Visualizing microbial societies: exposing the principles of single-cell phenotypic heterogeneity via massively multiplexed imaging

Bacteria are social organisms that interact and coordinate their behaviors to shape our world. Whereas their clonal populations are genetically identical, they contain phenotypically distinct members.

This diversity provides resilience to unpredictable environmental changes, such as antibiotic exposure or nutrient depletion.

It also facilitates cooperative interactions between different sub-population via specialization in costly activities such as virulence factor production, forming an extended basis for sociality.

Yet, the phenotypic landscape in any given species remains largely unexplored due to the technical challenges of profiling individual bacteria, particularly in spatially structured biofilms and host tissues.

Recent breakthroughs in microbial single-cell transcriptomics, developed by the PI of the current proposal (Dar et al., Science 2021), now provide a unique opportunity to illuminate this hidden complexity.This proposal seeks a systematic and experimentally derived view of phenotypic variation.

We will comparatively study pathogenic and non-pathogenic Pseudomonas species in three settings, each illuminating distinct core principles of cell-cell variability.

In Objective 1, we will focus on free-living populations, building on the massive multiplexing capacity of our method to comprehensively map phenotypic cell states, outline their interplay with physiological and environmental factors, and study their evolution.

We will characterize the spatiotemporal dynamics of cell states directly within 3D biofilms in Objective 2, and contextualize our results in vivo during infection in Objective 3, simultaneously measuring host-and-microbe spatial expression.Comprehensively studying phenotypic heterogeneity is a critical next step for understanding how microbes survive in complex environments, socially interact, and subvert their hosts during infection.

If successfully executed, this proposal will shed light on the plasticity that defines microbial li