Genetic Blueprints for Resilience: From Pollutants to Pandemics

The rapid expansion of biotechnology and genetics research provides us with powerful systems to investigate pollutants, diagnostic markers, metabolic signaling pathways, and mutational impacts across diverse domains. Advances in genomics, transcriptomics, proteomics, metabolomics, and epigenetics have enabled us to decode complex biological responses to environmental stressors, toxic exposures, and emerging pathogens. While single-omics studies have yielded important insights, the integration of multi-omics approaches is only beginning to reveal the full spectrum of genetic resilience mechanisms.Pollutants, toxicity, and metabolic disruptions represent complex regulatory systems, and the limitations of studying them in isolation are becoming increasingly evident. Multi-omics integration is expected to elucidate the mechanisms of pollutant-induced genetic changes, discover novel biomarkers with diagnostic and prognostic potential, explore therapeutic targets, and ultimately enable predictive, preventive, and personalized strategies for biotechnology, agriculture, and public health. The goal of this Research Topic is to analyze differences in genetic signatures, metabolic pathways, toxicity responses, and resilience strategies across biological systems, including plants, microbes, and humans. Through molecular classification and integrative analysis, we aim to improve diagnostic accuracy, risk stratification, and intervention design. The focus will be on papers that bridge bioinformatics with experimental validation, though submissions will be evaluated case by case based on overall merit.This Research Topic aims to highlight integrative genetic models that connect pollutants, diagnostic markers, metabolic signaling, and resilience strategies, while evaluating their predictive and translational potential. We are particularly interested in, but not limited to, research in the fields of multi-omics, machine learning, tissue culture systems, and pandemic preparedness. We also welcome submissions that extend these approaches to complex diseases, environmental stressors, and biotechnological applications.We invite contributions that include, but are not limited to:• Integration of pollutant response models using multi-omics data• Discovery of diagnostic and prognostic biomarkers for toxicity and metabolic disorders• Machine/deep learning tools for pollutant–genome and marker–disease analysis• Plant tissue culture and microbe–plant consortia as genetic models for pollutant remediation• Multi-omics integrative analysis of metabolic signaling signatures• Mutation-driven adaptation studies in stress and pollutant tolerance• Epigenetic and methylation analysis under toxic exposures• Gene–gene and gene–environment interaction networks in pollutant and pathogen resilience• Pandemic preparedness: genetic blueprints for host–pathogen interactions and rapid diagnostics• Synthetic biology and genome editing strategies for resilience and remediation• Translational toxicogenomics for regulatory and commercial mandates Topic editors: GAURAV MUDGAL, Barathi Seetharaman, Govindappa Venu Source: https://www.frontiersin.org/research-topics/78097/genetic-blueprints-for-resilience-from-pollutants-to-pandemics