Microsplit: Single-Cell RNA-Sequencing Technology for Microbes

I present µSPLiT (microbial split-pool ligation transcriptomics), a high-throughput single-cell RNA-sequencing (scRNA-seq) method tailored specifically for bacterial communities. A technology based on combinatorial split-pool transcript indexing, µSPLiT easily scales to process hundreds of thousands of cells in a single experiment without need for specialized equipment. We show that µSPLiT can be used simultaneously on gram-positive and gram-negative bacteria and provides single-cell transcriptomic data that resolves heterogeneous functional states within bacterial communities.

ScRNA-seq methods have become a mainstream tool for profiling cell types and states in eukaryotes. However, because of technical challenges, these methods so far have not been compatible with bacteria. µSPLiT is uniquely suited to overcome these challenges since it does not require isolation of individual microbes in droplets or wells and allows sample multiplexing for parallel screening of experimental conditions. Scaling exponentially with the number of barcoding rounds, µSPLiT enables a massive increase in the number of cells that can be sequenced, which makes it uniquely suitable for profiling large and diverse microbial communities.

We validated µSPLiT to detect stress responses in a mixed-species consortium of gram-positive and gram-negative model organisms E. coli and B. subtilis, and profiled transcriptional changes in B. subtilis cultures transitioning from logarithmic to stationary phase of growth. We showed that µSPLiT can be used to resolve heterogeneous subpopulations of cells activating specific transcriptional programs in different conditions, providing a first to date unbiased single-cell transcriptomic overview of metabolic and developmental shifts in gene expression. Next, µSPLiT will be applied to resolve heterogeneous functional cell states and cell-to-cell variation in the complex multi-species natural communities such as the microbiota.