published_or_final_version / abstract / toc / Ecology and Biodiversity / Master / Master of Philosophy

Gene expression heterogeneity underlies critical bacterial phenotypes including antibiotic tolerance, pathogenesis, and communication. Though microbial population heterogeneity has been appreciated for decades, we still lack a complete view of single-cell gene expression and phenotypic states. Various tools, including bulk RNA-seq and proteomics, are available for probing all genes on a population-level. Conversely, fluorescent protein reporters and in situ hybridization can capture single-cell states but only for a limited number of genes. Single-cell RNA-sequencing (scRNA-seq), which can quantify expression of all genes with resolution for individual cells, has revolutionized studies of heterogeneous eukaryotic populations. However, adaptation to bacteria has been hindered by technical barriers. This thesis will describe the development of high-throughput scRNA-seq for bacteria and its application to uncover a distinct transcriptional state of rare antibiotic-tolerant cells called persisters. Chapter 2 presents prokaryotic expression profiling by tagging RNA in situ and sequencing (PETRI-seq), our novel scRNA-seq technology. I will detail how PETRI-seq was optimized to overcome bacteria-specific challenges, including lack of mRNA polyadenylation, thick cell walls, and extremely low mRNA abundance. Using combinatorial indexing, PETRI-seq uniquely barcodes tens of thousands of gram-negative and/or gram-positive cells in a single experiment at low cost. In proof-of-concept experiments, we show robust discrimination of E. coli growth phases and identification of rare prophage activation in S. aureus. PETRI-seq will be broadly useful for characterizing bacterial heterogeneity in many contexts. Chapter 3 describes an expansive investigation into antibiotic persistence in E. coli. When a population is treated with lethal antibiotics, persisters are rare cells that can survive the exposure by assuming a relatively dormant state. Understanding the gene expression state and molecular drivers of persistence has been a longstanding goal with major potential to inform drug development and clinical practice. We have applied PETRI-seq to multiple models of E. coli persistence and discovered a distinct transcriptional state underlying this phenotype. In parallel, we used genome-wide CRISPR-interference to probe the functional contribution of every gene to the persistence phenotype. We discovered multiple driver genes and pathways. Comprehensive validation established Lon protease and YqgE as key gene products modulating translation rate, post-starvation dormancy, and persistence. Our work is a major step in defining the physiological state of persistence and the molecular processes leading cells into this state. In all, this thesis demonstrates how a new generation of systems approaches, including scRNA-seq and CRISPR-interference, enable new discoveries about long-studied phenomena. The overarching approach is broadly applicable with potential to inspire a wide range of microbiology studies.