The development of a database for metabolomics - looking back on ten years of experience. (2015)

• Record Type: Journal Article
• Authors: Ravenzwaay, Bennard Van; Kamp, Hennicke; Montoya-Parra, Gina Alejandra; Strauss, Volker; Fabian, Eric; Mellert, Werner; Krennrich, Gerhard; Walk, Tilmann; Peter, Erik; Looser, Ralf; Herold, Michael
• Is Part Of: International journal of biotechnology. Volume 14 Number 1(2015)
• Page Start: 47
• Page End: 68
• Publication Date: 2015
• Subjects: metabolomics database -- chemical MOA -- mode of action -- statistics -- quality assurance -- toxicity prediction -- metabolite patterns -- pairwise comparison -- biochemical pathways -- normality -- variability control -- signal to noise ratio -- SNR -- joint assessment; Biotechnology -- Economic aspects -- Periodicals; Biotechnology -- Research -- Periodicals; 338.47660605
• Languages: English
• ISSNs: 0963-6048

Abstract

Metabolome profiles of ca. 750 compounds obtained from blood samples from 28 day rat studies (OECD 407) were combined with toxicity profiles in one database over ten years to predict toxicity of new compounds. We provide detailed descriptions of procedures and recommendations for 'omics data-bases. Control of variability (biological, sampling/storage and technical measurement) is essential. At the start of large scale projects control variability should be extensively investigated. Reference (positive control) substances should be used to evaluate and obtain a good signal/noise ratio. Procedures should be documented in standard operating procedures and followed meticulously. Exact repeats of positive controls should be regularly performed, to assess variability of positive responses. Control data should be regularly checked for shifts and analysed to obtain information concerning normality. If possible, data should be analysed by multiple procedures and conclusions should be drawn based on a joint assessment, not unlike peer review processes in histopathology.