Abstract
Cellular noise refers to stochastic fluctuations in the abundance of intracellular molecules, which can give rise to stochasticity in specific cellular functions. One example of stochastic fluctuations pertains to gene expression, which can lead to the emergence of significant phenotypic heterogeneity among isogenic cells under identical growth conditions. This form of phenotypic variability also pertains to antibiotic survival, where cells persist antibiotics without acquiring mutations, as in antibiotic resistance. To probe these stochastic effects, single-cell investigations are required to uncover the cell-to-cell differences in growth or stress-response. In turn, single-cell investigations necessitate advanced experimental methods. This thesis focuses on both developing such advanced experimental methods and applying them to investigate the effects of cellular noise on growth and response to antibiotics. To this end, in Chapter 2 of this dissertation, I present two methods to assemble microfluidics: Solvent Immersion Imprint Lithography (SIIL) which is compatible for analyzing single anaerobic cells, as well as cast molding lithography for investigating single aerobic cells. Specifically, I expanded SIIL to microfabricate microfluidics in polymethylmethacrylate (PMMA), while cast-molding helped to assemble microfluidics with a high success rate. In Chapter 3, I present a novel polymer microarray that greatly improves the throughput of single-cell tracking over 4 generations and accurately extracts optical-phase information from single cells. Quantifying cellular growth of single E.coli cells with these microarrays enabled correlations between cell size, density, mass and growth rates and related surprising findings of how density fluctuations regulate growth and fitness, as detailed in Chapter 4. In Chapter 5, I studied the effect of cellular noise on antibiotic response using the same microarrays. These results revealed that not every cell dies at the same time and an unexpected link between survival duration and states of reduced metabolic activity that cells enter just before death.