Seung-Geun Park, Eunseo Lee, Hyun-Yi Kim, Tae Hyun Yoon
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A systems biology approach to understand temporal evolution of silver nanoparticle toxicity.
Silver nanoparticles (AgNPs) are widely used in industrial and biomedical applications, however, their toxicity mechanisms at the molecular level are not completely understood. To address this gap, we investigate the temporal dynamics of gene expression in human lung epithelial cells exposed to AgNPs, integrating transcriptomic analysis, gene ontology (GO) enrichment, protein-protein interaction (PPI) networks, and dynamic simulations. GO analysis highlights early activation of ribosomal biogenesis and stress pathways, transitioning DNA repair and cell cycle regulation at later stages. PPI networks identify ribosomal proteins and DNA damage regulators as key hub genes. Dynamic simulations modeled gene expression changes over 48 hours, uncovering sequential activation of stress response genes, followed by DNA repair attempts and apoptotic signaling as cellular damage persisted. Through modeling the interplay between molecular responses and cell viability, the simulations provided a predictive temporal framework for advancing nanotoxicology research, providing insights into AgNPs-induced molecular disturbances, contributing to safety assessments.
期刊介绍:
npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology.
We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.