RT Journal Article
SR Electronic
T1 Droplet-based single cell RNA sequencing of bacteria identifies known and previously unseen cellular states
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.03.10.434868
DO 10.1101/2021.03.10.434868
A1 Ryan McNulty
A1 Duluxan Sritharan
A1 Shichen Liu
A1 Sahand Hormoz
A1 Adam Z. Rosenthal
YR 2021
UL http://biorxiv.org/content/early/2021/03/10/2021.03.10.434868.abstract
AB Clonal bacterial populations rely on transcriptional variation to differentiate into specialized cell states that increase the community’s fitness. Such heterogeneous gene expression is implicated in many fundamental microbial processes including sporulation, cell communication, detoxification, substrate utilization, competence, biofilm formation, motility, pathogenicity, and antibiotic resistance1. To identify these specialized cell states and determine the processes by which they develop, we need to study isogenic bacterial populations at the single cell level2,3. Here, we develop a method that uses DNA probes and leverages an existing commercial microfluidic platform (10X Chromium) to conduct bacterial single cell RNA sequencing. We sequenced the transcriptome of over 15,000 individual bacterial cells, detecting on average 365 transcripts mapping to 265 genes per cell in B. subtilis and 329 transcripts mapping to 149 genes per cell in E. coli. Our findings correctly identify known cell states and uncover previously unreported cell states. Interestingly, we find that some metabolic pathways segregate into distinct subpopulations across different bacteria and growth conditions, suggesting that some cellular processes may be more prone to differentiation than others. Our high throughput, highly resolved single cell transcriptomic platform can be broadly used for understanding heterogeneity in microbial populations.Competing Interest StatementThe authors have declared no competing interest.