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Livestock metabolomics and the livestock metabolome: A systematic review
Open accessAbstract
Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.
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“To date, the majority of rumen metabolome studies have used liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR), with the latter the most used due to reliability and absolute quantification (Goldansaz et al., 2017).”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Goldansaz et al., 2017
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Cites
Metabolomics—the link between genotypes and phenotypes
Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445
HMDB: the Human Metabolome Database
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl923 · Cited by 3,219
Self-citationMetabolomics — the link between genotypes and phenotypes
Fiehn, O. (2002) · Springer eBooks · doi:10.1007/978-94-010-0448-0_11 · Cited by 3,168
HMDB 3.0—The Human Metabolome Database in 2013
Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., Djoumbou-Feunang, Y., Mandal, R., Aziat, F., Dong, E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1065 · Cited by 2,845
Self-citationMetabolomics: beyond biomarkers and towards mechanisms
Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.25 · Cited by 2,829
Livestock production: recent trends, future prospects
Thornton, P. K. (2010) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2010.0134 · Cited by 2,217
HMDB: a knowledgebase for the human metabolome
Wishart, D. S., Knox, C., Guo, A. C., Eisner, R., Young, N., Gautam, B., Hau, D., Psychogios, N., Dong, E., Bouatra, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn810 · Cited by 1,874
Self-citationPsychogios, N., Hau, D., Peng, J., Guo, A. C., Mandal, R., Bouatra, S., Sinelnikov, I. V., Krishnamurthy, R., Eisner, R., Gautam, B., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016957 · Cited by 1,779
Self-citationBouatra, S., Aziat, F., Mandal, R., Guo, A. C., Wilson, M. R., Knox, C., Bjorndahl, T. C., Krishnamurthy, R., Saleem, F., Liu, P., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073076 · Cited by 1,530
Self-citationMetabolomics--the link between genotypes and phenotypes.
Fiehn, O. (2002) · PubMed · Cited by 1,517
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Huws, S. A., Creevey, C. J., Oyama, L. B., Mizrahi, I., Denman, S. E., Popova, M., Muñoz-Tamayo, R., Forano, E., Waters, S. M., Hess, M., et al. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.02161 · Cited by 487
Review: Ruminal microbiome and microbial metabolome: effects of diet and ruminant host
Newbold, C. J., & Ramos‐Morales, E. (2020) · animal · doi:10.1017/s1751731119003252 · Cited by 289
Review: Enhancing gastrointestinal health in dairy cows
Plaizier, J. C. B., Mesgaran, M. D., Derakhshani, H., Golder, H. M., Khafipour, E., Kleen, J. L., Lean, I. J., Loor, J. J., Penner, G. B., & Zebeli, Q. (2018) · animal · doi:10.1017/s1751731118001921 · Cited by 249
Metabolomic selection for enhanced fruit flavor
Colantonio, V., Ferrão, L. F. V., Tieman, D. M., Bliznyuk, N., Sims, C. A., Klee, H. J., Muńoz, P., & Resende, M. F. R. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2115865119 · Cited by 219
Translational Metabolomics: Current Challenges and Future Opportunities
Pinu, F. R., Goldansaz, S. A., & Jaine, J. (2019) · Metabolites · doi:10.3390/metabo9060108 · Cited by 233
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Metadata
- Authors
- Goldansaz, S. A., Guo, A. C., Sajed, T., Steele, M. A., Plastow, G. S., & Wishart, D. S.
- Affiliations
- University of Alberta (CA)
- Corresponding author
- Wishart, David S.
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-05-22
- Volume
- 12
- Issue
- 5
- Pages
- e0177675
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC5439675
- OpenAlex
- W2619865607
- Cited by
- 379
- References
- 100
- Citations by year
- 2026: 42 · 2025: 49 · 2024: 36 · 2023: 46 · 2022: 51 · 2021: 60 · 2020: 50 · 2019: 25 · 2018: 19 · 2017: 1
- FWCI
- 2.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Genome Canada
- Genome Alberta
- Alberta Livestock and Meat Agency
- Agriculture Funding Consortium
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
- Keywords
- animal health assessment, disease diagnosis, biomarker discovery, feed efficiency, milk production, growth potential, cattle, sheep, goats, horses, pigs, metabolite quantification
- MeSH terms
- Animals, Cattle, Goats, Horses, Sheep, Swine, Internet, Quantitative Trait Loci, Metabolomics, Metabolome, Livestock, Databases, Chemical
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