Effect of Yak Milk on Intestinal Microbiota and Metabolism in Mice
Abstract
In order to investigate the effect of long-term consumption of yak milk on the intestinal flora and metabolism and to explore the correlation between acclimation to monodiet and yak milk intake in high-altitude pastoral areas, this study used metagenomics and metabolomics to evaluate the gut microbial community structure and metabolites of mice fed yak milk or Holstein cow milk. Results showed that compared with the control group (normal saline solution), at the phylum level, ingestion of yak milk improved the relative abundance of Actinobacteria (33.27%), Bacteroidetes (24.31%) and Verrucomicrobia (11.08%), while ingestion of Holstein cow milk increased the relative abundance of Firmicutes (43.74%) and Bacteroidetes (24.75%). At the genus level, yak milk consumption increased the relative abundance of Ackermania (11.80%), Bacteroides (6.09%) and Limosilactobacillus (4.77%), while Holstein cow milk consumption increased the relative abundance of Lactobacillus (28.62%), Duncaniella (6.15%) and Limosilactobacillus (6.49%). Both yak and Holstein cow milk up-regulated carbohydrate and nucleotide metabolism. Furthermore, yak milk significantly up-regulated amino acid metabolism, cofactor and vitamin metabolism, energy metabolism, the biosynthesis of secondary metabolites, and the biosynthesis and metabolism of peptidoglycan. Metabolomics revealed that yak milk increased the contents of metabolites such as VB1, (+/-) 12 (13)-DiHOME, coenzyme Q2 and sulfonymethazine, as well as steroid hormone biosynthesis, cofactor biosynthesis, 2-oxyarboxylate metabolism, VB6 metabolism and phenylalanine metabolism in mice. Investigation of intestinal tissue morphology showed that the intestinal wall became thicker with increasing diversity and richness of the gut microbiota and the intestinal villi became longer and denser without deformity or breakage. In conclusion, yak milk has a positive effect on the intestinal flora and metabolism in mice, and this study provides a scientific basis for further development and utilization of yak milk.
References
BODE L. Human milk oligosaccharides: every baby needs a sugar mama[J]. Glycobiology, 2012, 22(9): 1147-1162. DOI:10.1093/glycob/cws074.
WALSH C, LANE J A, VAN SINDEREN D, et al. Human milk oligosaccharides: shaping the infant gut microbiota and supporting health[J]. Journal of Functional Foods, 2020, 72: 104074. DOI:10.1016/j.jff.2020.104074.
CHARBONNEAU M R, O’DONNELL D, BLANTON L V, et al. Sialylated milk oligosaccharides promote microbiota-dependent growth in models of infant undernutrition[J]. Cell, 2016, 164(5): 859-871. DOI:10.1016/j.cell.2016.01.024.
HOPPE C, MØLGAARD C, JUUL A, et al. High intakes of skimmed milk, but not meat, increase serum IGF-I and IGFBP-3 in eight-year-old boys[J]. European Journal of Clinical Nutrition, 2004, 58(9): 1211-1216. DOI:10.1038/sj.ejcn.1601948.
BARTOK C J, VENTURA A K. Mechanisms underlying the association between breastfeeding and obesity[J]. International Journal of Pediatric Obesity, 2009, 4(4): 196-204. DOI:10.3109/17477160902763309.
FAN Y, PEDERSEN O J N R M. Gut microbiota in human metabolic health and disease[J]. Nature Reviews Microbiology, 2021, 19(1): 55-71. DOI:10.1038/s41579-020-0433-9.
KOH A, DE VADDER F, KOVATCHEVA-DATCHARY P, et al. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites[J]. Cell, 2016, 165(6): 1332-1345. DOI:10.1016/j.cell.2016.05.041.
BELKAID Y, HAND T W. Role of the microbiota in immunity and inflammation[J]. Cell, 2014, 157(1): 121-141. DOI:10.1016/j.cell.2014.03.011.
ZHANG C, JIAO S, WANG Z A, et al. Exploring effects of chitosan oligosaccharides on mice gut microbiota in in vitro fermentation and animal model[J]. Frontiers in Microbiology, 2018, 9: 2388. DOI:10.3389/fmicb.2018.02388.
DELANEY C, VEENA C L R, BUTCHER M C, et al. Limitations of using 16S rRNA microbiome sequencing to predict oral squamous cell carcinoma[J]. APMIS, 2023, 131(6): 262-276. DOI:10.1111/apm.13315.
FABI P, ILKKA P, SAMI Ä, et al. H&E multi-laboratory staining variance exploration with machine learning[J]. Applied Sciences, 2022, 12(15): 7511. DOI:10.3390/app12157511.
BOLGER A M, LOHSE M, USADEL B. Trimmomatic: a flexible trimmer for Illumina sequence data[J]. Bioinformatics, 2014, 30(15): 2114-2120. DOI:10.1093/bioinformatics/btu170.
LANGMEAD B, SALZBERG S L. Fast gapped-read alignment with Bowtie 2[J]. Nature Methods, 2012, 9(4): 357-359. DOI:10.1038/nmeth.1923.
SEGATA N, IZARD J, WALDRON L, et al. Metagenomic biomarker discovery and explanation[J]. Genome Biology, 2011, 12: 1-18. DOI:10.1186/gb-2011-12-6-r60.
ZHU W, LOMSADZE A, BORODOVSKY M. Ab initio gene identification in metagenomic sequences[J]. Nucleic Acids Research, 2010, 38(12): e132. DOI:10.1093/nar/gkq275.
KIM J, KIM M S, KOH A Y, et al. FMAP: functional mapping and analysis pipeline for metagenomics and metatranscriptomics studies[J]. BMC Bioinformatics, 2016, 17: 1-8. DOI:10.1186/s12859-016-1278-0.
FRANZOSA E A, MCIVER L J, RAHNAVARD G, et al. Species-level functional profiling of metagenomes and metatranscriptomes[J]. Nature Methods, 2018, 15(11): 962-968. DOI:10.1038/s41592-018-0176-y.
BOLGER A M, LOHSE M, USADEL B. Trimmomatic: a flexible trimmer for Illumina sequence data[J]. Bioinformatics, 2014, 30(15): 2114-2120. DOI:10.1093/bioinformatics/btu170.
WOOD D E, SALZBERG S L. Kraken: ultrafast metagenomic sequence classification using exact alignments[J]. Genome Biology, 2014, 15: 1-12. DOI:10.1186/gb-2014-15-3-r46.
LU J, BREITWIESER F P, THIELEN P, et al. Bracken: estimating species abundance in metagenomics data[J]. PeerJ Computer Science, 2017, 3: e104. DOI:10.7717/peerj-cs.104.
MARTÍNEZ J L, COQUE T M, BAQUERO F. What is a resistance gene? ranking risk in resistomes[J]. Nature Reviews Microbiology, 2015, 13(2): 116-123. DOI:10.1038/nrmicro3399.
KHORRAMINEZHAD L, LECLERCQ M, O’CONNOR S, et al. Dairy product intake modifies gut microbiota composition among hyperinsulinemic individuals[J]. European Journal of Nutrition, 2021, 60: 159-167. DOI:10.1007/s00394-020-02226-z.
ECKBURG P B, BIK E M, BERNSTEIN C N, et al. Diversity of the human intestinal microbial flora[J]. Science, 2005, 308: 1635-1638. DOI:10.1126/science.1110591.
O’CALLAGHAN A, VAN SINDEREN D. Bifidobacteria and their role as members of the human gut microbiota[J]. Frontiers in Microbiology, 2016, 7: 206360. DOI:10.3389/fmicb.2016.00925.
EVERARD A, BELZER C, GEURTS L, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls dietinduced obesity[J]. Proceedings of the National Academy of Sciences, 2013, 110(22): 9066-9071. DOI:10.1073/pnas.1219451110.
XU J, MAHOWALD M A, LEY R E, et al. Evolution of symbiotic bacteria in the distal human intestine[J]. PLoS Biology, 2007, 5(7): e156. DOI:10.1371/journal.pbio.0050156.
MANZETTI S, ZHANG J, VAN DER SPOEL D. Thiamin function, metabolism, uptake, and transport[J]. Biochemistry, 2014, 53(5): 821-835. DOI:10.1021/bi401618y.
TURUNEN M, OLSSON J, DALLNER G. Metabolism and function of coenzyme Q[J]. Biochimica et Biophysica Acta (BBA)-Biomembranes, 2004, 1660(1/2): 171-199. DOI:10.1016/j.bbamem.2003.11.012.
MOZAFFARIAN D, HAO T, RIMM E B, et al. Changes in diet and lifestyle and long-term weight gain in women and men[J]. New England Journal of Medicine, 2011, 364(25): 2392-2404. DOI:10.1056/NEJMoa1014296.
PAN A, SUN Q, BERNSTEIN A M, et al. Red meat consumption and mortality: results from 2 prospective cohort studies[J]. Archives of Internal Medicine, 2012, 172(7): 555-563. DOI:10.1001/archinternmed.2011.2287.
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