Rumen bacteria influence milk protein yield of yak grazing on the Qinghai-Tibet plateau
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Objective: Ruminants are completely dependent on their microbiota for rumen fermentation, feed digestion, and consequently, their metabolism for productivity. This study aimed to evaluate the rumen bacteria of lactating yaks with different milk protein yields, using high-throughput sequencing technology, in order to understand the influence of these bacteria on milk production.Methods: Yaks with similar high milk protein yield (high milk yield and high milk protein content, HH; n = 12) and low milk protein yield (low milk yield and low milk protein content, LL; n = 12) were randomly selected from 57 mid-lactation yaks. Ruminal contents were collected using an oral stomach tube from the 24 yaks selected. High-throughput sequencing of bacterial 16S rRNA gene was used.Results: Ruminal ammonia N, total volatile fatty acids, acetate, propionate, and isobutyrate concentrations were found to be higher in HH than LL yaks. Community richness (Chao 1 index) and diversity indices (Shannon index) of rumen microbiota were higher in LL than HH yaks. Relative abundances of the Bacteroidetes and Tenericutes phyla in the rumen fluid were significantly increased in HH than LL yaks, but significantly decreased for Firmicutes. Relative abundances of the Succiniclasticum, Butyrivibrio 2, Prevotella 1, and Prevotellaceae UCG-001 genera in the rumen fluid of HH yaks was significantly increased, but significantly decreased for Christensenellaceae R-7 group and Coprococcus 1. Principal coordinates analysis on unweighted UniFrac distances revealed that the bacterial community structure of rumen differed between yaks with high and low milk protein yields. Furthermore, rumen microbiota were functionally enriched in relation to transporters, ABC transporters, ribosome, and urine metabolism, and also significantly altered in HH and LL yaks.Conclusion: We observed significant differences in the composition, diversity, fermentation product concentrations, and function of ruminal microorganisms between yaks with high and low milk protein yields, suggesting the potential influence of rumen microbiota on milk protein yield in yaks. A deeper understanding of this process may allow future modulation of the rumen microbiome for improved agricultural yield through bacterial community design.
Abstract
Objective: Ruminants are completely dependent on their microbiota for rumen fermentation, feed digestion, and consequently, their metabolism for productivity. This study aimed to evaluate the rumen bacteria of lactating yaks with different milk protein yields, using high-throughput sequencing technology, in order to understand the influence of these bacteria on milk production. Methods: Yaks with similar high milk protein yield (high milk yield and high milk protein content, HH; n = 12) and low milk protein yield (low milk yield and low milk protein content, LL; n = 12) were randomly selected from 57 mid-lactation yaks. Ruminal contents were collected using an oral stomach tube from the 24 yaks selected. High-throughput sequencing of bacterial 16S rRNA gene was used. Results: Ruminal ammonia N, total volatile fatty acids, acetate, propionate, and isobutyrate concentrations were found to be higher in HH than LL yaks. Community richness (Chao 1 index) and diversity indices (Shannon index) of rumen microbiota were higher in LL than HH yaks. Relative abundances of the Bacteroidetes and Tenericutes phyla in the rumen fluid were significantly increased in HH than LL yaks, but significantly decreased for Firmicutes. Relative abundances of the Succiniclasticum, Butyrivibrio 2, Prevotella 1, and Prevotellaceae UCG-001 genera in the rumen fluid of HH yaks was significantly increased, but significantly decreased for Christensenellaceae R-7 group and Coprococcus 1. Principal coordinates analysis on unweighted UniFrac distances revealed that the bacterial community structure of rumen differed between yaks with high and low milk protein yields. Furthermore, rumen microbiota were functionally enriched in relation to transporters, ABC transporters, ribosome, and urine metabolism, and also significantly altered in HH and LL yaks. Conclusion: We observed significant differences in the composition, diversity, fermentation product concentrations, and function of ruminal microorganisms between yaks with high and low milk protein yields, suggesting the potential influence of rumen microbiota on milk protein yield in yaks. A deeper understanding of this process may allow future modulation of the rumen microbiome for improved agricultural yield through bacterial community design.
참고문헌 (52)
- Xue MY, "Assessment of rumen bacteria in dairy cows with varied milk protein yield", J Dairy Sci, 102, pp.5031~5041 (2019)[DOI]
- Baumgard LH, "A 100-year review : regulation of nutrient partitioning to support lactation", J Dairy Sci, 100, pp.10353~10366 (2017)[DOI]
- Hernandez-Sanabria E, "Correlation of particular bacterial PCR-denaturing gradient gel electrophoresis patterns with bovine ruminal fermentation parameters and feed efficiency traits", Appl Environ Microbiol, 76, pp.6338~6350 (2010)[DOI]
- Lima FS, "Prepartum and postpartum rumen fluid microbiomes : characterization and correlation with production traits in dairy cows", Appl Environ Microbiol, 81, pp.1327~1337 (2015)[DOI]
- Jami E, "Potential role of the bovine rumen microbiome in modulating milk composition and feed efficiency", PLoS One, 9, pp.e85423~ (2014)[DOI]
- Bergman EN, "Energy contributions of volatile fatty acids from the gastrointestinal tract in various species", Physiol Rev, 70, pp.567~590 (1990)[DOI]
- Hackmann TJ, "Maximizing efficiency of rumen microbial protein production", Front Microbiol, 6, pp.465~ (2015)[DOI]
- Hurtaud C, "Effect of infused volatile fatty acids and caseinate on milk composition and coagulation in dairy cows", J Dairy Sci, 76, pp.3011~3020 (1993)[DOI]
- E. E. Connor, "TRIENNIAL LACTATION SYMPOSIUM: Opportunities for improving milk production efficiency in dairy cattle1,2", Journal of Animal Science, 90(5), pp.1687~1694 (2012), Oxford University Press (OUP)[DOI]
- Arndt C, "Feed conversion efficiency in dairy cows : Repeatability, variation in digestion and metabolism of energy and nitrogen, and ruminal methanogens", J Dairy Sci, 98, pp.3938~3950 (2015)[DOI]
- Pryce JE, "Accuracy of genomic predictions of residual feed intake and 250-day body weight in growing heifers using 625, 000 single nucleotide polymorphism markers", J Dairy Sci, 95, pp.2108~2119 (2012)[DOI]
- VandeHaar MJ, "Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency", J Dairy Sci, 99, pp.4941~4954 (2016)[DOI]
- Jewell KA, "Ruminal bacterial community composition in dairy cows is dynamic over the course of multiple lactations and correlates with feed efficiency", Appl Environ Microbiol, 81, pp.4697710~ (2015)[DOI]
- Shabat SKB, "Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants", ISME J, 10, pp.2958~2972 (2016)[DOI]
- Fan QS, "Mineral nutritional status of yaks(Bos Grunniens)grazing on the Qinghai-Tibetan Plateau", Animals, 9, pp.468~ (2019)[DOI]
- Fan Q, "Chemical composition of milk and rumen microbiome diversity of yak, impacting by herbage grown at different phenological periods on the Qinghai-Tibet plateau", Animals, 10, pp.1030~ (2020)[DOI]
- Xia W, "Short communication : Characterization of gene expression profiles related to yak milk protein synthesis during the lactation cycle", J Dairy Sci, 101, pp.11150~11158 (2018)[DOI]
- Yang CY, "Grazing activity increases decomposition of yak dung and litter in an alpine meadow on the Qinghai-Tibet plateau", Plant Soil, 444, pp.239~250 (2019)[DOI]
- AOAC, "Official methods of analysis of the Association of Official Analytical Chemists International (17th ed.)", AOAC International, ~ (2002)
- National Food Safety Standard of China, "Determination of lactose and sucrose in foods for infants and young children milk and milk products : GB 5413. 21-2010", Ministry of Health of the People's Republic of China, ~ (2010)
- Van Soest PJ, "Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition", J Dairy Sci, 74, pp.3583~3597 (1991)[DOI]
- Ma L, "Yak rumen microbial diversity at different forage growth stages of an alpine meadow on the Qinghai-Tibet plateau", Peer J, 7, pp.e7645~ (2019)[DOI]
- Chaney AL, "Modified reagents for determination of urea and ammonia", Clin Chem, 8, pp.130~132 (1962)[DOI]
- Dennis KL, "Adenomatous polyps are driven by microbe-instigated focal inflammation and are controlled by IL-10-producing T cells", Cancer Res, 73, pp.5905~5913 (2013)[DOI]
- Magoč T, "FLASH : Fast length adjustment of short reads to improve genome assemblies", Bioinformatics, 27, pp.2957~2963 (2011)[DOI]
- Caporaso JG, "QIIME allows analysis of high-throughput community sequencing data", Nat Methods, 7, pp.335~336 (2010)[DOI]
- Edgar RC, "UPARSE : Highly accurate OTU sequences from microbial amplicon reads", Nat Methods, 10, pp.996~998 (2013)[DOI]
- Lozupone C, "UniFrac : A new phylogenetic method for comparing microbial communities", Appl Environ Microbiol, 71, pp.8228~8235 (2005)[DOI]
- Berry D, "Deciphering microbial interactions and detecting keystone species with co-occurrence networks", Front Microbiol, 5, pp.219~ (2014)[DOI]
- Aßhauer KP, "Tax4Fun : predicting functional profiles from metagenomic 16S rRNA data", Bioinformatics, 31, pp.2882~2884 (2015)[DOI]
- Kiddy CA, "A review of research on genetic variation in physiological characteristics related to performance in dairy cattle", J Dairy Sci, 62, pp.818~824 (1979)[DOI]
- Grant RJ, "Feeding behavior and management factors during the transition period in dairy cattle", J Anim Sci, 73, pp.2791~2803 (1995)[DOI]
- Xue D, "Rumen prokaryotic communities of ruminants under different feeding paradigms on the Qinghai-Tibetan Plateau", Syst Appl Microbiol, 40, pp.227~236 (2017)[DOI]
- Li F, "Metatranscriptomic profiling reveals linkages between the active rumen microbiome and feed efficiency in beef cattle", Appl Environ Microbiol, 83, pp.e00061-17~ (2017)[DOI]
- D.M. Bickhart, "Symposium review: Host–rumen microbe interactions may be leveraged to improve the productivity of dairy cows", Journal of Dairy Science, 101(8), pp.7680~7689 (2018), American Dairy Science Association[DOI]
- Purushe J, "Comparative genome analysis of Prevotella ruminicola and Prevotella bryantii : insights into their environmental niche", Microb Ecol, 60, pp.721~729 (2010)[DOI]
- Morotomi M, "Description of Christensenella minuta gen. nov., sp. nov., isolated from human faeces, which forms a distinct branch in the order Clostridiales, and proposal of Christensenellaceae fam. nov", Int J Syst Evol Microbiol, 62, pp.144~149 (2012)[DOI]
- Liu C, "Dynamic alterations in yak rumen bacteria community and metabolome characteristics in response to feed type", Front Microbiol, 10, pp.1116~ (2019)[DOI]
- Power ME, "Challenges in the quest for keystones : identifying keystone species is difficult-but essential to understanding how loss of species will affect ecosystems", BioSci, 46, pp.609~620 (1996)[DOI]
- Indugu N, "Comparison of rumen bacterial communities in dairy herds of different production", BMC Microbiol, 17, pp.190~ (2017)[DOI]
- Cunha CS, "Assessing the impact of rumen microbial communities on methane emissions and production traits in Holstein cows in a tropical climate", Syst Appl Microbiol, 40, pp.492~499 (2017)[DOI]
- Fernando SC, "Rumen microbial population dynamics during adaptation to a high-grain diet", Appl Environ Microbiol, 76, pp.7482~7490 (2010)[DOI]
- Wallace RJ, "The rumen microbial metagenome associated with high methane production in cattle", BMC Genomics, 16, pp.839~ (2015)[DOI]
- McCabe MS, "Illumina MiSeq phylogenetic amplicon sequencing shows a large reduction of an uncharacterised Succinivibrionaceae and an increase of the Methanobrevibacter gottschalkii Clade in feed restricted cattle", PLoS One, 10, pp.e0133234~ (2015)[DOI]
- Pope PB, "Isolation of Succinivibrionaceae implicated in low methane emissions from Tammar wallabies", Science, 333, pp.646~648 (2011)[DOI]
- Liu H, "Effects of glucose availability on expression of the key genes involved in synthesis of milk fat, lactose and glucose metabolism in bovine mammary epithelial cells", PLoS One, 8, pp.e66092~ (2013)[DOI]
- Martin R, "Early life : gut microbiota and immune development in infancy", Benef Microbes, 1, pp.367~382 (2010)[DOI]
- Kamke J, "Rumen metagenome and metatranscriptome analyses of low methane yield sheep reveals a Sharpea-enriched microbiome characterised by lactic acid formation and utilisation", Microbiome, 4, pp.56~ (2016)[DOI]
- Shi W, "Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome", Genome Res, 24, pp.1517~1525 (2014)[DOI]
- Zeng SZ, "Composition, diversity and function of intestinal microbiota in pacific white shrimp(Litopenaeus vannamei)at different culture stages", Peer J, 5, pp.e3986~ (2017)[DOI]
- Hamana K, "Covalently linked polyamines in the cell wall peptidoglycan of the anaerobes belonging to the order Selenomonadales", J Gen Appl Microbiol, 58, pp.339~347 (2012)[DOI]
- Xue MY, "Multi-omics reveals that the rumen microbiome and its metabolome together with the host metabolome contribute to individualized dairy cow performance", Microbiome, 8, pp.64~ (2020)[DOI]