Microbial communities exhibit significant phenotypic heterogeneity, even among genetically identical cells. Phenotypic heterogeneity leads to the emergence of drug-tolerant subpopulations (persister cells), that can survive drug treatments and serve as reservoirs for the evolution of resistant clones. This phenomenon contributes to the persistence of infections and facilitates the emergence of antimicrobial resistance (AMR). To effectively combat AMR, it is crucial to understand the mechanisms driving the emergence of drug-tolerant bacterial and fungal subpopulations. Current single-cell approaches, such as microbial single-cell RNA sequencing (scRNA-seq), provide information on mRNA abundance. However, scRNA-seq lacks information regarding ribosome dynamics and metabolic status. On the contrary, ribosome profiling provides a snapshot of active translation for bacteria, but it does not yet provide single-cell information. To bridge this gap, I propose developing a novel multimodal microbial single-cell sequencing (MuSiC) approach, which will provide information on mRNA abundance, ribosome dynamics, intracellular amino acid availability, and phenotypic antimicrobial response (aim 1). I will apply it to investigate heterogenous response to antimicrobial treatment in isolated strains and biofilms (aim 2). Finally, I will expand it to the complex vaginal microbiome communities and investigate the crosstalk between pathogens and the host microbiome (aim 3). This project aims to elucidate the molecular mechanisms driving phenotypic heterogeneity in microbial populations, offering insights into the emergence of drug-tolerant cells. MuSiC is expected to identify novel key regulatory processes contributing to AMR. Ultimately, we aim to advance the understanding of microbial biology and contribute to more effective control of AMR.