Microorganisms shape the composition of the medium they are growing in, which in turn has profound consequences on the reprogramming of the population gene-expression profile. In this paper, we investigate the progressive changes in pH and sugar availability in the medium of a growing Escherichia coli (E. coli) culture. We show how these changes have an effect on both the cellular heterogeneity within the microbial community and the gene-expression profile of the microbial population. We measure the changes in gene-expression as E. coli moves from lag, to exponential, and finally into stationary phase. We found that pathways linked to the changes in the medium composition such as ribosomal, tricarboxylic acid cycle (TCA), transport, and metabolism pathways are strongly regulated during the different growth phases. In order to quantify the corresponding temporal changes in the population heterogeneity, we measure the fraction of E. coli persisters surviving different antibiotic treatments during the various phases of growth. We show that the composition of the medium in which β-lactams or quinolones, but not aminoglycosides, are dissolved strongly affects the measured phenotypic heterogeneity within the culture. Our findings contribute to a better understanding on how the composition of the culture medium influences both the reprogramming in the population gene-expression and the emergence of phenotypic variants.

Here, we report a label-free gold nanoparticle-based single-molecule optical platform to study the immobilization, activity, and thermodynamics of single enzymes. The sensor uses plasmonic gold nanoparticles coupled to optical whispering gallery modes (WGMs) to probe enzyme conformational dynamics during turnover at a microsecond time resolution. Using a glucosidase enzyme as the model system, we explore the temperature dependence of the enzyme turnover at the single-molecule (SM) level. A recent physical model for understanding enzyme temperature dependencies (macromolecular rate theory; MMRT) has emerged as a powerful tool to study the relationship between enzyme turnover and thermodynamics. Using WGMs, SM enzyme measurements enable us to accurately track turnover as a function of conformational changes and therefore to quantitatively probe the key feature of the MMRT model, the activation heat capacity, at the ultimate level of SM. Our data shows that WGMs are extraordinarily sensitive to protein conformational change and can discern both multiple steps with turnover as well as microscopic conformational substates within those steps. The temperature dependence studies show that the MMRT model can be applied to a range of steps within turnover at the SM scale that is associated with conformational change. Our study validates the notion that MMRT captures differences in dynamics between states. The WGM sensors provide a platform for the quantitative analysis of SM activation heat capacity, applying MMRT to the label-free sensing of microsecond substates of active enzymes.

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