DOI: 10.5061/dryad.1g1jwsv86
title: Data and code from: Imaging flow cytometry enables label-free cell sorting of morphological variants from populations of the unculturable bacterium <em>Pasteuria ramosa</em>

description: 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 (&gt; 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.
description: # Dryad dataset Dataset DOI:
 [10.5061/dryad.1g1jwsv86](https://doi.org/10.5061/dryad.1g1jwsv86) ##
 Description of the data and file structure *Daphnia magna* were
 experimentally infected with the bacterial parasite *Pasteuria ramosa*,
 which produces morphologically distinct stages ("morphologies")
 during its life cycle. Hosts were culled at various points post-infection.
 The composition of the *P. ramosa* cell population was analyzed using both
 an Attune Cytpix imaging flow cytometer and a (non-imaging) Influx
 cell-sorter ("pre-sort analysis"). The Influx cell-sorter was
 used to sort different target morphologies. The composition of the
 resulting sorted sample was then assessed using the Attune Cytpix, to
 quantify the purity of the sorted sample ("post-sort" analysis).
 For the sake of efficiency, a random sample of events was inspected.  Full
 details of the methods are given in the publication.  ### Files and
 variables #### File: vocelleetal_analysis_v2.Rmd **Description:** R
 Markdown file containing the code used to generate the Figure 2 &
 Table S4 of the manuscript. Note that Figure 1 was generated using
 proprietary FCS Express software and Microsoft Powerpoint.  #### File:
 vocelleetal_data_v2.csv **Description:** Spreadsheet containing details of
 each sort and the results of the post-sort validation analysis.  #####
 Variables * sample_name: unique sample name * run_date: date sample
 analyzed using the Influx cell-sorter * gs_conf: gating strategy * gs_id:
 unique gating strategy id * target: *Pasteuria* morphology that we aimed
 to sort.  * e_in: number of "events" in the sample analyzed via
 the Influx. * e_out: number of "events" in the sorted sample.  *
 e_attune: number of "events" from the sorted-sample analyzed via
 the Attune. * e_validated: number of event-images inspected for validation
 purposes * b_target: number of *Pasteuria* cells of the target-morphology
 observed in validation subset * non_b: number of non-bacterial events
 observed in observed in validation subset * b_nontarget: number of
 non-target *Pasteuria* observed in validation subset * notes: Operator
 notes on morphologies observed during post-sort analysis #### File:
 vocelleetal_analysis_v2.html **Description:** HTML output of the R
 file vocelleetal_analysis.Rmd ## Code/software The data was analyzed using
 R software, version 4.2.  The code, which includes details of the packages
 required, is provided as a .Rmd file.