In silico evaluation of PCB toxicity by integrative bioinformatics approach for food contaminants biomarker identification

Many diseases are the outcome of a complex inter-relationship between multiple genetic and environmental factors. Research suggests that individual susceptibility is influenced more by certain genes than by exposure to environmental agents. The startup of Human genome project has induced the activation, by NIEHS, of a companion project: the Enviromental Genomic Project (EGP). The main goal of EGP is to better understand how individuals differ in their susceptibility to environmental agents and how these susceptibilities change over time,taking genetic variability into account. The new 'omics' technologies have enhanced the capability to massively screen thousand of genes or proteins at the same time. The capability to screen thousand genes at time allows to speed up the identification of biomarkers, not only as single molecule but also in their functional context (metabolic level). In this study we investigated, by using an integrated ‘in silico’ and ‘in vitro’ analysis, the possible use of biomarkers of exposure to Polychlorinated Biphenyls (PCBs) and Polycyclic Aromatic Hydrocarbons (PAHs) on multipotent preadipocites in a complex food matrix by using a double bioinformatics/genomics approach. Experimental data constitute the basic knowledge for ‘integrative bioinformatics’ analysis. In this study we have combined and analysed the results of two different data mining processes: 1) Bioinformatics data mining that has been performed on some publically available databases (PubChem, KEGG, PharmaKb). 2) Chemoinformatics data by screening the Chemical Abstract Systems. The results of two ‘in silico’ analysis has been used to rank food contaminant taking their preferential cellular and tissue target into account.