Massively-parallel Microbial mRNA Sequencing (M3-Seq) reveals heterogenous behaviors in bacteria at single-cell resolution

Abstract

Bacterial populations are highly adaptive. They can respond to stress and survive in shifting environments. How the behaviors of individual bacteria vary during stress, however, is poorly understood. To identify and characterize rare bacterial subpopulations, technologies for single-cell transcriptional profiling have been developed. Existing approaches, though, are all limited in some technical capacity (e.g., number of cells or transcripts that can be profiled). Due in part to these limitations, few conditions have yet been studied with these tools. Here, we develop Massively-parallel Microbial mRNA sequencing (M3-Seq), a single-cell RNA-sequencing platform for bacteria that pairs combinatorial cell indexing with post hoc rRNA depletion. We show that M3-Seq can profile hundreds of thousands of bacterial cells from different species under a range of conditions in single experiments. We then apply M3-Seq to reveal rare populations, insights into bet hedging strategies during stress responses, and host responses to phage infection.