Comparative investigation to analyse the critical role of NFE2L2 gene in heavy metal induced toxicity through in silico approaches

Background: Accumulation of heavy metals like copper, nickel, arsenic, cobalt, and cadmium are increasing day by day. Accumulation of these heavy metals poses serious threats to human health. Elemental toxicity percentage has been found to be increased day-by-day and creating different minor to major problems from tissue to the gene level. Different important gene expressions are altered due to the contamination of such heavy metals. The present study aimed to identify a common target gene that is involved in the toxicity of major heavy metals and to study the major impact of the gene on the concerned biological system. Methods: In the progression of the work, major genes involved in copper, nickel, arsenic, cobalt, and cadmium toxicity were listed through intense data curation, and a pathway showing the correlation and physical interaction of all the genes that were constructed using in-silico tools STRING and Gene Mania database. Further, functional and expression analysis of the discovered gene was done using in-silico tools like genome-wide association study (GWAS), genotype-tissue expression (GTEx), and RegulomeDB. Results: According to the network analysis, NFE2L2 was recognized as a common target involved in the above-mentioned heavy metals toxicity. Expression analysis revealed that the highest expression of NFE2L2 was observed in tissues of oesophagus, ovary, bladder, vagina, thyroid, and skin. Detailed investigation at the pathway level revealed that the involvement was importantly observed in immunodeficiency and developmental delay. Conclusion: The study opened a wide vision that the major target of such toxicants is various pathways of neurobiological distress and biological processes, and hence, it can be considered as a susceptible target for heavy metals-induced toxicity.

Comparative investigation to analyse the critical role of NFE2L2 gene in heavy metal induced toxicity through in silico approaches Keywords:

Heavy metals , Brain , Gene expression , Environmental pollutants