mDrop-seq: Massively parallel single-cell RNA-seq of Saccharomyces cerevisiae and Candida albicans

Abstract

Advances in high-throughput single-cell mRNA sequencing (scRNA-seq) have been limited till date by technical challenges like tough cell walls and low RNA quantity that prevented transcriptomic profiling of microbial species at throughput. We present microbial Drop-seq or mDrop-seq, a high-throughput scRNA-seq technique that is used on two yeast species, Saccharomyces cerevisiae, a popular model organism and Candida albicans, a common opportunistic pathogen. We benchmarked mDrop-seq for sensitivity and specificity and used it to profile 35,109 S. cerevisiae cells to detect variation in mRNA levels between them. As a proof of concept, we quantified expression differences in heat-shocked S. cerevisiae using mDrop-seq. We detected differential activation of stress response genes within a seemingly homogenous population of S. cerevisiae under heat-shock. We also applied mDrop-seq to C. albicans cells, a polymorphic and clinically relevant yeast species with thicker cell wall compared to S. cerevisiae. Single cell transcriptomes in 39,705 C. albicans cells was characterized using mDrop-seq under different conditions, including exposure to fluconazole, a common anti-fungal drug. We noted differential regulation in stress response and drug target pathways between C. albicans cells, changes in cell cycle patterns and marked increases in histone activity. These experiments are among the first high throughput single cell RNA-seq on different yeast species and demonstrate mDrop-seq as an affordable, easily implementable, and scalable technique that can quantify the variability in gene expression in different yeast species. We hope that mDrop-seq will lead to better understanding of genetic variation in yeasts in response to stimuli and find immediate applications in investigating drug resistance and infection outcome.