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Marathe, R.

Publications and source records attributed to Marathe, R..

3 recordsLinked to original sources

High-throughput Virtual Screen of Endocrine-disrupting Chemicals Identifies Disruptors of EGFR Signaling

Chemical exposures during pregnancy are linked to an increased risk of pregnancy complications that contribute significantly to maternal and infant morbidity and mortality and can lead to long term health consequences for both the mother and the offspring. The placenta, a central regulator of pregnancy health, is a direct target of environmental toxicants. Epidermal growth factor receptor (EGFR), highly expressed in the placenta, regulates proliferation, migration, invasion, fusion, and cellular bioenergetics. To identify compounds of environmental concern with potential for EGFR-disrupting activity, we optimized a high-throughput virtual screening protocol for the identification of EGFR inhibitors and achieved enrichment factors of EF1% = 10.09, EF5% = 3.86, and EF10% = 3.0 in a benchmarking dataset. We applied this protocol to screen the Collaborative Estrogen Receptor Activity Prediction Project database, finding that top-scoring compounds were enriched for aromatic and fused-ring chemical classes, including dyes. Kinase activity assays revealed that two out of thirteen selected compounds, Vat Red 32 and Reactive Red 136, inhibited EGFR kinase activity with micromolar IC50 values. Additionally, pose refinement with molecular dynamics simulations characterized the binding interactions of Reactive Red 136 within the EGFR kinase domain, and functional assays in HTR-8/SVneo placental trophoblast cells showed that Reactive Red 136, but not Vat Red 32, partially attenuated EGF-mediated cell migration despite both compounds inhibiting EGFR kinase activity. Together, this study has generated an enriched dataset of candidate environmental EGFR modulators, with experimental validation confirming enrichment for EGFR-disrupting activity among the selected compounds. These results provide a valuable resource for toxicological studies.

pharmacology and toxicology↗

Placental DNA methylation levels at CYP2E1 and IRS2 are associated with child outcome in a prospective autism study

DNA methylation acts at the interface of genetic and environmental factors relevant for autism spectrum disorder (ASD). Placenta, normally discarded at birth, is a potentially rich source of DNA methylation patterns predictive of ASD in the child. Here, we performed whole methylome analyses of placentas from a prospective study of high-risk pregnancies. 400 differentially methylated regions (DMRs) discriminated placentas stored from children later diagnosed with ASD compared to typical controls. These ASD DMRs were significantly enriched at promoters, mapped to 596 genes functionally enriched in neuronal development, and overlapped genetic ASD risk. ASD DMRs at CYP2E1 and IRS2 reached genome-wide significance, replicated by pyrosequencing, and correlated with expression. Methylation at CYP2E1 associated with both ASD diagnosis and cis genotype, while methylation at IRS2 was unaffected by cis genotype but modified by preconceptional maternal prenatal vitamin use. This study therefore identified two potentially useful early epigenetic markers for ASD in placenta.

genetics↗

Superposition of survival curves as a tool for epistasis analysis of longevity interventions

A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard epistasis analysis compares the extension of mean lifespan achieved by a combination of interventions to the prediction under an additive or multiplicative null model, but neither model is fundamentally justified. Moreover, the target of longevity interventions is not mean life span but the entire survival curve. Here we formulate superposition principles that predict the survival curve resulting from a combination of two interventions based on the survival curves of the individual treatments, and quantify epistasis as the deviation from this prediction. We test the method on a published data set comprising survival curves for all combinations of 4 different longevity interventions in Caenorhabditis elegans. We find that epistasis is generally weak even when the standard analysis indicates otherwise.

genetics↗