DOI: 10.5061/dryad.5mkkwh7c7
title: Tuning interdomain conjugation toward in situ population modification in yeasts

description: The ability to modify and control natural and engineered microbiomes is
 essential for biotechnology and biomedicine. Fungi are critical members of
 most microbiomes, yet technology for modifying the fungal members of a
 microbiome has lagged far behind that for bacteria. Interdomain
 conjugation (IDC) is a promising approach, as DNA transfer from bacterial
 cells to yeast enables in situ modification. While such genetic transfers
 have been known to naturally occur in a wide range of eukaryotes, and are
 thought to contribute to their evolution, IDC has been understudied as a
 technique to control fungal or fungal-bacterial consortia. One major
 obstacle to widespread use of IDC is its limited efficiency. In this work,
 we utilize interactions between genetically tractable Escherichia coli and
 Saccharomyces cerevisiae to control the incidence of IDC. We test the
 landscape of population interactions between the bacterial donors and
 yeast recipients to find that bacterial commensalism leads to maximized
 IDC, both in culture and in mixed colonies. We demonstrate the capacity of
 cell-to-cell binding via mannoproteins to assist both IDC incidence and
 bacterial commensalism in culture, and model how these tunable controls
 can predictably yield a range of IDC outcomes. Further, we demonstrate
 that these lessons can be utilized to lastingly alter a recipient yeast
 population, by both “rescuing” a poor-growing recipient population and
 collapsing a stable population via a novel IDC-mediated CRISPR/Cas9
 system.
description: Data was
 collected as described in the Materials and Methods section of
 Stindt, <em>et al</em>.
description: MATLAB
description: All data here to be used in conjunction with custom MATLAB scripts found
 at
 [https://github.com/mccleanlab/Stindt_2023](https://github.com/mccleanlab/Stindt_2023) ## The following three data files contain all analyzed data used for plotted figures in Stindt et. al. 2023: \__Consolidated_Data.mat includes source data for Figures 1-3, 5-7, SI Figures 2-7, 13-20. Compiled data is from analyzed flow cytometry, fluorimetry, and image analyses, with experiments organized by Plate numbers and experiment date. Use this data with All_plots script to generate most figures. "All_plots" script also specifies which experimental info (plate, date) corresponds to each figure. \__Conjugation_Clump_Data.mat includes image analysis and fluorimetry data used for model fitting in Figure 4, SI Figures 8-12. For use with modeling scripts in the GitHub repository for this paper. AllFits.mat includes all saved model parameters used in Figure 4, SI Figures 8-12. For use with modeling scripts in the GitHub repository for this paper. ## Additional raw data found here can be used to reanalyze (i.e. recompile) the above data files, and are organized by data type: "Clumping Images" includes raw .nd2 images from Nikon Ti Eclipse inverted fluorescence microscopy of clumped cocultures, as well as converted .png and .tif formats, and a "Convert" ImageJ macro used to convert files from .nd2. TIFF images can be used directly with "ClumpAnalyze" script to reanalyze clump size and bacterial coincidence, Figure 3 and SI Figures 5-6. Within each filetype folder, samples are named using the following fields: * Day of batch culturing eg "D2" = day 2 * The dilution from batch culture plate eg "50Dil" = 1:50 dilution. "Und" = undiluted * Mannose designation. "Min" = mannose-minus, "Plus" = mannose-plus. These should be cross referenced with the PlateMaps file. If neither designation is present, use the first plate map that contains both sample types * The plate well number. See PlateMaps.png to determine which sample pertains to the plate well * A nonsense value that pertains to imaging code * The image number, eg "2" = the second image taken for that well "Colony Images" includes raw .czi images from AxioZoom microscopy of mixed colony expansion assays, as well as converted .png and .tif formats, and a "Convert" ImageJ macro used to convert files from .czi. TIFF images can be used directly with "ExpAnalyze" and corresponding function scripts to extract image analysis data for Figure 5 (colocalization), SI Figure 13 (radial intensities). Within each filetype folder, images are named using the following fields (these are hardcoded into processing script as well): * Day of imaging eg "Day1" = 1 day of growth before imaging * The cells imaged, based on the following shorthand: * "AM" = kMM127 + pMM0893, ie Ecross cis transfer donor * "AT" = kMM127 + pMM0892 + pMM1438, ie Ecross trans transfer donor * "WM" = kMM0011 + pMM0893, ie E cis transfer donor * "WT" = kMM0011 + pMM0892 + pMM1438, ie E trans transfer donor * "16" = yMM1636 ie S recipient * "15" = yMM1585 ie Scross recipient for cis donors * "17" = yMM1720 ie Scross recipient for trans donors * Percentage of leu and trp in media eg "100" = 100% LW * Colony number eg "13" = colony 13 of original plate "Flow Cytometry" includes folders for each experiment used, identified by date and Figure in paper. Within each are gates used to identify populations and raw data (fcs) from Attune measurements. Raw data is further organized by day of batch culturing and voltage used for measuring (bacterial or yeast voltage), with each folder additionally containing the corresponding sample information in the form of Excel spreadsheet. This file structure is required for use with "FlowAnalyze" and corresponding function scripts. Within each folder are FCS files per well of 96-well plate (eg "....A12" is the FCS for well A12), which can be matched to sample info by the "...Labels" xlsx file. Folder name fields are as follows: * Day of batch culturing eg "Day2" = day 2 * An experiment designator. This can be ignored, since the experiments are noted in each root folder * Voltage used. "B" = voltage used to count bacterial cells, "Y" = voltage used to count yeast cells "Fluorimetry" includes raw Tecan Spark fluorescence data from batch cultures, identified by date and Figure in paper. Within each can be found Excel spreadsheet exports, one for each day of batch culturing, as well as a consolidated spreadsheet that additionally includes sample information