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Colonic microbiome profiles for improved feed efficiency can be identified despite major effects of farm of origin and contemporary group in pigs

Published online by Cambridge University Press:  01 July 2020

S. Vigors Open the ORCID record for S. Vigors [Opens in a new window] ,
J. V. O’ Doherty Open the ORCID record for J. V. O’ Doherty [Opens in a new window]  and
T. Sweeney Open the ORCID record for T. Sweeney [Opens in a new window]
S. Vigors
Affiliation:
School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
J. V. O’ Doherty
Affiliation:
School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
T. Sweeney*
Affiliation:
School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland
*
†E-mail: [email protected]
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Abstract

While feed efficiency (FE) is a trait of great economic importance to the pig industry, the influence of the intestinal microbiome in determining FE is not well understood. The objective of this experiment was to determine the relative influence of FE and farm of birth on the pig colonic microbiome. Animals divergent in residual feed intake (RFI) were sourced from two geographically distinct locations (farms A + B) in Ireland. The 8 most efficient (low RFI (LRFI)) and 8 least efficient (high RFI, (HRFI)) pigs from farm A and 12 LRFI and 12 HRFI pigs from farm B were sacrificed. Colonic digesta was collected for microbial analysis using 16S ribosomal RNA gene sequencing and also for volatile fatty acid analysis. The α-diversity differed between the farms in this study, with pigs from farm A having greater diversity based on Shannon and InvSimpson measures compared to pigs from farm B (P < 0.05), with no difference identified in either Chao1 or observed measures of diversity (P > 0.05). In the analysis of β-diversity, pigs clustered based on farm of birth rather than RFI. Variation in the management of piglets, weight of the piglets, season of the year, sanitary status and dam dietary influence could potentially be causative factors in this large variation between farms. However, despite significant variation in the microbial profile between farms, consistent taxonomic differences were identified between RFI groups. Within the phylum Bacteroidetes, the LRFI pigs had increased abundance of BS11 (P < 0.05) and a tendency toward increased Bacteroidaceae (P < 0.10) relative to the HRFI group. At genus level, the LRFI pigs had increased abundance of Colinsella (P < 0.05), a tendency toward increased Bacteroides and CF231 (P < 0.10). At species level, Ruminococcus flavefaciens had increased abundance in the LRFI compared to the HRFI animals. In conclusion, while farm of birth has a substantial influence on microbial diversity in the pig colon, a microbial signature indicative of FE status was apparent.

Keywords

residual feed intakeswinecolonic microbiotafarm16S rRNA sequencing
Type
Research Article
Information
animal , Volume 14 , Issue 12 , December 2020 , pp. 2472 - 2480
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Animal Consortium

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References

Canny, GO and McCormick, BA 2008. Bacteria in the intestine, helpful residents or enemies from within? Infection and Immunity 76, 3360–3373.CrossRefGoogle ScholarPubMed
Caporaso, JG, Kuczynski, J, Stombaugh, J, Bittinger, K, Bushman, FD, Costello, EK, Fierer, N, Peña, AG, Goodrich, JK, Gordon, JI, Huttley, GA, Kelley, ST, Knights, D, Koenig, JE, Ley, RE, Lozupone, CA, McDonald, D, Muegge, BD, Pirrung, M, Reeder, J, Sevinsky, JR, Turnbaugh, PJ, Walters, WA, Widmann, J, Yatsunenko, T, Zaneveld, J and Knight, R 2010. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336.CrossRefGoogle ScholarPubMed
Clarke, LC, Sweeney, T, Curley, E, Duffy, SK, Rajauria, G and O’Doherty, JV 2018. The variation in chemical composition of barley feed with or without enzyme supplementation influences nutrient digestibility and subsequently affects performance in piglets. Journal of Animal Physiology and Animal Nutrition 102, 799–809.CrossRefGoogle ScholarPubMed
DeSantis, TZ, Hugenholtz, P, Larsen, N, Rojas, M, Brodie, EL, Keller, K, Huber, T, Dalevi, D, Hu, P and Andersen, GL 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology 72, 5069–5072.CrossRefGoogle ScholarPubMed
Dunkelberger, JR, Boddicker, NJ, Serão, NVL, Young, JM, Rowland, RRR and Dekkers, JCM 2015. Response of pigs divergently selected for residual feed intake to experimental infection with the PRRS virus. Livestock Science 177, 132–141.CrossRefGoogle Scholar
Haas, BJ, Gevers, D, Earl, AM, Feldgarden, M, Ward, DV, Giannoukos, G, Ciulla, D, Tabbaa, D, Highlander, SK, Sodergren, E, Methe, B, DeSantis, TZ, Petrosino, JF, Knight, R and Birren, BW 2011. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Research 21, 494–504.CrossRefGoogle ScholarPubMed
Hamady, M, Lozupone, C and Knight, R 2010. Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. The ISME Journal 4, 17–27.CrossRefGoogle ScholarPubMed
Han, GG, Lee, J-Y, Jin, G-D, Park, J, Choi, YH, Kang, S-K, Chae, BJ, Kim, EB and Choi, Y-J 2018. Tracing of the fecal microbiota of commercial pigs at five growth stages from birth to shipment. Scientific Reports 8, 6012.CrossRefGoogle ScholarPubMed
Kil, DY, Kim, BG and Stein, HH 2013. Feed energy evaluation for growing pigs. Asian-Australasian Journal of Animal Sciences 26, 1205–1217.CrossRefGoogle ScholarPubMed
Kubasova, T, Davidova-Gerzova, L, Babak, V, Cejkova, D, Montagne, L, Le-Floc’h, N and Rychlik, I 2018. Effects of host genetics and environmental conditions on fecal microbiota composition of pigs. PLoS ONE 13, e0201901.CrossRefGoogle ScholarPubMed
Langille, MG, Zaneveld, J, Caporaso, JG, McDonald, D, Knights, D, Reyes, JA, Clemente, JC, Burkepile, DE, Thurber, RLV and Knight, R 2013. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology 31, 814.CrossRefGoogle ScholarPubMed
Looft, T, Allen, HK, Cantarel, BL, Levine, UY, Bayles, DO, Alt, DP, Henrissat, B and Stanton, TB 2014. Bacteria, phages and pigs: the effects of in-feed antibiotics on the microbiome at different gut locations. The ISME Journal 8, 1566–1576.CrossRefGoogle ScholarPubMed
Love, MI, Huber, W and Anders, S 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15, 550.CrossRefGoogle ScholarPubMed
Malinen, E, Krogius-Kurikka, L, Lyra, A, Nikkilä, J, Jääskeläinen, A, Rinttilä, T, Vilpponen-Salmela, T, von Wright, AJ and Palva, A 2010. Association of symptoms with gastrointestinal microbiota in irritable bowel syndrome. World Journal of Gastroenterology 16, 4532–4540.CrossRefGoogle ScholarPubMed
Mani, V, Harris, AJ, Keating, AF, Weber, TE, Dekkers, JCM and Gabler, NK 2013. Intestinal integrity, endotoxin transport and detoxification in pigs divergently selected for residual feed intake. Journal of Animal Science 91, 2141–2150.CrossRefGoogle ScholarPubMed
McCormack, UM, Curião, T, Buzoianu, SG, Prieto, ML, Ryan, T, Varley, P, Crispie, F, Magowan, E, Metzler-Zebeli, BU, Berry, D, O’Sullivan, O, Cotter, PD, Gardiner, GE and Lawlor, PG 2017. Exploring a possible link between the intestinal microbiota and feed efficiency in pigs. Applied and Environmental Microbiology 83, e00380–e00317.CrossRefGoogle ScholarPubMed
McMurdie, PJ and Holmes, S 2013. Phyloseq: an R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 8, e61217.CrossRefGoogle Scholar
Noblet, J, Karege, C, Dubois, S and van Milgen, J 1999. Metabolic utilization of energy and maintenance requirements in growing pigs: effects of sex and genotype. Journal of Animal Science 77, 1208–1216.CrossRefGoogle ScholarPubMed
Pajarillo, EAB, Chae, J-P, Balolong, MP, Kim, HB and Kang, D-K 2014. Assessment of fecal bacterial diversity among healthy piglets during the weaning transition. Journal of General and Applied Microbiology 60, 140–146.CrossRefGoogle Scholar
Rainey, FA 2015. Ruminococcaceae fam. nov. https://doi.org/10.1002/9781118960608.fbm00136.CrossRefGoogle Scholar
Rakhshandeh, A, Dekkers, JC, Kerr, BJ, Weber, TE, English, J and Gabler, NK 2012. Effect of immune system stimulation and divergent selection for residual feed intake on digestive capacity of the small intestine in growing pigs. Journal of Animal Science 90 (suppl. 4), 233–235.CrossRefGoogle ScholarPubMed
Rideout, JR, He, Y, Navas-Molina, JA, Walters, WA, Ursell, LK, Gibbons, SM, Chase, J, McDonald, D, Gonzalez, A, Robbins-Pianka, A, Clemente, JC, Gilbert, JA, Huse, SM, Zhou, H-W, Knight, R and Caporaso, JG 2014. Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences. PeerJ 2, e545.CrossRefGoogle ScholarPubMed
Roehe, R, Dewhurst, RJ, Duthie, C-A, Rooke, JA, McKain, N, Ross, DW, Hyslop, JJ, Waterhouse, A, Freeman, TC, Watson, M and Wallace, RJ 2016. Bovine host genetic variation influences rumen microbial methane production with best selection criterion for low methane emitting and efficiently feed converting hosts based on metagenomic gene abundance. PLOS Genetics 12, e1005846.CrossRefGoogle ScholarPubMed
Salyers, AA, Vercellotti, JR, West, SE and Wilkins, TD 1977. Fermentation of mucin and plant polysaccharides by strains of Bacteroides from the human colon. Applied and Environmental Microbiology 33, 319–322.CrossRefGoogle ScholarPubMed
Siegerstetter, SC, Schmitz-Esser, S, Magowan, E, Wetzels, SU, Zebeli, Q, Lawlor, PG, O’Connell, NE and Metzler-Zebeli, BU 2017. Intestinal microbiota profiles associated with low and high residual feed intake in chickens across two geographical locations. PLoS ONE 12, e0187766.CrossRefGoogle ScholarPubMed
Solden, LM, Hoyt, DW, Collins, WB, Plank, JE, Daly, RA, Hildebrand, E, Beavers, TJ, Wolfe, R, Nicora, CD, Purvine, SO, Carstensen, M, Lipton, MS, Spalinger, DE, Firkins, JL, Wolfe, BA and Wrighton, KC 2017. New roles in hemicellulosic sugar fermentation for the uncultivated Bacteroidetes family BS11. The ISME Journal 11, 691–703.CrossRefGoogle ScholarPubMed
Varel, VH, Fryda, SJ and Robinson, IM 1984. Cellulolytic bacteria from pig large intestine. Applied and Environmental Microbiology 47, 219–221.CrossRefGoogle ScholarPubMed
Varley, PF, Flynn, B, Callan, JJ and O’Doherty, JV 2011. Effect of phytase level in a low phosphorus diet on performance and bone development in weaner pigs and the subsequent effect on finisher pig bone development. Livestock Science 138, 152–158.CrossRefGoogle Scholar
Vigors, S, O’Doherty, JV, Bryan, K and Sweeney, T 2019. A comparative analysis of the transcriptome profiles of liver and muscle tissue in pigs divergent for feed efficiency. BMC Genomics 20, 461.CrossRefGoogle ScholarPubMed
Vigors, S, Sweeney, T, O’Shea, CJ, Kelly, AK and O’Doherty, JV 2016. Pigs that are divergent in feed efficiency, differ in intestinal enzyme and nutrient transporter gene expression, nutrient digestibility and microbial activity. Animal 10, 1848–1855.CrossRefGoogle ScholarPubMed
Walker, AW, Ince, J, Duncan, SH, Webster, LM, Holtrop, G, Ze, X, Brown, D, Stares, MD, Scott, P, Bergerat, A, Louis, P, McIntosh, F, Johnstone, AM, Lobley, GE, Parkhill, J and Flint, HJ 2010. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. The ISME Journal 5, 220.CrossRefGoogle ScholarPubMed
Wexler, AG and Goodman, AL 2017. An insider’s perspective: bacteroides as a window into the microbiome. Nature Microbiology 2, 17026–17026.CrossRefGoogle ScholarPubMed
Wickham, H 2009. ggplot2: elegant graphics for data analysis. (ed. Gentleman, R, Hornik, K and Parmigiani, G), pp. 1–211, Springer Publishing Company, Incorporated, New York, NY, USA.Google Scholar
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