Literature DB >> 26819881

Rethinking Mass Spectrometry-Based Small Molecule Identification Strategies in Metabolomics.

Fumio Matsuda1.   

Abstract

The CASMI 2013 (Critical Assessment of Small Molecule Identification 2013, http://casmi-contest.org/) contest was held to systematically evaluate strategies used for mass spectrometry-based identification of small molecules. The results of the contest highlight that, because of the extensive efforts made towards the construction of databases and search tools, database-assisted small molecule identification can now automatically annotate some metabolite signals found in the metabolome data. In this commentary, the current state of metabolite annotation is compared with that of transcriptomics and proteomics. The comparison suggested that certain limitations in the metabolite annotation process need to be addressed, such as (i) the completeness of the database, (ii) the conversion between raw data and structure, (iii) the one-to-one correspondence between measured data and correct search results, and (iv) the false discovery rate in database search results.

Keywords:  database; false discovery rate; metabolomics; small molecule identification

Year:  2014        PMID: 26819881      PMCID: PMC4321339          DOI: 10.5702/massspectrometry.S0038

Source DB:  PubMed          Journal:  Mass Spectrom (Tokyo)        ISSN: 2186-5116


  35 in total

1.  KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research.

Authors:  Farit Mochamad Afendi; Taketo Okada; Mami Yamazaki; Aki Hirai-Morita; Yukiko Nakamura; Kensuke Nakamura; Shun Ikeda; Hiroki Takahashi; Md Altaf-Ul-Amin; Latifah K Darusman; Kazuki Saito; Shigehiko Kanaya
Journal:  Plant Cell Physiol       Date:  2011-11-28       Impact factor: 4.927

2.  Prediction of error associated with false-positive rate determination for peptide identification in large-scale proteomics experiments using a combined reverse and forward peptide sequence database strategy.

Authors:  Edward L Huttlin; Adrian D Hegeman; Amy C Harms; Michael R Sussman
Journal:  J Proteome Res       Date:  2007-01       Impact factor: 4.466

Review 3.  Transcriptomics in the RNA-seq era.

Authors:  Paul A McGettigan
Journal:  Curr Opin Chem Biol       Date:  2013-01-02       Impact factor: 8.822

4.  Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes.

Authors:  S Karlin; S F Altschul
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

Review 5.  Next-generation sequencing platforms.

Authors:  Elaine R Mardis
Journal:  Annu Rev Anal Chem (Palo Alto Calif)       Date:  2013       Impact factor: 10.745

6.  Metabolite identification and quantitation in LC-MS/MS-based metabolomics.

Authors:  Jun Feng Xiao; Bin Zhou; Habtom W Ressom
Journal:  Trends Analyt Chem       Date:  2012-02-01       Impact factor: 12.296

7.  Basic analytical systems for lipidomics by mass spectrometry in Japan.

Authors:  Ryo Taguchi; Mashahiro Nishijima; Takao Shimizu
Journal:  Methods Enzymol       Date:  2007       Impact factor: 1.600

8.  In silico fragmentation for computer assisted identification of metabolite mass spectra.

Authors:  Sebastian Wolf; Stephan Schmidt; Matthias Müller-Hannemann; Steffen Neumann
Journal:  BMC Bioinformatics       Date:  2010-03-22       Impact factor: 3.169

9.  Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity.

Authors:  Fumio Matsuda; Ryo Nakabayashi; Yuji Sawada; Makoto Suzuki; Masami Y Hirai; Shigehiko Kanaya; Kazuki Saito
Journal:  Front Plant Sci       Date:  2011-08-22       Impact factor: 5.753

10.  HMDB: the Human Metabolome Database.

Authors:  David S Wishart; Dan Tzur; Craig Knox; Roman Eisner; An Chi Guo; Nelson Young; Dean Cheng; Kevin Jewell; David Arndt; Summit Sawhney; Chris Fung; Lisa Nikolai; Mike Lewis; Marie-Aude Coutouly; Ian Forsythe; Peter Tang; Savita Shrivastava; Kevin Jeroncic; Paul Stothard; Godwin Amegbey; David Block; David D Hau; James Wagner; Jessica Miniaci; Melisa Clements; Mulu Gebremedhin; Natalie Guo; Ying Zhang; Gavin E Duggan; Glen D Macinnis; Alim M Weljie; Reza Dowlatabadi; Fiona Bamforth; Derrick Clive; Russ Greiner; Liang Li; Tom Marrie; Brian D Sykes; Hans J Vogel; Lori Querengesser
Journal:  Nucleic Acids Res       Date:  2007-01       Impact factor: 16.971

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  5 in total

1.  Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.

Authors:  Xusheng Wang; Drew R Jones; Timothy I Shaw; Ji-Hoon Cho; Yuanyuan Wang; Haiyan Tan; Boer Xie; Suiping Zhou; Yuxin Li; Junmin Peng
Journal:  J Proteome Res       Date:  2018-05-29       Impact factor: 4.466

2.  Technical Challenges in Mass Spectrometry-Based Metabolomics.

Authors:  Fumio Matsuda
Journal:  Mass Spectrom (Tokyo)       Date:  2016-11-25

Review 3.  Untargeted Metabolomics Strategies-Challenges and Emerging Directions.

Authors:  Alexandra C Schrimpe-Rutledge; Simona G Codreanu; Stacy D Sherrod; John A McLean
Journal:  J Am Soc Mass Spectrom       Date:  2016-09-13       Impact factor: 3.109

4.  Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

Authors:  Anna Marco-Ramell; Magali Palau-Rodriguez; Ania Alay; Sara Tulipani; Mireia Urpi-Sarda; Alex Sanchez-Pla; Cristina Andres-Lacueva
Journal:  BMC Bioinformatics       Date:  2018-01-02       Impact factor: 3.169

5.  A Perspective and Framework for Developing Sample Type Specific Databases for LC/MS-Based Clinical Metabolomics.

Authors:  Nichole A Reisdorph; Scott Walmsley; Rick Reisdorph
Journal:  Metabolites       Date:  2019-12-21
  5 in total

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