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Anim Biosci > Volume 33(10); 2020 > Article
Dong, Hu, Wan, Gong, and Feng: Effects of husbandry systems and Chinese indigenous chicken strain on cecum microbial diversity

Abstract

Objective

This study was to evaluate the effect of husbandry systems and strains on cecum microbial diversity of Jingyang chickens under the same dietary conditions.

Methods

A total of 320 laying hens (body weight, 1.70±0.15 kg; 47 weeks old) were randomly allocated to one of the four treatments: i) Silver-feathered hens in enrichment cages (SEC) with an individual cage (70×60×75 cm), ii) Silver-feathered hens in free range (SFR) with the stocking density of 1.5 chickens per ten square meters, iii) Gold-feathered hens in enrichment cages (GEC), iv) Gold-feathered hens in free range (GFR). The experiment lasted 8 weeks and the cecum fecal samples were collected for 16S rDNA high throughput sequencing at the end of experiment.

Results

i) The core microbiota was composed of Bacteroidetes (49% to 60%), Firmicutes (21% to 32%) and Proteobacteria (2% to 4%) at the phylum level. ii) The core bacteria were Bacteroides (26% to 31%), Rikenellaceae (9% to 16%), Parabacteroides (2% to 5%) and Lachnoclostridium (2% to 6%) at the genus level. iii) The indexes of operational taxonomic unit, Shannon, Simpson and observed species were all higher in SFR group than in SEC group while in GEC group than in GFR group, with SFR group showing the greatest diversity of cecum microorganisms among the four groups. iv) The clustering result was consistent with the strain classification, with a similar composition of cecum bacteria in the two strains of laying hens.

Conclusion

The core microbiota were not altered by husbandry systems or strains. The free-range system increased the diversity of cecal microbes only for silver feathered hens. However, the cecum microbial composition was similar in two strain treatments under the same dietary conditions.

INTRODUCTION

Asian indigenous chickens under the traditional husbandry system (free range) enjoy the advantages of better adaptation to endemic diseases and other harsh environmental stresses as well as requiring minimal care and low cost, which are in accordance with the wishes of local farmers [1]. The meat and eggs of some indigenous chickens are preferred over those of exotic breeds because of their unique flavor; meanwhile, the international voice for animal welfare allows the chicken industry to become more competitive by stressing the welfare advantages of the free-range system. This system is not only environmentally friendly and enables the animals to enjoy higher welfare standards and produce agricultural products with better quality and better flavor [2], but also provides job opportunities to the low-income population in rural areas [3].
Jingyang chicken, a Chinese indigenous breed from Jianshi county, Hubei, China with a unique appearance and good meat quality, has two strains of silver feather and gold feather. The quality and flavor of chicken products are related to the intestinal microbial community, which not only provides nutrition for the host, but also helps to maintain the balance of the intestinal microecology, and ensures the health and development of the intestinal tract [4, 5]. Particularly, the core flora of intestinal tract directly affects its normal function [6], which is closely related to the chicken products such as meat and eggs. Moreover, intestinal microbial community can be jointly affected by genetics and husbandry systems. The gut microflora is a complex ecosystem with a symbiotic relationship to the host, and interactions between them affect the physiological, immune and nutritional status of the host [7]. In general, the intestinal microbial system mainly focuses on microbial community composition and diversity. The intestinal microbial diversity is essential for animals to digest and absorb nutrients, maintain intestinal biochemical and physiological functions, and promote the development of immune system [8,9].
Unlike ruminants which mainly depend on ruminal microorganisms to digest cellulose, monogastric animals such as chickens are primarily dependent on the fermentation and degradation of microbes in the large intestine for digestion of cellulose [10]. Besides genetic factors, husbandry systems also make important contributions to the diversity of cecum microflora. Compared with caged chickens, free-range chickens have free access to feed herbage, seeds and insects, leading to accumulation of many intestinal microbes from the environment and formation of cecum microbial communities. Therefore, studies on the formation and diversity (species and richness) of the cecum microflora are of great significance for improving animal production performance and product quality.
In recent years, cecum microorganism has been a research focus, and a range of techniques have been developed to facilitate its research, such as denaturing gradient gel electrophoresis [11], terminal restriction fragment length polymorphism (T-RFLP) [12], real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) [13] and anaerobic cultivation [14]. In this study, Illumina MiSeq sequencing was adopted due to its advantages of high resolution for characterization of the microbial community, large coverage and low cost [15].
Diet has been reported as the biggest determinant of the composition of chicken intestinal flora [16]. The primary aim of this study was to explore the effects of the two variables (husbandry system and strain) on the chicken cecum microorganisms under the same dietary conditions. The results of this study can provide theoretical guidance to the farmers who are engaged in ecological breeding of indigenous chickens.

MATERIALS AND METHODS

Animal care

Animal experiments were performed under the institutional guidelines of Ecological Chicken Farm in Jianshi County of Hubei Province and Laboratory of Poultry Genetics, College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, China. The experiments were performed according to recommendations proposed by the European Commission (1997) to minimize the suffering of animals.

Experimental design and administration

Jingyang chickens were reared in the Fire Phoenix Ecological Breeding Cooperative of Jianshi County (Hubei, China). A total of 320 laying hens (body weight, 1.70±0.15 kg; 47 weeks old), derived from silver feather (S-line = 160 hens) and gold feather (G-line = 160 hens), under the two husbandry systems of enrichment cages (EC) and free range (FR) were randomly divided into four groups (80 hens per group): silver-feathered hens in enrichment cages (SEC), silver-feathered hens in free range (SFR), gold-feathered hens in enrichment cages (GEC), and gold-feathered hens in free range (GFR). For EC husbandry system, each hen was reared in an individual cage (70×60×75 cm) with controlled conditions of 18°C to 22°C, 16L/8D photoperiod/day. For FR husbandry system, chickens were raised in mountain areas characterized by arbor evergreen coniferous in the visible small stones and grains of sand, with a stocking density of 1.5 chickens per 10 square meters. Chickens in EC and FR were fed the same local standard diet (2,700 kcal/kg, 13% protein, 1% calcium, 0.45% phosphorous) (DB 42/T 686-2011) and drinking water ad libitum during the experiment period.

Sampling and measurements

At the end of the 60-day experiment, 5 chickens were randomly selected from each treatment (a total of 4 treatments × 5 repeat = 20) and the cecal samples were collected in a cryopreservation tubes and then mixed and stored in liquid nitrogen at −70°C.
Microbial genome DNA was extracted from cecal samples by using QIAamp DNA stool mini kit (Tiangen Biotech, Beijing, China) according to the manufacturer’s instructions. PCR amplification of the V3–V4 region of the 16S ribosomal RNA (rRNA) gene was performed using the 341F/802R primer set (341F: CCTAYGGGRBGCASCAG; 802R: GGACTAC NNGGGTATCTAAT) as previously reported [17]. Only the products without primer dimers and contaminant bands were used for 16S rDNA high throughput sequencing at Shanghai Personal Biotechnology Co., Ltd (Shanghai, China).

Data analysis

The screened and obtained high-quality sequences uploaded to quantitative insights into microbial ecology (QIIME, v1.8.0), were clustered into operational taxonomic units (OTUs) with a sequence similarity of >97% using the USEARCH software.

RESULTS AND DISCUSSION

Operational taxonomic unit analysis results of cecum microbes

The OTU analysis results of cecum microbes are presented in Table 1 and 2. A total of 22,660 OTUs consisted of 5,880, 6,245, 6,316, and 4,219 OTUs in SEC, GEC, SFR, and GFR, respectively (Table 1), and the annotation results are shown at various classification levels and the number of annotations in species is far less than that in genus level (Table 2). Moreover, the rarefaction curve (Figure 1) tends to be flat as sequencing depth increases and the number of OTUs reaches a plateau, with a sample coverage rate of over 0.96 (Table 3). These results confirmed that our sequencing has covered most of the sample species, and the sequencing results fully reflect the microbial diversity of the samples.

Abundance and diversity analysis of cecum microbiota

The results of abundance and diversity analysis are presented in Table 3. In silver-feathered chickens, Shannon index and Simpson index of SFR were higher than those of SEC. Nevertheless, compared with GFR, GEC showed higher values of chao1, Shannon index, and Simpson index. Bailey et al [18] found that exposure to prolonged restraint pressure (a stress method used to induce physiological responses in an animal by restricting its free movement) results in a decrease in the abundance and diversity of intestinal flora in mice. Thus, some of the above results in the present study could be explained by a prolonged restraint pressure-induced decrease in the relative abundance of bacteria of chickens in cages. However, Chao1, a species richness index, was lower in free-range groups than in cage groups. In our former research, a higher level of lactobacilli was observed in free range group, which could inhibit the proliferation of other bacteria and promote gut health [19]. GFR showed the maximum content of Lactobacillus, but the minimum content of chao1, Shannon index, and Simpson index in our present study. These data demonstrated that Lactobacillus did inhibit the growth of some bacteria.

Microbial community composition in cecum

The core microbiota of the 4 groups were counted at the phylum level (Table 4) and genus level (Table 5). At the phylum level, core members are microbes belonging to Bacteroidetes (49% to 60%), Firmicutes (21% to 32%), and Proteobacteria (2% to 4%), which are similar to the results reported in broilers [20], Dagu chickens [21], and Tibetan Chickens [22]. It is reported that the total proportion of Firmicutes and Bacteroides is even more than 90% in some mammalian species [23,24], and the Firmicutes/Bacteroides ratio can directly reflect the capacity of energy absorption and storage of host, such as the increase of the proportion of Firmicutes due to the deposition of fat [25], or the increase of the proportion of Bacteroides with the decrease of the Firmicutes/Bacteroides ratio due to enormous absorption of cellulose food [23,26]. In our study, the total proportion of Bacteroidetes and Firmicutes was more than 75% in Jingyang chickens, which was higher in free-range groups (SFR 81.61%; GFR 82.12%) than in enrichment-cage groups (SEC 76.38%; GEC 75.33%). The ratio of Firmicutes/Bacteroides was lower in GFR (23.00%/59.12%) than in GEC (21.20%/54.13%), whereas opposite results were obtained for silver-feather hens (SFR vs SEC). The reduced ratio of Firmicutes/Bacteroides in GFR group may be attributed to the higher cellulose food intakes in free range environment.
The core bacteria were Bacteroides (26% to 31%), Rikenellaceae (9% to 16%), Parabacteroides (2% to 5%), and Lachnoclostridium (2% to 6%) at the genus level. Ruminococcaceae was higher in SFR (2.25%) than in SEC (1.23%) as well as higher in GFR (1.4%) than in GEC (0.78%). Combined with our previous research results on cecum index, we speculate that the increased of free-range husbandry in the accumulation of microorganisms is related to cellulose degradation, which can be supported by the studies of Saengkerdsub et al [27], Lu et al [28], and Latham et al [29], who reported that ruminococcaceae was responsible for cellulose digestion.

Abundance and clustering analysis of relative bacterial communities

A further analysis was conducted to discover the relative bacterial community abundance at the phylum level, and the results are shown in Figure 2. The phyla were divided into four groups. Group 1 (Synergistes, Phascolarctobacterium, Megasphaera, Megamonas, Sutterella, and Parabacteroides) was predominant in SEC. Group 2 (Ruminococcaceae, Lachnoclostridium, Alloprevotella, Christensenellaceae, Oribacterium, and Anaerotruncus) was typical in SFR. Group 3 (Treponema, Odoribacter, Prevotellaceae, Sphaerochaeta, Desulfovibrio, and Ruminococceae) and Group 4 (Bacteroides, Subdoligranulum, Eubacterium, Saccharimonas, Rikenellaceae, and Lachnoclostridium) were observed in GEC and GFR, respectively. The clustering was dependent on hen strains (gold vs silver).
The clustering result was consistent with the strain classification: the silver-feather strain and the gold-feather strain. Actually, factors affecting the intestinal microbiotas are host and environment, with the former mainly referring to heredity, age and endocrinology, and the latter involving diet, geographical environment, lifestyle, and the use of antibiotics [16,30]. Diet has been reported as the dominant factor for the intestinal microbial community in the formation of host genotype [16]. In this study, we explored other factors affecting cecum microbial diversity under the same dietary conditions. Our study proved that the genetic factor has a greater impact than husbandry system on cecum microbial diversity in Jingyang chickens.

CONCLUSION

In conclusion, Bacteroides is the most abundant in cecum microbiotas of Jingyang chickens, followed by Firmicutes and Proteobacteria. Free range husbandry system as well as strain have observable effects on diversity of the cecum microorganism of Jingyang chickens. However, genetic factors show a more significant influence than husbandry system on cecum microbial diversity of chickens when fed the same diet.

Notes

CONFLICT OF INTEREST

We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

ACKNOWLEDGMENTS

The authors thank the Project Funders: The project from the Fundamental Research Funds for the Central Universities of China (Project No. 2662013PY008) and the project of innovative actions on agricultural science and technology in Hubei province: innovation on environmental friendly feeding technologies of livestock and poultry with high quality and efficiency (Project No. 2018skjcx05) for financing this study, Ecological Chicken Farm in Jianshi County of Hubei Province for supporting the materials in this study. The authors also thank the supervisor for the guidance of the test design and the help of the partners.

Figure 1
Species rarefaction curve. There is no intersection point after the zero point of the curve, and the order from high to low is GEC, SFR, SEC, GFR respectively.
ajas-19-0157f1.jpg
Figure 2
Heat maps of species abundance and clustering. The phylum classification position clustering (horizontal) and top 35 phylum sample clustering (vertical clustering). Different color means the different relative abundance of the phylum in all the four samples.
ajas-19-0157f2.jpg
Table 1
Sequencing data and OTUs annotation
Group1) Raw PE2) Raw tags2) Clean tags2) Effective tags2) Avg Len2) OTUs number2)
SEC 100,563 86,795 83,500 81,123 456 5,880
SFR 102,343 89,821 86,752 83,586 455 6,316
GEC 92,222 79,597 76,626 73,960 457 6,245
GFR 86,700 75,441 72,728 72,027 457 4,219

OTU, operational taxonomic units.

1) SEC, silver-feathered hens in enrichment cages; SFR, silver-feathered hens in free range; GEC, gold-feathered hens in enrichment cages; GFR, gold-feathered hens in free range.

2) Raw PE, the original PE (paired-end) reads; Raw tags, tag sequences obtained after splicing; Clean tags, a sequence with low-quality and short-length tags being removed; Effective tags, tag sequence collected for further analysis after filtering the chimera; Avg Len, the average length of effective tags; OTUs number, the number of OTUs obtained per sample.

Table 2
Classification of OTUs annotation results
Group1) Unassigned Kingdom Phylum Class Order Family Genus Species
SEC 1,353 1 20 5 92 719 3,673 17
SFR 1,332 4 19 4 87 733 4,119 18
GEC 1,443 2 17 4 101 721 3,944 13
GFR 727 2 12 4 71 541 2,855 7

OTU, operational taxonomic units.

1) SEC, silver-feathered hens in enrichment cages; SFR, silver-feathered hens in free range; GEC, gold-feathered hens in enrichment cages; GFR, gold-feathered hens in free range.

Table 3
Abundance and diversity analysis of cecum microbiota
Group1) Chao1 Shannon Simpson observed species Goods coverage
SEC 8367.58 9.05 0.99 5591.1 0.96
SFR 8218.05 9.32 0.991 6009.3 0.96
GEC 8028.44 9.13 0.989 6244.9 0.97
GFR 6752.82 8.44 0.987 4173.7 0.97

1) SEC, silver-feathered hens in enrichment cages; SFR, silver-feathered hens in free range; GEC, gold-feathered hens in enrichment cages; GFR, gold-feathered hens in free range.

Table 4
Phylum distribution of cecum bacteria
Items SEC1) SFR1) GEC1) GFR1)
Bacteroidetes 50.12 49.66 54.13 59.12
Firmicutes 26.26 31.95 21.2 23
Proteobacteria 3.26 2.87 3.11 2.35
Spirochaetae 0.82 0.78 2.21 1.04
Synergistetes 1.31 0.59 0.78 0.23
Saccharibacteria 0.3 0.38 0.26 0.71
SHA-109 0.54 0.6 0.17 0.23
Actinobacteria 0.53 0.6 0.21 0.59
Verrucomicrobia 0.21 0.29 0.05 0.12
Euryarchaeota 0.15 0.12 0.09 0.21
Others 16.51 12.15 17.81 12.39

1) SEC, silver-feathered hens in enrichment cages; SFR, silver-feathered hens in free range; GEC, gold-feathered hens in enrichment cages; GFR, gold-feathered hens in free range.

Table 5
Genus distribution of cecum bacteria
Items SEC1) SFR1) GEC1) GFR1)
Bacteroides 27.87 26.42 28.86 30.55
Rikenellaceae 9.03 11.73 11.29 15.31
Parabacteroides 4.75 3.45 2.24 2.52
Lachnoclostridium 3.37 5.1 2.75 3.51
Desulfovibrio 2.32 2.21 2.56 1.89
Prevotellaceae 2.35 1.61 4.03 3.15
Ruminococcaceae 1.23 2.25 0.78 1.4
Christensenellaceae 1.11 1.52 0.6 0.8
Others 47.98 45.71 46.89 40.86

1) SEC, silver-feathered hens in enrichment cages; SFR, silver-feathered hens in free range; GEC, gold-feathered hens in enrichment cages; GFR, gold-feathered hens in free range.

REFERENCES

1. Akyurek H, Orhan ZC. Effects of phytase supplementation on the performance and egg quality of free-range layers. Int J Curr Res 2016; 8:44142–7.

2. Sundrum A. Organic livestock farming: a critical review. Livest Prod Sci 2001; 67:207–15. https://doi.org/10.1016/S0301-6226(00)00188-3
crossref
3. Albokhadai I. Hematological and some biochemical values of indigenous chickens in Al-Ahsa, Saudi Arabia during summer season. Asian J Poult Sci 2012; 6:138–45. https://doi.org/10.3923/ajpsaj.2012.138.145
crossref
4. Danielsen M, Hornshøj H, Siggers RH, Jensen BB, van Kessel AG, Bendixen E. Effects of bacterial colonization on the porcine intestinal proteome. J Proteome Res 2007; 6:2596–604. https://doi.org/10.1021/pr070038b
crossref pmid
5. Les D, Margaret MFN, Relman DA. An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature 2007; 449:811–8. https://doi.org/10.1038/nature06245
crossref pmid pdf
6. Turnbaugh P, Hamady M, Yatsunenko T, et al. A core gut microbiome in obese and lean twins. Nature 2009; 457:480–4. https://doi.org/10.1038/nature07540
crossref pmid pdf
7. Zhao L, Wang G, Siegel P, et al. Quantitative genetic background of the host influences gut microbiomes in chickens. Sci Rep 2013; 3:1163 https://doi.org/10.1038/srep01163
crossref pmid pmc pdf
8. Shira EB, Sklan D, Friedman A. Impaired immune responses in broiler hatchling hindgut following delayed access to feed. Vet Immunol Immunopathol 2005; 105:33–45. https://doi.org/10.1016/j.vetimm.2004.12.011
crossref
9. Niba AT, Beal JD, Kudi AC, Brooks PH. Bacterial fermentation in the gastrointestinal tract of non-ruminants: Influence of fermented feeds and fermentable carbohydrates. Trop Anim Health Prod 2009; 41:1393 https://doi.org/10.1007/s11250-009-9327-6
crossref pmid pdf
10. Wenk C. The role of dietary fibre in the digestive physiology of the pig. Anim Feed Sci Technol 2001; 90:21–33. https://doi.org/10.1016/S0377-8401(01)00194-8
crossref
11. Gong J, Yu H, Liu T, et al. Effects of zinc bacitracin, bird age and access to range on bacterial microbiota in the ileum and caeca of broiler chickens. J Appl Microbiol 2008; 104:1372–82. https://doi.org/10.1111/j.1365-2672.2007.03699.x
crossref pmid
12. Gong J, Forster RJ, Yu H, et al. Diversity and phylogenetic analysis of bacteria in the mucosa of chicken ceca and comparison with bacteria in the cecal lumen. FEMS Microbiol Lett 2002; 208:1–7. https://doi.org/10.1111/j.1574-6968.2002.tb11051.x
crossref pmid pdf
13. Smirnov A, Perez R, Amit-Romach E, Sklan D, Uni Z. Mucin dynamics and microbial populations in chicken small intestine are changed by dietary probiotic and antibiotic growth promoter supplementation. J Nutr 2005; 135:187–92. https://doi.org/10.1093/jn/135.2.187
crossref pmid pdf
14. Lan PTN, Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of cecal microbiota in chicken by the use of 16S rDNA clone libraries. Microbiol Immunol 2002; 46:371–82. https://doi.org/10.1111/j.1348-0421.2002.tb02709.x
crossref pmid
15. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 2013; 79:5112–20. https://doi.org/10.1128/AEM.01043-13
crossref pmid pmc
16. Carmody R, Gerber G, Luevano JM, et al. Diet Dominates host genotype in shaping the murine gut microbiota. Cell Host Microbe 2015; 17:72–84. https://doi.org/10.1016/j.chom.2014.11.010
crossref pmid
17. Zhao L, Wang G, Siegel P, et al. Quantitative genetic background of the host influences gut microbiomes in chickens. Sci Rep 2013; 3:1163 https://doi.org/10.1038/srep01163
crossref pmid pmc pdf
18. Bailey MT, Dowd SE, Parry NM, Galley JD, Schauer DB, Lyte M. Stressor exposure disrupts commensal microbial populations in the intestines and leads to increased colonization by Citrobacter rodentium . Infect Immun 2010; 78:1509–19. https://doi.org/10.1128/IAI.00862-09
crossref pmid pmc
19. Choe DW, Loh TC, Foo HL, Hairbejo M, Awis QS. Egg production, faecal pH and microbial population, small intestine morphology, and plasma and yolk cholesterol in laying hens given liquid metabolites produced by Lactobacillus plantarum strains. Br Poult Sci 2012; 53:106–15. https://doi.org/10.1080/00071668.2012.659653
crossref
20. Lan PTN, Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of cecal microbiota in chicken by the use of 16S rDNA clone libraries. Microbiol Immunol 2002; 46:371–82. https://doi.org/10.1111/j.1348-0421.2002.tb02709.x
crossref pmid
21. Xu Y, Yang H, Zhang L, et al. High-throughput sequencing technology to reveal the composition and function of cecal microbiota in Dagu chicken. BMC Microbiol 2016; 16:259 https://doi.org/10.1186/s12866-016-0877-2
crossref pmid pmc pdf
22. Zhou X, Jiang X, Yang C, et al. Cecal microbiota of Tibetan Chickens from five geographic regions were determined by 16S rRNA sequencing. Microbiologyopen 2016; 5:753–62. https://doi.org/10.1002/mbo3.367
crossref pmid pmc
23. Ley RE, Micah H, Catherine L, et al. Evolution of mammals and their gut microbes. 2008; 320:1647–51. https://doi.org/10.1126/science.1155725
crossref
24. Leser TD, Amenuvor JZ, Jensen TK, Lindecrona RH, Mette B, Kristian ML. Culture-independent analysis of gut bacteria: the pig gastrointestinal tract microbiota revisited. Appl Environ Microbiol 2002; 68:673–90. https://doi.org/10.1128/AEM.68.2.673-690.2002
crossref pmid pmc
25. Turnbaugh PJ, Ley RE, Mahowald MA, Vincent M, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006; 444:1027–31. https://doi.org/10.1038/nature05414
crossref pmid pdf
26. Carlotta DF, Duccio C, Monica DP, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci USA 2010; 107:14691–6.
crossref pmid
27. Saengkerdsub S, Herrera P, Woodward CL, Anderson RC, Nisbet DJ, Ricke SC. Detection of methane and quantification of methanogenic archaea in faeces from young broiler chickens using real-time PCR. Lett Appl Microbiol 2007; 45:629–34. https://doi.org/10.1111/j.1472-765X.2007.02243.x
crossref pmid
28. Lu J, Idris U, Harmon B, Hofacre C, Maurer JJ, Lee MD. Diversity and succession of the intestinal bacterial community of the maturing broiler chicken. Appl Environ Microbiol 2003; 69:6816–24. 10.1128/AEM.69.11.6816-6824.2003
crossref
29. Latham MJ, Wolin MJ. Fermentation of cellulose by Ruminococcus flavefaciens in the presence and absence of Methanobacterium ruminantium. Appl Environ Microbiol 1977; 34:297–301.
crossref pmid pmc
30. Sybille T, June Z, Michael K, Roy M, Marco ML. The intestinal microbiota in aged mice is modulated by dietary resistant starch and correlated with improvements in host responses. FEMS Microbiol Ecol 2013; 83:299–309. https://doi.org/10.1111/j.1574-6941.2012.01475.x
crossref pmid pdf


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