Genome-scale label-free imaging reveals cellular physiology encoded in bacterial collective architecture
TL;DR
The results show that bacterial multicellular development is an interpretable signature of genotype-phenotype relationships, which can be captured from simple brightfield timelapses, and µPULLI can be used to determine a drug target, characterize other pathogens, and classify bacterial species.
Abstract
DNA sequencing unified microbial genotyping into a single, comprehensive readout, yet phenotyping remains a slow and fragmented endeavor. Here, we introduce Microbial Phenotyping Using Low-magnification Label-free Imaging (µPULLI), a computer vision platform that extracts microcolony and population-level phenotypes from brightfield timelapses of liquid culture growth. Using µPULLI, we screened a genome-scale Vibrio cholerae mutant library, recording more than 200,000 images, which revealed that core bacterial pathways shape community architecture. Functionally related mutants converge in appearance, allowing us to resolve processes as distinct as biofilm formation, motility, central metabolism, cofactor biosynthesis, and envelope composition using a single approach. We further show µPULLI can be used to determine a drug target, characterize other pathogens, and classify bacterial species. Our results show that bacterial multicellular development is an interpretable signature of genotype-phenotype relationships, which can be captured from simple brightfield timelapses. We release the µPULLI pipeline and an interactive atlas of community forms.