An Integrative Multi-Omics Workflow to Address Multifactorial Toxicology Experiments

摘要: Toxicology studies can take advantage of omics approaches to better understand the phenomena underlying phenotypic alterations induced by different types exposure certain toxicants. Nevertheless, in order analyse data generated from multifactorial studies, dedicated analysis tools are needed. In this work, we propose a new workflow comprising both factor deconvolution and integration multiple analytical platforms. As case study, 3D neural cell cultures were exposed trimethyltin (TMT) relevance culture maturation state, duration, as well TMT concentration simultaneously studied using metabolomic approach combining four complementary techniques (reversed-phase LC hydrophilic interaction LC, hyphenated mass spectrometry positive negative ionization modes). The ANOVA multiblock OPLS (AMOPLS) method allowed us decompose quantify contribution experimental factors on outcome exposure. Results showed that most important overall metabolic variability came state treatment duration. Even though effects represented smallest observed modulation among three factors, it was highly statistically significant. MetaCore™ pathway tool revealed TMT-induced biosynthetic pathways neuronal differentiation signaling processes, with predominant deleterious effect GABAergic glutamatergic neurons. This confirmed proteomic data, increasing confidence mechanistic understanding such toxicant