From bacterial growth laws to detecting drug action mechanisms

Bacterial adaptation to environmental shifts and antibiotic stresses involves system-wide reallocation of proteome resources. Existing growth laws capture reallocation between large functional groups but lack the resolution to describe gene-resolved proteomics data. Here we discuss enzyme-specific growth laws that relate expression changes under stress to expression and substrate saturation at high growth. We show that growth response of expression is linear with two distinct patterns: enzymes in pathways unaffected by a perturbation respond homogeneously, enzymes downstream of perturbed reactions display heterogeneous shifts even within the same pathway. We derive these laws from a metabolic model integrating growth-optimal resource allocation, enzyme kinetics, and network structure; we validate predictions by multi-omics data from E. coli. Next, we apply enzyme-specific growth laws to detect drug action; specifically, we infer which perturbed metabolic functions constrain growth. Our approach provides a mechanistic basis to interpret proteome changes under antibiotic challenge and a strategy to uncover metabolic vulnerabilities for antimicrobial therapy.