A biphasic metabolism-β-lactamase production landscape governs the inoculum effect in β-lactamase-expressing Escherichia coli.

Abstract

The inoculum effect (IE) reduces antibiotic efficacy in vitro and in clinical settings, yet remains difficult to predict. IE limits antibiotic efficacy but remains unpredictable, particularly in resistant bacteria, where resistance mechanisms and bacterial physiology interact in poorly understood ways. Using Escherichia coli expressing the NDM-1 {beta}-lactamase and clinical isolates, we quantified metabolism, growth rate, {beta}-lactamase expression, and IE across diverse growth environments. Across enzyme classes, antibiotics, and clinical isolates, we find that IE is governed by a conserved, biphasic dependence on metabolism normalized by growth rate. Mathematical modeling shows that this behavior reflects a tradeoff between {beta}lactamasemediated protection and metabolismpotentiated antibiotic lethality. These findings establish a predictive, physiology-based framework for IE in resistant bacteria and explain why resistance determinants alone fail to predict treatment outcomes across environments, including the clinic. Significance StatementAntibiotic efficacy depends on both bacterial resistance and physiology, yet these factors are rarely integrated when predicting treatment outcomes. One important consequence of their interaction is the inoculum effect (IE), in which antibiotic efficacy depends on the density of a resistant bacterial population. Here, we show that IE in {beta}lactamase-expressing bacteria is governed by a conserved physiological tradeoff between metabolism and growth. Across growth environments, antibiotics, inocula, and clinical isolates, IE is strongest at intermediate metabolic states, reflecting a balance between resistancemediated protection and metabolismpotentiated antibiotic lethality. This framework helps explain why resistance determinants alone are insufficient to account for IE and underscores the role of bacterial physiology in shaping antibiotic responses.