• 1.

    Pedersen S, Cribb A, Windeyer M, Read EK, French D, Banse HE. Risk factors for equine glandular and squamous gastric disease in show jumping Warmbloods. Equine Vet J. 2018:747751.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Begg LM, O’Sullivan CB. The prevalence and distribution of gastric ulceration in 345 racehorses. Aust Vet J. 2003;81:199201.

  • 3.

    Banse HE, MacLeod H, Crosby C, Windeyer MC. Prevalence of and risk factors for equine glandular and squamous gastric disease in polo horses. Can Vet J. 2018;59:880884.

    • Search Google Scholar
    • Export Citation
  • 4.

    Tamzali Y, Marguet C, Priymenko N, et al. Prevalence of gastric ulcer syndrome in high-level endurance horses. Equine Vet J. 2011;43:141144.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Monki J, Hewetson M, Virtala A-MK. Risk factors for equine gastric glandular disease: a case control study in a Finnish referral hospital population. J Vet Intern Med. 2016;30:12701275.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Sykes BW, Bowen M, Habershon-Butcher JL, Green M, Hallowell GD. Management factors and clinical implications of glandular and squamous gastric disease in horses. J Vet Intern Med. 2019;33:233240.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Lanas A, Chan FKL. Peptic ulcer disease. Lancet. 2017;390:613624.

  • 8.

    Dong HJ, Ho H, Hwang H, et al. Diversity of the gastric microbiota in Thoroughbred racehorses having gastric ulcer. J Microbiol Biotechnol. 2016;26:763774.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Perkins GA, den Bakker HC, Burton AJ, et al. Equine stomachs harbor an abundant and diverse mucosal microbiota. Appl Environ Microbiol. 2012;78:25222532.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Murray MJ, Schusser GF, Pipers FS, Gross SJ. Factors associated with gastric lesions in Thoroughbred racehorses. Equine Vet J. 1996;28:7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11.

    Li XX, Wong GL, To KF, et al. Bacterial microbiota profiling in gastritis without Helicobacter pylori infection or non-steroidal anti-inflammatory drug use. PLoS One. 2009;4:e7985.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Sung JJY, Coker OO, Chu E, et al. Gastric microbes associated with gastric inflammation, atrophy and intestinal metaplasia 1 year after Helicobacter pylori eradication. Gut. 2020;69:15721580.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Waterman JJ, Kapur R. Upper gastrointestinal issues in athletes. Curr Sports Med Rep. 2012;11:99104.

  • 14.

    Erdman KA, Jones KW, Madden RF, Gammack N, Parnell JA. Dietary patterns in runners with gastrointestinal disorders. Nutrients. 2021;448.

    • Search Google Scholar
    • Export Citation
  • 15.

    Rajilic-Stojanovic M, Figueiredo C, Smet A, et al. Systematic review: gastric microbiota in health and disease. Aliment Pharmacol Ther. 2020;51:582602.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Smith KA, Pugh JN, Duca FA, Close GL, Ormsbee MJ. Gastrointestinal pathophysiology during endurance exercise: endocrine, microbiome, and nutritional influences. Eur J Appl Physiol. 2021;121:26572674.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Clarke SF, Murphy EF, O’Sullivan O, et al. Exercise and associated dietary extremes impact on gut microbial diversity. Gut. 2014;63:19131920.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Jang LG, Choi G, Kim SW, Kim BY, Lee S, Park H. The combination of sport and sport-specific diet is associated with characteristics of gut microbiota: an observational study. J Int Soc Sports Nutr. 2019;16:21.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Paul LJ, Ericsson AC, Andrews FM, et al. Gastric microbiome in horses with and without equine glandular gastric disease. J Vet Intern Med. 2021;35:24582464.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Ericsson AC, Johnson PJ, Lopes MA, Perry SC, Lanter HR. A microbiological map of the healthy equine gastrointestinal tract. PloS One. 2016;11:e0166523.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Stewart HL, Pitta D, Indugu N, et al. Changes in the faecal bacterial microbiota during hospitalisation of horses with colic and the effect of different causes of colic. Equine Vet J. 2021;53:11191131.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Willette JA, Pitta D, Indugu N, et al. Experimental crossover study on the effects of withholding feed for 24 h on the equine faecal bacterial microbiota in healthy mares. BMC Vet Res. 2021;17:3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Sykes B, Jokisalo J. Rethinking equine gastric ulcer syndrome: Part 1–terminology, clinical signs and diagnosis. Equine Vet Educ. 2014;26:543547.

  • 24.

    Ericsson AC, Davis JW, Spollen W, et al. Effects of vendor and genetic background on the composition of the fecal microbiota of inbred mice. PloS One. 2015;10:e0116704.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal. 2011;17:1012.

  • 26.

    Bolyen E, Rideout JR, Dillon MR, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852857.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581583.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Pruesse E, Quast C, Knittel K, et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007;35:71887196.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Hammer Ø, Harper DAT, Ryan PD. PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron. 2001;4:9.

    • Search Google Scholar
    • Export Citation
  • 30.

    Costa MC, Silva G, Ramos RV, et al. Characterization and comparison of the bacterial microbiota in different gastrointestinal tract compartments in horses. Vet J. 2015;205:7480.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Reitano E, de’Angelis N, Gavriilidis P, et al. Oral bacterial microbiota in digestive cancer patients: a systematic review. Microorganisms. 2021;9:2585.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Louis S, Tappu RM, Damms-Machado A, Huson DH, Bischoff SC. Characterization of the gut microbial community of obese patients following a weight-loss intervention using whole metagenome shotgun sequencing. PLoS One. 2016;11:e0149564.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Dong TS, Jacobs JP, Agopian V, et al. Duodenal microbiome and serum metabolites predict hepatocellular carcinoma in a multicenter cohort of patients with cirrhosis. Digest Dis Sci. 2021;67:852857.

    • Search Google Scholar
    • Export Citation
  • 34.

    Guilloux CA, Lamoureux C, Beauruelle C, Héry-Arnaud G. Porphyromonas: a neglected potential key genus in human microbiomes. Anaerobe. 2021;68:102230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35.

    Bressa C, Bailen-Andrino M, Perez-Santiago J, et al. Differences in gut microbiota profile between women with active lifestyle and sedentary women. PLoS One. 2017;12:e0171352.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36.

    Sato M, Suzuki Y. Alterations in intestinal microbiota in ultramarathon runners. Sci Rep. 2022;12:6984.

  • 37.

    Mohr AE, Jager R, Carpenter KC, et al. The athletic gut microbiota. J Int Soc Sports Nutr. 2020;17:24.

Advertisement

Dietary and management factors influence the equine gastric microbiome

Linda J. PaulLouisiana State University, Veterinary Clinical Sciences, Equine Health Studies Program, Baton Rouge, LA

Search for other papers by Linda J. Paul in
Current site
Google Scholar
PubMed
Close
 DVM, DACVIM
,
Aaron C. EricssonUniversity of Missouri, Metagenomics Center, Equine Gut Group, Columbia, MO

Search for other papers by Aaron C. Ericsson in
Current site
Google Scholar
PubMed
Close
 DVM, PhD
,
Frank M. AndrewsLouisiana State University, Veterinary Clinical Sciences, Equine Health Studies Program, Baton Rouge, LA

Search for other papers by Frank M. Andrews in
Current site
Google Scholar
PubMed
Close
 MS, DVM, DACVIM
,
Zachary McAdamsUniversity of Missouri, Metagenomics Center, Equine Gut Group, Columbia, MO

Search for other papers by Zachary McAdams in
Current site
Google Scholar
PubMed
Close
 BS
,
Michael L. KeowenLouisiana State University, Veterinary Clinical Sciences, Equine Health Studies Program, Baton Rouge, LA

Search for other papers by Michael L. Keowen in
Current site
Google Scholar
PubMed
Close
 BS
,
Michael P. St BlancLouisiana State University, Veterinary Clinical Sciences, Equine Health Studies Program, Baton Rouge, LA

Search for other papers by Michael P. St Blanc in
Current site
Google Scholar
PubMed
Close
 DVM
, and
Heidi E. BanseLouisiana State University, Veterinary Clinical Sciences, Equine Health Studies Program, Baton Rouge, LA

Search for other papers by Heidi E. Banse in
Current site
Google Scholar
PubMed
Close
 DVM, DACVIM, PhD

Abstract

OBJECTIVE

The purpose of this study was to characterize the relationship of diet and management factors with the glandular gastric mucosal microbiome. We hypothesize that the gastric mucosal microbial community is influenced by diet and management factors. Our specific objective is to characterize the gastric mucosal microbiome in relation to these factors.

ANIMALS

57 client-owned horses in the southern Louisiana region with and without equine glandular gastric disease.

PROCEDURES

Diet and management data were collected via a questionnaire. Gastroscopy was used for evaluation of equine gastric ulcer syndrome and collection of glandular mucosal pinch biopsies. 16S rRNA amplicon sequencing was used for microbiome analysis. Similarity and diversity indices and sequence read counts of individual taxa were compared between diet and management factors.

RESULTS

Differences were detected in association with offering hay, type of hay, sweet feed, turnout, and stalling. Offering hay and stalling showed differences in similarity indices, whereas hay type, sweet feed, and turnout showed differences in similarity and diversity indices. Offering hay, hay type, and sweet feed were also associated with differences in individual sequence read counts.

CLINICAL RELEVANCE

This study provides preliminary characterization of the complex relationship between the glandular gastric microbiome and diet/management factors. The ideal microbiome to promote a healthy glandular gastric environment remains unknown.

Abstract

OBJECTIVE

The purpose of this study was to characterize the relationship of diet and management factors with the glandular gastric mucosal microbiome. We hypothesize that the gastric mucosal microbial community is influenced by diet and management factors. Our specific objective is to characterize the gastric mucosal microbiome in relation to these factors.

ANIMALS

57 client-owned horses in the southern Louisiana region with and without equine glandular gastric disease.

PROCEDURES

Diet and management data were collected via a questionnaire. Gastroscopy was used for evaluation of equine gastric ulcer syndrome and collection of glandular mucosal pinch biopsies. 16S rRNA amplicon sequencing was used for microbiome analysis. Similarity and diversity indices and sequence read counts of individual taxa were compared between diet and management factors.

RESULTS

Differences were detected in association with offering hay, type of hay, sweet feed, turnout, and stalling. Offering hay and stalling showed differences in similarity indices, whereas hay type, sweet feed, and turnout showed differences in similarity and diversity indices. Offering hay, hay type, and sweet feed were also associated with differences in individual sequence read counts.

CLINICAL RELEVANCE

This study provides preliminary characterization of the complex relationship between the glandular gastric microbiome and diet/management factors. The ideal microbiome to promote a healthy glandular gastric environment remains unknown.

Supplementary Materials

    • Supplementary Table S1 (PDF 122 KB)

Contributor Notes

Corresponding author: Dr. Paul (lindapaul@lsu.edu)