sites for the oligosaccharide chains which have a high proportion in mucins. The physiological functions of mucin are described as lubrication of the gut epithelium, protection of the epithelium against acidic conditions and proteases and selective diffusion barrier for nutrients. Further microbiota-associated functions are fixation of commensal bacteria, protection of the epithelium from pathogens, and substrate for bacterial fermentation. OSPINA-ROJAS et al. (2013) found that intestinal mucin secretion of broilers linearly increased with the proportion of glycine and serine in diets.

### Processes using metabolization products of glycine or serine

**Uric acid:** In uricotelic species like birds, ammonia is detoxified and excreted as uric acid being the main excretion product of N metabolism. The formation of each molecule of uric acid requires one molecule of glycine to build the purine ring. In addition, protein synthesis and cell proliferation depends on DNA synthesis, which requires glycine to form purines (WANG et al., 2013).

**Creatine:** Glycine is an integral part of creatine along with arginine. Creatine can either be directly supplied by feed derived from animal products or produced by endogenous synthesis. In a first step arginine reacts with glycine to form guanidino acetic acid. In a second step, guanidino acetic acid is methylated to form creatinine.
**Cysteine synthesis:** Most species cannot synthesize cysteine de novo but can metabolize cysteine from methionine. Serine is required when cystathionine is formed from homocysteine. Cystathionine further reacts to cysteine and ammonia (VELÍŠEK and CEJPEK, 2006).

**Bile salts:** Primary bile salts are synthesized from cholesterol in the liver and then conjugated with either glycine or taurine. In different animal species, 75 to 85% of the produced bile salts were found to be glycine conjugates (HAFKENSCHEID and HECTORS, 1975). Glycine deficiency was found to affect fat digestibility and therefore the AME<sub>N</sub> concentration in feed (OSPINA-ROJAS et al., 2013).

## Response to dietary glycine and serine

Since the importance of glycine and serine in poultry nutrition has been recognized, the publication rate of studies enlarging knowledge about effects of glycine and serine has increased. Several dose-response studies investigating the effect of dietary glycine and serine were published. A compilation of some studies shows that the response to dietary Gly<sub>equi</sub> was inconsistent (Figure 1). Therefore, factors influencing the response to Gly<sub>equi</sub> in reduced CP diets should be better understood. Such factors are addressed in the following section.

<figure><img src="image_6.png" /><figcaption>**Figure 1.** Dietary Gly<sub>equi</sub> needed to achieve 95% of the maximum gain:feed response (based on the 10 studies used by SIEGERT et al., 2015c)</figcaption></figure>

## Effect of cysteine

POWELL et al. (2011) found that the impact of glycine and serine on G:F is explained by the conversion of methionine to cysteine, for which serine is required. They found an improved G:F after addition of Gly to a diet adequate in total sulfur AA (TSAA) but deficient in cysteine. Further inclusion of methionine showed no improvement in growth performance, but the addition of cysteine above the requirement reduced the positive effects of glycine supplementation. Low CP concentrations are often associated with the inclusion of pure ingredients, such as DL-methionine. Because cysteine is usually not added, the ratio between methionine and TSAA (Met/TSAA ratio) in diets is increased upon supplementing DL-methionine disregarding a specific requirement of cysteine.

The dietary concentrations of both methionine and cysteine have a substantial impact on the requirement for dietary Gly<sub>equi</sub> (Table 1). Fulfilling the requirement for both methionine and cysteine in birds reduces the necessity of the conversion of methionine to cysteine. Each molecule of methionine not converted to cysteine reduces the requirement for Gly<sub>equi</sub>.

<table><caption>**Table 1.** Dietary Gly<sub>equi</sub> concentrations at 95% of maximum G:F in a meta-analysis compiled from 10 peer-reviewed studies investigating growth response of about 1 to 21 days old broilers (derived from SIEGERT et al., 2015c)</caption><thead><tr><th></th><th></th><th>Gly<sub>equi</sub> (g/kg)</th></tr></thead><tbody><tr><td rowspan="2">Met/TSAA ratio</td><td>0.5</td><td>19.9</td></tr><tr><td>0.8</td><td>13.8</td></tr><tr><td rowspan="2">Cys concentration</td><td>2 g/kg</td><td>14.8</td></tr><tr><td>5 g/kg</td><td>21.1</td></tr></tbody></table>

## Effect of endogenous precursors of glycine

Several substances can be metabolized to glycine or serine. Glycine can be metabolized from threonine, which can either be metabolized directly to glycine via the enzyme threonine aldolase with acetaldehyde as a byproduct or via threonine dehydrogenase with 2-amino-3-ketobutyrate as an intermediate step, which further reacts to glycine, acetyl-
CoA, and aminoacetone. Another precursor is choline which, with betaine as an intermediate step, is metabolized to glycine if homocysteine is available. Other endogenous precursors of glycine are glyoxylate in combination with alanine, and trimethyllysine where glycine is produced as a byproduct of carnitine synthesis. However, glyoxylate has no relevance in broiler feeding, and the potential quantity of glycine metabolized from trimethyllysine is low (MELÉNDEZ-HEVIA et al., 2009).

**Threonine:** Different levels of G:F and average daily gain (ADG) can be achieved with distinct combinations of Gly<sub>equi</sub> and Thr concentrations (Figure 2). An increase in Thr concentration reduces the Gly<sub>equi</sub> concentration required to achieve certain response levels. One molecule of threonine can be converted to one molecule of glycine. Given the molar weights of both molecules, the replacement value due to endogenous conversion of 1 mass unit of threonine cannot exceed 0.63 mass units of glycine. Much higher replacement can be derived from the graphs in Figure 2.

<figure><img src="image_7.png" /><figcaption>**Figure 2.** Dietary Gly<sub>equi</sub> necessary to achieve 95% of maximum G:F and ADG of broilers from day 7 to 21 post hatching depending on dietary threonine (SIEGERT et al., 2015b)</figcaption></figure>

A replacement value of dietary threonine to dietary glycine exceeding the possibility to be explained by endogenous conversion was also found in other studies (e.g. OSPINA-ROJAS et al., 2013). The high replacement value originates most likely due to an excess supply of other AA. If threonine limited growth performance, then the excess essential AA had to be catabolized. Increasing the threonine concentration probably reduced the amount of catabolized AA (other than threonine), thereby reducing the need for Gly<sub>equi</sub> to be used for uric acid formation.

**Choline:** Choline can considerably affect the Gly<sub>equi</sub> concentration required to achieve a certain level of response in G:F and ADG. The replacement effect of dietary choline for Gly<sub>equi</sub> is lower than the replacement effect of threonine (SIEGERT et al., 2015b). To our knowledge, interactive effects between glycine and choline were not reported in other literature.

## Concentrations of Gly<sub>equi</sub> in feedstuffs

The concentration of Gly<sub>equi</sub> varies considerably between and within types of feedstuffs (Table 2). However, the variation in the proportion of Gly<sub>equi</sub> in CP is low and ranges between 7.3 and 8.3 g/100g CP in most cereals, cereal byproducts, brewery byproducts, oil seeds and pulses. Proportion of Gly<sub>equi</sub> in CP is highest in meat meal and meat and bone meal.

Because the variation of the proportion of Gly<sub>equi</sub> in CP is low, using only vegetable ingredients in feed formulation causes the dietary concentration of Gly<sub>equi</sub> to depend mainly on the CP concentration of the diet. It is hardly possible to increase or decrease the proportion of Gly<sub>equi</sub> in CP of plant-based diets. Some animal byproducts are useful to elevate the Gly<sub>equi</sub> concentration in diets but feeding of animal-derived proteins to poultry currently is generally prohibited in the European Union (EUROPEAN COMMISSION, 2001). Feed additives potentially suitable for elevating the Gly<sub>equi</sub> concentration in feedstuff are free glycine and L-serine, which are currently also not approved in the European Union (EUROPEAN COMMISSION, 2014). Consequently, current legislation in the European Union is not in support of reducing the CP concentration in poultry diets.
<table><caption>**Table 2.** Concentrations of Gly<sub>equi</sub> and proportion of Gly<sub>equi</sub> in the protein of selected feedstuffs relevant for animal feeding (extracted from EVONIK, 2010)</caption><thead><tr><th>Feedstuffs</th><th></th><th>Gly<sub>equi</sub><br>(g/kg DM)</th><th>Gly<sub>equi</sub><br>(g/100g CP)</th></tr></thead><tbody><tr><td rowspan="3">Cereals</td><td>Winter wheat</td><td>8.3</td><td>7.4</td></tr><tr><td>Corn</td><td>6.6</td><td>7.3</td></tr><tr><td>Triticale</td><td>9.5</td><td>7.3</td></tr><tr><td rowspan="3">Oil seeds</td><td>Rapeseed meal</td><td>31.7</td><td>7.9</td></tr><tr><td>Soybean meal</td><td>41.6</td><td>7.8</td></tr><tr><td>Sunflower expeller</td><td>44.4</td><td>8.3</td></tr><tr><td rowspan="2">Pulses</td><td>Field peas</td><td>18.5</td><td>7.6</td></tr><tr><td>Lupins</td><td>30.4</td><td>7.4</td></tr><tr><td rowspan="2">Non-animal byproducts</td><td>Wheat bran</td><td>11.4</td><td>8.2</td></tr><tr><td>Brewer's dried yeast</td><td>35.3</td><td>7.8</td></tr><tr><td rowspan="3">Animal byproducts</td><td>Fish meal</td><td>64.3</td><td>6.4</td></tr><tr><td>Meat meal</td><td>11.4</td><td>14.8</td></tr><tr><td>Meat and bone meal</td><td>14.9</td><td>17.7</td></tr></tbody></table>

## Perspectives of crude protein reduction

Current research mainly aims to find ways to reduce the CP concentration without compromising growth and feed efficiency achieved with nowadays common CP concentrations (amongst others CORZO et al., 2005; DEAN et al., 2006), which is at about 21 to 22% in diets.

DEAN et al. (2006) summarized that in literature growth and feed efficiency was reduced in broilers fed with diets containing less than 19 to 20% CP even when the requirement for essential AA was met. If the concentrations of glycine and serine were adequate, growth and feed efficiency of broilers fed diets containing 17 to 18% CP were at the level of diets containing more than 20% CP (CORZO et al., 2004; DEAN et al., 2006; SIEGERT et al., 2015c).

The Met/TSAA ratio, the concentrations of endogenous precursors, and other nutrient concentrations influencing the response to Gly<sub>equi</sub> probably were suboptimal in the studies mentioned above. Consequently, further reduction of the CP concentration in diets without negative effects on performance should be possible through optimization of both the dietary Gly<sub>equi</sub> concentration and factors influencing the response to Gly<sub>equi</sub>. According to a personal estimate, this would enable to reduce the CP concentration in diets to about 16% in feed of broilers from 1 to 21 days of age. This estimate needs to be verified by targeted investigations.

Glycine and serine are the first nonessential AA of which requirement values were quantified. The possibility to further reduce the CP concentration in diets without adverse effects on performance can be expected when the role of other nonessential AA is better understood and their requirement values are assessable.

## Conclusion

Because protein sources for animal feeding will become more expensive, further CP reduction and therefore optimization of nutrient composition will be necessary in future. Glycine and serine are very likely to become growth-limiting when diets with a CP concentration below 20% are fed. Consideration of Gly<sub>equi</sub> enables to reduce the CP concentration remarkably without adverse effects on performance compared to the current standard. The requirement for Gly<sub>equi</sub> depends on other dietary characteristics. The role of cysteine and threonine has already been investigated but other influencing factors are still to be addressed.
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# REVISITING AMINO ACID NUTRITION

P. Belloir¹,², M. Lessire¹, C. Berri¹, W. Lambert², E. Corrent², S. Tesseraud¹

¹INRA, UR83 Recherches Avicoles, 37380 Nouzilly, France; ²Ajinomoto-Eurolysine SAS, 153 rue de Courcelles, 75817 Paris Cedex 1, France; Sophie.Tesseraud@tours.inra.fr

## Summary

Amino acids are recognized as anabolic factors that induce protein gain by stimulating protein synthesis while inhibiting proteolysis, and they are important substrates for the synthesis of various nitrogenous compounds. There is also increasing evidence that amino acids act as key regulators of metabolism through the control of major metabolic pathways in various tissues and organs. Elucidating the mechanisms involved in such regulation can provide a basis to optimize amino acid requirements and to control protein mass, body composition and meat quality while ensuring greater efficiency of production systems. However, with the aim of improving understanding of the response of chickens to nutrition, new approaches and technology (e.g. comparative physiology, genomics and modeling) are also available to decipher mechanisms which could not be adequately analyzed a few years ago. This review presents the recent advances in this area generating original scientific knowledge and optimizing dietary amino acid provision (quantitative and qualitative) over time in relation to production targets. Emphasis is also placed on the limits of the information available for broiler chickens.

**Keywords:** amino acid; nutrition; low crude protein diet; combined approaches; broiler

## Introduction

One major issue in poultry production is the development of feeding strategies that are more efficient and more eco-friendly by reducing waste. Among these strategies, one aim is reduction of the crude protein content in a diet fortified with adequate amounts of currently available free amino acids (e.g. L-Lys, DL-Met, L-Thr, L-Val and L-Trp) in order to achieve increased protein utilization efficiency while maintaining animal growth performance and reducing nitrogen excretion.

Amino acids have a major effect on the control of protein metabolism. They are components of tissue proteins and provision at insufficient levels leads to reduced protein synthesis. Provision of the different essential amino acids is therefore a prerequisite for maintaining optimal rates of protein synthesis, an unquestionably major concept in protein nutrition. However, optimizing amino acid nutrition requires consideration of the different functions of amino acids, which are recognized to have several significant influences. Amino acids are precursors of important molecules. For example, cysteine is required for the synthesis of glutathione and taurine, which are essential compounds for host defense against oxidative stress (METAYER et al., 2008). Methionine is a source of the methyl groups needed for all biological methylation reactions, including methylation of DNA and histones involved in epigenetic regulation (TESSERAUD et al., 2009; WATERLAND, 2006; WATERLAND and MICHELS, 2007). Moreover, studies conducted during the last decade indicate that amino acids act as regulators of various metabolic pathways (see TESSERAUD et al., 2011; WU, 2009 & 2013 for reviews). The mechanisms through which amino acids control tissue metabolism in poultry are not discussed here. Following an overview of the role of amino acids and setting out the interest of revisiting amino acid nutrition in poultry production, we then describe the strategies developed to adjust amino acid provision in low crude protein diets and discuss the recent advances in amino acid nutrition, with the aim of optimizing broiler growth performance and product quality.

### Overview of the role and importance of amino acids in controlling growth, body composition and product quality

Amino acids exert their actions in various tissues and organs, including splanchnic tissues that control the distribution of nutrients between tissues since they are the first tissues exposed to newly absorbed nutrients due to their anatomical position (first-pass splanchnic extraction; see NIETO and LOBLEY (1999) for a review). The nutritional regulation of protein metabolism by amino acids has also been intensively studied in skeletal muscles since such nutrients are recognized as anabolic factors, which induce protein gain by stimulating protein synthesis while inhibiting proteolysis. The aim of the various studies performed to date has thus been to improve and control muscle growth and meat quality in animal production and to preserve muscle growth in critical situations (e.g. stress, infection). Indeed, due to the differences between the amino acid composition of the acute-phase and muscle proteins, a considerable amount of muscle protein must be degraded to provide the amino acids used in the acute-phase response (REEDS et al., 1994). Under-
standing the mechanisms by which amino acids regulate protein metabolism is therefore essential to improve control of the use of nutrients and to optimize dietary amino acid provision.

Dietary amino acids are major determinants of the carcass components of broilers, as abdominal fat content and breast meat yield are influenced by their levels (MORAN and BILGILI, 1990; LECLERCQ, 1995). Lysine is known to have specific effects on carcass composition and, for instance, lysine deficiency greatly reduces breast muscle proportion (TESSERAUD et al., 1996a, b). It should be noted that neither threonine nor valine exhibits as pronounced an effect on body composition as that of lysine, as demonstrated in experiments in which these three amino acids were studied together in similar conditions (LECLERCQ, 1998). Interestingly, increasing the level of lysine in the diet of broilers (beyond the requirement for growth) reduced drip loss of breast muscle during storage by increasing its ultimate pH (pHu; BERRI et al., 2008). This result was consistent with the general hypothesis that breast muscle hypertrophy in broilers is accompanied by a decrease in glycogen storage (BERRI et al., 2007). Breast meat traits and pHu have also been reported to be affected by distributing diets varying in amino acid content over a very short period (3 days) before slaughter (GUARDIA et al., 2014). Provision of various amino acids (and the resulting amino acid balance or imbalance) may indeed affect the proportion of nutrients used for glycogen storage and hence the pHu. It should be noted that changes in pHu caused by variations in dietary amino acid profiles were fairly moderate in the latter study. However, they significantly affected breast meat lightness that itself is strongly correlated with the water holding capacity of meat and processing yield (QIAO et al., 2002; PETRACCI et al., 2004; ZHUANG and SAVAGE, 2010).

Amino acid provision has been shown to have an impact on the chemical composition of tissues, with a potential effect on meat quality. In particular, Met and/or Cys deficiency affects lipid and protein content, and also amino acid composition of tissue proteins in chickens (CONDE-AGUILERA et al., 2013), as previously reported in piglets (CONDE-AGUILERA et al., 2010 & 2014). Sulfur amino acid provision has also been reported to modify meat susceptibility to oxidation. For example, according to the Met source provided in the diet (DL-Met or hydroxy analog of methionine, DL-HMTBA), oxidative stress and lipid peroxidation will be greater or less significant (MARTIN-VENEGAS et al., 2006; SWENNEN et al., 2011; WILLEMSEN et al., 2011). Fully or partially replacing DL-Met by its hydroxyl-analog HMTBA has indeed been shown to reduce breast meat susceptibility to oxidation (leg and breast meat) and also to increase its pHu, with positive consequences on storage and processing ability (MERCIER et al., 2009).

## Why revisit amino acid nutrition?

In chickens, as in other farm animals, amino acids have to be provided in the diet in balanced proportions to optimize performance and feed utilization (D'MELLO, 2003). This necessitates precise evaluation of amino acid requirements, whereas they are influenced by many environmental and dietary factors as well as by the animal itself, including age, sex and strain. Moreover, it has been established that dietary amino acid requirements vary according to the performance criteria chosen for optimization. For example, higher dietary Lys requirement is generally found for the feed conversion ratio (FCR) and breast meat yield compared to body weight gain (HAN and BAKER, 1994; LECLERCQ, 1998; MACK et al., 1999; DOZIER et al., 2009 & 2010). These findings together involve reinforcing research into the responses to amino acid provision in terms of performance, body composition and quality of products. Furthermore, modern broiler genotypes, which have been greatly improved in terms of weight gain and feed efficiency, may require higher dietary amino acid content to optimize performance and breast meat yield compared to broilers of past years (SI et al., 2001; DOZIER et al., 2010). Indeed, there is evidence that the response to dietary amino acid provision is modified by genetic selection. For instance, genetically lean chickens are more sensitive than fat chickens to diets containing less crude protein or fewer essential amino acids (LECLERCQ et al., 1993 & 1994; MORAN, 1994; LECLERCQ, 1995; JLALI et al., 2012). There is better use of dietary amino acids by lean genotypes. Similarly, an experimental line selected for high breast development and low abdominal fat percentage exhibited a more efficient utilization of Lys for body weight and *Pectoralis major* muscle protein deposition compared to the control line maintained without selection (TESSERAUD et al., 1999). The different levels of responsiveness to changes in dietary Lys intake can be explained by differences in protein metabolism (TESSERAUD et al., 2001).

Revisiting amino acid nutrition stems from the need to reduce the crude protein content of diets, which is a major issue for sustainable poultry production from economic, environmental and social points of view. For example, formulating diets with the constraint of too high crude protein levels results in massive incorporation of soybean meal. This raw material is controversial as a feedstuff because of the price volatility, its environmental impact (deforestation, transport) and the GMO (genetically modified organisms) issue. Decreasing dietary crude protein levels can reduce dependency on soybean but also leads to the incorporation of larger amounts of free amino acids to maintain dietary amino acid
balance. It also reduces nitrogen excretion resulting from excessive amounts of undigested nitrogen or excess provision of amino acids (i.e. beyond requirements). This reduction of waste also allows improvement of litter quality (e.g. lower water consumption and excretion, lower litter humidity), and contributes to a better health status of livestock (MEDA et al., 2011; VAN CAUWENBERGHE and BURNHAM, 2001). Nevertheless, formulation of low crude protein diets requires good understanding of the nutritional characteristics of raw materials and controlling the provision of digestible essential amino acids (Lys, Met (+ Cys), Thr, Val, Ile, Leu, Trp, Arg, Phe (+ Tyr), His), the need for the most limiting essential amino acids being satisfied by incorporating free amino acids. To balance the diet, practical formulation is generally based on an 'ideal profile' of essential amino acids, for instance maximizing growth performance. The requirements for essential amino acids in ideal protein are usually expressed as a proportion of Lys (HAN and BAKER, 1994; NRC, 1994; EMMERT and BAKER, 1997). Although many profiles have been provided and updated (MACK et al., 1999; ROSTAGNO et al., 2011; WU, 2014), decreasing dietary crude protein content is still difficult to achieve without negatively affecting broiler performance (DEAN et al., 2006; WAGUESPACK et al., 2009; BELLOIR et al., unpublished data). What makes these findings surprising is that decreasing dietary crude protein content does not result in any particular problems in pigs (see the next paragraph).

## Limits of available data

Reducing dietary crude protein content by using free amino acids in pigs maintains performance as long as the amino acid requirements are met. For example, it has been known for a decade that supplementation with Lys, Met, Thr and Trp in free form allows a reduction in dietary crude protein level of approximately 4% units (FIGUEROA et al., 2003; KERR et al., 2003). A recent study even showed that it is possible to formulate very low protein diets that maintain piglet growth with the use of free Val, Leu, Ile, His and Phe, on top of the usual free amino acids Lys, Met, Thr and Trp (GLOAGUEN et al., 2014). Moreover, soybean meal can be totally replaced by cereals and free amino acids.

To determine the extent to which low crude protein diets can be used in poultry, it is important to synthesize and analyze reliable scientific information. The information available is indeed sometimes fragmented (for example, the majority of studies have been performed in young chickens between 1 and 21 days of age), not always consistent and corresponding to very different experimental designs and conditions, in particular with regard to the extent of protein level decrease and the modalities applied to achieve it. A bibliography database has recently been established for that purpose for broilers (BELLOIR et al., 2015a). The first database included 56 trials originating from 29 publications focusing on a decrease in dietary protein published after 1990. The information computed in the database included the experimental design, broiler performance levels and the composition of the diets which were recalculated on a common basis (SAUVANT et al., 2004). The database therefore included the levels of total amino acids, and also levels of digestible amino acids to avoid any experimental bias due to differences in amino acid digestibility between raw materials. Briefly, formulating low crude protein diets was systematically associated with the incorporation of L-Lys, DL-Met and L-Thr. L-Val, L-Ile and L-Arg were also often used in addition to these amino acids. The preliminary analysis showed impaired growth and feed efficiency in many trials. This loss of performance was thought to be due to the incorporation of large amounts of free amino acids in replacement of the protein fraction from the raw materials or to inadequate amino acid provision. The first hypothesis was recently tested in an experimental trial where the impact of the form of provision (protein vs free amino acids) on broiler performance was evaluated (BELLOIR et al., unpublished data). In the trial, 30% of the dietary crude protein fraction was gradually replaced by either a highly digestible protein (casein) or a mixture of free amino acids whose amino acid profile was exactly the same as for casein. When chickens were fed more than 3.8% dietary free amino acids as replacement for casein protein, the feed conversion ratio and breast meat yield were impaired. Chickens were able to adapt their digestive physiology to increasing provision of free amino acids, at least for levels lower than 3.8% (e.g. increased surface of villi and increased expression of amino acid transporters). Beyond this level, the digestive absorption capacity may be affected, limiting the use of nutrients by the animal, which could partly explain poorer performance. However, in practice, the use of amino acids in free form should not be a problem, since the quantities reached for formulating low crude protein diets (15% CP) may not exceed 1.7% free amino acids (BELLOIR et al., unpublished data).

From the bibliography database presented above, fifteen trials were then selected according to two 'selection criteria': 1) the level of digestible Lys that had to be sub-limiting and constant when dietary crude protein was decreased, and 2) the dietary digestible essential amino acid profile in that had to be approximately consistent with the 'ideal' protein (MACK et al., 1999; ROSTAGNO et al., 2011). After selection, trial results were compiled and analyzed graphically to assess the effects of protein decrease on levels of performance. On average, low protein diets corresponded to a
reduction in dietary crude protein content of approximately 2% units (compared to the positive control recalculated for each trial). In these conditions, low protein-related variability of performance levels was observed above a digestible Lys/crude protein ratio of 6.5. The majority of trials tested only two levels (i.e. positive control and experiment low protein diets) which did not allow modeling of the chicken performance responses to decreases in dietary crude protein. However, this meta-analysis approach already indicates specific features of trials in which production performance is maintained and emphasizes certain assumptions concerning the impact of low protein diets in broiler chickens. In particular, it appears necessary to pay attention to the Thr:Lys ratio used and to take into account the next limiting essential amino acids (Val, Ile and Arg). It should be noted that these assumptions are supported by recent studies (BELLOIR et al., 2015b & c). Moreover, this meta-analysis indicates that a further reduction in dietary crude protein level (below 17%) may necessitate including an adequate level of certain non-essential amino acids.

## Recent advances in amino acid nutrition

The above assumptions highlight the inadequate provision of certain amino acids when using low crude protein diets. Another issue in amino acid nutrition originates from formulating balanced diets with the increasing number of production criteria (e.g. including meat quality in addition to growth performance), and improving animal health (importance of ‘functional’ amino acids). For example, Thr is sometimes deficient in low crude protein diets (see above), despite its crucial importance for maintaining intestinal integrity and immune function (WU, 2009). A recent meta-analysis reported that the digestible Thr:Lys requirement of broilers was estimated to be at least 67% and was thought to be even higher in critical environmental conditions (LAMBERT et al., 2015a). With regard to the optimization of meat quality, it has been shown that dietary Lys and amino acid levels affected the quality traits of breast meat, including color, drip loss and pHu (BELLOIR et al., unpublished data). For example, deficient amino acid provision (i.e. essential amino acids other than Lys) combined with a reduced Lys content favored the production of meat with high pHu (> 6.0), while more acid meat (< 5.85) was produced with higher levels of amino acids (essential amino acids other than Lys) combined with a low Lys content. In this trial, maximum changes in pHu induced by dietary treatments reached 0.29 pH unit. This change in pHu was quite high compared to previously released studies: maximum extent of 0.20 pH unit with dietary Lys variations (BERRI et al., 2008), 0.14 pH unit with short term variations in dietary amino acids profiles (GUARDIA et al., 2014) and 0.13 pH unit between different genotypes selected for growth criteria (BERRI et al., 2005).

Recent advances in amino acid nutrition have benefited from combined approaches including meta-analyses, nutritional and metabolic studies. The major challenges for the future are integrating the data obtained at various levels from the cell to the animal and the complete understanding of amino acid metabolism for rational use in nutrition. An example of such difficulties was reported in a review of the role of sulfur amino acids in controlling nutrient metabolism and cell functions, with the emphasis placed on the implications for nutrition (TESSERAUD et al., 2009). A large number of studies have indeed been devoted to exploring the key roles of sulfur amino acids, but further experiments are still necessary to obtain direct evidence regarding some of their effects on nutrient metabolism, cell functions and physiological responses in animals on physiological (e.g. early nutrition) or physiopathological conditions (disease, environmental stress). In particular, the effects of sulfur amino acids should be analyzed under circumstances affecting oxidative status and gene expression. Recommendations for Met and Cys intake have to be revisited in the light of their roles and the intricacies of sulfur amino acid metabolism. Further experiments are also necessary to improve the integration of the various roles of sulfur amino acids at the whole-body level. These findings are particularly interesting in birds due to the high Met and Cys requirements for feather synthesis. The content of Cys has to be taken into account when adjusting the provision of Met, while also taking into account their potential interactions with Gly-Ser, as summarized in Fig. 1. Glycine (or Gly+Ser because of equimolar and reversible conversion between them) must also be present in the diet in sufficient quantities, since Gly is not synthesized quickly enough to meet the metabolic needs (i.e. precursor for the synthesis of uric acid). There is evidence of a positive effect on chicken performance of Gly supplementation in low protein diets (DEAN et al., 2006). Nevertheless, there are conflicting reports in the literature and a recent meta-analysis indicates that it is still difficult to establish reliable Gly+Ser requirements for broilers due to the low number of dose responses available, and probably limiting factors or bias in these dose responses (LAMBERT et al., 2015b). In addition, the interaction between Gly and Thr (Fig. 1) has to be investigated, the quantitative importance of Gly synthesis from Thr being probably dependent on Thr dietary availability (WANG et al., 2013; LAMBERT et al., 2015c).
<figure><img src="image_8.png" /></figure>

**Figure 1. Metabolism of amino acids, interactions and particular features in avian species.** General outline of metabolic pathways involving amino acids with a focus on some of them of particular interest in birds (underlined in black): sulfur amino acids (Met and Cys) due to the high requirement for feather synthesis; Thr, sometimes supplied in inadequate amounts in low crude protein diets, especially in challenging environmental conditions; amino acids considered as 'nutritionally essential' in birds. For example, Arg cannot be synthesized via the urea cycle; Pro, synthesized from Arg, Glu or Gln in most mammals, cannot be synthesized at sufficient levels in birds; Gly, a precursor for the synthesis of uric acid (nitrogen excretion in uric acid form instead of urea) is not synthesized quickly enough to meet metabolic needs. It (alone or in combination with Ser because of conversion between these amino acids) must also be present in sufficient quantities in the diet.

**Conclusions**

Amino acid nutrition is an old story and the issue is always improving the control of nutrient utilization and optimizing dietary amino acid provision for animal production purposes. Reducing the crude protein content of diets for broilers appears to have major benefits for the sustainability of animal production, but is difficult to achieve in chickens despite the knowledge available on amino acids. This can be partly explained by the complexity of mechanisms involved in the control of metabolism and also interactions between amino acids whose importance and implications for nutrition need to be examined and even hierarchized. Authors often focus on particular points and the difficulty is to integrate all the data available to propose recommendations. A major challenge for future studies will be to improve the integration of data without oversimplification, while taking into account the findings/concepts which are generalizable or dependent on a particular condition such as the experimental design, physiological situations, including early life, etc. Such studies will certainly provide a rationale for nutritional advice in the future.

**Acknowledgements**

Some of the studies presented as examples in this review received financial support from INRA, the French Ministry of Agriculture and representatives of the animal feed industry (Adisseo, Ajinomoto Eurolysine s.a.s.).
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# THE NUTRITIONAL VALUE OF YELLOW LUPIN (LUPINUS LUTEUS) FOR BROILERS

**S. Kaczmarek, M. Hejdysz, and A. Rutkowski**

Poznan University of Life Sciences, Department of Animal Nutrition and Feed Management, Wołyńska 33, 60-637

Poznań, Poland; sebak1@up.poznan.pl

## Abstract

Yellow lupine seeds, 7 varieties were harvested in 2013. The experiment was conducted with 240, 16-day old Ross 308 male chickens. The reared birds were randomly located in cages and allotted 7 dietary treatments (10 replications in each, three birds per replication). For seven days, birds were fed experimental diets (30 % - yellow lupine seeds) and basal diet (70 % - maize-soybean). On day 20 and 21, excreta were individually collected twice per day and immediately frozen. On the 22nd day of the experiment, 30 chickens from each group were sacrificed and the ileum was removed. To allow digestibility to be determined, 3 g/kg TiO₂ was included as a marker. Apparent ileal digestibility (AID) was calculated using the difference method. Total NSP content in seeds ranged from 261 to 288, soluble NSP ranged from 24 to 95 mg/g (as-is basis). There were differences (P<0.05) in ileal digesta viscosity (4.97 to 8.61 mPas·s) and feed intake (115 – 121 g/d/bird) between yellow lupine cultivars. The obtained correlation coefficients (r) for raffinose content explained over 85% DM AID variability (r = -0.85, P<0.05) and 58% ether extract AID variability (r = -0.58, P<0.05). The relationship between soluble NSP content and the ether extract AID (r=0.26) was linear (P<0.05).

**Keywords:** yellow lupin, viscosity, ileal digestibility, non-starch polysaccharides,

## Introduction

It is well known that nutrient composition and anti-nutritional factors in yellow lupin, generally, depend on the cultivar and growing conditions. The published data on nutrient and amino acid utilization and apparent metabolisable energy (AME) of yellow lupins for broilers are limited and inconsistent (GDALA and BURACZEWSKA, 1996, ALLOUI et al., 1994). In our previous study (KACZMAREK et al., 2014), it was found that raffinose content in blue lupine seeds was affecting AMEN and nutrient utilization. ZALEWSKI et al. (2001), LAHUTA (2011) showed that lupin seeds carbohydrates composition is affected by environmental conditions and it could be different across batches. Whole lupin seeds still contain approximately 35% NSP, of with over 5% are water soluble limiting the application in poultry feeding (GDALA and BURACZEWSKA, 1996).

The aim of the study was to explain causes of variations in feed intake, nutrient digestibility of Polish cultivars of yellow lupin meal (YLM) for broiler chickens.

## Material and Methods

The basal diet was mixed in proportion 70:30 (w/w) with corresponding YLM. To allow digestibility to be determined, 3 g/kg titanium dioxide was included as a non-absorbable marker. All diets were offered in mash form ad libitum. The experiment was conducted on 240, 16-day old Ross 308 male chickens. The birds were randomly allocated to 8 dietary treatments (10 replications in each). Birds were kept in individual cages. In 7 treatments, diets containing a lupin meal (Perkoz, Lord, Parys, Baryt, Dukat, Mister, Taper cv.) and basal diet in proportion 70:30 were fed. Birds in one treatment were fed only the basal diet. Each bird had unlimited access to water and feed. For five days, birds were fed experimental diets for accommodation. On day 19 and 20, excreta were individually collected twice per day and immediately frozen for future analyses (n=10). On day 21 of the experiment, all chickens from each group were sacrificed and the ileum was removed. Digesta were flushed from the terminal ileum (15 cm, adjacent to the ileo-caecal junction) and pooled (3 birds/sample) to provide sufficient material for chemical analyses (n=10).

## Results

Total NSP content in seeds ranged from 261 to 288 and soluble NSP ranged from 24 to 95 mg/g (as-is basis). There were differences (P<0.05) in viscosity of ileal digesta (4.97 to 8.61 mPas·s) and feed intake (115 – 121 g/d/bird) between lupine cultivars. The obtained correlation coefficient (r) for raffinose content explained over 85% DM AID variability (r = -0.85, P<0.05) and 58% ether extract AID variability (r = -0.58, P<0.05). The relationship between soluble NSP content and the ether extract AID (r=0.26) was linear (P<0.05). There was no effect of the investigated traits (raffinose and soluble NSP content or ileal viscosity) on average feed intake. However, a tendency (P=0.09) was observed for decreased FI as raffinose content increased in the diets (r = -0.23). In our previous trial (KACZMAREK et al., 2014), we found that raffinose affected negatively AMEN of blue lupine seed meals. Additionally, COON et al. (1990) and LESKE et
al. (1993) demonstrated that stachyose and raffinose content affected negatively TME<sub>N</sub> of soy protein concentrate or SBM. Generally, it is suggested that legume oligosaccharides have hygroscopic properties and may affect transit of GIT digesta by elevating intestinal osmolarity (SMITS and ANNISON, 1996).

<table><caption>**Table 1.** Pearson's correlation coefficients between lupin seed traits ileal digesta and digestibility or feed intake of broiler chickens.</caption><thead><tr><th>Traits</th><th>Response</th><th>r</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="4">Raffinose content</td><td>EE AID</td><td>-0.58</td><td>&lt;0.05</td></tr><tr><td>DM AID</td><td>-0.85</td><td>&lt;0.05</td></tr><tr><td>CP</td><td>-0.46</td><td>&lt;0.05</td></tr><tr><td>FI</td><td>-0.23</td><td>0.09</td></tr><tr><td rowspan="4">Soluble NSP content</td><td>EE AID</td><td>-0.26</td><td>0.06</td></tr><tr><td>DM AID</td><td>-0.39</td><td>&lt;0.05</td></tr><tr><td>CP</td><td>-0.15</td><td>0.26</td></tr><tr><td>FI</td><td>0.06</td><td>0.64</td></tr><tr><td rowspan="4">Ileal viscosity</td><td>EE AID</td><td>-0.54</td><td>&lt;0.05</td></tr><tr><td>DM AID</td><td>-0.46</td><td>&lt;0.05</td></tr><tr><td>CP</td><td>-0.35</td><td>&lt;0.05</td></tr><tr><td>FI</td><td>-0.04</td><td>0.77</td></tr></tbody></table>

EE – ether extract, AID – apparent ileal digestibility, DM – dry matter, CP – crude protein, FI – feed intake.

## Conclusions

It can be concluded that the inherent variability of seeds may partially explain why birds responded differently across trials (including this experiment) to the inclusion of similar YLM doses. It seems that the nutritional value of yellow lupin seeds for broilers depends, to a considerable extent, on raffinose content and ileal viscosity (soluble NSP content).

## Literature

* **ALLOUI, O., SMULIKOWSKA, S., CHIBOWSKA, M. and PASTUSZEWSKA, B.** (1994) The nutritive value of lupin seeds [I.Luteus I.Angustifolius and I.Albus] for broiler chickens as affected by variety and enzyme supplementation *Journal of Animal and Feed Sciences* **3**: 215-227.

* **COON, C. N., LESKE, K. L., AKAVANICHAN, O. and CHENG, T. K.** (1990) Effect of oligosaccharide-free soybean meal on true metabolizable energy and fiber digestion in adult roosters. *Poult Sci* **69**: 787-793.

* **GDALA, J. and BURACZEWSKA, L.** (1996) Chemical composition and carbohydrate content of seeds from several lupin species. *Journal of Animal and Feed Sciences* **5**: 403-416.

* **KACZMAREK, S. A., KASPROWICZ-POTOCKA, M., HEJDYSZ, M., MIKULA, R. and RUTKOWSKI, A.** (2014) The nutritional value of narrow-leafed lupin (lupinus angustifolius) for broilers. *Journal of Animal and Feed Sciences* **23**: 160-166.

* **LAHUTA, L. G., R** (2011) Raffinose in seedlings of winter vetch (vicia villosa roth.) under osmotic stress and followed by recovery. *Acta Physiologiae Plantarum* **33**: 725-733.

* **LESKE, K. L., JEVNE, C. J. and COON, C. N.** (1993) Effect of oligosaccharide additions on nitrogen-corrected true metabolizable energy of soy protein concentrate. *Poult Sci* **72**: 664-668.

* **SMITS, C. H. M. and ANNISON, G.** (1996) Non-starch plant polysaccharides in broiler nutrition – towards a physiologically valid approach to their determination. *World's Poultry Science Journal* **52**: 203-221.

* **ZALEWSKI, K., LAHUTA, L. and HORBOWICZ, M.** (2001) The effect of soil drought on the composition of carbohydrates in yellow lupin seeds and triticale kernels. *Acta Physiologiae Plantarum* **23**: 73-78.
# EVALUATION OF A LYS TO ARG ANTAGONISM IN LOW CRUDE PROTEIN DIETS FOR BROILER CHICKENS

K. Schedle<fnref n="1" />, R. Leitgeb<fnref n="1" />, J. Bartelt<fnref n="2" />, E. Corrent³

## Abstract

A trial was conducted to evaluate the Lys and Arg interactive effect on production performance and slaughter characteristics. A total of 414 eight-day-old chicks were divided into 6 treatment groups (6 replicates). Diets 1 and 2 were high in dietary crude protein (CP) and differed in Lys (21% CP and 1.05% or 0.9% true digestibility of an amino acid (TD) Lys in grower; 19% CP and 0.95% or 0.8% TD Lys in finisher). Diets 3 to 6 were low in CP (19.5% in grower; 17.5% in finisher), differed in TD Lys (1.05% or 0.90% in grower; 0.95% or 0.80% in finisher) and TD Arg:Lys ratio (85% or 105% in grower and finisher). Differences between treatments were tested by ANOVA for diets 1 to 6. In an additional two-way ANOVA differences between diets 3 to 6 were evaluated.

Reducing CP did not affect zootechnical or slaughter performance (except abdominal fat) if the diet was high in both TD Lys and Arg:Lys ratio. High Lys diets showed a higher production performance, carcass weight, carcass yield, and breast meat yield at both high and low CP diets compared to low Lys diets (p<0.01). High Arg:Lys ratio improved F:G and resulted in higher carcass weight, breast meat weight and carcass yield (p<0.05). An interaction between Arg and Lys was only observed for carcass weight and breast meat yield (p<0.05). In conclusion, reducing CP in broiler diets does not impact performance when the animals are fed adequate amount of Lys and Arg. No Lys x Arg antagonism at low CP diets was observed except for tissues rich in meat.

**Keywords:** broiler, Lys to Arg antagonism, performance

## Introduction

The knowledge of the requirement of essential amino acids helps to optimise the different nutritional inputs at various stages of broiler production. In low dietary crude protein (CP) diets for broiler chickens, a deficient Arg supply cannot be excluded. Furthermore, the performance reducing effect of high Lys diets in the case of a non-adequate Arg supply is described in literature (Jones 1964, Brake 2001). Hence, the present study should evaluate a potential Lys x Arg antagonism in modern diets for broiler chickens.

## Material and Methods

Grounded feed and water were provided *ad libitum*. One day old broiler chicks (ROSS 308) were divided evenly into 36 pens and were fed a commercial starter feed (13.5 MJ AME<sub>N</sub>, 18.0% CP) in the first week (preperiod). On life day 8, chicks of each replicate (6 pens) were weighed combined, to determine average body weight (BW). Subsequently, chicks which had less than 80% of the average BW were removed from the trial.

The study started with 414 eight-day old broiler chicks and was divided in a grower (0 to 21 days) and a finisher period (21 to 36 days). Four trial groups (TG) differing in Lys and Arg content (Table 1, TG 3-6) were created. Additionally, two diets (TG 1 and 2) higher in CP were involved in the study, to assess a dietary CP reducing effect on performance. All other essential amino acids were formulated according to the ideal protein (Lys:Met+Cys:Thr:Trp:ile = 100:75:67:21:67). Grower and finisher diets (13.2 MJ AME<sub>N</sub>) were based on corn, wheat, soy bean meal with hulls, DDGS, corn gluten meal, vegetable oil and grass green meal.

<table><caption>**Table 1:** Study design based on analysed (CP,AA content) and calculated (TD values) nutrient values</caption><thead><tr><th rowspan="3">Traits</th><th colspan="10">Trial groups (TG)</th></tr><tr><th colspan="6">Grower: from day 8 to 21</th><th colspan="5">Finisher: from day 21 to 36</th></tr><tr><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th></tr></thead><tbody><tr><td>CP, g/kg</td><td>209</td><td>205</td><td>197</td><td>190</td><td>190</td><td>192</td><td>194</td><td>190</td><td>180</td><td>182</td><td>175</td><td>177</td></tr><tr><td>TD Lys, g/kg</td><td>10.5</td><td>9.0</td><td>10.5</td><td>10.5</td><td>9.0</td><td>9.0</td><td>9.5</td><td>8.0</td><td>9.5</td><td>9.5</td><td>8.0</td><td>8.0</td></tr><tr><td>TD Arg, g/kg</td><td>11.3</td><td>9.4</td><td>8.9</td><td>11.0</td><td>7.6</td><td>8.5</td><td>10.0</td><td>8.4</td><td>8.1</td><td>10.0</td><td>6.8</td><td>8.4</td></tr><tr><td>TD Arg:Lys</td><td>107.6</td><td>104.4</td><td>84.8</td><td>104.8</td><td>84.4</td><td>105.9</td><td>105.3</td><td>105.0</td><td>85.3</td><td>105.3</td><td>85.0</td><td>105.0</td></tr></tbody></table>

<footnote n="1">¹Department for Agrobiotechnology, University of Natural Resources and Life Sciences, Vienna, 1190 Vienna, Austria;</footnote>

<footnote n="2">²Lohmann Animal Nutrition GmbH, Cuxhaven, Germany; ³Ajinomoto Eurolysine S.A.S., Paris, France;</footnote>

<footnote>karl.schedle@boku.ac.at</footnote>
The digestibility of free AA was assumed to be 100% (CHUNG and BAKER, 1992). True digestibility (TD) coefficients obtained from published tables (SAUVANT et al., 2004) were applied to the analysed amino acid levels in each ingredi-ent to formulate diets on a TD amino acid basis.

Daily feed intake (dFI), average daily gain (ADG) and feed:gain (F:G) were corrected for mortality. Means separation for each variable was performed by Tukey-Kramer-Test. The tables present the least square means (LS-means) of the dietary treatments derived from the analysis of variance as well as the pooled standard error of means (SEM). Signifi-cant differences among means (*P* < 0.05) are indicated by superscripts.

## Results

The results of zootechnical performance are presented in Table 2.

<table><caption>**Table 2:** Results of the growth performance</caption><thead><tr><th></th><th>high</th><th>high</th><th>low</th><th>low</th><th>low</th><th>low</th><th></th><th></th></tr></thead><tbody><tr><td>CP content</td><td>high</td><td>high</td><td>high</td><td>high</td><td>high</td><td>high</td><td>SEM</td><td>p-value</td></tr><tr><td>TD Lys content</td><td>high</td><td>low</td><td>high</td><td>high</td><td>low</td><td>low</td><td></td><td></td></tr><tr><td>Arg to Lys ratio</td><td>105%</td><td>105%</td><td>85%</td><td>105%</td><td>85%</td><td>105%</td><td></td><td></td></tr><tr><td>BW at day 8, g</td><td>179</td><td>176</td><td>178</td><td>178</td><td>177</td><td>172</td><td>1.81</td><td>0.923</td></tr><tr><td>BW at day 21, g</td><td>848<sup>a</sup></td><td>739<sup>b</sup></td><td>817<sup>a</sup></td><td>843<sup>a</sup></td><td>737<sup>b</sup></td><td>740<sup>b</sup></td><td>9.44</td><td>&lt;0.0001</td></tr><tr><td>BW at day 36, g</td><td>2173<sup>a</sup></td><td>1760<sup>c</sup></td><td>1992<sup>b</sup></td><td>2078<sup>ab</sup></td><td>1735<sup>c</sup></td><td>1731<sup>c</sup></td><td>31.94</td><td>&lt;0.0001</td></tr><tr><td colspan="9">Grower period</td></tr><tr><td>ADG, g</td><td>48<sup>a</sup></td><td>40<sup>b</sup></td><td>46<sup>a</sup></td><td>47<sup>a</sup></td><td>40<sup>b</sup></td><td>41<sup>b</sup></td><td>0.65</td><td>&lt;0.0001</td></tr><tr><td>dFI, g</td><td>72<sup>b</sup></td><td>67<sup>c</sup></td><td>73<sup>a</sup></td><td>72<sup>ab</sup></td><td>68<sup>c</sup></td><td>68<sup>c</sup></td><td>0.52</td><td>&lt;0.0001</td></tr><tr><td>F:G, kg/kg</td><td>1.50<sup>b</sup></td><td>1.68<sup>a</sup></td><td>1.60<sup>ab</sup></td><td>1.53<sup>b</sup></td><td>1.73<sup>a</sup></td><td>1.67<sup>a</sup></td><td>0.02</td><td>&lt;0.0001</td></tr><tr><td colspan="9">Finisher period</td></tr><tr><td>ADG, g</td><td>83<sup>a</sup></td><td>64<sup>c</sup></td><td>73<sup>b</sup></td><td>77<sup>ab</sup></td><td>63<sup>c</sup></td><td>62<sup>c</sup></td><td>1.44</td><td>&lt;0.0001</td></tr><tr><td>dFI, g</td><td>138<sup>a</sup></td><td>113<sup>c</sup></td><td>129<sup>ab</sup></td><td>132<sup>ab</sup></td><td>121<sup>b</sup></td><td>113<sup>c</sup></td><td>1.94</td><td>&lt;0.0001</td></tr><tr><td>F:G, kg/kg</td><td>1.67<sup>b</sup></td><td>1.76<sup>b</sup></td><td>1.78<sup>ab</sup></td><td>1.71<sup>b</sup></td><td>1.93<sup>a</sup></td><td>1.83<sup>ab</sup></td><td>0.02</td><td>&lt;0.0001</td></tr></tbody></table>

The study started with an average bird weight of 177 ± 1.81 g. After 14 trial days, significant differences between treat-ments were observed. In the grower period, birds applying Lys enhanced diets reached higher BW, ADG, dFI and an improved F:G (*P* < 0.05). No differences between treatments were observed regarding TD Arg:Lys ratio in the low CP diets. In the finisher period, similar effects were observed regarding Lys content. Birds receiving the low protein low Lys high Arg diet (TG 6) showed a significantly lower dFI compared to the low protein low Lys low Arg diet (TG 5) (*P* < 0.05), while in the low protein high Lys high Arg (TG 4) diet a numerically increased ADG was observed compared to the low protein high Lys low Arg (TG 3) diet (*P* > 0.05). In both periods, no significant effect of increased Arg was re-corded but the F:G was numerically improved by 3.5 to 4.4% in growers and by 3.9 to 5.2% in finishers when feeding 105% TD Arg:Lys compared to 85%.

The results of slaughter performance are listed in Table 3. Animals receiving the high protein high Lys diet (TG 1) and the low protein high Lys and high Arg diet (TG 4) recorded the highest carcass weights. In contrast to this, the low Lys diets showed lower carcass weights in both high and low CP (*P* < 0.05). The abdominal fat content was reduced by the high protein diets (*P* < 0.05). Dressing percentage was comparable to the results of the live weights. Furthermore, an interaction (*P* < 0.05) between Lys content and Arg ratio in low CP diets, resulting in heavier carcass weights for birds receiving the high Lys high Arg diet (TG 4) compared to high Lys low Arg diet (TG 3), was detected. Higher Lys con-tents resulted in a higher relative proportion of breast meat, and reminder of carcass as well as a lower proportion of legs compared to low Lys diets (*p*<0.05). Regarding the parameter breast meat proportion an interaction (*P* < 0.05) was observed, resulting in larger breast meat proportion for birds receiving the high Lys high Arg diet (TG4) compared to high Lys low Arg diet (TG3).
<table><caption>**Table 3:** Results of the slaughter performance and relative proportion of carcass parts compared to the carcass for grilling</caption><thead><tr><th></th><th>high</th><th>high</th><th>low</th><th>low</th><th>low</th><th>low</th><th></th><th></th></tr></thead><tbody><tr><td>CP content</td><td>high</td><td>high</td><td>high</td><td>high</td><td>high</td><td>high</td><td>SEM</td><td>p-value</td></tr><tr><td>TD Lys content</td><td>high</td><td>low</td><td>high</td><td>high</td><td>low</td><td>low</td><td></td><td></td></tr><tr><td>Arg to Lys ratio</td><td>105%</td><td>105%</td><td>85%</td><td>105%</td><td>85%</td><td>105%</td><td></td><td></td></tr><tr><td>Carcass for grilling, g</td><td>1546<sup>a</sup></td><td>1210<sup>c</sup></td><td>1396<sup>b</sup></td><td>1504<sup>a</sup></td><td>1171<sup>c</sup></td><td>1170<sup>c</sup></td><td>12.88</td><td>&lt;0.0001</td></tr><tr><td>Abdominal fat, g</td><td>34<sup>d</sup></td><td>35<sup>cd</sup></td><td>44<sup>a</sup></td><td>40<sup>abc</sup></td><td>40<sup>ab</sup></td><td>37<sup>bcd</sup></td><td>0.54</td><td>&lt;0.0001</td></tr><tr><td>Heart, g</td><td>9.9<sup>a</sup></td><td>8.2<sup>bc</sup></td><td>8.9<sup>b</sup></td><td>9.1<sup>b</sup></td><td>7.8<sup>c</sup></td><td>7.7<sup>c</sup></td><td>0.09</td><td>&lt;0.0001</td></tr><tr><td>Liver, g</td><td>44<sup>a</sup></td><td>33<sup>b</sup></td><td>42<sup>a</sup></td><td>42<sup>a</sup></td><td>35<sup>b</sup></td><td>32<sup>b</sup></td><td>0.43</td><td>&lt;0.0001</td></tr><tr><td>Gizzard, g</td><td>29<sup>a</sup></td><td>26<sup>bc</sup></td><td>27<sup>ab</sup></td><td>26<sup>bc</sup></td><td>25<sup>b</sup></td><td>25<sup>bc</sup></td><td>0.19</td><td>&lt;0.0001</td></tr><tr><td>Dressing, %</td><td>79.8<sup>a</sup></td><td>77.7<sup>c</sup></td><td>78.7<sup>b</sup></td><td>79.8<sup>a</sup></td><td>77.4<sup>c</sup></td><td>78.4<sup>b</sup></td><td>0.08</td><td>&lt;0.0001</td></tr><tr><td colspan="9">Relative proportion of carcass parts compared to the carcass for grilling</td></tr><tr><td>Breast meat, %</td><td>30.7<sup>a</sup></td><td>25.5<sup>d</sup></td><td>27.6<sup>bc</sup></td><td>29.4<sup>ab</sup></td><td>26.3<sup>cd</sup></td><td>25.7<sup>cd</sup></td><td>0.32</td><td>&lt;0.0001</td></tr><tr><td>Legs, %</td><td>27.9<sup>c</sup></td><td>30.5<sup>a</sup></td><td>29.3<sup>abc</sup></td><td>28.4<sup>bc</sup></td><td>29.9<sup>abc</sup></td><td>30.1<sup>ab</sup></td><td>0.23</td><td>0.001</td></tr><tr><td>Remainder of carcass, %</td><td>31.5<sup>b</sup></td><td>33.2<sup>a</sup></td><td>32.3<sup>ab</sup></td><td>31.4<sup>b</sup></td><td>33.1<sup>a</sup></td><td>33.0<sup>a</sup></td><td>0.15</td><td>&lt;0.0001</td></tr></tbody></table>

**Conclusion**

In general, the well known performance improving effect of Lys in low and high CP diets was confirmed with the present study. A higher TD Arg to Lys ratio improved F:G, carcass weights and dressing percentage. Furthermore, an interaction between Lys and Arg was recorded for the parameters carcass weight and breast meat percentage. However, no Lys x Arg antagonism was detected for growth performance of broiler chickens in this trial.

**References**

BRAKE, J., 2001: Optimum dietary arginine:lysine ratio for broiler chickens is altered during heat stress in association with changes in intestinal uptake and dietary sodium chloride. Br. Poult. Sci. 39, 639-647.

CHUNG, T.K., D.H. BAKER, 1992: Apparent and true amino acid digestibility of a crystalline amino acid mixture and of casein: comparison of values obtained with ileal-cannulated pigs and cecectomized cockerels. J. Anim. Sci. 70, 3781-3790.

JONES, J.D., 1964: Lysine – Arginine Antagonism in the Chick. J. Nutr. 84, 313-321.

SAUVANT, D., J.M. PEREZ, G. TRAN, (eds.) 2004: Tables of composition and nutritional value of feed materials. Wageningen Academic Publisher, ISBN 9076998418
# FIBER IN POULTRY NUTRITION: BONUS OR BURDEN?

S. de Vries

Ingredient Research Centre, Nutreco R&D, P.O. Box 220, 5830 AE Boxmeer, the Netherlands;
sonja.de.vries@nutreco.com

## Abbreviated title: Fiber in poultry nutrition

## Summary

The generic term fiber encompasses a very diverse group of polymers, with varying physicochemical properties. It is well known that dietary fiber can contribute significantly to the nutritive value of poultry diets both directly, as energy source, and indirectly, through its effects on digestive and metabolic processes. In order to more accurately predict the nutritive effect of fiber from raw materials, a better characterization of fiber fractions, their degradation in the chicken, and their physiological effects are required. Traditional analytical methods to analyze fiber, as crude fiber (CF) and neutral detergent fiber (NDF), recover only a variable part of the fiber fraction and are hence unfit to evaluate fiber fractions in raw materials and poultry diets. For scientific purposes, the enzymatic-chemical (Englyst or Uppsala) methods are more appropriate, whereas for routine analyses the AOAC (2009.01/2011.25) method for total, insoluble, and soluble dietary fiber can be used. In the chicken, solubilization is a prerequisite for fermentation, but even if solubilized during the digestive processes, a substantial part of non-starch polysaccharides (NSP) may remain undegraded. Coefficients of apparent total tract digestibility of NSP in chicken range between 0 and 0.4 and generally reflect differences in solubility of the fiber fraction. Besides, physical entanglement of polysaccharides in the cell wall matrix also time available for fermentation and the absence of appropriate enzyme activities as determined by the microbial colonization in the gastrointestinal tract are possible limiting factors for NSP degradation. Although fiber in poultry nutrition is often associated with reduced energy availability due to its minor role in energy supply and interference with digestive processes, low to moderate amounts of fiber (up to 50 g/kg) might be beneficial for gastrointestinal development, function, and health, thereby enhancing nutrient digestibility and growth performance. A better understanding on the relation between specific fiber fractions and factors as GIT development, digesta retention time, and microbial colonization will help to develop nutritional strategies using specific fiber fractions to steer on GIT health and function to enhance performance, especially under suboptimal environmental conditions.

**Key words:** analytical methods, fermentation, fibre, gastrointestinal health, non-starch polysaccharides,

## Introduction

Although abundantly present in many feed ingredients used for poultry diets, dietary fiber (DF) has received little attention poultry nutrition for many years. It is well known that dietary fiber can contribute significantly to the nutritive value of diets both directly, as energy source (JAMROZ et al., 2002, JØRGENSEN et al., 1996), and indirectly, through its effects on digestive and metabolic processes (CHOCT et al., 1996, JØRGENSEN et al., 1996, SMITS et al., 2000, SMITS et al., 1998, SMITS et al., 1997, ANNISON, 1993, MONTAGNE et al., 2003). The generic term fiber, however, encompasses a very diverse group of polymers, with varying physicochemical properties, which hampers prediction of the nutritive value of fiber fractions. Not only the quantity of fiber, but maybe even more importantly, the type of fiber will determine the digestive utilization of the diet and, hence, affect its energetic value, either positively or negatively. In order to more accurately predict the nutritive effect of fiber from raw materials, a better characterization of fiber fractions, their degradation in the chicken, and their physiological effects are required.

## How to track and trace the dietary fiber fraction?

### CHALLENGES IN THE ANALYSIS OF DIETARY FIBER

Albeit extensive debates on the appropriate definition and adequate analytical methods, DF is generally defined as the non-digestible fraction of plant cell walls in food and feed ingredients<fnref n="1" /> and typically includes oligosaccharides, pectic polysaccharides, hemicellulose, cellulose, lignin, gums, and some minor associated plant cell wall substances (DE VRIES, 2004). Although the chemical constitution of these cell wall fractions varies widely, they can be considered alike

<footnote n="1">¹ The currently most widely accepted definition of DF includes Dietary fiber means carbohydrate polymers with three or more monomeric units, which are not hydrolyzed by the endogenous enzymes in the small intestine of humans (JONES, 2014, CODEX ALIMENTARIUS COMMISSION, 2013).</footnote>
from a nutritional viewpoint, as they are not enzymatically digested and exert similar physiological properties. Resistant starch – which is by definition resistant to enzymatic digestion, but mostly not originating from the cell wall (ASP and BJÖRCK, 1992) – is often included based on its similar behavior in the gastrointestinal tract.

Several methods to analyze DF – or its specific components as non-digestible oligosaccharides non-starch polysaccharides (NSP), RS, or lignin – are available (DE VRIES, 2004). Historically in animal nutrition, the gravimetrically based crude fiber (CF), and later neutral (NDF) and acid detergent fiber (ADF) methods, have been used. Although these methods, based on chemical extraction with alkali and acid solutions, are robust to analytical variation and might correlate well with degradability of specific fiber fractions in the animal (MERTENS, 2003), they recover only part of the fiber fraction (Figure 1). Depending on the material, a variable, but considerable part of the fiber fraction – such as cereal β-glucans and some pectic polysaccharides – can be solubilized and hence excluded from the detergent and crude fiber methods, whereas some other pectic polysaccharides that precipitate in strong acid will be included in the ADF fraction (MERTENS, 2003). In addition, also the physical characteristics of the sample, such as particle size, are of importance, because particles can be lost during the filtration step of these gravimetric methods. For CF, for example, this means that depending on the fiber structure of the material, 80-85 % of the hemicellulose, 0 to 60 % of the cellulose, and 10 to 95 % of the lignin are not recovered in this fraction (MERTENS, 2003). It follows that comparison between diets or feed ingredients with distinct fiber structures and physicochemical properties based on these analytical methods is specious. Moreover, this hampers not only comparisons between fiber sources, but also evaluation of fiber degradation in the animal, as physicochemical properties of the ingested feed will be modified by digestive processes along the gastrointestinal tract (GIT).

<figure><img src="image_9.png" /><figcaption>**Figure 1.** Indicative composition of total dietary fiber* (solid black line), fiber fractions analyzed by gravimetric methods† (dashed grey line), or calculated as residual fraction (calculated NSP)‡ (dashed-dotted grey line).*Analyzed by ‘rational’ methods as sum of non-starch polysaccharides (enzymatic-chemical methods) and lignin. Oligosaccharides can be separately quantified by liquid chromatography (MCCLEARY et al., 2011). †Empiric gravimetric methods, such as crude fiber or neutral detergent fiber (VAN SOEST et al., 1991). Recovery of various fractions depends on method and physical characteristics of sample (e.g. particle size). ‡Residual organic material after subtraction of ash, crude protein, crude fat, starch, and ethanol (40%)-soluble sugars from DM (CVB, 2011), including NSP, lignin, residual components not analyzed by the proximate system, and accumulated analytical error. Calculated NSP (dashed-dotted grey line) minus crude fiber (dashed grey line) approximates nitrogen-free extract minus digestible starch and sugars. Adapted from ZIELINSKI ET AL. (2013).</figcaption></figure>

Alternatively, in feed formulation the fiber fraction is often calculated as the residual fraction remaining after subtraction of several components analyzed by the proximate or Weende analysis system (AOAC, 2009). In this system, the nitrogen-free extract (NFE) is defined as the organic material remaining after subtraction of ash, crude protein (CP), crude fat, and crude fiber from the dry matter (DM), representing the carbohydrate fraction that is potentially degraded in the animal without distinguishing between easily digestible starch and sugars and the (partly) fermentable fiber fraction.
Due to the lack of specificity of the CF-method as described above, NFE also may contain considerable part of the lignin and poorly degradable NSP. The calculated NSP fractions as reported in the Dutch CVB tables (CVB, 2011, Figure 1), are obtained by subtraction of ash, CP, crude fat, starch, and ethanol-soluble sugars, and hence include NSP, lignin, and some low-molecular-weight carbohydrates that precipitate in 40%-ethanol. In both NFE and NSP fractions, components not analyzed by the proximate system – such as some nitrogenous components and vitamins – and analytical errors associated with the analyses accumulate in these residual fractions. Hence, the exact composition of these fractions depends on the raw material and its physicochemical properties.

For scientific purposes, a more appropriate alternative, is the use of enzymatic-chemical methods, as the Englyst or the Uppsala procedures (BACH KNUDSEN, 2001, ZIELINSKI et al., 2013). In these, so-called, “rational”<fnref n="2" /> methods, NSP are measured as the sum of constituent monosaccharides released by acid hydrolysis of samples after removal of starch and small saccharides. Not only do these methods provide detailed information on the chemical composition of the fiber fraction, they also have the advantage that they are not sensitive to physical factors such as solubility and particle size of samples, which makes them more appropriate to evaluate fiber degradability in the animal. In addition, they are species-independent as opposed to the empirical DF methods that are typically optimized for their application in human. These sophisticated methods, are, however, not suitable for routine analysis as they are expensive, both in terms of labor and equipment, and are less robust to analytical errors due to the multiple subsequent analytical steps, as well as the small amount of sample material. Furthermore, the small amount of sample material hampers representative sampling in inhomogeneous feed materials. With the recent advances and consensus on optimization of analytical methods for DF in the human nutrition field (ZIELINSKI et al., 2013), the enzymatic-gravimetric methods for total, insoluble, and soluble DF recognized by AOAC (2009.01/2011.25) have evolved in robust methods that may be used for routine analyses of fiber fractions for day-to-day feed formulation practices. These methods could be further optimized in terms of filtration procedures, to avoid confounding effects of particle size. Additionally, near-infrared reflectance spectroscopy (NIRS) might be used to predict contents of DF and specific DF fractions (KAYS and BARTON, 2002, KAYS et al., 1996)).

## MEASURING THE FATE OF DIETARY FIBER ALONG THE GASTROINTESTINAL TRACT

As discussed above, the nature of the gravimetric fiber methods makes them unfit to monitor degradation of fiber along the GIT, as changes in physicochemical properties of ingested fiber fractions during digestion confound the results. Hence, the use of “rational” methods is preferred for digestibility studies. When evaluating fiber degradation along the GIT, not only methods to correctly analyze the fiber constituents, but also obtaining a representative sample of the GIT contents can be challenging. In chickens, soluble and solid digesta fractions are separated and retrograde digesta flows occur. Often, fiber-rich diets have pronounced effects on physical characteristics of the feed matrix, thereby affecting a.o. digesta flow and transit time (ROBERTSON, 1988). These processes may complicate digestion studies, particularly, but not exclusively, when fiber degradation is the matter of interest (DE VRIES et al., 2014a). Unrealistic high ileal and cecal digestibility values for NSP, sometimes exceeding total tract digestibility (PETTERSSON and ÅMAN, 1989, JAMROZ et al., 2002, BRENES et al., 2003, DE VRIES et al., 2014a), clearly indicate that the marker method is unsuitable to measure fiber degradation along the GIT in chicken. In future research, a dual phase marker system combined with mathematical modelling of digesta flow pathways, quantitative digesta collection, and stable isotope methods can be helpful to keep track of fiber fractions along the GIT. When apparent total tract degradation of NSP is measured, separation of digesta fractions does not have to be an issue provided that the collection time is sufficiently long and a representative sample of the excreta is collected. Ceca empty at irregular intervals; approximately 2 to 4 times a day, majorly in the morning, just after onset of light, and in the afternoon (HERRICK and EDGAR, 1947, GASAWAY and WHITE, 1975). Hence, short collection periods at single time points may promote selective recovery of excreta, resulting in considerable over- or underrepresentation of cecal contents and erroneous digestibility estimates for fermentable matter.

<footnote n="2">² Rational refers to methods in which an identifiable chemical or analyte is quantitated, as opposed to empirical, non-analyte specific, methods (ZIELINSKI et al., 2013).</footnote>
# Fate of fiber in the gastrointestinal tract

## FIBER DEGRADATION IN THE CHICKEN

Degradation of NSP in the animal depends to a large degree on the original cell wall matrix in which the polysaccharides are embedded (DE VRIES et al., 2012). In chickens, ceca access is restricted to fluids and small particles (<0.2mm) and consequently solid digesta won't reach the major site of fiber degradation (JÓZEFIAK et al., 2004). It follows that NSP should be solubilized in order to be fermented. However, a substantial fraction of canola meal NSP that were solubilized during transit through the GIT, remained undegraded in broilers (PUSTJENS et al., 2014) indicating that also the time available for fermentation or the lack of appropriate enzyme activities are possible limiting factors in NSP degradation.

Coefficients of apparent total tract digestibility (CATTD) of NSP in chicken, as reported in literature range between 0 and 0.4 and generally reflect differences in solubility of the NSP fractions of the various feed ingredients (Table 1). Degradation of NSP is particularly low (0-0.1) in diets containing poorly solubilizable NSP from ingredients as maize or some sources of canola meal (MENG and SLOMINSKI, 2005, SLOMINSKI et al., 1994b, DE VRIES et al., 2014b), whereas higher CATTD of NSP (0.2-0.4) are found for diets that contain more soluble NSP, originating mainly from cereal grains as barley, oats, wheat, and rye. Degradability of NSP from the wheat-soybean meal (SBM) diets, with and without inclusion of several fiber-rich byproducts, in the studies of BOROS et al. (2004) and MENG et al. (2005) are lower than expected based on NSP solubility. In these studies excreta were collected for a period of only 3 h, and selective recovery of ceca contents due the irregular emptying of the ceca may have resulted in erroneous CATTD estimates. Also the CATTD of NSP from diets containing pea fiber in the study of JØRGENSEN et al. (1994) are lower than expected based on the NSP solubility. Apparently, the soluble NSP of this product, which is produced by water extraction of peas and has a high water-binding capacity, were poorly degraded and likely pea fiber even impeded degradation of barley NSP.

In common feed practices, NSP-degrading enzymes are usually added to broiler and laying hen diets. The use of such enzymes can facilitate degradation of specific NSP structures, when either appropriate enzyme activities are lacking or when time is limiting their full operation. Depending on e.g. the NSP source and the type of enzymes used, CATTD of NSP can be improved over 0.2 units in broilers (PUSTJENS et al., 2014, PETTERSSON and ÅMAN, 1989, MENG and SLOMINSKI, 2005, MENG et al., 2006, BOROS et al., 2004, JIA and SLOMINSKI, 2010, MARSMAN et al., 1997), whereas the effect in adult birds can be even greater (MENG et al., 2006, LÁZARO et al., 2003, SLOMINSKI and CAMPBELL, 1990). Effects of common feed processing technologies are typically smaller, and generally mainly affect easily solubilizable NSP such as cereal β-glucans (DE VRIES et al., 2012).

## FIBER AS NUTRIENT: DOES IT MAKE A DIFFERENCE?

Non-starch polysaccharides can be partly fermented by the microbiota residing in the gastrointestinal tract of the animal. The end products of NSP fermentation, short chain fatty acids (SCFA), can be absorbed and used as energy source (DIERICK et al., 1989, JØRGENSEN et al., 1997, JUST et al., 1983). Given that less than 40% of NSP are degraded, the lower efficiency of energy utilization obtained from microbial fermentation compared with enzymatic digestion, and the potential higher energy requirements for fiber-rich ingredients (DIERICK et al., 1989), it follows that, generally, the contribution of NSP to the energy supply in the bird is expected to be minor (JØRGENSEN et al., 1996). In addition, DF can interfere with digestive processes, thereby often reducing digestion and absorption of other nutrients from the diet (FENGLER and MARQUARDT, 1988, CHOCT and ANNISON, 1992b, CHOCT and ANNISON, 1992a, MONTAGNE et al., 2003, SMITS et al., 2000, SMITS et al., 1997, SMITS et al., 1998). Hence, DF is often considered as diluent or even anti-nutritional factor, in poultry nutrition. However, as reviewed by MATEOS et al. (2012), DF play an important role in GIT development and functioning and when fed at low to moderate levels (up to 50 g/kg) may enhance GIT health, nutrient digestibility, and bird performance. Especially insoluble, recalcitrant, fiber fractions that resist fermentation in the gut may be important from this perspective due to their effects on gizzard function and digesta retention time in the GIT (HETLAND et al., 2004). A better understanding on the relation between specific fiber fractions and factors as GIT development, digesta retention time, and microbial colonization will help to develop nutritional strategies using specific fiber fractions to steer on GIT health and function to enhance performance, especially under suboptimal environmental conditions.
<table><caption>**Table 1.** Coefficient of apparent total tract digestibility (CATTD) of non-starch polysaccharides (NSP) in chickens<fnref n="1" />.</caption><thead><tr><th>Diet characteristics<br>Main NSP sources<sup>2</sup></th><th>Adaptation<sup>3</sup></th><th>NSP<br>content<sup>4</sup></th><th>NSP<br>Solubility<sup>5</sup></th><th>CATTD</th><th>Bird type</th><th>Reference<sup>6</sup></th></tr></thead><tbody><tr><td>Barley (100)</td><td>0 to 63 d<sup>7</sup></td><td>45</td><td>0.29</td><td>0.31</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Barley (73), oat bran (27)</td><td>0 to 63 d<sup>7</sup></td><td>91</td><td>0.43</td><td>0.35</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Barley (65), oat bran (35)</td><td>0 to 63 d<sup>7</sup></td><td>127</td><td>0.39</td><td>0.25</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Barley (47), SBM (31), wheat (22)</td><td>41 d</td><td>127</td><td>0.31</td><td>0.39</td><td>Male broilers (6 wk)</td><td>2</td></tr><tr><td>Wheat bran (51), barley (49)</td><td>0 to 63 d<sup>7</sup></td><td>132</td><td>0.27</td><td>0.19</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Wheat bran (61), barley (39)</td><td>0 to 63 d<sup>7</sup></td><td>203</td><td>0.18</td><td>0.16</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Wheat (70), SBM (30)</td><td>37 d</td><td>97<sup>8</sup></td><td>0.24<sup>9</sup></td><td>0.05</td><td>Male broilers (7 wk)</td><td>3</td></tr><tr><td>Wheat (45) SBM (27), canola meal (12),<br>wheat screenings (10), peas (6)</td><td>12 d</td><td>101<sup>8</sup></td><td>0.25<sup>9</sup></td><td>0.06</td><td>Male broilers (2-3 wk)</td><td>4</td></tr><tr><td>Wheat (37) SBM (33), barley (16), canola<br>meal (9), wheat screenings (5)</td><td>37 d</td><td>120<sup>8</sup></td><td>0.31<sup>9</sup></td><td>0.15</td><td>Male broilers (7 wk)</td><td>3</td></tr><tr><td>Rye (58), SBM (26), wheat (16)</td><td>20 d</td><td>121</td><td>0.26</td><td>0.40</td><td>Mixed sex broilers (5-6 wk)</td><td>5</td></tr><tr><td>Pea fiber (54), barley (36)</td><td>0 to 63 d<sup>7</sup></td><td>149</td><td>0.40</td><td>0.06</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Pea fiber (64), barley (46)</td><td>0 to 63 d<sup>7</sup></td><td>251</td><td>0.40</td><td>0.12</td><td>Male broilers (2-13 wk)</td><td>1</td></tr><tr><td>Maize (54), peas (49)</td><td>12 d</td><td>88</td><td>0.07</td><td>0.05</td><td>Male broilers (2-3 wk)</td><td>6</td></tr><tr><td>Maize (100)</td><td>12 d</td><td>57</td><td>0.08</td><td>0.08</td><td>Male broilers (2-3 wk)</td><td>6</td></tr><tr><td>Maize (100)</td><td>11 d</td><td>68</td><td>0.10<sup>9</sup></td><td>0.14</td><td>Female broilers (4-5 wk)</td><td>7</td></tr><tr><td>Maize (52), SBM (48)</td><td>12 d</td><td>100</td><td>0.09</td><td>0.09</td><td>Male broilers (2-3 wk)</td><td>6</td></tr><tr><td>SBM (51), maize (35), canola meal (14)</td><td>12 d</td><td>136<sup>9</sup></td><td>0.16<sup>9</sup></td><td>0.12</td><td>Male broilers (2-3 wk)</td><td>8</td></tr><tr><td>SBM (51), maize (35), canola seed (14)</td><td>12 d</td><td>136<sup>9</sup></td><td>0.16<sup>9</sup></td><td>0.11</td><td>Male broilers (2-3 wk)</td><td>8</td></tr><tr><td>Canola meal (75), maize (25)</td><td>11 d</td><td>176</td><td>0.25<sup>9</sup></td><td>0.20</td><td>Female broilers (4-5 wk)</td><td>7</td></tr><tr><td>Canola meal (56), maize (44)</td><td>12 d</td><td>106</td><td>0.09</td><td>0.08</td><td>Male broilers (2-3 wk)</td><td>6</td></tr><tr><td>Canola meal, brown seeded (100)</td><td>7 d</td><td>91</td><td>0.10</td><td>0.03</td><td>Adult laying hens</td><td>9</td></tr><tr><td>Canola meal, yellow seeded (100)</td><td>7 d</td><td>113</td><td>0.09</td><td>0.09</td><td>Adult laying hens</td><td>9</td></tr><tr><td>Canola meal (100)</td><td>4 d</td><td>71</td><td>0.14</td><td>0.02</td><td>Adult laying hens</td><td>10</td></tr></tbody></table>

## Conclusion

Traditional analytical methods to analyze fiber, as crude fiber (CF) and neutral detergent fiber (NDF), recover only a variable part of the fiber fraction and are hence unfit to evaluate fiber fractions in raw materials and poultry diets. For scientific purposes, the enzymatic-chemical (Englyst or Uppsala) methods are more appropriate, whereas for routine analyses the AOAC (2009.01/2011.25) method for total, insoluble, and soluble dietary fiber can be used. Coefficients of apparent total tract digestibility of NSP in chicken range between 0 and 0.4 and generally reflect differences in solubility of the fiber fraction. Besides, physical entanglement of polysaccharides in the cell wall matrix also time available for fermentation and the absence of appropriate enzyme activities as determined by the microbial colonization in the gastrointestinal tract are possible limiting factors for NSP degradation. Although fiber in poultry nutrition is often associated

<footnote n="1">¹ Only studies that reported CATTD of total NSP in (semi-purified) complete diets were included. Studies in which CATTD measurements were preceded by fasting were excluded.</footnote>

<footnote n="2">² Values between brackets indicate contribution of NSP from raw materials to total NSP content of diet (%) calculated using data from original publications or BACH KNUDSEN (1997).</footnote>

<footnote n="3">³ Time in days (d) birds were allowed to adapt to the diet before CATTD measurements.</footnote>

<footnote n="4">⁴ NSP content of diet (g/kg DM) as reported or calculated from analyzed NSP contents of raw materials, unless indicated otherwise. Dry matter contents diets were assumed to be 900 g/kg, if not provided.</footnote>

<footnote n="5">⁵ Fraction of soluble NSP in total NSP (g/g), calculated from analyzed NSP contents, unless indicated otherwise.</footnote>

<footnote n="6">⁶ Data from: 1. JØRGENSEN et al. (1996); 2. JAMROZ et al. (2002); 3. BOROS et al. (2004); 4. MENG et al. (2005); 5. PETTERSON and ÅMAN (1989); 6. MENG and SLOMINSKI (2005); 7. DE VRIES et al. (2014b); 8. MENG et al. (2006); 9. SLOMINSKI et al. (1994); and 10. SLOMINSKI and CAMPBELL (1990).</footnote>

<footnote n="7">⁷ CATTD was measured during two blocks of five and four weeks from 12 d of age onwards, without preceding adaptation.</footnote>

<footnote n="8">⁸ Calculated based on data from BACH KNUDSEN (1997) and SLOMINSKI et al. (2004).</footnote>

<footnote n="9">⁹ Calculated based on data from BACH KNUDSEN (1997).</footnote>
with reduced energy availability due to its minor role in energy supply and interference with digestive processes, low to moderate amounts of fiber (up to 50 g/kg) might be beneficial for gastrointestinal development, function, and health, thereby enhancing nutrient digestibility and growth performance. A better understanding on the relation between specific fiber fractions and factors as GIT development, digesta retention time, and microbial colonization will help to develop nutritional strategies using specific fiber fractions to steer on GIT health and function to enhance performance, especially under suboptimal environmental conditions.

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# COMPARATIVE INTERESTS AND LIMITS OF METABOLIZABLE ENERGY AND NET ENERGY FOR EVALUATING POULTRY AND PIG FEEDS

Jean Noblet

INRA – UMR PEGASE – F 35590 Saint-Gilles, France; jean.noblet@rennes.inra.fr

## Summary

The evaluation of the energy content of pig or poultry feeds has been most commonly based on their DE or ME contents. However, the closest estimate of the "true" energy value of a feed should be its NE content, which takes into account differences in metabolic utilization of ME of nutrients. This review considers some methodological aspects of NE determination. Experimental data in pigs indicate that the NE/ME ratio varies greatly with the chemical composition of diets and nutrient, with ratios for fat (90%) and starch (80%) that are higher than for protein and dietary fibre (60%). This has marked consequences on the relative energy values of ingredients according to the energy system that is used. The NE system is also better in predicting the performance of pigs. With regard to poultry, the ranking between nutrients for NE/ME is similar to what is observed in pigs but with smaller differences between nutrients. However, complementary data are required to propose a convincing and functional NE system for poultry. In any case, the accuracy of the NE value is highly dependent on the accuracy of DE or ME values or digestible nutrient contents that are used as predictors of NE values. Overall, there is an obvious advantage in using NE systems for pigs while further investigations are required for implementing a reliable NE system for poultry.

## Introduction

The cost of feed is the most important cost of pig or broiler meat production (#60-70%) and the energy component represents the greatest proportion. Therefore, it is important to estimate precisely the energy value of feeds, either for least-cost formulation purposes or for adapting feed supply to energy requirements of animals. Evaluation of energy content of pig or poultry feeds was firstly and most commonly based on their DE or ME contents (only ME for poultry). However, the closest estimate of the "true" energy value of a feed corresponds to its NE content which takes into account differences in metabolic utilization of ME between nutrients. In addition, in a NE system, energy requirements and diet energy values are expressed on a same basis which should theoretically be independent of the feed characteristics. The objectives of this paper are then to present 1/ the available energy systems for pig feeds with emphasis given to NE systems and 2/ the corresponding available data on energy utilization in poultry (broilers). An overview of the methodological aspects of energy evaluation of pig and poultry feeds will introduce the topics.

## Methodological aspects

Not all gross energy (GE) of a feed is available for meeting the requirements of animals since variable proportions of GE are lost in excreta (faeces and urine in pigs), as fermentation gases (i.e., methane, hydrogen) and as heat (or heat increment, HI). The DE content of a feed (in pigs) is equal to its GE content minus faecal energy losses after digestion in the digestive tract. The ME content of a feed corresponds to the difference between the DE content and energy losses in urine and gases in pigs; for poultry, it is simply the difference between feed gross energy and energy losses in excreta and fermentation gases. Most of the energy lost in gases is due to methane production, which typically is very small in growing pigs and poultry and most ME values in literature and tables for growing pigs and poultry ignore energy losses as methane. As illustrated later on, it is not the case in adult pigs (Le Goff et al., 2002). In addition and unlike amino acids evaluation, most energy values do not consider energy losses related to the gut activity (i.e. endogenous losses) and DE and ME values are then apparent values. Finally, in the case of poultry, it is still rather common to consider that digestible N is totally excreted as uric acid and then to adjust the ME values for a zero N balance, even though that situation is unrealistic.

Net energy is defined as the ME content minus HI associated with feed utilization (i.e., energy cost of ingestion and digestion and HI related to metabolic utilization of ME) and the energy cost corresponding to a "normal" level of physical activity. However, the HI of a given feed (as % of ME) depends on several physiological/animal factors and may not be constant over a large range of ME intakes for a given animal. For instance, the HI tends to be lower below than above maintenance energy supply (Noblet et al., 1993; 1994a; 1994b) or when ME is used for fat deposition compared with protein deposition (Noblet et al., 1999). Therefore, for comparing different feeds for their HI or the efficiencies of ME utilization, it is necessary to calculate these values under similar conditions (e.g., feeding levels), at protein
and amino acid supplies meeting the requirement and/or constant composition of the gain and/or at a given physiological stage.

While DE (pig) and ME (pig, poultry) contents are rather easy to measure, NE is more complex to evaluate, especially the so-called HI which corresponds to the rate of increase of heat production (HP) per unit of ME intake increase. In practice, the HI is calculated as the difference between HP in a "standard" fed state and HP in a fasting state (FHP) and related to the ME intake in the fed state. For a growing animal, the NE intake is then calculated as the sum of retained energy (RE) at this "standard" feeding level and fasting heat production at zero activity (FHP) (Noblet et al., 1994a; Noblet and van Milgen, 2004; 2013). The corresponding NE value or the efficiency of ME for NE (k as NE/ME) then correspond to a combined utilization of energy for meeting requirements for maintenance and for growth. Different methods are used in order to measure either HP (indirect calorimetry in respiration chambers, for instance; and RE equals ME intake minus HP) or energy gain (comparative slaughter method, for instance). The indirect calorimetry method is the most used, especially for large animals, since it allows measurements over a short period of time (i.e. a few days) and it is far more flexible and informative in order, for instance, to partition the total HP between different components (van Milgen et al., 1997). The value of FHP can be calculated by extrapolating HP measured at different feeding levels to zero ME intake. However, this method, even though it has been widely used in the past and is still used nowadays, has important limitations, mainly because the growing animal adapts its FHP to its feeding/energy level prior to fasting (Labussière et al., 2011) and questions severely the use and meaning of extrapolated HP at zero ME intake for getting an estimate of FHP. Consequently, direct measurements of FHP according to appropriate methods are highly preferable (Noblet et al., 1994a; 2015). In practice, the use of literature measurements of FHP is an alternative solution. Finally, the mode of expression of FHP is also quite critical. In brief and for being practical, it is now accepted that FHP averages 750 kJ per kg BW<sup>0.60</sup> in growing pigs (Barea et al., 2010) and 450 kJ per kg BW<sup>0.70</sup> in broilers (Noblet et al., 2015).

From a practical point of view and to avoid bias in the calculation of NE for a series of feeds, it is necessary to carry out energy balance measurements in similar animals (i.e., same sex, same breed and the same body-weight range), to keep these animals in a temperature-controlled environment within their thermoneutral zone, to minimize variation in behaviour, and to feed the animals at the same energy level with balanced diets so that the animals can express their production/growth potential. Under these circumstances, an erroneous estimate of FHP will affect the absolute NE value but not the ranking between feeds. This also means that NE should not be measured in animals fed a single ingredient for which the chemical characteristics are usually quite different from those of a complete balanced diet.

Measurements of DE and ME are easy to implement and can be undertaken on a large number of feeds at a reasonable cost. On the other hand, the measurement of NE is more complex and expensive and cannot then be implemented routinely, either for complete feeds or ingredients. The alternative is to keep measuring DE or ME contents and to use literature NE prediction equations that were obtained from experiments carried out under strict and standardized conditions with DE or ME values as predictors of NE. As illustrated later, the situation is rather operational for pigs; it would not be the case for broilers or poultry.

## Energy utilization in pigs

For most pig diets, the digestibility coefficient of energy (DCe) varies between 70 and 90% but the variation is larger for feed ingredients (10 to 100%). Most of the variation of DCe is related to the presence of dietary fiber (DF) which is less digestible than other nutrients (#50% vs 80-100% for starch, sugars, fat or protein) and which also reduces the apparent fecal digestibility of other dietary nutrients such as crude protein and fat. Consequently, DCe is linearly and negatively related to the DF content of the feed (Le Goff and Noblet, 2001; table 1). The coefficients relating DCe to DF are such that DF essentially dilutes the diet, at least in growing pigs (table 1). In other terms, even though DF is partly digested by the young growing pig, it provides very little DE to the animal. Digestibility of energy can be modified by technological treatments. Pelleting, for instance, increases the energy digestibility of feeds by about 1% (Le Gall et al., 2009). However, the improvement is more important for some ingredients such as full fat rapeseed or (high oil) corn for which pelleting improves the digestibility of fat with subsequent marked differences in their DE value between mash and pellet forms (Noblet, 2006).