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Data and code from: Imaging flow cytometry enables label-free cell sorting of morphological variants from populations of the unculturable bacterium Pasteuria ramosa

Vocelle, Daniel12; Thompson, Lindsey1; Bernard, Matthew P.1; Wale, Nina1

Research facility: Michigan State University Flow Cytometry Core
Published Nov 21, 2025 on Dryad. https://doi.org/10.5061/dryad.1g1jwsv86

Data files

Nov 21, 2025 version files 1.17 MB

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Abstract

Bacterial populations often display remarkable morphological heterogeneity. Flow cytometric cell sorting (often called FACS) is an important tool for understanding this diversity. FACS allows researchers to obtain pure samples of each morphological variant (or morphotype) that is present within a mixed population of cells and thus permits each morphotype to be phenotyped. In FACS, cells are first labeled with fluorescent markers such as antibodies or transgenic constructs, and then separated out based on their possession of these labels. However, since the development of fluorescent labels requires a priori knowledge of bacterial biology, it is often impossible to apply FACS to understudied and/or unculturable bacteria. This challenge has limited our capacity to investigate the biology of bacterial size and shape in all but a small, largely culturable subset of bacterial taxa. Here, we present an innovative strategy that permits label-free cell sorting of bacterial morphotypes, using an unculturable, pleiomorphic pathogen (Pasteuria ramosa) as a model bacterium. We show that imaging flow cytometry (IFC) can be used to systematically identify light-scattering and autofluorescence “signatures” of bacterial morphotypes, on which basis cell sorting can be conducted. Critically, our IFC-enabled cell sorting strategy yields samples of sufficient purity (> 90 %) for common downstream analyses e.g., “-omics” analyses. Our work represents an innovative application of IFC and provides an economical, widely applicable solution to a central problem in the study of bacterial diversity.