A microfluidic platform for quantitative analysis of single mycobacteria cells

Abstract

Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB), is the leading bacterial cause of death worldwide. A significant barrier to global MTB eradication is 'latent' TB infection, where MTB persists in the human host in a metabolically dormant and highly drug-tolerant state. Latently infected individuals constitute a vast global reservoir of disease (~2 billion people worldwide), and the heightened drug tolerance of dormant MTB necessitates long antibiotic treatments (up to 9 months of combination antibiotic therapy). MTB dormancy is thought to be the result of an adaptive response to host-induced stresses, involving coordinated transcriptional regulation of hundreds of genes as well as numerous metabolic changes. Currently, our understanding of this process is limited by a lack of tools for studying dynamic behavior in single cells. Gene regulation is a dynamic phenomenon that occurs within each cell individually, but many assays rely on steady-state measurements of a population average and thus fail to capture important information about the dynamics of cellular behavior. Additionally, cell-to-cell phenotypic variation has been identified as a key source of microbial drug tolerance, further highlighting the need for single-cell studies. To address this need, we developed a microfluidic platform to study Mycobacteria species at the single-cell level. This platform enables on-chip culture and fluorescent imaging of live cells in precisely controlled conditions, and can thus be used to study dynamic processes within single cells as well as phenotypic heterogeneity across a cellular population. We used this platform to obtain diverse new insights about mycobacterial biology, using the fast-growing mycobacterium M smegmatis. 1) We directly observed gene regulation by the transcription factor KstR in single cells, confirming regulatory interactions that had been predicted computationally. 2)We analyzed morphology, growth, and division data across hundreds of single cells and found that cell division in Mycobacteria is governed using size-based, rather than time-based, control mechanisms. 3) We found that individual cells exhibit considerable differences in their responses to antibiotic stress, and that these differences have implications for cellular survival.