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      Livestock metabolomics and the livestock metabolome: A systematic review

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          Abstract

          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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          Most cited references82

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          Metabolomics--the link between genotypes and phenotypes.

          Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms 'transcriptome' and proteome', the set of metabolites synthesized by a biological system constitute its 'metabolome'. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.
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            HMDB: a knowledgebase for the human metabolome

            The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.
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              Heavy metals and living systems: An overview

              Heavy metals are natural constituents of the earth's crust, but indiscriminate human activities have drastically altered their geochemical cycles and biochemical balance. This results in accumulation of metals in plant parts having secondary metabolites, which is responsible for a particular pharmacological activity. Prolonged exposure to heavy metals such as cadmium, copper, lead, nickel, and zinc can cause deleterious health effects in humans. Molecular understanding of plant metal accumulation has numerous biotechnological implications also, the long term effects of which might not be yet known.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 May 2017
                2017
                : 12
                : 5
                : e0177675
                Affiliations
                [1 ]Department of Agriculture, Food and Nutritional Sciences, University of Alberta, Edmonton, Alberta, Canada
                [2 ]Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
                [3 ]Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada
                Wageningen UR Livestock Research, NETHERLANDS
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: SAG DSW MAS GSP.

                • Data curation: SAG.

                • Formal analysis: SAG ACG TS.

                • Funding acquisition: SAG DSW GSP.

                • Investigation: SAG.

                • Methodology: SAG DSW.

                • Project administration: SAG DSW.

                • Resources: SAG DSW.

                • Software: SAG ACG TS.

                • Supervision: SAG DSW.

                • Validation: SAG.

                • Visualization: SAG.

                • Writing – original draft: SAG.

                • Writing – review & editing: SAG DSW MAS GSP.

                Author information
                http://orcid.org/0000-0002-9051-3680
                Article
                PONE-D-16-41397
                10.1371/journal.pone.0177675
                5439675
                28531195
                bf710149-5bc1-4d5e-8fd4-1362a48dcbcc
                © 2017 Goldansaz et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 October 2016
                : 1 May 2017
                Page count
                Figures: 4, Tables: 4, Pages: 26
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100008762, Genome Canada;
                Award Recipient :
                Funded by: Genome Alberta
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002715, Alberta Livestock and Meat Agency;
                Award Recipient :
                Funded by: Agriculture Funding Consortium
                Award Recipient :
                Funding for this research has been provided by Genome Canada (to DSW), Genome Alberta (to DSW), Alberta Livestock and Meat Agency (to SAG) and Agriculture Funding Consortium (to SAG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolomics
                Biology and Life Sciences
                Agriculture
                Livestock
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolites
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Biology and Life Sciences
                Veterinary Science
                Veterinary Diseases
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Equines
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Bovines
                Cattle
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Cattle
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Sheep
                Custom metadata
                All of the livestock metabolomics data are available with open access online at The Livestock Metabolome Database ( www.lmdb.ca).

                Uncategorized
                Uncategorized

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