Dar Lab

Quorum sensing (QS) orchestrates collective responses in bacteria. Yet, how individuality arises and functions within a system designed to unify behavior remains poorly understood. Here, we use imaging-transcriptomics to comprehensively profile the QS transcriptional response of the opportunistic pathogen Pseudomonas aeruginosa at single-cell resolution. We observe heterogeneity across all stages of QS, from signal production to public goods expression. While most cells cooperate, the extent of public goods contribution varies substantially, primarily due to transcriptional noise. Additionally, cells expressing high levels of a given exoproduct were often enriched for multiple other public goods. Expression of QS signal synthases, particularly in the Las and PQS systems, exhibits extreme cell-cell variability indicative of regulation, and exceeding levels observed in known differentiation into hypervirulent or motile subpopulations. These patterns are dynamic, peaking during early signaling, suggesting that a subset of highly committed cells may influence key decision points in the QS response. We find that cellular memory carried from prior growth cycles shapes QS dynamics via signaling-primed cells but does not influence de novo formation of hyper-signaling cells. Differentiation into hyper-signaling subpopulations is also robust to exogenous autoinducers across a wide concentration range, suggesting it is likely mediated by an internal mechanism. Despite variation in QS network outputs between strains, hyper-signaling subpopulations consistently emerge across diverse isolates, pointing to an evolutionarily conserved strategy. Our findings recast QS as a system that embeds a deliberately heterogeneous entry point within an otherwise synchronizing program, offering new insight into how bacterial populations balance cooperation and conflict.Competing Interest StatementThe authors have declared no competing interest.European Research Council, https://ror.org/0472cxd90, 101117863

Capturing the heterogeneous phenotypes of microbial populations at relevant spatiotemporal scales is highly challenging. Here, we present par-seqFISH (parallel sequential fluorescence in situ hybridization), a transcriptome-imaging approach that records gene expression and spatial context within microscale assemblies at a single-cell and molecule resolution. We applied this approach to the opportunistic pathogen Pseudomonas aeruginosa, analyzing about 600,000 individuals across dozens of conditions in planktonic and biofilm cultures. We identified numerous metabolic- and virulence-related transcriptional states that emerged dynamically during planktonic growth, as well as highly spatially resolved metabolic heterogeneity in sessile populations. Our data reveal that distinct physiological states can coexist within the same biofilm just several micrometers away, underscoring the importance of the microenvironment. Our results illustrate the complex dynamics of microbial populations and present a new way of studying them at high resolution.