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 3^rd 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.

Acquisition: This dataset was acquired using a Zeiss Lightsheet Z.1 system fitted with a 5X detection objective (Zeiss EC Plan-Neofluar 420330-8210) and 4X light sheet forming objectives (Zeiss LSFM 400900-9010).  During imaging, the polyacrylamide gel sample was mounted to a coverslip and immersed in 1X Tris-buffered Saline with Tween (details provided in the Methods section of the manuscript).  

Analysis: Analysis scripts for 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 relevant subdirectories of the main portion of the dataset (Supporting data: 3D projection electrophoresis for single-cell immunoblotting).

Data Overview
This dataset contains the tiled light sheet microscopy image (Zeiss .czi format) of  the 'Gel 5' separation (separated 2019-09-10) probed and imaged 2019-10-03 ('Gel 2' in Figure 5).  For this dataset, the sample was imaged in the fluorescence channels corresponding to the probed GAPDH (AlexaFluor 488) and Beta Tubulin (AlexaFluor 647) proteins (relevant only to Supplementary Figure 6).

The large .czi file was split into pieces for upload using Rclone (https://rclone.org/chunker/).  All of the files with the same base filename can be sequentially concatenated (e.g. with 'cat' or Rclone) to reconstitute the original large file.  An example workflow on MacOS is as follows:

1. Download all of the chunked files into a directory.
2. In Terminal, navigate to the directory containing the chunked files.
3. Run the following command to concatenate the files: 
   cat 2019-09-10_Gel5_EPProbed_GAPDH488bTub647.czi.rclone_chunk.0* > 2019-09-10_Gel5_EPProbed_GAPDH488bTub647_Merged.czi
4. Open the merged file by dragging and dropping onto Fiji and selecting the Bio-Formats import parameters, or by opening in Zeiss Zen Lite.

Linked Data
Additional data are available in separate, linked data publications due to file size constraints:

1. Analyzed data and additional README files corresponding to this dataset are presented in the main data publication for this manuscript: 'Supporting data: 3D projection electrophoresis for single-cell immunoblotting' (DOI: 10.6078/D1B13V).  That data publication's README files mention this dataset where relevant.
2. 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).
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 Actinin protein channels (DOI: 10.6078/D1811G).

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

Analysis
Analysis scripts to analyze light sheet microscopy images of projection electrophoresis separations are available in the following GitHub repository: https://github.com/samanthagrist/projection_ep_analysis (in the 'single-cell-lightsheet-analysis' subdirectory).  Initialization files and analyzed data files for the analysis scripts corresponding to this dataset are included in the main data publication for this manuscript (in the 'SI_Fig6_Single_Cell_Migration_Comparison/lightsheet/ subdirectory)