Integrating omics to understand induced metabolic remodeling across biological scales

Abstract

Mass spectrometry-based omics has emerged as a powerful framework for resolving how biological systems respond to environmental and nutritional perturbations. By enabling simultaneous measurement of thousands of proteins and metabolites, these approaches reveal coordinated molecular networks underlying adaptation, stress response, and metabolic flexibility. This dissertation applies shotgun proteomics and time-resolved metabolomics to characterize dynamic biological responses across microbial and human systems, demonstrating how molecular-level measurements can be translated into mechanistic and physiological insight. In Escherichia coli, shotgun proteomics was used to investigate the regulatory role of ArsR, a transcription factor traditionally classified as a repressor of arsenic resistance genes. Contrary to this canonical view, ArsR was found to coordinate broad activation of metabolic and redox- related proteins, including enzymes involved in amino acid catabolism, central carbon metabolism, and thiol-based redox buffering. This activating role was evident both in the presence and absence of arsenic stress, repositioning ArsR as a pleiotropic regulator with functional influence extending beyond its defined operon. In humans, time-resolved serum metabolomics was applied to a randomized 12-week lentil dietary intervention in adults at elevated cardiometabolic risk. Postprandial responses to a standardized high-fat meal were profiled hourly, capturing the dynamic structure of metabolic change rather than static endpoints. Long-term lentil consumption remodeled the postprandial metabolome, particularly during the early postprandial phase, in a manner consistent with improved lipid handling and metabolic resilience. These findings demonstrate that biological responses to perturbation are not defined by static molecular states, but by coordinated, time dependent network remodeling. Mass spectrometry- based omics provides the resolution necessary to capture these dynamics, establishing a unifying framework for translating molecular change into biological meaning across scales, from microbial adaptation to human metabolic health.