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Effects of high ambient temperature on the community structure and composition of ileal microbiome of broilers
Effects of high ambient temperature on the community structure and composition of ileal microbiome of broilers X. J. Wang,∗ J. H. Feng,∗,1 M. H. Zhang,∗ X. M. Li,∗ D. D. Ma,∗ and S. S. Chang†,∗ ∗
State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; and † College of Agriculture, Hebei University of Engineering, Handan 056021, China ibacterium, Rothia, Alistipes, Azospirillum, and Oscillibacter were enriched, while Coprococcus and Streptococcus were reduced in heat-stressed broilers. High temperature significantly influenced the alpha diversity, with higher observed species (P = 0.004), whole-tree phylogenetic diversity (P = 0.002), and Chao 1 (P = 0.002), but the Pielou, Shannon, and Simpson indices were unaltered (P > 0.05), indicating that high temperature increased the ileal microbiota species richness. Based on unweighted UniFrac distance metric matrices, principal component analysis showed that the HT group formed a distinct cluster clearly set apart from the TC group. Analysis of similarity also indicated that samples within groups were more similar to each other than to any samples from other groups (R = 0.626; P = 0.004). In conclusion, high temperature influenced the bacterial composition and community structure of the ileal microbiota of broilers, specifically by increasing the species richness.
ABSTRACT The intestinal microbiome has been shown to influence animal nutrient metabolism and immune homeostasis. The present study aimed to examine the effect of heat stress on the intestinal microbiome of broilers using pyrosequencing technologies. Ninety-six Arbor Acres broiler chicks were allocated to thermoneutral control (TC; 21 ± 1◦ C) and high ambient temperature (HT; 31 ± 1◦ C) groups (6 cages of 8 birds per group), respectively, and raised in 2 controlled climate chambers from 28 to 42 d old. Genomic DNA was extracted from ileal contents isolated from 6 male broiler chicks of each group at 42 d old, and then amplified based on the V3–4 hyper-variable region of 16S rRNA. High temperature had no significant effects, but tended to influence the relative abundance of major phyla and orders in the broilers’ ileal microbiota. Analysis of linear effect size feature selection identified 9 discriminative features (genus level, linear discriminant analysis score > 3). Clostridium XIVb, Streptophyta, Faecal-
Key words: community structure, ileal microbiota, broiler chicken, high temperature, pyrosequencing 2018 Poultry Science 0:1–6 http://dx.doi.org/10.3382/ps/pey032
INTRODUCTION
exposed to high temperature. Song et al. (2014) demonstrated that heat stress reduced the viable counts of Lactobacillus and Bifidobacterium, and increased the viable counts of coliforms and Clostridium in the small intestinal contents of broilers. Suzuki et al. (1983) also showed using culture techniques that heat stress resulted in a marked change in the bacterial composition within chicken intestine. However, it is well recognized that many of these bacteria have not yet been cultured in the laboratory. Recent advances in high-throughput sequencing technologies, coupled with efficient bioinformatics tools, have enabled in-depth analysis of the microbiome of poultry (Aranda-Olmedo and Rubio, 2016; Xiao et al., 2016). In contrast to traditional microbiological techniques, these approaches provide a relatively comprehensive description of the intestinal microbiota. The aim of the present study was to provide a deeper understanding of the effect of heat stress on the intestinal microbiome of broilers using high-throughput sequencing technologies.
Heat stress has detrimental effects on poultry growth and health (Smith, 1993; Sohail et al., 2012; Mack et al., 2013). A growing number of studies has shown that the gut microbiota plays an important role in the body’s health and growth, by impacting intestinal morphology, feed digestion and nutrient absorption, the development of the immune system, and the proliferation of pathogenic intestinal bacteria (Oakley et al., 2014; Waite and Taylor, 2014, 2015; Mohd Shaufi et al., 2015). Using denaturing gradient gel electrophoresis, Burkholder et al. (2008) found that the intestinal microbial community structure changed when broilers were C 2018 Poultry Science Association Inc. Received October 11, 2017. Accepted March 8, 2018. 1 Corresponding author: [email protected]
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MATERIALS AND METHODS Birds, Treatments, and Sample Collection Arbor Acres broiler chicks were reared in onetier cages from one d old on a standard corn– soybean meal diet and had ad libitum access to feed and water. The room temperature was adjusted according to the Arbor Acres broiler management guide. The birds were reared in compliance with the Guidelines for Experimental Animals established by the Ministry of Science and Technology (Beijing, China). At 21 d of age, 96 broiler chicks of similar body weight (BW) were selected and allocated to thermoneutral control (TC) and high ambient temperature (HT) groups (6 cages of 8 birds per group), respectively, and raised in 2 controlled climate chambers. After 7 d of adaptation (21◦ C and 60%), from 28 to 42 d old, the broilers of the TC group remained under a constant 21 ± 1◦ C and 60 ± 10% RH, while those of the HT group were maintained under a constant high temperature of 31 ± 1◦ C, also at 60 ± 10% RH. At 42 d of age, 6 male broiler chicks were selected randomly from each group and euthanized by cervical dislocation. Immediately after sacrifice, the ileal contents (contents of the section between Meckel’s diverticulum and the ileocecal junction) of each bird were aseptically collected in sterile vials, frozen in liquid nitrogen, and stored at −80◦ C until using for the sequencing of microbial genes.
DNA Extraction, Amplification of 16S rRNA Gene, and Pyrosequencing Total bacteria genomic DNA was extracted from frozen ileum contents using the E.Z.N.A. Stool DNA Kits (Omega Bio-tek, Norcross, GA). The DNA integrity was assessed visually using 1.0% (w/v) agarose gel (containing ethidium bromide) electrophoresis. The microbial 16S rDNA was amplified with indices and adaptors-linked universal primers 341F (5 -ACTCCTACGGGAGGCAGCAG-3 ) and 806R (5 -GGACTACHVGGGTWTCTAAT-3 ) targeting the V3–4 region. PCR was performed using KAPA HiFi Hotstart PCR kit high-fidelity enzyme to ensure the accuracy and efficiency of amplification as a template of diluted genomic DNA. PCR products were detected using 2% agarose gel electrophoresis, and then recovered using AxyPrep DNA gel Recovery Kit (AXYGEN), and quantified by the Qubit 2.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA). Pyrosequencing was performed using Illumina HiSeq PE250 platform (Illumina, San Diego, CA) at the RealBio Technology Inc. (Shanghai, China).
Sequence Analysis and Phylogenetic Classification All the raw sequences obtained from Illumina HiSeq were firstly quality-filtered to remove tags with length of < 220 nt, average quality score of < 20, and tags containing >3 ambiguous bases by PANDAseq. After discarding the singletons, the high-quality tags were clustered into operational taxonomic units (OTU) using Usearch with a similarity threshold of 0.97, and the OTU were further subjected to the taxonomybased analysis using the Ribosomal Database Project (RDP) database. Alpha diversity (Simpson, Shannon, Chao1, PD-whole-tree index, Observed Species) and beta diversity were analyzed using QIIME (Paul and Josephine, 2004). Linear discriminant analysis (LDA) effect size (LEfSe) analyses were performed with the LEfSe tool (Segata et al., 2011). The relative abundance of bacteria was expressed as the percentage.
Statistical Analysis The differences of alpha diversity (Simpson, Shannon, Chao1, PD-whole-tree index, Observed Species) and mean relative abundance of bacteria between the 2 groups were analyzed by the Mann–Whitney test using SAS software (version 9.2; SAS Inst. Inc., Cary, NC). P < 0.05 was considered statistically significant. Principal coordinate analysis (PCoA) and analysis of similarity (ANOSIM) tests were conducted based on the weighted and unweighted Unifrac distance. ANOSIM tests the null hypothesis that microbial communities were significantly different between the 2 groups and provides a test statistic R, with values close to 1 meaning high dissimilarity between groups and high similarity within groups. LEfSe analysis uses the Mann–Whitney test to detect significantly different abundances and performs LDA scores to estimate the effect size (threshold ≥ 3).
RESULTS Evaluation of Pyrosequencing Data After assembling and quality filtering, a total of 432,280 sequences was obtained from 12 samples, with the number of sequences ranging from 33,168 to 38,763 per individual, and were clustered into 70 to 228 OTU per sample, resulting in a total of 382 OTU for all samples at a 97% sequence similarity value. The rarefaction curves (Figure 1) show that the rarefied sequencing depth (31,621) reveals most bacterial communities in all samples.
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EFFECT OF HIGH TEMPERATURE ON MICROBIOME OF BROILER
Figure 1. Rarefaction curves of Chao1 indices (A) and Observed Species index (B) for each sample.
Table 1. Effects of high temperature on alpha-diversity of the broiler ileal microbiota.
HT group TC group P-value
goods Coverage
Pielou
Observed Species
PD whole-tree
Chao1
Shannon
Simpson
1.00 1.00 0.13
0.33 0.34 1.00
157.83 73.17 0.002
12.64 8.13 0.002
175.90 95.52 0.004
2.27 1.90 0.59
0.56 0.57 0.70
Variation in Alpha Diversity Alpha diversity is presented in Table 1. In comparison with the TC group, mean observed species (P = 0.004), whole-tree PD (P = 0.002), and Chao 1 (P = 0.002) were higher in the HT group. However, the Pielou (P = 1.00), Shannon (P = 0.59), and Simpson indices (P = 0.70) were not significantly different between the 2 groups.
Variation in Beta Diversity PCoA revealed that the HT group formed a distinct cluster clearly set apart from the TC group based on the unweighted UniFrac metric (Figure 2b), but there was no clear difference between the TC and HT groups on the basis of the weighted UniFrac metric (Figure 2a). The test statistic (R) of ANOSIM was 0.626 (P = 0.004; Figure 3b) on unweighted UniFrac and −0.017 (P = 0.55; Figure 3a) on weighted UniFrac, indicating that samples within groups were more similar to each other than to any samples from other groups (based on unweighted UniFrac).
(92.21%), and lower relative abundance of Proteobacteria (1.93%) and Bacteroidetes (2.58%; Figure 4A). The predominant orders in the ileal contents of the TC group were Clostridiales (72.67%), Lactobacillales (12.86%), Enterobacteriales (7.30%), and Bacterioidales (5.07%). The HT group samples showed a higher relative abundance of the Lactobacillales (25.04%) and lower relative abundance of the Clostridiales (66.90%), Enterobacteriales (1.56%), and Bacterioidales (2.55%; Figure 4B). However, none of these differences was statistically significant by the Mann–Whitney test.
Differentiating Taxa We employed LEfSe to identify the specific taxa in the ileal microbiome that were significantly associated with high temperature. LEfSe identified 9 discriminative features (genus level, linear discriminant analysis score > 3, Figure 5). The microbiota in the HT group was enriched with Clostridium XIVb, Streptophyta, Faecalibacterium, Rothia, Alistipes, Azospirillum, and Oscillibacter. Coprococcus and Streptococcus were enriched in the TC group compared with their levels in the HT group.
Comparison of Microbial Composition at the Phylum and Order Levels At the phylum level, most of the sequences from the ileal contents of TC group chickens were assigned to Firmicutes (85.64%), followed by Proteobacteria (7.39%) and Bacteroidetes (5.07%). The HT group samples showed higher relative abundance of Firmicutes
DISCUSSION Using denaturing gradient gel electrophoresis, Burkholder et al. (2008) found that the number of bands and the similarity coefficients were changed when broilers were exposed to high temperatures, which indicated that heat stress impacted the intestinal microbial
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Figure 2. Principal coordinate analysis (PCoA) of the community membership based on the weighted (A) and unweighted (B) UniFrac distance, with the distribution of the samples in the high temperature group (HT) and thermoneutral control group (TC), along the first principal coordinate axis shown alongside on the below, along the second principal coordinate axis shown alongside on the right (∗∗∗ P < 0.001, Mann–Whitney U).
Figure 3. Analysis of similarity (ANOSIM) of the community membership based on the weighted (A) and unweighted (B) UniFrac distance metric matrices. For similarity within high temperature group (HT), thermoneutral control group (TC), and all the samples.
community structure. The results in the present study also show that high temperature exerted a significant influence on the overall bacterial community structure of the gut microbiota in broilers. Specifically, the high temperature significantly increased all the species richness indices of the bacterial community (observed species, whole-tree PD, and Chao 1), but had no significant effects on the Shannon, Simpson, or Pielou index. Shannon and Simpson indices comprehensively reflect the species richness and the community evenness, and the Pielou index reflects the bacterial community evenness. So we speculated that the high temperature may increase the species richness, but has no significant effects on homogenization of the ileal microbiota of the broilers. Analysis of the beta diversity shows that the HT group formed a distinct cluster clearly set apart from the TC group based on the unweighted UniFrac metric, but did not when based on the weighted UniFrac (which calculates the relative abundance of microbiota). This result also supported the above hypothesis. The dominant phyla in the ilea of poultry are Firmicutes, Proteobacteria, Bacteroidetes, and
Actinobacteria (Bjerrum et al., 2006; Xiao et al., 2016), in accordance with the current findings. At the order level, the ileal contents are dominated by Clostridiales, Enterobacteriales, Lactobacillales, and Bacterioidales (Bjerrum et al., 2006; Xiao et al., 2016). The relative abundance of these dominant orders in our study was slightly different from the results of Bjerrum et al. (2006). The varying microbiota profiles across different trials may attributed to setting, location, and feed variations (Stanley et al., 2013). Using culture techniques, Song et al. (2014) demonstrated that heat stress reduced the viable counts of Lactobacillus and Bifidobacterium and increased the viable counts of coliforms and Clostridium in the small intestinal contents of broilers. Suzuki et al. (1983) found that the counts of Enterobacteriaceae reduced, while those of Streptococcus and Staphylococcus increased in the small intestine of heat-stressed chicks. The results of the current study show tendencies for Lactobacillales to be more abundant, and Enterobacteriales to be less so, in the ileal contents of chicks exposed to high temperatures. However, limited by the number of samples
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EFFECT OF HIGH TEMPERATURE ON MICROBIOME OF BROILER
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Figure 4. Relative abundance of major phylum (A) and order (B) in the lieal contents of individual broilers in the high temperature group (HT1-HT6) and thermoneutral control group (TC1-TC6).
Figure 5. Histogram of the LDA scores computed for genera differentially abundant between High temperature group (HT) and thermoneutral control group (TC) individuals. Genera enriched in heat-stressed individuals are indicated with a negative LDA score, and genera enriched in control group individuals have a positive score. The LDA score indicates the effect size and ranking of each differentially abundant taxon.
analyzed, none of these differences was statistically significant. The analysis of individual bird samples has demonstrated significant variation in microbiota structure within single treatment groups (Stanley et al., 2013), so a more robust sampling regimen is required to demonstrate the effects of high temperature on the predominant composition of the microbiota in broilers. We identified 9 taxa that discriminated the groups. Recent research has revealed that Clostridium XIVb was enriched in diarrheic patients (Ling et al., 2014). The members of Clostridium XIVb were previously
observed in poultry with ulcerative enteritis (Berkhoff, 1985). The decreased abundance of Coprococcus species has been associated with irritable bowel syndrome, including colonic hypersensitivity, bloating, and gastrointestinal (GI) discomfort in humans (Malinen et al., 2010). Lee et al. (2014) also found by using LEfSe that Coprococcus was significantly lower in patients with diarrhea. Heat stress has serious adverse impacts on intestinal morphology, integrity, and mucosal immunity in poultry (Burkholder et al., 2008; Song et al., 2014; Quinteiro-Filhoa et al., 2017). The variation in
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Clostridium and Coprococcus abundance observed in the present study may be associated with intestinal injury induced by high temperatures. Faecalibacterium is characterized by its anti-inflammatory activity within the gut, has been frequently reported to be decreased in GI inflammation, and is important in maintaining GI health (Minamoto et al., 2015; Suchodolski et al., 2015). However, significantly higher levels of the genus Faecalibacterium in heat-stressed broilers were observed in the present study, which cannot be used to explain the intestinal injury induced by high temperature. Further studies with larger samples are required to identify the taxa that are strongly correlated with intestinal injury induced by high temperature. Such differentially abundant bacteria maybe represent new stress markers and target populations that could potentially be modified in order to improve animal growth and health. In conclusion, the high temperature influenced the bacterial composition and community structure of the ileal microbiota of broilers, specifically by increasing the species richness.
ACKNOWLEDGMENTS This study was supported by the National Key Research and Development Program of China (2016YFD0500509). This research also was supported by the Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences (ASTIP-IAS07).
REFERENCES Aranda-Olmedo, I., and L. A. Rubio. 2016. Heterogeneous size datasets of broiler intestinal microbial communities can be analyzed without normalization. Poult. Sci. 00:1–7. Berkhoff, H. A. 1985. Clostridium-colinum sp-nov, nom rev, the causative agent of ulcerative enteritis (quail disease) in quail, chickens, and pheasants. Int. J. Syst. Bacteriol. 35:155–159. Bjerrum, L., R. Engberg, T. D. Leser, B. B. Jensen, K. Finster, and K. Pedersen. 2006. Microbial community composition of the ileum and cecum of broiler chickens as revealed by molecular and culture-based techniques. Poult. Sci. 85:1151–1164. Burkholder, K. M., K. L. Thompson, M. E. Einstein, T. J. Applegate, and J. A. Patterson. 2008. Influence of stressors on normal intestinal microbiota, intestinal morphology, and susceptibility to salmonella enteritidis colonization in broilers. Poult. Sci. 87:1734– 1741. Lee, J. R., T. Muthukumar, D. Dadhania, N. C. Toussaint, L. Ling, E. Pamer, and M. Suthanthiran. 2014. Gut microbial community structure and complications. following kidney transplantation: A pilot study. Transplantation. 98:697–705. Ling, Z. X., X. Liu, X. Y. Jia, Y. W. Cheng, Y. Q. Luo, L. Yuan, Y. Z. Wang, C. N. Zhao, S. Guo, L. J. Li, X. W. Xu,, and C. L. Xiang. 2014. Impacts of infection with different toxigenic Clostridium difficile strains on faecal microbiota in children. Sci. Rep. 4:7485.
Mack, L. A., J. N. Felver-Gant, R. L. Dennis, and H. W. Cheng. 2013. Genetic variation alter production and behavioral responses following heat stress in 2 strains of laying hens. Poult. Sci. 92:285– 294. Malinen, E., L. Krogius-Kurikka, A. Lyra, J. Nikkila, A. Jaaskelainen, T. Rinttila, T. Vilpponen-Salmela, A. J. V. Wright, and A. Palva. 2010. Association of symptoms with gastrointestinal microbiota in irritable bowel syndrome. World. J. Gastroenterol. 16:4532–4540. Minamoto, Y., C. C. Otoni, S. M. Steelman, O. Buyukleblebici, J. M. Steiner, A. E. Jergens, and J. S. Suchodolski. 2015. Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease. Gut. Microbes. 6: 33–47. Mohd Shaufi, M. A., C. C. Sieo, C. W. Chong, H. M. Gan, and Y. W. Ho. 2015. Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses. Gut Pathog. 7:4. Oakley, B. B., H. S. Lillehoj, M. H. Kogut, W. K. Kim, J. J. Maurer, A. Pedroso, M. D. Lee, S. R. Collett, T. J. Johnson, and N. A. Cox. 2014. The chicken gastrointestinal microbiome. FEMS Microbiol. Lett. 360:100–112. Paul, F. K., and Y. A. Josephine 2004. Bacterial diversity in aquatic and other environments: What 16S rDNA libraries can tell us. FEMS Microbiol. Ecol 47:161–177. Quinteiro-Filhoa, W. M., A. S. Calefia, D. S. G. Cruza, T. P. A. Aloiad, A. Zagera, C. S. Astolfi-Ferreirab, J. A. Piantino Ferreirab, S. Sharif, and J. Palermo-Netoa. 2017. Heat stress decreases expression of the cytokines, avian β -defensins 4 and 6 and Toll-like receptor 2 in broiler chickens infected with Salmonella Enteritidis. Veterinary Immunology and Immunopathology. 186:19–28. Segata, N., J. Izard, L. Waldron, D. Gevers, L. Miropolsky, W. S. Garrett, and C. Huttenhower. 2011. Metagenomic biomarker discovery and explanation. Genome Biol. 12:R60. Smith, M. O. 1993. Parts yield of broilers reared under cycling high temperatures. Poult. Sci. 72:1146–1150. Sohail, M. U., M. E. Hume, J. A. Byrd, D. J. Nisbet, A. Ljaz, A. Sohail, M. Z. Shabbir, and H. Rehman. 2012. Effect of supplementation of prebiotic mannan-oligosaccharides and probiotic mixture on growth performance of broilers subjected to chronic heat stress. Poult Sci 91:2235–2240. Song, J., K. Xiao, Y. L. Ke, L. F. Jiao, C. H. Hu, Q. Y. Diao, B. Shi, and X. T. Zou. 2014. Effect of a probiotic mixture on intestinal microflora, morphology, and barrier integrity of broilers subjected to heat stress. Poult. Sci. 93:581–588. Stanley, D., M. S. Geier, R. J. Hughes, S. E. Denman, and R. J. Moore. 2013. Highly variable microbiota development in the chicken gastrointestinal tract. PLoS. One. 8:e84290. Suchodolski, J. S., M. L. Foster, M. U. Sohail, C. Leutenegger, E. V. Queen, J. M. Steiner, and S. L. Marks. 2015. The fecal microbiome in cats with diarrhea. PLoS. One. 10:e0127378. Suzuki, K., R. Harasawa, Y. Yoshitake, and T. Matsuoka. 1983. Effects of crowding and heat stress on intestinal flora, body weight gain, and feed efficiency of growing rats and chicks. Nippon Juigaku Zasshi 45:331–338. Waite, D. W., and M. W. Taylor. 2014. Characterizing the avian gut microbiota: Membership, driving influences, and potential function. Front Microbiol. 5:223. Waite, D. W., and M. W. Taylor. 2015. Exploring the avian gut microbiota: Current trends and future directions. Front Microbiol. 6:673. Xiao, Y. P., Y. Xiang, W. D. Zhou, J. G. Chen, K. F. Li, and H. Yang. 2016. Microbial community mapping in intestinal tract of broiler chicken. Poult. Sci. 96:1387–1393.
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State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; and † College of Agriculture, Hebei University of Engineering, Handan 056021, China ibacterium, Rothia, Alistipes, Azospirillum, and Oscillibacter were enriched, while Coprococcus and Streptococcus were reduced in heat-stressed broilers. High temperature significantly influenced the alpha diversity, with higher observed species (P = 0.004), whole-tree phylogenetic diversity (P = 0.002), and Chao 1 (P = 0.002), but the Pielou, Shannon, and Simpson indices were unaltered (P > 0.05), indicating that high temperature increased the ileal microbiota species richness. Based on unweighted UniFrac distance metric matrices, principal component analysis showed that the HT group formed a distinct cluster clearly set apart from the TC group. Analysis of similarity also indicated that samples within groups were more similar to each other than to any samples from other groups (R = 0.626; P = 0.004). In conclusion, high temperature influenced the bacterial composition and community structure of the ileal microbiota of broilers, specifically by increasing the species richness.
ABSTRACT The intestinal microbiome has been shown to influence animal nutrient metabolism and immune homeostasis. The present study aimed to examine the effect of heat stress on the intestinal microbiome of broilers using pyrosequencing technologies. Ninety-six Arbor Acres broiler chicks were allocated to thermoneutral control (TC; 21 ± 1◦ C) and high ambient temperature (HT; 31 ± 1◦ C) groups (6 cages of 8 birds per group), respectively, and raised in 2 controlled climate chambers from 28 to 42 d old. Genomic DNA was extracted from ileal contents isolated from 6 male broiler chicks of each group at 42 d old, and then amplified based on the V3–4 hyper-variable region of 16S rRNA. High temperature had no significant effects, but tended to influence the relative abundance of major phyla and orders in the broilers’ ileal microbiota. Analysis of linear effect size feature selection identified 9 discriminative features (genus level, linear discriminant analysis score > 3). Clostridium XIVb, Streptophyta, Faecal-
Key words: community structure, ileal microbiota, broiler chicken, high temperature, pyrosequencing 2018 Poultry Science 0:1–6 http://dx.doi.org/10.3382/ps/pey032
INTRODUCTION
exposed to high temperature. Song et al. (2014) demonstrated that heat stress reduced the viable counts of Lactobacillus and Bifidobacterium, and increased the viable counts of coliforms and Clostridium in the small intestinal contents of broilers. Suzuki et al. (1983) also showed using culture techniques that heat stress resulted in a marked change in the bacterial composition within chicken intestine. However, it is well recognized that many of these bacteria have not yet been cultured in the laboratory. Recent advances in high-throughput sequencing technologies, coupled with efficient bioinformatics tools, have enabled in-depth analysis of the microbiome of poultry (Aranda-Olmedo and Rubio, 2016; Xiao et al., 2016). In contrast to traditional microbiological techniques, these approaches provide a relatively comprehensive description of the intestinal microbiota. The aim of the present study was to provide a deeper understanding of the effect of heat stress on the intestinal microbiome of broilers using high-throughput sequencing technologies.
Heat stress has detrimental effects on poultry growth and health (Smith, 1993; Sohail et al., 2012; Mack et al., 2013). A growing number of studies has shown that the gut microbiota plays an important role in the body’s health and growth, by impacting intestinal morphology, feed digestion and nutrient absorption, the development of the immune system, and the proliferation of pathogenic intestinal bacteria (Oakley et al., 2014; Waite and Taylor, 2014, 2015; Mohd Shaufi et al., 2015). Using denaturing gradient gel electrophoresis, Burkholder et al. (2008) found that the intestinal microbial community structure changed when broilers were C 2018 Poultry Science Association Inc. Received October 11, 2017. Accepted March 8, 2018. 1 Corresponding author: [email protected]
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MATERIALS AND METHODS Birds, Treatments, and Sample Collection Arbor Acres broiler chicks were reared in onetier cages from one d old on a standard corn– soybean meal diet and had ad libitum access to feed and water. The room temperature was adjusted according to the Arbor Acres broiler management guide. The birds were reared in compliance with the Guidelines for Experimental Animals established by the Ministry of Science and Technology (Beijing, China). At 21 d of age, 96 broiler chicks of similar body weight (BW) were selected and allocated to thermoneutral control (TC) and high ambient temperature (HT) groups (6 cages of 8 birds per group), respectively, and raised in 2 controlled climate chambers. After 7 d of adaptation (21◦ C and 60%), from 28 to 42 d old, the broilers of the TC group remained under a constant 21 ± 1◦ C and 60 ± 10% RH, while those of the HT group were maintained under a constant high temperature of 31 ± 1◦ C, also at 60 ± 10% RH. At 42 d of age, 6 male broiler chicks were selected randomly from each group and euthanized by cervical dislocation. Immediately after sacrifice, the ileal contents (contents of the section between Meckel’s diverticulum and the ileocecal junction) of each bird were aseptically collected in sterile vials, frozen in liquid nitrogen, and stored at −80◦ C until using for the sequencing of microbial genes.
DNA Extraction, Amplification of 16S rRNA Gene, and Pyrosequencing Total bacteria genomic DNA was extracted from frozen ileum contents using the E.Z.N.A. Stool DNA Kits (Omega Bio-tek, Norcross, GA). The DNA integrity was assessed visually using 1.0% (w/v) agarose gel (containing ethidium bromide) electrophoresis. The microbial 16S rDNA was amplified with indices and adaptors-linked universal primers 341F (5 -ACTCCTACGGGAGGCAGCAG-3 ) and 806R (5 -GGACTACHVGGGTWTCTAAT-3 ) targeting the V3–4 region. PCR was performed using KAPA HiFi Hotstart PCR kit high-fidelity enzyme to ensure the accuracy and efficiency of amplification as a template of diluted genomic DNA. PCR products were detected using 2% agarose gel electrophoresis, and then recovered using AxyPrep DNA gel Recovery Kit (AXYGEN), and quantified by the Qubit 2.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA). Pyrosequencing was performed using Illumina HiSeq PE250 platform (Illumina, San Diego, CA) at the RealBio Technology Inc. (Shanghai, China).
Sequence Analysis and Phylogenetic Classification All the raw sequences obtained from Illumina HiSeq were firstly quality-filtered to remove tags with length of < 220 nt, average quality score of < 20, and tags containing >3 ambiguous bases by PANDAseq. After discarding the singletons, the high-quality tags were clustered into operational taxonomic units (OTU) using Usearch with a similarity threshold of 0.97, and the OTU were further subjected to the taxonomybased analysis using the Ribosomal Database Project (RDP) database. Alpha diversity (Simpson, Shannon, Chao1, PD-whole-tree index, Observed Species) and beta diversity were analyzed using QIIME (Paul and Josephine, 2004). Linear discriminant analysis (LDA) effect size (LEfSe) analyses were performed with the LEfSe tool (Segata et al., 2011). The relative abundance of bacteria was expressed as the percentage.
Statistical Analysis The differences of alpha diversity (Simpson, Shannon, Chao1, PD-whole-tree index, Observed Species) and mean relative abundance of bacteria between the 2 groups were analyzed by the Mann–Whitney test using SAS software (version 9.2; SAS Inst. Inc., Cary, NC). P < 0.05 was considered statistically significant. Principal coordinate analysis (PCoA) and analysis of similarity (ANOSIM) tests were conducted based on the weighted and unweighted Unifrac distance. ANOSIM tests the null hypothesis that microbial communities were significantly different between the 2 groups and provides a test statistic R, with values close to 1 meaning high dissimilarity between groups and high similarity within groups. LEfSe analysis uses the Mann–Whitney test to detect significantly different abundances and performs LDA scores to estimate the effect size (threshold ≥ 3).
RESULTS Evaluation of Pyrosequencing Data After assembling and quality filtering, a total of 432,280 sequences was obtained from 12 samples, with the number of sequences ranging from 33,168 to 38,763 per individual, and were clustered into 70 to 228 OTU per sample, resulting in a total of 382 OTU for all samples at a 97% sequence similarity value. The rarefaction curves (Figure 1) show that the rarefied sequencing depth (31,621) reveals most bacterial communities in all samples.
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Figure 1. Rarefaction curves of Chao1 indices (A) and Observed Species index (B) for each sample.
Table 1. Effects of high temperature on alpha-diversity of the broiler ileal microbiota.
HT group TC group P-value
goods Coverage
Pielou
Observed Species
PD whole-tree
Chao1
Shannon
Simpson
1.00 1.00 0.13
0.33 0.34 1.00
157.83 73.17 0.002
12.64 8.13 0.002
175.90 95.52 0.004
2.27 1.90 0.59
0.56 0.57 0.70
Variation in Alpha Diversity Alpha diversity is presented in Table 1. In comparison with the TC group, mean observed species (P = 0.004), whole-tree PD (P = 0.002), and Chao 1 (P = 0.002) were higher in the HT group. However, the Pielou (P = 1.00), Shannon (P = 0.59), and Simpson indices (P = 0.70) were not significantly different between the 2 groups.
Variation in Beta Diversity PCoA revealed that the HT group formed a distinct cluster clearly set apart from the TC group based on the unweighted UniFrac metric (Figure 2b), but there was no clear difference between the TC and HT groups on the basis of the weighted UniFrac metric (Figure 2a). The test statistic (R) of ANOSIM was 0.626 (P = 0.004; Figure 3b) on unweighted UniFrac and −0.017 (P = 0.55; Figure 3a) on weighted UniFrac, indicating that samples within groups were more similar to each other than to any samples from other groups (based on unweighted UniFrac).
(92.21%), and lower relative abundance of Proteobacteria (1.93%) and Bacteroidetes (2.58%; Figure 4A). The predominant orders in the ileal contents of the TC group were Clostridiales (72.67%), Lactobacillales (12.86%), Enterobacteriales (7.30%), and Bacterioidales (5.07%). The HT group samples showed a higher relative abundance of the Lactobacillales (25.04%) and lower relative abundance of the Clostridiales (66.90%), Enterobacteriales (1.56%), and Bacterioidales (2.55%; Figure 4B). However, none of these differences was statistically significant by the Mann–Whitney test.
Differentiating Taxa We employed LEfSe to identify the specific taxa in the ileal microbiome that were significantly associated with high temperature. LEfSe identified 9 discriminative features (genus level, linear discriminant analysis score > 3, Figure 5). The microbiota in the HT group was enriched with Clostridium XIVb, Streptophyta, Faecalibacterium, Rothia, Alistipes, Azospirillum, and Oscillibacter. Coprococcus and Streptococcus were enriched in the TC group compared with their levels in the HT group.
Comparison of Microbial Composition at the Phylum and Order Levels At the phylum level, most of the sequences from the ileal contents of TC group chickens were assigned to Firmicutes (85.64%), followed by Proteobacteria (7.39%) and Bacteroidetes (5.07%). The HT group samples showed higher relative abundance of Firmicutes
DISCUSSION Using denaturing gradient gel electrophoresis, Burkholder et al. (2008) found that the number of bands and the similarity coefficients were changed when broilers were exposed to high temperatures, which indicated that heat stress impacted the intestinal microbial
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Figure 2. Principal coordinate analysis (PCoA) of the community membership based on the weighted (A) and unweighted (B) UniFrac distance, with the distribution of the samples in the high temperature group (HT) and thermoneutral control group (TC), along the first principal coordinate axis shown alongside on the below, along the second principal coordinate axis shown alongside on the right (∗∗∗ P < 0.001, Mann–Whitney U).
Figure 3. Analysis of similarity (ANOSIM) of the community membership based on the weighted (A) and unweighted (B) UniFrac distance metric matrices. For similarity within high temperature group (HT), thermoneutral control group (TC), and all the samples.
community structure. The results in the present study also show that high temperature exerted a significant influence on the overall bacterial community structure of the gut microbiota in broilers. Specifically, the high temperature significantly increased all the species richness indices of the bacterial community (observed species, whole-tree PD, and Chao 1), but had no significant effects on the Shannon, Simpson, or Pielou index. Shannon and Simpson indices comprehensively reflect the species richness and the community evenness, and the Pielou index reflects the bacterial community evenness. So we speculated that the high temperature may increase the species richness, but has no significant effects on homogenization of the ileal microbiota of the broilers. Analysis of the beta diversity shows that the HT group formed a distinct cluster clearly set apart from the TC group based on the unweighted UniFrac metric, but did not when based on the weighted UniFrac (which calculates the relative abundance of microbiota). This result also supported the above hypothesis. The dominant phyla in the ilea of poultry are Firmicutes, Proteobacteria, Bacteroidetes, and
Actinobacteria (Bjerrum et al., 2006; Xiao et al., 2016), in accordance with the current findings. At the order level, the ileal contents are dominated by Clostridiales, Enterobacteriales, Lactobacillales, and Bacterioidales (Bjerrum et al., 2006; Xiao et al., 2016). The relative abundance of these dominant orders in our study was slightly different from the results of Bjerrum et al. (2006). The varying microbiota profiles across different trials may attributed to setting, location, and feed variations (Stanley et al., 2013). Using culture techniques, Song et al. (2014) demonstrated that heat stress reduced the viable counts of Lactobacillus and Bifidobacterium and increased the viable counts of coliforms and Clostridium in the small intestinal contents of broilers. Suzuki et al. (1983) found that the counts of Enterobacteriaceae reduced, while those of Streptococcus and Staphylococcus increased in the small intestine of heat-stressed chicks. The results of the current study show tendencies for Lactobacillales to be more abundant, and Enterobacteriales to be less so, in the ileal contents of chicks exposed to high temperatures. However, limited by the number of samples
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EFFECT OF HIGH TEMPERATURE ON MICROBIOME OF BROILER
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Figure 4. Relative abundance of major phylum (A) and order (B) in the lieal contents of individual broilers in the high temperature group (HT1-HT6) and thermoneutral control group (TC1-TC6).
Figure 5. Histogram of the LDA scores computed for genera differentially abundant between High temperature group (HT) and thermoneutral control group (TC) individuals. Genera enriched in heat-stressed individuals are indicated with a negative LDA score, and genera enriched in control group individuals have a positive score. The LDA score indicates the effect size and ranking of each differentially abundant taxon.
analyzed, none of these differences was statistically significant. The analysis of individual bird samples has demonstrated significant variation in microbiota structure within single treatment groups (Stanley et al., 2013), so a more robust sampling regimen is required to demonstrate the effects of high temperature on the predominant composition of the microbiota in broilers. We identified 9 taxa that discriminated the groups. Recent research has revealed that Clostridium XIVb was enriched in diarrheic patients (Ling et al., 2014). The members of Clostridium XIVb were previously
observed in poultry with ulcerative enteritis (Berkhoff, 1985). The decreased abundance of Coprococcus species has been associated with irritable bowel syndrome, including colonic hypersensitivity, bloating, and gastrointestinal (GI) discomfort in humans (Malinen et al., 2010). Lee et al. (2014) also found by using LEfSe that Coprococcus was significantly lower in patients with diarrhea. Heat stress has serious adverse impacts on intestinal morphology, integrity, and mucosal immunity in poultry (Burkholder et al., 2008; Song et al., 2014; Quinteiro-Filhoa et al., 2017). The variation in
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Clostridium and Coprococcus abundance observed in the present study may be associated with intestinal injury induced by high temperatures. Faecalibacterium is characterized by its anti-inflammatory activity within the gut, has been frequently reported to be decreased in GI inflammation, and is important in maintaining GI health (Minamoto et al., 2015; Suchodolski et al., 2015). However, significantly higher levels of the genus Faecalibacterium in heat-stressed broilers were observed in the present study, which cannot be used to explain the intestinal injury induced by high temperature. Further studies with larger samples are required to identify the taxa that are strongly correlated with intestinal injury induced by high temperature. Such differentially abundant bacteria maybe represent new stress markers and target populations that could potentially be modified in order to improve animal growth and health. In conclusion, the high temperature influenced the bacterial composition and community structure of the ileal microbiota of broilers, specifically by increasing the species richness.
ACKNOWLEDGMENTS This study was supported by the National Key Research and Development Program of China (2016YFD0500509). This research also was supported by the Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences (ASTIP-IAS07).
REFERENCES Aranda-Olmedo, I., and L. A. Rubio. 2016. Heterogeneous size datasets of broiler intestinal microbial communities can be analyzed without normalization. Poult. Sci. 00:1–7. Berkhoff, H. A. 1985. Clostridium-colinum sp-nov, nom rev, the causative agent of ulcerative enteritis (quail disease) in quail, chickens, and pheasants. Int. J. Syst. Bacteriol. 35:155–159. Bjerrum, L., R. Engberg, T. D. Leser, B. B. Jensen, K. Finster, and K. Pedersen. 2006. Microbial community composition of the ileum and cecum of broiler chickens as revealed by molecular and culture-based techniques. Poult. Sci. 85:1151–1164. Burkholder, K. M., K. L. Thompson, M. E. Einstein, T. J. Applegate, and J. A. Patterson. 2008. Influence of stressors on normal intestinal microbiota, intestinal morphology, and susceptibility to salmonella enteritidis colonization in broilers. Poult. Sci. 87:1734– 1741. Lee, J. R., T. Muthukumar, D. Dadhania, N. C. Toussaint, L. Ling, E. Pamer, and M. Suthanthiran. 2014. Gut microbial community structure and complications. following kidney transplantation: A pilot study. Transplantation. 98:697–705. Ling, Z. X., X. Liu, X. Y. Jia, Y. W. Cheng, Y. Q. Luo, L. Yuan, Y. Z. Wang, C. N. Zhao, S. Guo, L. J. Li, X. W. Xu,, and C. L. Xiang. 2014. Impacts of infection with different toxigenic Clostridium difficile strains on faecal microbiota in children. Sci. Rep. 4:7485.
Mack, L. A., J. N. Felver-Gant, R. L. Dennis, and H. W. Cheng. 2013. Genetic variation alter production and behavioral responses following heat stress in 2 strains of laying hens. Poult. Sci. 92:285– 294. Malinen, E., L. Krogius-Kurikka, A. Lyra, J. Nikkila, A. Jaaskelainen, T. Rinttila, T. Vilpponen-Salmela, A. J. V. Wright, and A. Palva. 2010. Association of symptoms with gastrointestinal microbiota in irritable bowel syndrome. World. J. Gastroenterol. 16:4532–4540. Minamoto, Y., C. C. Otoni, S. M. Steelman, O. Buyukleblebici, J. M. Steiner, A. E. Jergens, and J. S. Suchodolski. 2015. Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease. Gut. Microbes. 6: 33–47. Mohd Shaufi, M. A., C. C. Sieo, C. W. Chong, H. M. Gan, and Y. W. Ho. 2015. Deciphering chicken gut microbial dynamics based on high-throughput 16S rRNA metagenomics analyses. Gut Pathog. 7:4. Oakley, B. B., H. S. Lillehoj, M. H. Kogut, W. K. Kim, J. J. Maurer, A. Pedroso, M. D. Lee, S. R. Collett, T. J. Johnson, and N. A. Cox. 2014. The chicken gastrointestinal microbiome. FEMS Microbiol. Lett. 360:100–112. Paul, F. K., and Y. A. Josephine 2004. Bacterial diversity in aquatic and other environments: What 16S rDNA libraries can tell us. FEMS Microbiol. Ecol 47:161–177. Quinteiro-Filhoa, W. M., A. S. Calefia, D. S. G. Cruza, T. P. A. Aloiad, A. Zagera, C. S. Astolfi-Ferreirab, J. A. Piantino Ferreirab, S. Sharif, and J. Palermo-Netoa. 2017. Heat stress decreases expression of the cytokines, avian β -defensins 4 and 6 and Toll-like receptor 2 in broiler chickens infected with Salmonella Enteritidis. Veterinary Immunology and Immunopathology. 186:19–28. Segata, N., J. Izard, L. Waldron, D. Gevers, L. Miropolsky, W. S. Garrett, and C. Huttenhower. 2011. Metagenomic biomarker discovery and explanation. Genome Biol. 12:R60. Smith, M. O. 1993. Parts yield of broilers reared under cycling high temperatures. Poult. Sci. 72:1146–1150. Sohail, M. U., M. E. Hume, J. A. Byrd, D. J. Nisbet, A. Ljaz, A. Sohail, M. Z. Shabbir, and H. Rehman. 2012. Effect of supplementation of prebiotic mannan-oligosaccharides and probiotic mixture on growth performance of broilers subjected to chronic heat stress. Poult Sci 91:2235–2240. Song, J., K. Xiao, Y. L. Ke, L. F. Jiao, C. H. Hu, Q. Y. Diao, B. Shi, and X. T. Zou. 2014. Effect of a probiotic mixture on intestinal microflora, morphology, and barrier integrity of broilers subjected to heat stress. Poult. Sci. 93:581–588. Stanley, D., M. S. Geier, R. J. Hughes, S. E. Denman, and R. J. Moore. 2013. Highly variable microbiota development in the chicken gastrointestinal tract. PLoS. One. 8:e84290. Suchodolski, J. S., M. L. Foster, M. U. Sohail, C. Leutenegger, E. V. Queen, J. M. Steiner, and S. L. Marks. 2015. The fecal microbiome in cats with diarrhea. PLoS. One. 10:e0127378. Suzuki, K., R. Harasawa, Y. Yoshitake, and T. Matsuoka. 1983. Effects of crowding and heat stress on intestinal flora, body weight gain, and feed efficiency of growing rats and chicks. Nippon Juigaku Zasshi 45:331–338. Waite, D. W., and M. W. Taylor. 2014. Characterizing the avian gut microbiota: Membership, driving influences, and potential function. Front Microbiol. 5:223. Waite, D. W., and M. W. Taylor. 2015. Exploring the avian gut microbiota: Current trends and future directions. Front Microbiol. 6:673. Xiao, Y. P., Y. Xiang, W. D. Zhou, J. G. Chen, K. F. Li, and H. Yang. 2016. Microbial community mapping in intestinal tract of broiler chicken. Poult. Sci. 96:1387–1393.
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