Hostname: page-component-848d4c4894-tn8tq Total loading time: 0 Render date: 2024-06-26T18:38:17.912Z Has data issue: false hasContentIssue false

Comparison of the bacterial community structure within the equine hindgut and faeces using Automated Ribosomal Intergenic Spacer Analysis (ARISA)

Published online by Cambridge University Press:  30 July 2014

S. Sadet-Bourgeteau
Affiliation:
AgroSup Dijon, URANIE, USC1335 Nutrition du cheval athlète, 26 Bd Docteur Petitjean, F-21079 Dijon, France
C. Philippeau
Affiliation:
AgroSup Dijon, URANIE, USC1335 Nutrition du cheval athlète, 26 Bd Docteur Petitjean, F-21079 Dijon, France
S. Dequiedt
Affiliation:
INRA, UMR 1347 Agroécologie Plateforme GenoSol, 17 rue de Sully, 21065 Dijon, France
V. Julliand*
Affiliation:
AgroSup Dijon, URANIE, USC1335 Nutrition du cheval athlète, 26 Bd Docteur Petitjean, F-21079 Dijon, France
Get access

Abstract

The horse’s hindgut bacterial ecosystem has often been studied using faecal samples. However few studies compared both bacterial ecosystems and the validity of using faecal samples may be questionable. Hence, the present study aimed to compare the structure of the equine bacterial community in the hindgut (caecum, right ventral colon) and faeces using a fingerprint technique known as Automated Ribosomal Intergenic Spacer Analysis (ARISA). Two DNA extraction methods were also assessed. Intestinal contents and faeces were sampled 3 h after the morning meal on four adult fistulated horses fed meadow hay and pelleted concentrate. Irrespective of the intestinal segment, Principal Component Analysis of ARISA profiles showed a strong individual effect (P<0.0001). However, across the study, faecal bacterial community structure significantly (P<0.001) differed from those of the caecum and colon, while there was no difference between the two hindgut communities. The use of a QIAamp® DNA Stool Mini kit increased the quality of DNA extracted irrespective of sample type. The differences observed between faecal and hindgut bacterial communities challenge the use of faeces as a representative for hindgut activity. Further investigations are necessary to compare bacterial activity between the hindgut and faeces in order to understand the validity of using faecal samples.

Type
Research Article
Copyright
© The Animal Consortium 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Boom, R, Sol, CJ, Salimans, MM, Jansen, CL, Wertheim-van Dillen, PM and van der Noordaa, J 1990. Rapid and simple method for purification of nucleic acids. Journal of Clinical Microbiology 28, 495503.CrossRefGoogle ScholarPubMed
Brocard, D, Gillet, F and Legendre, P 2011. Numerical ecology with R.CrossRefGoogle Scholar
Camp, JG, Kanther, M, Semova, I and Rawls, JF 2009. Patterns and scales in gastrointestinal microbial ecology. Gastroenterology 136, 19892002.CrossRefGoogle ScholarPubMed
Daly, K, Stewart, CS, Flint, HJ and Shirazi-Beechey, SP 2001. Bacterial diversity within the equine large intestine as revealed by molecular analysis of cloned 16S rRNA genes. FEMS Microbiology Ecology 38, 141151.CrossRefGoogle Scholar
de Fombelle, A, Varloud, M, Goachet, A-G, Jacotot, E, Philippeau, C, Drogoul, C and Julliand, V 2003. Characterisation of the microbial and biochemical profile of the different segments of the digestive tract in horses fed two distinct diets. Animal Science 77, 293304.CrossRefGoogle Scholar
Dougal, K, Blackmore, TM, Pachebat, J, Harris, P and Newbold, CJ 2011. Comparison of bacterial populations from caecum, right dorsal colon and feces of horses’ using terminal restrition fragment length polymorphism (TRFLP). Journal of Equine Veterinary Science 31, 230356.CrossRefGoogle Scholar
Dougal, K, Harris, PA, Edwards, A, Pachebat, JA, Blackmore, TM, Worgan, HJ and Newbold, CJ 2012. A comparison of the microbiome and the metabolome of different regions of the equine hindgut. FEMS Microbiology Ecology 82, 642652.CrossRefGoogle ScholarPubMed
Drogoul, C, Poncet, C and Tisserand, JL 2000. Feeding ground and pelleted hay rather than chopped hay to ponies: 1. Consequences for in vivo digestibility and rate of passage of digesta. Animal Feed Science and Technology 87, 117130.CrossRefGoogle Scholar
Faubladier, C, Julliand, V, Veiga, L and Chaucheyras-Durand, F 2006. Comparison of colon and faeces microbial diversities in horses using molecular techniques. In Proceedings of the 5th Joint INRA-RRI Gastrointestinal Tract Microbiology Symposium, June 2006, Aberdeen, Scotland.Google Scholar
Foltan, P, Sheppard, S, Konvicka, M and Symondson, WOC 2005. The significance of facultative scavenging in generalist predator nutrition: detecting decayed prey in the guts of predators using PCR. Molecular Ecology 14, 41474158.CrossRefGoogle ScholarPubMed
Grønvold, A-MR, L'Abée-Lund, TM, Strand, E, Sørum, H, Yannarell, AC and Mackie, RI 2010. Fecal microbiota of horses in the clinical setting: potential effects of penicillin and general anesthesia. Veterinary Microbiology 145, 366372.CrossRefGoogle ScholarPubMed
Hastie, PM, Mitchell, K and Murray, JMD 2008. Semi-quantitative analysis of Ruminococcus flavefaciens, Fibrobacter succinogenes and Streptococcus bovis in the equine large intestine using real-time polymerase chain reaction. British Journal of Nutrition 100, 561568.CrossRefGoogle ScholarPubMed
Kobayashi, Y, Koike, S, Miyaji, M, Hata, H and Tanaka, K 2006. Hindgut microbes, fermentation and their seasonal variations in Hokkaido native horses compared to light horses. Ecological Research 21, 285291.CrossRefGoogle Scholar
Kovacs, A, Yacoby, K and Gophna, U 2010. A systematic assessment of Automated Ribosomal Intergenic Spacer Analysis (ARISA) as a tool for estimating bacterial richness. Research in Microbiology 161, 192197.CrossRefGoogle ScholarPubMed
Martin-Rosset, W, Andrieu, J, Vermorel, M and Jestin, M 2006. Routine methods for predicting the net energy and protein values of concentrates for horses in the UFC and MADC systems. Livestock Science 100, 5369.CrossRefGoogle Scholar
Martin-Rosset, W, Vermorel, M, Doreau, M, Tisserand, JL and Andrieu, J 1994. The french horse feed evaluation systems and recommended allowances for energy and protein. Livestock Production Science 40, 3756.CrossRefGoogle Scholar
McOrist, AL, Jackson, M and Bird, AR 2002. A comparison of five methods for extraction of bacterial DNA from human faecal samples. Journal of Microbiological Methods 50, 131139.CrossRefGoogle ScholarPubMed
Müller, CE, von Rosen, D and Udén, P 2008. Effect of forage conservation method on microbial flora and fermentation pattern in forage and in equine colon and faeces. Livestock Science 119, 116128.CrossRefGoogle Scholar
Nechvatal, JM, Ram, JL, Basson, MD, Namprachan, P, Niec, SR, Badsha, KZ, Matherly, LH, Majumdar, APN and Kato, I 2008. Fecal collection, ambient preservation, and DNA extraction for PCR amplification of bacterial and human markers from human feces. Journal of Microbiological Methods 72, 124132.CrossRefGoogle ScholarPubMed
Ranjard, L, Poly, F, Lata, J-C, Mougel, C, Thioulouse, J and Nazaret, S 2001. Characterization of bacterial and fungal soil communities by Automated Ribosomal Intergenic Spacer Analysis fingerprints: biological and methodological variability. Applied and Environmental Microbiology 67, 44794487.CrossRefGoogle ScholarPubMed
Ranjard, L, Lejon, DPH, Mougel, C, Schehrer, L, Merdinoglu, D and Chaussod, R 2003. Sampling strategy in molecular microbial ecology: influence of soil sample size on DNA fingerprinting analysis of fungal and bacterial communities. Environmental Microbiology 5, 11111120.CrossRefGoogle ScholarPubMed
Sadet-Bourgeteau, S, Chaucheyras-Durand, F, Forano, E and Julliand, V 2011. Evolution of the equine gut bacterial community according to dietary changes and live yeast supplementation as assessed by Automated Ribosomal Intergenic Spacer Analysis (ARISA). Proceedings of Conference on Gastrointestinal Function, April 2011, Chicago, USA.Google Scholar
Salonen, A, Nikkilä, J, Jalanka-Tuovinen, J, Immonen, O, Rajilic-Stojanovic, M, Kekkonen, RA, Palva, A and de Vos, WM 2010. Comparative analysis of fecal DNA extraction methods with phylogenetic microarray: effective recovery of bacterial and archaeal DNA using mechanical cell lysis. Journal of Microbiological Methods 81, 127134.CrossRefGoogle ScholarPubMed
Schoster, A, Arroyo, L, Staempfli, H and Weese, J 2013. Comparison of microbial populations in the small intestine, large intestine and feces of healthy horses using terminal restriction fragment length polymorphism. BMC Research Notes 6, 91.CrossRefGoogle ScholarPubMed
Thioulouse, J and Dray, S 2007. Interactive multivariate data analysisin R with the ade4 and ade4TkGUI packages. Journal of Statistical Software 22, 114.CrossRefGoogle Scholar
Vörös, A 2008. Diet related changes in the gastrointestinal microbiota of horses. Master Thesis, Swedish University of Agricultural Sciences, Uppsala, Sweden.Google Scholar
Willing, B, Vörös, A, Roos, S, Jones, C, Jansson, A and Lindberg, JE 2009. Changes in faecal bacteria associated with concentrate and forage-only diets fed to horses in training. Equine Veterinary Journal 41, 908914.CrossRefGoogle ScholarPubMed
Yamano, H, Koike, S, Kobayashi, Y and Hata, H 2008. Phylogenetic analysis of hindgut microbiota in Hokkaido native horses compared to light horses. Animal Science Journal 79, 234242.CrossRefGoogle Scholar
Yu, Z and Morrison, M 2004. Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques 36, 808812.CrossRefGoogle ScholarPubMed