Literature DB >> 28025166

Considerations when choosing a genetic model organism for metabolomics studies.

Laura K Reed1, Charles F Baer2, Arthur S Edison3.   

Abstract

Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.
Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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Year:  2016        PMID: 28025166      PMCID: PMC5337163          DOI: 10.1016/j.cbpa.2016.12.005

Source DB:  PubMed          Journal:  Curr Opin Chem Biol        ISSN: 1367-5931            Impact factor:   8.822


  82 in total

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Authors:  Sarah K Davies; Armand Leroi; Austin Burt; Jacob G Bundy; Charles F Baer
Journal:  Evolution       Date:  2016-08-24       Impact factor: 3.694

2.  A shortcut to identifying small molecule signals that regulate behavior and development in Caenorhabditis elegans.

Authors:  Chirag Pungaliya; Jagan Srinivasan; Bennett W Fox; Rabia U Malik; Andreas H Ludewig; Paul W Sternberg; Frank C Schroeder
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-03       Impact factor: 11.205

3.  Mutation Is a Sufficient and Robust Predictor of Genetic Variation for Mitotic Spindle Traits in Caenorhabditis elegans.

Authors:  Reza Farhadifar; José Miguel Ponciano; Erik C Andersen; Daniel J Needleman; Charles F Baer
Journal:  Genetics       Date:  2016-06-22       Impact factor: 4.562

4.  Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster.

Authors:  Caroline M Williams; Miki Watanabe; Mario R Guarracino; Maria B Ferraro; Arthur S Edison; Theodore J Morgan; Arezue F B Boroujerdi; Daniel A Hahn
Journal:  Evolution       Date:  2014-11-20       Impact factor: 3.694

5.  Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.

Authors:  Norbert Hubner; Caroline A Wallace; Heike Zimdahl; Enrico Petretto; Herbert Schulz; Fiona Maciver; Michael Mueller; Oliver Hummel; Jan Monti; Vaclav Zidek; Alena Musilova; Vladimir Kren; Helen Causton; Laurence Game; Gabriele Born; Sabine Schmidt; Anita Müller; Stuart A Cook; Theodore W Kurtz; John Whittaker; Michal Pravenec; Timothy J Aitman
Journal:  Nat Genet       Date:  2005-02-13       Impact factor: 38.330

6.  The Drosophila melanogaster Genetic Reference Panel.

Authors:  Trudy F C Mackay; Stephen Richards; Eric A Stone; Antonio Barbadilla; Julien F Ayroles; Dianhui Zhu; Sònia Casillas; Yi Han; Michael M Magwire; Julie M Cridland; Mark F Richardson; Robert R H Anholt; Maite Barrón; Crystal Bess; Kerstin Petra Blankenburg; Mary Anna Carbone; David Castellano; Lesley Chaboub; Laura Duncan; Zeke Harris; Mehwish Javaid; Joy Christina Jayaseelan; Shalini N Jhangiani; Katherine W Jordan; Fremiet Lara; Faye Lawrence; Sandra L Lee; Pablo Librado; Raquel S Linheiro; Richard F Lyman; Aaron J Mackey; Mala Munidasa; Donna Marie Muzny; Lynne Nazareth; Irene Newsham; Lora Perales; Ling-Ling Pu; Carson Qu; Miquel Ràmia; Jeffrey G Reid; Stephanie M Rollmann; Julio Rozas; Nehad Saada; Lavanya Turlapati; Kim C Worley; Yuan-Qing Wu; Akihiko Yamamoto; Yiming Zhu; Casey M Bergman; Kevin R Thornton; David Mittelman; Richard A Gibbs
Journal:  Nature       Date:  2012-02-08       Impact factor: 49.962

Review 7.  Microbial laboratory evolution in the era of genome-scale science.

Authors:  Tom M Conrad; Nathan E Lewis; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2011-07-05       Impact factor: 11.429

8.  Mapping an atlas of tissue-specific Drosophila melanogaster metabolomes by high resolution mass spectrometry.

Authors:  Venkateswara R Chintapalli; Mohammed Al Bratty; Dominika Korzekwa; David G Watson; Julian A T Dow
Journal:  PLoS One       Date:  2013-10-29       Impact factor: 3.240

9.  13C Metabolomics: NMR and IROA for Unknown Identification.

Authors:  Chaevien S Clendinen; Gregory S Stupp; Bing Wang; Timothy J Garrett; Arthur S Edison
Journal:  Curr Metabolomics       Date:  2016-08

10.  Finding the sources of missing heritability in a yeast cross.

Authors:  Joshua S Bloom; Ian M Ehrenreich; Wesley T Loo; Thúy-Lan Võ Lite; Leonid Kruglyak
Journal:  Nature       Date:  2013-02-03       Impact factor: 49.962

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  4 in total

Review 1.  Understanding Inborn Errors of Metabolism through Metabolomics.

Authors:  Karen Driesen; Peter Witters
Journal:  Metabolites       Date:  2022-04-27

2.  Metabolomics and lipidomics in Caenorhabditis elegans using a single-sample preparation.

Authors:  Marte Molenaars; Bauke V Schomakers; Hyung L Elfrink; Arwen W Gao; Martin A T Vervaart; Mia L Pras-Raves; Angela C Luyf; Reuben L Smith; Mark G Sterken; Jan E Kammenga; Antoine H C van Kampen; Georges E Janssens; Frédéric M Vaz; Michel van Weeghel; Riekelt H Houtkooper
Journal:  Dis Model Mech       Date:  2021-04-27       Impact factor: 5.758

Review 3.  From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data.

Authors:  Julijana Ivanisevic; Elizabeth J Want
Journal:  Metabolites       Date:  2019-12-17

4.  Metabolomic analysis of tomato seed germination.

Authors:  Rashid H Kazmi; Leo A J Willems; Ronny V L Joosen; Noorullah Khan; Wilco Ligterink; Henk W M Hilhorst
Journal:  Metabolomics       Date:  2017-10-23       Impact factor: 4.290

  4 in total

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