Skip to main content
zenodoopen

Supplementary File S2: Plasmids for independently tunable, low-noise gene expression

<p>Supplementary File S2 README</p> <p>2019-April-26</p> <p>&quot;Plasmids for independently tunable, low-noise gene expression&quot; (Version 2)</p> <p>João P. N. Silva, Soraia Vidigal Lopes, Diogo J. Grilo, Zach Hensel</p> <p>This file describes the contents of the supplementary file for this manuscript. Python scripts were run in a Python 3 environment on OSX with various scientific python packages updated as of April 2019. With minor modifications for any similar environment it should be possible to generate Figures 1, 2, and 4 in the manuscript from these scripts and raw data.</p> <p>Contents:</p> <p>\dna sequences<br> &nbsp;&nbsp; &nbsp;\pDG101.gb Annotated DNA sequence in genbank format of plasmid pDG101<br> &nbsp;&nbsp; &nbsp;\pJS101.gb Annotated DNA sequence in genbank format of plasmid pJS101 (AddGene #118280)<br> &nbsp;&nbsp; &nbsp;\pJS102.gb Annotated DNA sequence in genbank format of plasmid pJS102 (AddGene #118281)<br> &nbsp;&nbsp; &nbsp;\pZH501.gb Annotated DNA sequence in genbank format of plasmid pZH501<br> &nbsp;&nbsp; &nbsp;\pZH509.gb Annotated DNA sequence in genbank format of plasmid pZH509 (AddGene #102664)<br> &nbsp;&nbsp; &nbsp;\pZH713.gb Annotated DNA sequence in genbank format of plasmid pZH713<br> &nbsp;&nbsp; &nbsp;\ZHX99.gb Annotated DNA sequence in genbank format for E. coli MG1655 chromosome insertion mutant ZHX99<br> &nbsp;&nbsp; &nbsp;<br> \data<br> &nbsp;&nbsp; &nbsp;\DG FCS Data: Raw flow cytometry data from BioRad S3 sorted by day and experimental condition; file name format: plasmid_inducer-concentration_inducer-units_inducer.fcs<br> &nbsp;&nbsp; &nbsp;\pJS101 pDG101 independence<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;\&quot;quick scope intensity.ijm&quot; Fiji macro used to extract average fluorescence intensities<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;\&quot;Microscope Data\&quot; Microscope data analyzed using the above Fiji macro; directory names indicate ATc and IPTG concentrations for each experimentation condition/replicate<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;\&quot;intensity analysis\&quot;<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;X_nM_ATc_Y_uM_IPTG.csv files: Exported CSV data from Fiji for each condition<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;backgrounds.csv: Average intensity for every condition, image frame, and color for background subtraction<br> &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;\&quot;images for Figure 4&quot;: Image stack with raw images used to generate Fig 4A and 4B</p> <p>\code<br> &nbsp;&nbsp; &nbsp;\fcsAnalysis_final_181228.py step-wise script for generating Figures 1 and 2 from FCS data<br> &nbsp;&nbsp; &nbsp;\fcsCalcDirectory181228.py script containing functions for FCS analysis and figure generation<br> &nbsp;&nbsp; &nbsp;\fcsImages PDF figures output by FCS analysis scripts<br> &nbsp;&nbsp; &nbsp;\FlowCal-master Distribution of the FlowCal library used in analysis for this manuscript; this is distributed under the MIT license<br> &nbsp;&nbsp; &nbsp;\scopeAnalysisWorkflow190430.py step-wise script for generating Figures 4C and 4D from cell fluorescence microscopy data in CSV format exported from Fiji<br> &nbsp;&nbsp; &nbsp;\scopeCalcDirectory190430.py script containing functions for microscopy data analysis and figure generation</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4