Abstract
Comprehensive analysis of multi-omics data can reveal alterations in regulatory
pathways induced by cellular exposure to chemicals by characterizing biological
processes at the molecular level. Data-driven omics analysis, conducted in a dosedependent or dynamic manner, can facilitate comprehending toxicity mechanisms.
This study introduces a novel multi-omics data analysis designed to concurrently
examine dose-dependent and temporal patterns of cellular responses to chemical
perturbations. This analysis, encompassing preliminary exploration, pattern deconstruction, and network reconstruction of multi-omics data, provides a comprehensive
perspective on the dynamic behaviors of cells exposed to varying levels of chemical
stimuli. Importantly, this analysis is adaptable to any number of any omics layers,
including site-specific phosphoproteomics. We implemented this analysis on multiomics data obtained from HepG2 cells exposed to a range of caffeine doses over
varying durations and identified six response patterns, along with their associated
biomolecules and pathways. Our study demonstrates the effectiveness of the proposed multi-omics data analysis in capturing multi-dimensional patterns of cellular
response to chemical perturbation, enhancing understanding of pathway regulation
for chemical risk assessment.