Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria

Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.

Most microbial communities consist of a genetically diverse assembly of different organisms, and the level of genetic diversity plays an important part in community properties and functions. However, biological diversity also arises at a lower level of biological organization, between genetically identical cells that reside in the same microenvironment. In this Review, I outline the molecular mechanisms responsible for phenotypic heterogeneity and discuss how phenotypic heterogeneity allows genotypes to persist in fluctuating environments. I also describe how it promotes interactions between phenotypic subpopulations in clonal groups, providing microbial groups with new functionality.

Bacteria express many small RNAs for which the regulatory roles in pathogenesis have remained poorly understood due to a paucity of robust phenotypes in standard virulence assays. Here we use a generic 'dual RNA-seq' approach to profile RNA expression simultaneously in pathogen and host during Salmonella enterica serovar Typhimurium infection and reveal the molecular impact of bacterial riboregulators. We identify a PhoP-activated small RNA, PinT, which upon bacterial internalization temporally controls the expression of both invasion-associated effectors and virulence genes required for intracellular survival. This riboregulatory activity causes pervasive changes in coding and noncoding transcripts of the host. Interspecies correlation analysis links PinT to host cell JAK-STAT signalling, and we identify infection-specific alterations in multiple long noncoding RNAs. Our study provides a paradigm for a sensitive RNA-based analysis of intracellular bacterial pathogens and their hosts without physical separation, as well as a new discovery route for hidden functions of pathogen genes.