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Supporting data: 3D projection electrophoresis for single-cell immunoblotting (Part 1)

Cite this dataset

Grist, Samantha; Mourdoukoutas, Andoni; Herr, Amy (2020). Supporting data: 3D projection electrophoresis for single-cell immunoblotting (Part 1) [Dataset]. Dryad. https://doi.org/10.6078/D1B13V

Abstract

Immunoassays and mass spectrometry are powerful single-cell protein analysis tools; however, interfacing and throughput bottlenecks remain. Here, we introduce three-dimensional single-cell immunoblots to detect both cytosolic and nuclear proteins. The 3D microfluidic device is a photoactive polyacrylamide gel with a microwell array-patterned face (x-y) for cell isolation and lysis. Single-cell lysate in each microwell is ‘electrophoretically projected’ into the 3rd dimension (z-axis), separated by size, and photo-captured in the gel for immunoprobing and confocal/light-sheet imaging. Design and analysis are informed by the physics of 3D diffusion. Electrophoresis throughput is >2.5 cells/s (70X faster than published serial sampling), with 25 immunoblots/mm2 device area (>10X increase over previous immunoblots). The 3D microdevice design synchronizes analyses of hundreds of cells, compared to status quo serial analyses that impart hours-long delay between the first and last cell. Here, we introduce projection electrophoresis to augment the heavily genomic and transcriptomic single-cell atlases with protein-level profiling.

Methods

This dataset includes a mixture of different data types (fluorescence, confocal, and light sheet microscopy imaging as well as finite-element modelling) and was collected using the Methods described in the manuscript.  Processing used several custom MATLAB scripts.  Select short analysis scripts are included in the relevant data directories.  Additional, more extensive analysis scripts to analyze various types of projection electrophoresis data are available in the following GitHub repository: https://github.com/samanthagrist/projection_ep_analysis.  Acquisition and processing details for each portion of the dataset are available in the relevant README files included in the dataset.

Usage notes

As noted in the uploaded README file in the main directory:

Data Overview
The relevant data files are organized into sub-directories by manuscript and SI figure, and then by data type and/or figure sub-panel.  Each figure directory is uploaded as a .zip file, and contains sub-directories.  README files describing the data contents are available either in the main directory or sub-directories of each figure directory.  In addition to these data files, quantification of key figures and figure panels are also available in ProjectionEP_ManuscriptData_SUBMIT.xlsx.

Files included:

  1. ProjectionEP_ManuscriptData_SUBMIT.xlsx — spreadsheet containing quantification of key figures and figure panels from the manuscript.
  2. Fig1_GAPDH_PTBP1.zip — archive containing the data relevant to Figure 1 of the manuscript
  3. Fig2_Purified_BSA_OVA_IgG_Lectin_Transferrin.zip — archive containing the data relevant to Figure 2 of the manuscript
  4. Fig3_Purified_BSA_OVA_IgG_Diffusion.zip — archive containing the data relevant to Figure 3 of the manuscript
  5. Fig4_Single_Cell_Assay_Development.zip — archive containing the data relevant to Figure 4 of the manuscript
  6. Fig5_Single_Cell_Analysis.zip — archive containing the data relevant to Figure 5 of the manuscript
  7. SI_Fig1_Migration_Linearity_Optimization.zip — archive containing the data relevant to Supplementary Figure 1 of the manuscript
  8. SI_Fig2_Diffusive_Loss_Comparison_scWB.zip — archive containing the data relevant to Supplementary Figure 2 of the manuscript
  9. SI_Fig3_Lysis_Gel_Comparison.zip — archive containing a README file relevant to Supplementary Figure 3 of the manuscript (data are included in other archives)
  10. SI_Fig4_Single_Cell_Analysis_Confocal.zip— archive containing the data relevant to Supplementary Figure 4 of the manuscript
  11. SI_Fig5_Spatial_Migration_Duplicate_Gel.zip— archive containing the data relevant to Supplementary Figure 5 of the manuscript
  12. SI_Fig6_Single_Cell_Migration_Comparison.zip— archive containing the data relevant to Supplementary Figure 6 of the manuscript

Linked Data
Large, tiled, light sheet microscopy images are available in separate, linked data publications due to file size constraints:

  1. Tiled light sheet microscopy image for the 'Gel 6' separation probed and imaged 2019-10-03 ('Gel 1' in Figure 5), imaged in the GAPDH and Actinin protein channels (DOI: 10.6078/D1N989).
  2. Tiled light sheet microscopy image for the 'Gel 5' separation probed and imaged 2019-10-03 ('Gel 2' in Figure 5), imaged in the GAPDH and Actinin protein channels (DOI: 10.6078/D1811G).
  3. Tiled light sheet microscopy image for the 'Gel 5' separation probed and imaged 2019-10-03 ('Gel 2' in Figure 5), imaged in the GAPDH and Beta Tubulin protein channels (DOI: 10.6078/D1HH6C, relevant only to Supplementary Figure 6).

Please see the Related Works for links to these additional datasets.

Analysis
Select short analysis scripts are included in the relevant data directories.  Additional, more extensive analysis scripts to analyze various types of projection electrophoresis data are available in the following GitHub repository: https://github.com/samanthagrist/projection_ep_analysis

Funding

National Institutes of Health, Award: 1R33CA225296-01

Chan Zuckerberg Initiative (United States)

The Natural Sciences and Engineering Research Council of Canada Postdoctoral Fellowship Program

National Science Foundation