Exploring variation in the fecal microbial communities of Kasaragod Dwarf and Holstein crossbred cattle.


Journal

Antonie van Leeuwenhoek
ISSN: 1572-9699
Titre abrégé: Antonie Van Leeuwenhoek
Pays: Netherlands
ID NLM: 0372625

Informations de publication

Date de publication:
Jan 2023
Historique:
received: 04 02 2022
accepted: 30 10 2022
pubmed: 1 12 2022
medline: 11 1 2023
entrez: 30 11 2022
Statut: ppublish

Résumé

The gut microbiota and its impact on health and nutrition in animals, including cattle has been of intense interest in recent times. Cattle, in particular indigenous varieties like Kasaragod Dwarf cow, have not received the due consideration given to other non-native cattle breeds, and the composition of their fecal microbiome is yet to be established. This study applied 16S rRNA high-throughput sequencing of fecal samples and compared the Kasaragod Dwarf with the highly prevalent Holstein crossbred cattle. Variation in their microbial composition was confirmed by marker gene-based taxonomic analysis. Principle Coordinate Analysis (PCoA) showed the distinct microbial architecture of the two cattle types. While the two cattle types possess unique signature taxa, in Kasaragod Dwarf cattle, many of the identified genera, including Anaerovibrio, Succinivibrio, Roseburia, Coprococcus, Paludibacter, Sutterella, Coprobacillus, and Ruminobacter, have previously been shown to be present in higher abundance in animals with higher feed efficiency. This is the first report of Kasaragod Dwarf cattle fecal microbiome profiling. Our findings highlight the predominance of specific taxa potentially associated with different fermentation products and feed efficiency phenotypes in Kasaragod Dwarf cattle compared to Holstein crossbred cattle.

Identifiants

pubmed: 36450879
doi: 10.1007/s10482-022-01791-z
pii: 10.1007/s10482-022-01791-z
doi:

Substances chimiques

RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

53-65

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Références

Amin N, Seifert J (2021) Dynamic progression of the calf’s microbiome and its influence on host health. Comput Struct Biotechnol 19:989–1001. https://doi.org/10.1016/j.csbj.2021.01.035
doi: 10.1016/j.csbj.2021.01.035
Anilkumar K, Raghunandan KV (2003) The dwarf cattle and buffalo of Kerala. Kerala Agricultaral University, Mannuthy, pp 9–14
Arndt C, Powell JM, Aguerre MJ, Crump PM, Wattiaux MA (2015) Feed conversion efficiency in dairy cows: Repeatability, variation in digestion and metabolism of energy and nitrogen, and ruminal methanogens. J Dairy Sci 98:3938–3950. https://doi.org/10.3168/jds.2014-8449
doi: 10.3168/jds.2014-8449
Auffret MD, Stewart RD, Dewhurst RJ, Duthie CA, Watson M, Roehe R (2020) Identification of microbial genetic capacities and potential mechanisms within the rumen microbiome explaining differences in beef cattle feed efficiency. Front Microbiol 11:1229. https://doi.org/10.3389/fmicb.2020.01229
doi: 10.3389/fmicb.2020.01229
Bergamaschi M, Tiezzi F, Howard J, Huang YJ, Gray KA, Schillebeeckx C, McNulty NP, Maltecca C (2020) Gut microbiome composition differences among breeds impact feed efficiency in swine. Microbiome 8:110. https://doi.org/10.1186/s40168-020-00888-9
doi: 10.1186/s40168-020-00888-9
Blaut M, Clavel T (2007) Metabolic diversity of the intestinal microbiota: implications for health and disease. J Nutr 137:751S-755S. https://doi.org/10.1093/jn/137.3.751S
doi: 10.1093/jn/137.3.751S
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 J, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. https://doi.org/10.1038/nmeth.f.303
doi: 10.1038/nmeth.f.303
Caro-Quintero A, Ritalahti KM, Cusick KD, Löffler FE, Konstantinidis KT (2012) The chimeric genome of sphaerochaeta: nonspiral spirochetes that break with the prevalent dogma in spirochete biology. mBio 3:e00025-12. https://doi.org/10.1128/mBio.00025-12
doi: 10.1128/mBio.00025-12
Choo JM, Leong LE, Rogers GB (2015) Sample storage conditions significantly influence faecal microbiome profiles. Sci Rep 5:1–10. https://doi.org/10.1038/srep16350
doi: 10.1038/srep16350
Clarke KR, Somerfield PJ, Airoldi L, Warwick RM (2006) Exploring interactions by second-stage community analyses. J Exp Mar Biol Ecol 338:179–192. https://doi.org/10.1016/j.jembe.2006.06.019
doi: 10.1016/j.jembe.2006.06.019
Danielsson R, Dicksved J, Sun L, Gonda H, Müller B, SchnürerA BJ (2017) Methane production in dairy cows correlates with rumen methanogenic and bacterial community structure. Front Microbiol. https://doi.org/10.3389/fmicb.2017.00226
doi: 10.3389/fmicb.2017.00226
DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072. https://doi.org/10.1128/AEM.03006-05
doi: 10.1128/AEM.03006-05
Diao H, Yan HL, Xiao Y, Yu B, Yu J, He J, Zheng P, Zeng BH, Wei H, Mao XB, Chen DW (2016) Intestinal microbiota could transfer host Gut characteristics from pigs to mice. BMC Microbiol 16:238. https://doi.org/10.1186/s12866-016-0851-z
doi: 10.1186/s12866-016-0851-z
Dinsdale E (2013) Multivariate analysis of functional metagenomes. Front Gene. https://doi.org/10.3389/fgene.2013.00041
doi: 10.3389/fgene.2013.00041
Dvergedal H, Sandve SR, Angell IL, Klemetsdal G, Rudi K (2020) Association of gut microbiota with metabolism in juvenile Atlantic salmon. Microbiome 8:160. https://doi.org/10.1186/s40168-020-00938-2
doi: 10.1186/s40168-020-00938-2
Eren AM, Sogin ML, Morriso HG, Vineis JH, Fisher JC, Newton RJ, McLellan SL (2015) A single genus in the gut microbiome reflects host preference and specificity. ISME J 9:90–100. https://doi.org/10.1038/ismej.2014.97
doi: 10.1038/ismej.2014.97
Fan P, Bian B, Teng L, Nelson CD, Driver J, Elzo MA, Jeong KC (2020) Host genetic effects upon the early gut microbiota in a bovine model with graduated spectrum of genetic variation. ISME J 14:302–317. https://doi.org/10.1038/s41396-019-0529-2
doi: 10.1038/s41396-019-0529-2
Fan P, Nelson CD, Driver JD, Elzo MA, Peñagaricano F, Jeong KC (2021) Host genetics exerts lifelong effects upon hindgut microbiota and its association with bovine growth and immunity. ISME J 1:1–6. https://doi.org/10.1038/s41396-021-00925-x
doi: 10.1038/s41396-021-00925-x
Gardiner GE, Metzler-Zebeli BU, Lawlor PG (2020) Impact of intestinal microbiota on growth and feed efficiency in pigs: a review. Microorganisms 8:1886. https://doi.org/10.3390/microorganisms8121886
doi: 10.3390/microorganisms8121886
Gressley TF, Hall MB, Armentano LE (2011) Ruminant nutrition symposium: productivity, digestion, and health responses to hindgut acidosis in ruminants. J Anim Sci 89:1120–1130. https://doi.org/10.2527/jas.2010-3460
doi: 10.2527/jas.2010-3460
Hagey JV, Bhatnagar S, Heguy JM, Karle BM, Price PL, Meyer D, Maga EA (2019) Fecal microbial communities in a large representative cohort of California dairy cows. Front Microbiol 10:1093. https://doi.org/10.3389/fmicb.2019.01093
doi: 10.3389/fmicb.2019.01093
He M, Fang S, Huang X, Zhao Y, Ke S, Yang H, Li Z, Gao J, Chen C, Huang L (2016) Evaluating the contribution of gut microbiota to the variation of porcine fatness with the cecum and fecal samples. Front Microbiol 7:13. https://doi.org/10.3389/fmicb.2016.0210
doi: 10.3389/fmicb.2016.0210
Hernandez-Sanabria E, Goonewardene LA, Wang Z, Durunna ON, Moore SS, Guan LL (2012) Impact of feed efficiency and diet on adaptive variations in the bacterial community in the rumen fluid of cattle. AEM 78:12. https://doi.org/10.1128/AEM.05114-11
doi: 10.1128/AEM.05114-11
ICAR (2013) Nutrient requirements of animals- cattle and buffalo, 3
Khafipour E, Li S, Tun HM, Derakhshani H, Moossavi S, Plaizier JC (2016) Effects of grain feeding on microbiota in the digestive tract of cattle. Anim Front 6:13–9. https://doi.org/10.2527/af.2016-0018
doi: 10.2527/af.2016-0018
Kiros TG, Derakhshani H, Pinloche E, D’inca R, Marshall J, Auclair E, Khafipour E, Van Kessel A (2018) Effect of live yeast Saccharomyces cerevisiae (Actisaf Sc 47) supplementation on the performance and hindgut microbiota composition of weanling pigs. Sci Rep 8:5315. https://doi.org/10.1038/s41598-018-23373-8
doi: 10.1038/s41598-018-23373-8
Layden BT, Angueira AR, Brodsky M, Durai V, Lowe WL (2013) Short chain fatty acids and their receptors: new metabolic targets. Transl Res 161:131–140. https://doi.org/10.1016/j.trsl.2012.10.007
doi: 10.1016/j.trsl.2012.10.007
Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, Schlegel ML, Tucker TA, Schrenzel MD, Knight R, Gordon JI (2008) Evolution of mammals and their gut microbes. Science 320:1647–51. https://doi.org/10.1126/science.1155725
doi: 10.1126/science.1155725
Li F, Li C, Chen Y, Liu J, Zhang C, Irving B, Fitzsimmons C, Plastow G, Guan LL (2019) Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle. Microbiome 7:92. https://doi.org/10.1186/s40168-019-0699-1
doi: 10.1186/s40168-019-0699-1
Liu K, Zhang Y, Yu Z, Xu Q, Zheng N, Zhao S, Huang G, Wang J (2021) Ruminal microbiota–host interaction and its effect on nutrient metabolism. AnimNutr 7:49–55. https://doi.org/10.1016/j.aninu.2020.12.001
doi: 10.1016/j.aninu.2020.12.001
Lopes DR, La Reau AJ, Duarte MD, Detmann E, Bento CB, Mercadante ME, Bonilha SF, Suen G, Mantovani HC (2019) The bacterial and fungal microbiota of nelore steers is dynamic across the gastrointestinal tract and its fecal-associated microbiota is correlated to feed efficiency. Front Microbiol 10:1263. https://doi.org/10.3389/fmicb.2019.01263
doi: 10.3389/fmicb.2019.01263
Løvendahl P, Difford GF, Li B, Chagunda MGG, Huhtanen P, Lidauer MH, Lassen J, Lund P (2018) Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle. Animal 12:s336–s349. https://doi.org/10.1017/S1751731118002276
doi: 10.1017/S1751731118002276
Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R (2011) UniFrac: an effective distance metric for microbial community comparison. ISME J5:169–172. https://doi.org/10.1038/ismej.2010.133
doi: 10.1038/ismej.2010.133
Lu D, Tiezzi F, Schillebeeckx C, McNulty NP, Schwab C, Shull C, Maltecca C (2018) Host contributes to longitudinal diversity of fecal microbiota in swine selected for lean growth. Microbiome 6:4. https://doi.org/10.1186/s40168-017-0384-1
doi: 10.1186/s40168-017-0384-1
Magoč T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963. https://doi.org/10.1093/bioinformatics/btr507
doi: 10.1093/bioinformatics/btr507
Malmuthuge N, Guan LL (2017) Understanding host-microbial interactions in rumen: Searching the best opportunity for microbiota manipulation. J Anim Sci Biotechnol 8:8. https://doi.org/10.1186/s40104-016-0135-3
doi: 10.1186/s40104-016-0135-3
McGovern E, McGee M, Byrne CJ, Kenny DA, Kelly AK, Waters SM (2020) Investigation into the effect of divergent feed efficiency phenotype on the bovine rumen microbiota across diet and breed. Sci Rep 10:15317. https://doi.org/10.1038/s41598-020-71458-0
doi: 10.1038/s41598-020-71458-0
Monteiro HF, Zhou Z, Gomes MS, Peixoto PM, Bonsaglia EC, Canisso IF, Lima FS (2022) Rumen and lower gut microbiomes relationship with feed efficiency and production traits throughout the lactation of Holstein dairy cows. Sci Rep 12:1–14. https://doi.org/10.1038/s41598-022-08761-5
doi: 10.1038/s41598-022-08761-5
Myer PR (2019) Bovine genome-microbiome interactions: metagenomic frontier for the selection of efficient productivity in cattle systems. MSystems 4:e00103-19. https://doi.org/10.1128/mSystems.00103-19
doi: 10.1128/mSystems.00103-19
Myer PR, Freetly HC, Wells JE, Smith TPL, Kuehn LA (2017) Analysis of the gut bacterial communities in beef cattle and their association with feed intake, growth, and efficiency. J Anim Sci 95:3215. https://doi.org/10.2527/jas2016.1059
doi: 10.2527/jas2016.1059
O’Hara E, Neves AL, Song Y, Guan LL (2020) The role of the gut microbiome in cattle production and health: driver or passenger? Ann Rev Anim Biosci 8:199–220. https://doi.org/10.1146/annurev-animal-021419-083952
doi: 10.1146/annurev-animal-021419-083952
Oliphant K, Allen-Vercoe E (2019) Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health. Microbiome 7(1):1–15
doi: 10.1186/s40168-019-0704-8
Parmar NR, Pandit PD, Purohit HJ, Kumar KJI, Joshi CG (2017) Influence of diet composition on cattle rumen methanogenesis: a comparative metagenomic analysis in Indian and exotic cattle. Indian J Microbiol 57:226–234. https://doi.org/10.1007/s12088-016-0635-z
doi: 10.1007/s12088-016-0635-z
Patel RK, Jain M (2012) NGS QC toolkit: a toolkit for quality control of next generation sequencing data. PLoS ONE 7:e30619. https://doi.org/10.1371/journal.pone.0030619
doi: 10.1371/journal.pone.0030619
Paulson JN, Stine OC, Bravo HC, Pop M (2013) Differential abundance analysis for microbial marker-gene surveys. Nat Methods 10:1200–1202. https://doi.org/10.1038/nmeth.2658
doi: 10.1038/nmeth.2658
Paz HA, Anderson CL, Muller MJ, Kononoff PJ, Fernando SC (2016) Rumen bacterial community composition in holstein and jersey cows is different under same dietary condition and is not affected by sampling method. Front Microbiol 7:9. https://doi.org/10.3389/fmicb.2016.01206
doi: 10.3389/fmicb.2016.01206
Pulikkan J, Maji A, Dhakan DB, Saxena R, Mohan B, Anto MM, Agarwal N, Grace T, Sharma VK (2018) Gut microbial dysbiosis in indian children with autism spectrum disorders. Microb Ecol 76:1102–1114. https://doi.org/10.1007/s00248-018-1176-2
doi: 10.1007/s00248-018-1176-2
Qiu Q, Zhu Y, Qiu X, Gao C, Wang J, Wang H, He Y, Cao B, Su H (2019) Dynamic variations in fecal bacterial community and fermentation profile of Holstein steers in response to three stepwise density diets. Animals 9:560. https://doi.org/10.3390/ani9080560
doi: 10.3390/ani9080560
Ramesha KP, Divya P, Rao A, Basavaraju M, Jeyakumar S, Das DN, Kataktalware MA (2016) Assessment of genetic diversity among MalnadGidda, Punganur and Vechur-dwarf cattle breeds of India using microsatellite markers. Indian J Anim Sci 86:186–191
Ríos-Covián D, Ruas-Madiedo P, Margolles A, Gueimonde M, De Los Reyes-gavilán CG, Salazar N (2016) Intestinal short chain fatty acids and their link with diet and human health. Front Microbiol 7:185. https://doi.org/10.3389/fmicb.2016.00185
doi: 10.3389/fmicb.2016.00185
Sadan T, Aravindakshan TV, Radhika G, Anand LF, Ally K (2020) Metagenomic analysis exploring taxonomic diversity of rumen microbial communities in Vechur and crossbred cattle of Kerala state, India. J Appl Genetics 61:287–297. https://doi.org/10.1007/s13353-020-00547-7
doi: 10.1007/s13353-020-00547-7
Sanz-Fernandez M, Daniel JB, Seymour DJ, Kvidera SK, Bester Z, Doelman J, Martín-Tereso J (2020) Targeting the hindgut to improve health and performance in cattle. Animals 10:1817. https://doi.org/10.3390/ani10101817
doi: 10.3390/ani10101817
Saxena R, Dhakan DB, Mittal P, Waiker P, Chowdhury A, GhatakA SVK (2017) Metagenomic analysis of hot springs in central India reveals hydrocarbon degrading thermophiles and pathways essential for survival in extreme environments. Front Microbiol 7:2123. https://doi.org/10.3389/fmicb.2016.02123
doi: 10.3389/fmicb.2016.02123
Shabat SKB, Sasson G, Doron-Faigenboim A, Durman T, Yaacoby S, Miller BME, White BA, Shterzer N, Mizrahi I (2016) Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants. ISME J 10:2958–2972. https://doi.org/10.1038/ismej.2016.62
doi: 10.1038/ismej.2016.62
Srivastava AK, Patel JB, Ankuya KJ, Chauhan HD, Srivastava AK, Patel JB, Ankuya KJ, Chauhan HD, Pawar MM, Gupta JP (2019) Conservation of indigenous cattle breeds. J Anim Res 9:1–12
doi: 10.30954/2277-940X.01.2019.1
Stolze Y, Zakrzewski M, Maus I, Eikmeyer F, Jaenicke S, Rottmann N, Siebner C, Pühler A, Schlüter A (2015) Comparative metagenomics of biogas-producing microbial communities from production-scale biogas plants operating under wet or dry fermentation conditions. Biotechnol Biofuels 8:14. https://doi.org/10.1186/s13068-014-0193-8
doi: 10.1186/s13068-014-0193-8
Sun B, Wang X, Bernstein S, Huffman MA, Xia DP, Gu Z, Chen R, Sheeran LK, Wagner RS, Li J (2016) Marked variation between winter and spring gut microbiota in free-ranging Tibetan Macaques (Macaca thibetana). Sci Rep 6:26035. https://doi.org/10.1038/srep26035
doi: 10.1038/srep26035
Turnbaugh PJ, Gordon JI (2009) The core gut microbiome, energy balance and obesity. J Physiol 587:4153–8. https://doi.org/10.1113/jphysiol.2009.174136
doi: 10.1113/jphysiol.2009.174136
Uchiyama J, Murakami H, Sato R, Mizukami K, Suzuki T, Shima A, Ishihara G, Sogawa K, Sakaguchi M (2020) Examination of the fecal microbiota in dairy cows infected with bovine leukemia virus. Vet Microbiol 240:108547. https://doi.org/10.1016/j.vetmic.2019.108547
doi: 10.1016/j.vetmic.2019.108547
Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K, Gonzalez A, Lozupone C, Zaneveld JR, Vázquez-Baeza Y, Birmingham A, Hyde ER, Knight R (2017) Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 5:27. https://doi.org/10.1186/s40168-017-0237-y
doi: 10.1186/s40168-017-0237-y
Xue MY, Sun HZ, Wu XH, Liu JX, Guan LL (2020) Multi-omics reveals that the rumen microbiome and its metabolome together with the host metabolome contribute to individualized dairy cow performance. Microbiome 8:64. https://doi.org/10.1186/s40168-020-00819-8
doi: 10.1186/s40168-020-00819-8
Yang H, Huang X, Fang S, He M, Zhao Y, Wu Z, Yang M, Zhang Z, Chen C, Huang L (2017) Unraveling the fecal microbiota and metagenomic functional capacity associated with feed efficiency in pigs. Front Microbiol 8:1555. https://doi.org/10.3389/fmicb.2017.01555
doi: 10.3389/fmicb.2017.01555
Zhang J, Xu C, Huo D, Hu Q, Peng Q (2017) Comparative study of the gut microbiome potentially related to milk protein in Murrah buffaloes (Bubalusbubalis) and Chinese Holstein cattle. Sci Rep 7:42189. https://doi.org/10.1038/srep42189
doi: 10.1038/srep42189

Auteurs

M Deepthi (M)

Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Kasaragod, Kerala, 671316, India.

Kumar Arvind (K)

Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Kasaragod, Kerala, 671316, India.

Rituja Saxena (R)

Metagenomics and Systems Biology Group, Department of Biological Sciences, Indian Institute of Science Education and Research, Bhopal, Madhya Pradesh, 462066, India.

Joby Pulikkan (J)

Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Kasaragod, Kerala, 671316, India.

Vineet K Sharma (VK)

Metagenomics and Systems Biology Group, Department of Biological Sciences, Indian Institute of Science Education and Research, Bhopal, Madhya Pradesh, 462066, India.

Tony Grace (T)

Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Kasaragod, Kerala, 671316, India. tonygrace@cukerala.ac.in.

Articles similaires

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male
Humans Meals Time Factors Female Adult

Classifications MeSH