bioRxivMolecular BiologyPreprint
A proximity-dependent biotinylation map of a human cell: an interactive web resource
Christopher D. GoiD, James D.R. KnightiD, Archita Rajasekharan, Bhavisha Rathod, Geoffrey G. HeskethiD, Kento T. AbeiD, Ji-Young Youn, Payman Samavarchi-Tehrani, Hui Zhang, Lucie Y. Zhu, Evelyn PopieliD, Jean-Philippe Lambert, Étienne CoyaudiD, Sally W.T. Cheung, Dushyandi Rajendran, Cassandra J. WongiD, Hana Antonicka, Laurence Pelletier, Alexander F. PalazzoiD, Eric A. ShoubridgeiD, Brian RaughtiD, Anne‐Claude GingrasiD
Abstract summary
Claude Opus 5.5 · xhigh effort · 2 Nov 2026 · from the abstract
Profiling 192 subcellular markers by proximity-dependent biotinylation (BioID) in human HEK 293 cells maps 4,145 proteins across 32 compartments via 35,902 interactions, available with analysis tools at humancellmap.org.
High-throughput microscopy and biochemical fractionation coupled with mass spectrometry struggle to characterize intracellular compartments that are difficult to purify, such as non-membrane-bound structures. Applying proximity-dependent biotinylation (BioID) across 192 markers in living human cells maps protein localization across 32 subcellular compartments with higher specificity than prior methods.
Key results
ShownA BioID proximity map in HEK 293 cells assigns intracellular localizations to thousands of human proteins across 32 compartments with higher specificity than prior approaches.
Profiled 192 compartment markers from 32 subcellular compartments, identifying 35,902 high-confidence proximity interactions and localizing 4,145 unique proteins in HEK 293 cells. · Abstract
ShownLocalization predictions from the BioID map identified proteins at the mitochondrial outer membrane–endoplasmic reticulum (ER) interface required for mitochondrial homeostasis, and the dataset was deployed as an online analysis platform.
Community resource and user BioID localization analysis tools provided at humancellmap.org (specific protein names at the mitochondrial-ER interface are not stated in the abstract). · Abstract
Methods, data and reproducibility
Proximity-dependent biotinylation (BioID) was performed in living HEK 293 cells using 192 subcellular markers spanning 32 compartments to identify high-confidence proximity interactions, predict protein localizations, and build the humancellmap.org web resource.
- BioID proximity interaction dataset across 32 subcellular compartments in HEK 293 cells · human · n = 192 markers; 32 compartments; 35,902 interactions; 4,145 unique proteins
- Methods & tools
- BioID, humancellmap.org
- Data & accessions
- https://humancellmap.org/
Limitations (2)
- All proximity mapping in the abstract was performed in a single cell line (HEK 293 cells). · noted in this summary
- The abstract does not report quantitative specificity metrics or name the newly identified mitochondrial-ER interface proteins. · noted in this summary
Read this if you want a reference proximity-biotinylation map of 32 human subcellular compartments in HEK 293 cells or online tools to analyze your own BioID datasets.
- Citations
- 57
Abstract
Compartmentalization is a defining characteristic of eukaryotic cells, partitioning cellular processes into discrete subcellular locations. High throughput microscopy1 and biochemical fractionation coupled with mass spectrometry2-6 have helped to define the proteomes of a variety of organelles and macromolecular structures. However, many other intracellular compartments have remained refractory to such approaches, due for example to difficulty in purifying non-membrane bound structures. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach for defining the composition of cellular compartments in living cells7-10. Here we present a BioID-based map of a human cell based on 192 markers from 32 different subcellular compartments, comprising 35,902 high confidence proximity interactions, and defining the intracellular locations of 4,145 unique proteins in HEK 293 cells. Our localization predictions meet or exceed previous-approaches, with higher specificity, and enabled the discovery of proteins at the mitochondrial outer membrane-endoplasmic reticulum (ER) interface that are critical for mitochondrial homeostasis. Based on this dataset, we have established humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to better understand BioID datasets.
- organism: human
- assay: proteomics
- research focus: database / resource
- research focus: cell type annotation
- research focus: differential expression
- research focus: protein structure prediction
- approach: experimental assay
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