Williams CA, Kenny LB, Weinert JR, Sullivan K, Meyer W, Robson MG. Effects of 27 mo of rotational vs. continuous grazing on horse and pasture condition. Transl Anim Sci. 2020. https://doi.org/10.1093/tas/txaa084.
Article
PubMed
PubMed Central
Google Scholar
Taiz L, Zeiger E. Photosynthesis: carbon reactions. In: Taiz L, Zeiger E, editors. Plant physiology. 3rd ed. Sunderland: Sinauer Associates, Inc; 2002. p. 111–43.
Google Scholar
Moore KJ, White TA, Hintz RL, Patrick PK, Brummer EC. Sequential grazing of cool-and warm-season pastures. Agron J. 2004;96(4):1103–11. https://doi.org/10.2134/agronj1991.00021962008300060027x.
Article
Google Scholar
Tracy BF, Maughan M, Post N, Faulkner DB. Integrating annual and perennial warm-season grasses in a temperate grazing system. Crop Sci. 2010;50(5):2171–7. https://doi.org/10.2135/cropsci2010.02.0110.
Article
Google Scholar
DeBoer ML, Sheaffer CC, Grev AM, Catalano DN, Wells MS, Hathaway MR, Martinson KL. Yield, nutritive value, and preference of annual warm-season grasses grazed by horses. Agron J. 2017;109(5):2136–48. https://doi.org/10.2134/agronj2017.02.0099.
Article
CAS
Google Scholar
Ritz KE, Heins BJ, Moon R, Sheaffer C, Weyers SL. Forage yield and nutritive value of cool-season and warm-season forages for grazing organic dairy cattle. Agronomy. 2020;10(12):1963. https://doi.org/10.3390/agronomy10121963.
Article
CAS
Google Scholar
Weinert-Nelson JR, Meyer WA, Williams CA. Yield, nutritive value, and horse condition in integrated crabgrass and cool-season grass rotational grazing pasture systems. Transl Anim Sci. 2021. https://doi.org/10.1093/tas/txab208 (in press).
Article
PubMed
PubMed Central
Google Scholar
Teutsch C. Warm-season annual grasses for summer forage. Publication 418-004. Communication and marketing, College of Agriculture and Life Sciences, Virginia Polytechnic Inst. and State Univ.: Blacksburg; 2006.
Teff KS (Eragrostis teff (Zucc.)). Trotter. Promoting the Conservation and use of the under utilized crops. In: vol. 12. Institute of Plant Genetics and Crop Plant Research, Garersleben/International Plant Genetic Resource Institute. Rome, Italy; 1997.
Taliaferro CM. Breeding forage bermudagrass for the US Transition zone. In: Proceedings 59th southern pasture and forage crop improvement conference, Philadelphia, MS; 2005. p. 11–13.
Ditsch DC, Smith SR, Lacefield GD. Bermudagrass: a summer forage in Kentucky. Publication #AGR-48. University of Kentucky College of Agriculture, Lexington, KY; 2011.
Goodson J, Tyznik WJ, Cline JH, Dehority BA. Effects of an abrupt diet change from hay to concentrate on microbial numbers and physical environment in the cecum of the pony. Appl Environ Microbiol. 1988;54:1946–50. https://doi.org/10.1128/aem.54.8.1946-1950.1988.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hudson JM, Cohen ND, Gibbs PG, Thompson JA. Feeding practices associated with colic in horses. J Am Vet Med Assoc. 2001;219(10):1419–25. https://doi.org/10.2460/javma.2001.219.1419.
Article
CAS
PubMed
Google Scholar
Garner HE, Moore JN, Johnson JH, ClarkL AJF, Tritschler LG, Coffmann JR, Sprouse RF, Hutcheson DP, Salem CA. Changes in the caecal flora associated with the onset of laminitis. Equine Vet J. 1978;10:249–52. https://doi.org/10.1111/j.2042-3306.1978.tb02273.x.
Article
CAS
PubMed
Google Scholar
Millinovich GJ, Burrell PC, Pollitt CC, Klieve AV, Blackall LL, Ouwerkerk D, Woodland E, Trott DJ. Microbial ecology of the equine hindgut during oliofructose-induced laminitis. ISME J. 2008;2:1089–100. https://doi.org/10.1038/ismej.2008.67.
Article
CAS
Google Scholar
Tuniyazi M, He J, Guo J, Li S, Zhang N, Hu X, Fu Y. Changes of microbial and metabolome of the equine hindgut during oligofructose-induced laminitis. BMC Vet Res. 2021;17(1):1–13. https://doi.org/10.1186/s12917-020-02686-9.
Article
CAS
Google Scholar
Cohen ND, Matejka PL, Honnas CM, Hooper RN. Case-control study of the association between various management factors and development of colic in horses. Texas equine colic study group. J Am Vet Med Assoc. 1995;206(5):667–73.
CAS
PubMed
Google Scholar
Tinker MK, White NA, Lessard P, Thatcher CD, Pelzer KD, Davis B, Carmel DK. Prospective study of equine colic risk factors. Equine Vet J. 1997;29(6):454–8. https://doi.org/10.1111/j.2042-3306.1997.tb03158.x.
Article
CAS
PubMed
Google Scholar
Venable E, Kerley MS, Raub R. Assessment of equine fecal microbial profiles during and after a colic episode using pyrosequencing. J Equine Vet Sci. 2013;33:347. https://doi.org/10.1016/j.jevs.2013.03.066.
Article
Google Scholar
Weese JS, Holcombe SJ, Embertson RM, Kurtz KA, Roessner HA, Jalali M, Wismer SE. Changes in the faecal microbiota ofmares precede the development of post partum colic. Equine Vet J. 2015;47:641–9. https://doi.org/10.1111/evj.12361.
Article
CAS
PubMed
Google Scholar
Stewart HL, Southwood LL, Indugu N, Vecchiarelli B, Engiles JB, Pitta D. Differences in the equine faecal microbiota between horses presenting to a tertiary referral hospital for colic compared with an elective surgical procedure. Equine Vet J. 2019;51(3):336–42. https://doi.org/10.1111/evj.13010.
Article
CAS
PubMed
Google Scholar
United States Department of Agriculture. Lameness and laminitis in US horses. USDA: APHIS: US, CEAH, National Animal Health Monitoring System. United States Department of Agriculture, Washington DC; 2000.
United States Department of Agriculture. Baseline reference of equine health and management in the United States, 2015. USDA: APHIS: US, CEAH, National Animal Health Monitoring System. US Department of Agriculture, Washington DC. 2016.
Troya L, Blanco J, Romero I, Re M. Comparison of the colic incidence in a horse population with or without inclusion of germinated barley in the diet. Equine Vet Educ. 2020;32:28–32. https://doi.org/10.1111/eve.13274.
Article
Google Scholar
Fernandes KA, Kittelmann S, Rogers CW, Gee EK, Bolwell CF, Thomas BEN, DG,. Faecal microbiota of forage-fed horses in New Zealand and the population dynamics of microbial communities following dietary change. PLoS ONE. 2014;9(11):e112846. https://doi.org/10.1371/journal.pone.0112846.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang C, Zhang M, Wang S, Han R, Cao Y, Hua W, Mao Y, Zhang X, Pang X, Wei C. Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice. ISME J. 2010;4(2):232. https://doi.org/10.1038/ismej.2009.112.
Article
CAS
PubMed
Google Scholar
Zhang C, Li S, Yang L, Huang P, Li W, Wang S, Zhao G, Zhang M, Pang X, Yan Z. Structural modulation of gut microbiota in life-long calorie-restricted mice. Nat Commun. 2013;4:2163. https://doi.org/10.1038/ncomms3163.
Article
CAS
PubMed
Google Scholar
Dougal K, de la Fuente G, Harris PA, Girdwood SE, Pinloche E, Geor RJ, Nielsen BD, Schott HC II, Elzinga S, Newbold CJ. Characterisation of the faecal bacterial community in adult and elderly horses fed a high fibre, high oil or high starch diet using 454 pyrosequencing. PLoS ONE. 2014;9(2):e87424. https://doi.org/10.1371/journal.pone.0087424.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chatterton NJ, Harrison PA, Bennett JH, Asay KH. Carbohydrate partitioning in 185 accessions of gramineae grown under warm and cool temperatures. J Plant Physiol. 1989;134(2):169–79. https://doi.org/10.1016/S0176-1617(89)80051-3.
Article
CAS
Google Scholar
Jensen KB, Harrison P, Chatterton NJ, Bushman BS, Creech JE. Seasonal trends in nonstructural carbohydrates in cool-and warm-season grasses. Crop Sci. 2014;54(5):2328–40. https://doi.org/10.2135/cropsci2013.07.0465.
Article
CAS
Google Scholar
Hudson DJ, Leep RH, Dietz TS, Ragavendran A, Kravchenko A. Integrated warm-and cool-season grass and legume pastures: I. seasonal forage dynamics. Agron J. 2010;102(1):303–9. https://doi.org/10.2134/agronj2009.0204.
Article
Google Scholar
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37(8):852–7. https://doi.org/10.1038/s41587-019-0209-9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pelletier S, Tremblay GF, Bertrand A, Belanger G, Castonguay Y, Michaud R. Drying procedures affect non-structural carbohydrates and other nutritive value attributes in forage samples. Anim Feed Sci Technol. 2010;157:139–50. https://doi.org/10.1016/j.anifeedsci.2010.02.010.
Article
CAS
Google Scholar
Garber A, Hastie P, McGuinness D, Malarange P, Murray JA. Abrupt dietary changes between grass and hay alter faecal microbiota of ponies. PLoS ONE. 2020;15(8):e0237869. https://doi.org/10.1371/journal.pone.0237869.
Article
CAS
PubMed
PubMed Central
Google Scholar
Muhonen S, Connysson M, Lindberg JE, Julliand V, Bertilsson J, Jansson A. Effects of crude protein intake from grass silage-only diets on the equine colon ecosystem after an abrupt feed change. J Anim Sci. 2008;86(12):3465–72. https://doi.org/10.2527/jas.2007-0374.
Article
CAS
PubMed
Google Scholar
Grimm P, Philippeau C, Julliand V. Faecal parameters as biomarkers of the equine hindgut microbial ecosystem under dietary change. Animal. 2017;11(7):1136–45. https://doi.org/10.1017/S1751731116002779.
Article
CAS
PubMed
Google Scholar
Fitzgerald DM, Spence RJ, Stewart ZK, Prentis PJ, Sillence MN, De Laat MA. The effect of diet change and insulin dysregulation on the faecal microbiome of ponies. J Exper Biol. 2020;223(7):jeb219154. https://doi.org/10.1242/jeb.219154.
Article
Google Scholar
Respondek F, Goachet A, Julliand RFV. Effects of short-chain fructo-oligosaccharides on the microbial and biochemical profile of different segments of the gastro-intestinal tract in horses. Pferdeheilkunde. 2008;23(2):146. https://doi.org/10.21836/PEM20070206.
Article
Google Scholar
De Fombelle A, Julliand V, Drogoul C, Jacotot E. Feeding and microbial disorders in horses: 1-effects of an abrupt incorporation of two levels of barley in a hay diet on microbial profile and activities. J Equine Vet Sci. 2001;21:439–45. https://doi.org/10.1016/S0737-0806(01)70018-4.
Article
Google Scholar
Warzecha CM, Coverdale JA, Janecka JE, Leatherwood JL, Pinchak WE, Wickersham TA, McCann JC. Influence of short-term dietary starch inclusion on the equine cecal microbiome. J Anim Sci. 2017;95(11):5077–90. https://doi.org/10.2527/jas2017.1754.
Article
CAS
PubMed
PubMed Central
Google Scholar
Muhonen S, Julliand V, Lindberg JE, Bertilsson J, Jansson A. Effects on the equine colon ecosystem of grass silage and haylage diets after an abrupt change from hay. J Anim Sci. 2009;87(7):2291–8. https://doi.org/10.2527/jas.2008-1461.
Article
CAS
PubMed
Google Scholar
Zhang C, Zhao L. Strain-level dissection of the contribution of the gut microbiome to human metabolic disease. Genome Med. 2016;8(1):1–10. https://doi.org/10.1186/s13073-016-0304-1.
Article
Google Scholar
Pan F, Zhang L, Li M, Hu Y, Zeng B, Yuan H, Zhao L, Zhang C. Predominant gut Lactobacillus murinus strain mediates anti-inflammaging effects in calorie-restricted mice. Microbiome. 2018;6(1):1–17. https://doi.org/10.1186/s40168-018-0440-5.
Article
CAS
Google Scholar
Zhai R, Xue X, Zhang L, Yang X, Zhao L, Zhang C. Strain-specific anti-inflammatory properties of two Akkermansia muciniphila strains on chronic colitis in mice. Front Cell Infect Microbiol. 2019;9:239. https://doi.org/10.3389/fcimb.2019.00239.
Article
CAS
PubMed
PubMed Central
Google Scholar
Wu G, Zhao N, Zhang C, Lam YY, Zhao L. Guild-based analysis for understanding gut microbiome in human health and diseases. Genome Med. 2021;13(1):1–12. https://doi.org/10.1186/s13073-021-00840-y.
Article
Google Scholar
Mach N, Ruet A, Clark A, Bars-Cortina D, Ramayo-Caldas Y, Crisci E, Pennarun S, Dhorne-Pollet S, Foury A, Moisan MP, Lansade L. Priming for welfare: gut microbiota is associated with equitation conditions and behavior in horse athletes. Sci Rep. 2020;10(1):1–19. https://doi.org/10.1038/s41598-020-65444-9.
Article
CAS
Google Scholar
Husso A, Jalanka J, Alipour MJ, Huhti P, Kareskoski M, Pessa-Morikawa T, Iivanainen A, Niku M. The composition of the perinatal intestinal microbiota in horse. Sci Rep. 2020;10(1):1–12. https://doi.org/10.1038/s41598-019-57003-8.
Article
CAS
Google Scholar
Gomez A, Sharma AK, Grev A, Sheaffer C, Martinson K. The horse gut microbiome responds in a highly individualized manner to forage lignification. J Equine Vet Sci. 2021;96: 103306. https://doi.org/10.1016/j.jevs.2020.103306.
Article
PubMed
Google Scholar
Theelen MJ, Luiken RE, Wagenaar JA, Sloet van Oldruitenborgh-Oosterbaan MM, Rossen JW, Zomer AL. The equine faecal microbiota of healthy horses and ponies in The Netherlands: impact of host and environmental factors. Animals. 2021;11(6):1762. https://doi.org/10.3390/ani11061762.
Article
PubMed
PubMed Central
Google Scholar
Zhang C, Yin A, Li H, Wang R, Wu G, Shen J, Zhang M, Wang L, Hou Y, Ouyang H, Zhang Y. Dietary modulation of gut microbiota contributes to alleviation of both genetic and simple obesity in children. EBioMedicine. 2015;2(8):968–84. https://doi.org/10.1016/j.ebiom.2015.07.007.
Article
PubMed
PubMed Central
Google Scholar
Zhao L, Zhang F, Ding X, Wu G, Lam YY, Wang X, Fu H, Xue X, Lu C, Ma J, Yu L. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science. 2018;359(6380):1151–6. https://doi.org/10.1126/science.aao5774.
Article
CAS
PubMed
Google Scholar
Chen T, Liu AB, Sun S, Ajami NJ, Ross MC, Wang H, Zhang L, Reuhl K, Kobayashi K, Onishi JC, Zhao L, Yang CS. Green tea polyphenols modify the gut microbiome in db/db mice as co-abundance grouips correlating with the blood glucose lowering effect. Mol Nutr Food Res. 2019;63(8): 180164. https://doi.org/10.1002/mnfr.201801064.
Article
CAS
Google Scholar
Blackmore TM, Dugdale A, Argo CM, Curtis G, Pinloche E, Harris PA, Worgan HJ, Girwood SE, Dougal K, Newbold CJ, McEwan NR. Strong stability and host specific bacterial community in faeces of ponies. PLoS ONE. 2013;8(9): e75079. https://doi.org/10.1371/journal.pone.0075079.
Article
CAS
PubMed
PubMed Central
Google Scholar
Costa MC, Weese JS. The equine intestinal microbiome. Anim Health Res Rev. 2012;13(1):121–8. https://doi.org/10.1017/S1466252312000035.
Article
PubMed
Google Scholar
Proudman A, Darby C, Escalona E. Faecal microbiome of the Thoroughbred racehorse and its response to dietary amylase supplementation. Equine Vet J. 2014;46(S46):35. https://doi.org/10.1111/evj.12267_107.
Article
Google Scholar
Salem SE, Maddox TW, Berg A, Antczak P, Ketley JM, Williams NJ, Archer DC. Variation in faecal microbiota in a group of horses managed at pasture over a 12-month period. Sci Rep. 2018;8(1):8510. https://doi.org/10.1038/s41598-018-26930-3.
Article
CAS
PubMed
PubMed Central
Google Scholar
Johnson AJ, Vangay P, Al-Ghalith GA, Hillman BM, Ward TL, Shields-Cutler RR, Kim AD, Shmagel AK, Syed AN, Personalized Microbiome Students, Walter J. Daily sampling reveals personalized diet-microbiome associations in humans. Cell Host Microbe. 2019;25(6):789–802. https://doi.org/10.1016/j.chom.2019.05.005.
Article
CAS
PubMed
Google Scholar
Smits SA, Marcobal A, Higginbottom S, Sonnenburg JL, Kashyap PC. Individualized responses of gut microbiota to dietary intervention modeled in humanized mice. mSystems. 2016;1(5):e00098. https://doi.org/10.1128/mSystems.00098-16.
Article
PubMed
PubMed Central
Google Scholar
Ericsson AC, Johnson PJ, Gieche LM, Zobrist C, Bucy K, Townsend KS, Martin LM, LaCarrubba AM. The influence of diet change and oral metformin on blood glucose regulation and the fecal microbiota of healthy horses. Animals. 2021;11(4):976. https://doi.org/10.3390/ani11040976.
Article
PubMed
PubMed Central
Google Scholar
Zhu Y, Wang X, Deng L, Chen S, Zhu C, Li J. Effects of pasture grass, silage, and hay diet on equine fecal microbiota. Animals. 2021;11(5):1330. https://doi.org/10.3390/ani11051330.
Article
PubMed
PubMed Central
Google Scholar
Goodrich JK, Waters JL, Poole AC, Sutter JL, Koren O, Blekhman R, Beaumont M, Van Treuren W, Knight R, Bell JT, Spector TD, Clark AG, Ley RE. Human genetics shape the gut microbiome. Cell. 2014;159(4):789–99.
Article
CAS
Google Scholar
Svartström O, Alneberg J, Terrapon N, Lombard V, de Bruijn I, Malmsten J, Dalin A, Muller EEL, Shah P, Wilmes P, Henrissat B, Aspeborg H, Andersson AF. Ninety-nine de novo assembled genomes from the moose (Alces alces) rumen microbiome provide new insights into microbial plant biomass degradation. ISME J. 2017;11:2538–51. https://doi.org/10.1038/ismej.2017.108.
Article
CAS
PubMed
PubMed Central
Google Scholar
La Reau AJ, Suen G. The Ruminocci: key symbionts of the gut ecosystem. J Microbiol. 2018;56(3):199–208. https://doi.org/10.1007/s12275-018-8024-4.
Article
CAS
PubMed
Google Scholar
Tokuda G, Mikaelyan A, Fukui C, Watanabe H, Funishima M, Brune A. Fiber-associated spirochetes are major agents of hemicellulose degradation in the hindgut of wood-feeding higher termites. PNAS. 2018;115(51):E11996–2004. https://doi.org/10.1073/pnas.1810550115.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ren Q, Si H, Yan X, Liu C, Ding L, Long R, Li Z, Qiu Q. Bacterial communities in the solid, liquid, dorsal, and ventral epithelium fractions of yak (Bos grunniens) rumen. Microbiologyopen. 2020;9(2):e963. https://doi.org/10.1002/mbo3.963.
Article
CAS
PubMed
Google Scholar
Vital M, Jairong G, Rizzo R, Harrison T, Tiedje JM. Diet is a major factor governing the fecal butyrate-producing community structure across Mammalia, Aves and Reptilia. ISME J. 2015;9:832–43. https://doi.org/10.1038/ismej.2014.179.
Article
CAS
PubMed
Google Scholar
Perea K, Perz K, Olivo SK, Williams A, Lachman M, Ishaq SL, Thomson J, Yeoman CJ. J Anim Sci. 2017;95(6):2585–92. https://doi.org/10.2527/jas.2016.1222.
Article
CAS
PubMed
Google Scholar
Gharechahi J, Vahidi MF, Ding X-Z, Han J-L, Salekdeh GH. Temporal changes in microbial communities attached to forages with different lignocellulosic compositions in cattle rumen. FEMS Microbiol Ecol. 2020. https://doi.org/10.1093/femsec/fiaa069.
Article
PubMed
Google Scholar
Goodrich JK, Davenport ER, Waters JL, Clark AG, Ley RE. Cross-species comparisons of host genetic associations with the microbiome. Science. 2016;352:532–5. https://doi.org/10.1126/science.aad9379.DOI:10.1016/j.cell.2014.09.053.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lim MY, You HJ, Yoon HS, Kwon B, Lee JY, Lee S, Song Y, Lee K, Sung J, Ko G. The effect of heritability and host genetics on the gut microbiota and metabolic syndrome. Gut. 2017;66:1031–8. https://doi.org/10.1136/gutjnl-2015-311326.
Article
CAS
PubMed
Google Scholar
Waters JL, Ley RE. The human gut bacteria Christensenellaceae are widespread, heritable, and associated with health. BMC Biol. 2019;17:83. https://doi.org/10.1186/s12915-019-0699-4.
Article
PubMed
PubMed Central
Google Scholar
Ilmberger N, Güllert S, Dannenberg J, Rabausch U, Torres J, Wemheuer B, Alawi M, Poehlein A, Chow J, Turaev D, Rattei T. A comparative metagenome survey of the fecal microbiota of a breast- an a plant-fed Asian elephant reveals an unexpectedly high diversity of glycoside hydrolase family enzymes. PLoS ONE. 2014;9(9): e106707. https://doi.org/10.1371/journal.pone.0106707.
Article
CAS
PubMed
PubMed Central
Google Scholar
Li Y, Hu X, Yang S, Zhou J, Zhang T, Qi L, Sun X, Fan M, Xu S, Cha M, Zhang M. Comparative analysis of the gut microbiota composition between captive and wild forest musk deer. Front Microbiol. 2017;8:1705. https://doi.org/10.3389/fmicb.2017.01705.
Article
PubMed
PubMed Central
Google Scholar
Huang Q, Holman BD, Alexander T, Hu T, Jin L, Xu Z, McAllister TA, Acharya S, Zhao G, Wang Y. Fecal microbiota of lambs fed purple prairie clover (Dalea purpurea Vent) and alfalfa (Medicago sativa). Arch Microbiol. 2018;200(1):137–45. https://doi.org/10.1007/s00203-017-1427-5.
Article
CAS
PubMed
Google Scholar
Rodriquez C, Taminiau B, Brévers B, Avesani V, Van Broeck J, Leroux A, Gallot M, Bruwier A, Amory H, Delmée M, Daube G. Faecal microbiota characterisation of horses using 16 rdna barcoded pyrosequencing, and carriage rate of clostridium difficile at hospital admission. BMC Microbiol. 2015;15(1):1–14. https://doi.org/10.1186/s12866-015-0514-5.
Article
CAS
Google Scholar
Li Y, Zhang K, Yang L, Kai L, Defu H, Wronski T. Community composition and diversity of intestinal microbiota in captive and re-introduced Prezwalski’s Horse (Equus ferus prezwalskii). Front Microbiol. 2019;10:1821. https://doi.org/10.3389/fmicb.2019.01821.
Article
PubMed
PubMed Central
Google Scholar
Graf J. The family Rikenellaceae. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The prokaryotes. Berlin: Springer Berlin Heidelberg; 2014. p. 857–9. https://doi.org/10.1007/978-3-642-38954-2_134.
Chapter
Google Scholar
Asma Z, Sylvie C, Laurent C, Jérôme M, Christophe K, Oliver B, Annabelle TM, Francis E. Microbial ecology of the rumen evaluated by 454 GS FLX pyrosequencing is affected by starch and oil supplementation of diets. FEMS Microbio Ecol. 2013;83(2):504–14. https://doi.org/10.1111/1574-6941.12011.
Article
CAS
Google Scholar
Bomar I, Malz M, Colston S, Graf J. Directed culturing of microorganisms using metatranscriptomics. MBio. 2011;2(2):e00012-e111. https://doi.org/10.1128/mBio.00012-11.
Article
CAS
PubMed
PubMed Central
Google Scholar
Maurice CF, Knowles SC, Ladau J, Pollard KS, Fenton A, Pedersen AB, Turnbaugh PJ. Marked seasonal variation in the wild mouse gut microbiota. ISME J. 2015;9(11):2423–34. https://doi.org/10.1038/ismej.2015.53.
Article
CAS
PubMed
PubMed Central
Google Scholar
Amato KR, Leigh SR, Kent A, Mackie RI, Yeoman CJ, Stumpf RM, Wilson BA, Nelson KE, White BA, Garber PA. The gut microbiota appears to compensate for seasonal diet variation in the wild black howler monkey (Alouatta pigra). Microb Ecol. 2015;69(2):434–43. https://doi.org/10.1007/s00248-014-0554-7.
Article
CAS
PubMed
Google Scholar
Parfrey LW, Knight R. Spatial and temporal variability of the human microbiota. Clin Microbiol Infect. 2012;18(S4):5–7. https://doi.org/10.1111/j.1469-0691.2012.03861.x.
Article
Google Scholar
Williams CA, Kenny LB, Burk AO. Effects of grazing system, season, and forage carbohydrates on glucose and insulin dynamics of the grazing horse. J Anim Sci. 2019;97(6):2541–54. https://doi.org/10.1093/jas/skz103.
Article
PubMed
PubMed Central
Google Scholar
Kagan IA, Kirch BH, Thatcher CD, Strickland JR, Teutsch CD, Elvinger F, Pleasant RS. Seasonal and diurnal variation in simple sugar and fructan composition of orchardgrass pasture and hay in the Piedmont region of the United States. J Equine Vet Sci. 2011;31(8):488–97. https://doi.org/10.1016/j.jevs.2011.03.004.
Article
Google Scholar
Kagan IA, Kirch BH, Thatcher CD, Teutsch CD, Elvinger F, Shepherd DM, Pleasant S. Seasonal and diurnal changes in starch content and sugar profiles of Bermudagrass in the Piedmont region of the United States. J Equine Veterinary Sci. 2011;31(9):521–9. https://doi.org/10.1016/j.jevs.2011.08.010.
Article
Google Scholar
Weinert-Nelson JR, Meyer WA, Williams CA. Diurnal variation in forage nutrient composition of mixed cool-season grass, crabgrass, and bermudagrass pastures. J Equine Vet Sci. 2022;110: 103836. https://doi.org/10.1016/j.jevs.2021.103836.
Article
PubMed
Google Scholar
Berg EL, Fu CJ, Porter JH, Kerley MS. Fructooligosaccharide supplementation in the yearling horse: effects on fecal pH, microbial content, and volatile fatty acid concentrations. J Anim Sci. 2005;83(7):1549–53. https://doi.org/10.2527/2005.8371549x.
Article
CAS
PubMed
Google Scholar
Biddle AS, Stewart L, Blanchard J, Leschine S. Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in Diverse Gut Communities. Diversity. 2013;5(3):627–40. https://doi.org/10.3390/d5030627.
Article
Google Scholar
Lawson PA, Rainey FA. Proposal to restrict the genus Clostridium Prazmowski to Clostridium butyricum and related species. Int J Syst Evol. 2016;66(2):1009–16. https://doi.org/10.1099/ijsem.0.000824.
Article
CAS
Google Scholar
La Reau AJ, Suen G. The Ruminococci: key symbionts of the gut ecosystem. J Microbiol. 2018;56(3):199–208. https://doi.org/10.1007/s12275-018-8024-4.
Article
CAS
PubMed
Google Scholar
Willing B, Vörös A, Roos S, Jones C, Jansson A, Lindberg J. Changes in faecal bacteria associated with concentrate and forage-only diets fed to horses in training. Equine Vet J. 2009;41:908–14. https://doi.org/10.2746/042516409X447806.
Article
CAS
PubMed
Google Scholar
Sorensen RJ, Drouillard JS, Douthit TL, Ran Q, Marthaler DG, Kang Q, Vahl CI, Lattimer JM. Effect of hay type on cecal and fecal microbiome and fermentation parameters in horses. J Anim Sci. 2021. https://doi.org/10.1093/jas/skaa407.
Article
PubMed
Google Scholar
Office of the New Jersey State climatologist at Rutgers University: Rutgers New Jersey weather network. https://www.njweather.org/data (2021). Accessed 12 Jul 2021.
Henneke DR, Potter GD, Kreider JL, Yeates BF. Relationship between condition score, physical measurements and body fat percentage in mares. Equine Vet J. 1983;15(4):371–2. https://doi.org/10.1111/j.2042-3306.1983.tb01826.x.
Article
CAS
PubMed
Google Scholar
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens M, Betley J, Fraser L, Bauer M, Gormley N. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–4. https://doi.org/10.1038/ismej.2012.8.
Article
CAS
PubMed
PubMed Central
Google Scholar
R Development Core Team. R: A language and environment for statistical computing. 2010. http://cran.r-project.org.
McDonald D, Clemente JC, Kuczynski J, Rideout JR, Stombaugh J, Wendel D, Wilke A, Huse S, Hufnagle J, Meyer F, Knight R. The Biological observation matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. Gigascience. 2012;1(1):2047–217. https://doi.org/10.1186/2047-217X-1-7.
Article
Google Scholar
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581–3. https://doi.org/10.1038/nmeth.3869.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lane DJ. 16S/23S rRNA Sequencing. In: Stakebrandt E, Goodfellow M, editors. Nucleic acid techniques in bacterial systematics. New York City: John Wiley and Sons; 1991. p. 115–75.
Google Scholar
Price MN, Dehal PS, Arkin AP. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE. 2010;5(3):e9490. https://doi.org/10.1371/journal.pone.0009490.
Article
CAS
PubMed
PubMed Central
Google Scholar
Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80. https://doi.org/10.1093/molbev/mst010.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shannon CE. A mathematical theory of communication. Bell Sys Tech J. 1948;27(3):379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
Article
Google Scholar
Pielou EC. The measurement of diversity in different types of biological collections. J Theor Biol. 1966;13:131–44. https://doi.org/10.1016/0022-5193(66)90013-0.
Article
Google Scholar
Faith D. Conservation evaluation and phylogenetic diversity. Biol Conserv. 1992;61(1):1–10. https://doi.org/10.1016/0006-3207(92)91201-3.
Article
Google Scholar
McKinney W. Data structures for statistical computing in python. In: van der Walt S, Millman J, editors. Proceedings of the 9th python in science conference; 2010. p. 51–6.
Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K, Gonzalez A, Lozupone C, Zaneveld JR, Vázquez-Baeza Y, Birmingham A, Hyde ER. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017;5(1):1–18. https://doi.org/10.1186/s40168-017-0237-y.
Article
Google Scholar
Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Envir Microbiol. 2005;71(12):8228–35. https://doi.org/10.1128/AEM.71.12.8228-8235.2005.
Article
CAS
Google Scholar
Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and uqalitative β diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol. 2007;73(5):1576–85. https://doi.org/10.1128/AEM.01996-06.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hamady M, Lozupone C, Knight R. Fast unifrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequening and PhyloChip data. ISME J. 2010;4(1):17–27. https://doi.org/10.1038/ismej.2009.97.
Article
CAS
PubMed
Google Scholar
Chang Q, Luan Y, Sun F. Variance adjusted weighted UniFrac: a powerful beta diversity measure for comparing communities based on phylogeny. BMC Bioinform. 2011. https://doi.org/10.1186/1471-2105-12-118.
Article
Google Scholar
Chen J, Bittinger K, Charlson ES, Hofmann C, Lewis J, Wu GD, Collman G, Bushman FD, Li H. Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics. 2012;28(16):2106–13. https://doi.org/10.1093/bioinformatics/bts342.
Article
CAS
PubMed
PubMed Central
Google Scholar
McDonald D, Vázquez-Baeza Y, Koslicki D, McClelland J, Reeve N, Zhenjiang X, Gonzalez A, Knight R. Striped UniFrac: enabling microbiome analysis at unprecedented scale. Nat Methods. 2018;15(11):847–8. https://doi.org/10.1038/s41592-018-0187-8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 2001;26(1):32–46. https://doi.org/10.1111/j.1442-9993.2001.01070.pp.x.
Article
Google Scholar
Hagberg AA, Shult DA, Swart PJ. Exploring network structure, dynamics, and function using NetworkX. In: Varoquaux G, Vaught T, Millman J, editors. Proceedings of the 7th Python in Science Conference; 2008. p. 11–15.
Shaffer M, Thurimella K, Lozupone CA. SCNIC: Sparse correlation network investigation for compositional data. bioRxiv. 2020. https://doi.org/10.1101/2020.11.13.380733.
Article
PubMed
PubMed Central
Google Scholar
Bokulich N, Dillon M, Bolyen E, Kaehler BD, Huttley GA, Caporaso JG. q2-sample-classifier: machine-learning tools for microbiome classification and regression. J Open Source Softw. 2018;3(30):934. https://doi.org/10.21105/joss.00934.
Article
Google Scholar
Pedregosa F, Varoquaux G, Gramfort A, Michel B, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12:2825–30.
Google Scholar
Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. Microb Ecol Health Dis. 2015;26(1):27663. https://doi.org/10.3402/mehd.v26.27663.
Article
PubMed
Google Scholar
Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig K, Peplies J, Glockner FO. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucl Acids Res. 2007;35:7188–96.
Article
CAS
Google Scholar
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Pablo J, Glockner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl Acids Res. 2013;41:D590–6.
Article
CAS
Google Scholar
Rognes T, Flouri T, Nichols B, Quince C, Mahé F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016;4: e2584. https://doi.org/10.7717/peerj.2584.
Article
PubMed
PubMed Central
Google Scholar
Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, Huttley GA, Caparaso JG. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-eature-classifier plugin. Microbiome. 2018;1(6):90. https://doi.org/10.1186/s40168-018-0470-z.
Article
Google Scholar