OpenCell Microscopy Images

Version v1.0,

source

released 08 Dec 2021

Developed By
  • Leonetti Lab (Chan Zuckerberg Biohub San Francisco)
  • Mann Lab (Max Plank Institute)

The OpenCell microscopy images were taken alongside immunoprecipitation-mass spectrometry data to investigate protein localization and protein-protein interactions in the same cellular context. It contains confocal fluorescent microscopy images of live HEK293T cells. Each image has one protein endogenously tagged with GFP and DNA stained with Hoechst 33342. Across the dataset, 1,310 proteins were tagged, with each protein represented by four to six field-of-view images with z-stacks in 16-bit TIFF files.

Dataset Overview

Data Type

Fluorescence microscopy images

Citation

Publication: OpenCell: Endogenous tagging for the cartography of human cellular organization. Science (2022). https://doi.org/10.1126/science.abi6983

Dataset: OpenCell on AWS was accessed on [DATE] from https://registry.opendata.aws/czb-opencell.

Dataset Card Authors

Chan Zuckerberg Initiative

Dataset Card Contact

virtualcellmodels@chanzuckerberg.com

Uses

Primary Use Cases

Investigate cellular localization of proteins in live, single cells

Out-of-Scope or Unauthorized Use Cases

Do not use the dataset for the following purposes:

Dataset Structure

Each folder contains images for one tagged protein and there are four to six field-of-view images, each with a z-stack of around 100 slices per channel. A maximum-intensity z-projection is also provided. There are two channels for each image, the first one is for DNA and the second one is for the GFP-tagged protein.

Personal and Sensitive Information

No personal and sensitive information is included.

Dataset Creation

Curation Rationale

These images were taken alongside immunoprecipitation-mass spectrometry data to study protein localization and protein-protein interactions in the same cellular context

Data Collection and Processing

Cells were imaged live with Hoechst stain using a confocal microscope driven by automated image acquisition. The raw z-stack TIFF images and a maximum-projection of the z-stack are provided. More details see https://www.science.org/doi/10.1126/science.abi6983

Annotation process

The localization of each protein is annotated manually using three “grades”: grade 3 indicates a very prominent localization, grade 2 indicates unambiguous but less prominent localization, and grade 1 indicates weak or barely detectable localization. To obtain the annotations and see more details: https://opencell.czbiohub.org/download.

Who are the annotators?

The annotation was done by the team who generated and processed the data.

Bias, Risks, and Limitations

  • GFP tags sometimes could impact protein localization and protein-protein interactions.
  • Proteins may behave differently in different cell lines and cell types.

Acknowledgements

See source reference: https://www.science.org/doi/10.1126/science.abi6983