Mass SPectrometr Y ●●●●T i t l e●●●● DOI: 10.5702/massspectrometry.K0007

Vol. 3 (2014), K0007

Foreword Takaaki Nishioka Principal Organizer of the 2nd Critical Assessment of Small Molecule Identification (CASMI2013)

Mass spectrometry (MS) is a key analytical tool in metabolomics. The target of metabolomics is small molecules in biological samples. The tissues and blood of the human body, for example, typically contain not only endogenously synthesized human metabolites but also exogenous natural or artificial small molecules derived from foods and drugs. No complete list of small molecules in human cells is available and predictable from human genomic DNA sequences. Hence, the identification of small molecules detected by MS is dependent on searching databases that contain a collection of mass spectral data of known chemical compounds. The chemical coverage of such spectral data in the spectral databases is, however, only a small fraction of the small molecules that have been detected by MS. Most of the molecules detected are left unidentified, as unknown molecules. Thus, the chemical identification is regarded as a significant bottleneck in metabolomics. Accurate MS1 and MS2 data are rapidly increasing in mass spectral databases, although the chemical coverage of the accurate spectral data in the databases has not improved as rapidly. When the molecular formula of an unknown molecule is identified from the isotope peaks of accurate MS1 data, the candidates of the chemical structure of an unknown metabolite are retrieved by using the molecular formula from comprehensive chemical substance databases and could be further refined by interpreting MS2 data with automated tools. Consequently, researchers of metabolomics have great expectations for automated tools as alternative methods in the identification of small molecules—the bottleneck in metabolomics could be removed. In recent years, much progress has been made in developing automated tools for chemical identification. The first Critical Assessment of Small Molecular Identification (CASMI) contest, to evaluate the performance of automated tools for chemical identification, was initiated by Emma Schymanski and Steffen Newman in 2012. The contest participants interpreted, manually or automatically, blind MS1 and MS2 data provided as the challenges, and then had to determine the molecular formula and the chemical structure of the challenge molecules. The second contest, CASMI2013, was organized by 10 Japanese researchers and sponsored by the Spectral Data Division of the Mass Spectrometry Society of Japan. A total of 16 challenge molecules with their MS1 and MS2 data, analyzed with a mass accuracy ≤10 ppm, were released as the contest challenges to the public on September 2, 2013. The challenge molecules included metabolites, agrochemicals, environmental chemicals, and synthetic small molecules. The mass range of the challenge molecules was 210–1,442 Da. By the entry deadline of December 15, 2013, seven teams had submitted their solution candidates to the CASMI2013 organizers. The challenge molecules and their chemical structures were announced on January 1, 2014. The winner of CASMI2013, a team of Andrew Newsome and Dejan Nikolic, was announced on February 15, 2014. The winning team and four other teams submitted their manuscripts by March 31, 2014, which was the deadline for manuscript submission to the CASMI special issue in Mass Spectrometry. The winning team, which manually identified the solutions, reported how to reach the solutions by manually interpreting the data of each challenge. The other four teams, who developed their own automated tools, reported the state of the art of their automated tools and analyzed the reasons why their automated tools failed to identify some of the challenge molecules. In a research article, the CASMI2013 organizers (as the authors) reported that they analyzed the challenge data and revealed the reasons why some of the challenges were successfully solved, or not solved, by automated tools. In addition, one of the organizers reported a commentary that reviewed current problems associated with automated tools from three points of view.

© 2014 The Mass Spectrometry Society of Japan

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