PT  - JOURNAL ARTICLE
AU  - Christopher D. Go
AU  - James D.R. Knight
AU  - Archita Rajasekharan
AU  - Bhavisha Rathod
AU  - Geoffrey G. Hesketh
AU  - Kento T. Abe
AU  - Ji-Young Youn
AU  - Payman Samavarchi-Tehrani
AU  - Hui Zhang
AU  - Lucie Y. Zhu
AU  - Evelyn Popiel
AU  - Jean-Philippe Lambert
AU  - Étienne Coyaud
AU  - Sally W.T. Cheung
AU  - Dushyandi Rajendran
AU  - Cassandra J. Wong
AU  - Hana Antonicka
AU  - Laurence Pelletier
AU  - Brian Raught
AU  - Alexander F. Palazzo
AU  - Eric A. Shoubridge
AU  - Anne-Claude Gingras
TI  - A proximity biotinylation map of a human cell
AID  - 10.1101/796391
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 796391
4099  - http://biorxiv.org/content/early/2019/10/07/796391.short
4100  - http://biorxiv.org/content/early/2019/10/07/796391.full
AB  - Compartmentalization is an essential characteristic of eukaryotic cells, ensuring that cellular processes are partitioned to defined subcellular locations. High throughput microscopy1 and biochemical fractionation coupled with mass spectrometry2-6 have helped to define the proteomes of multiple organelles and macromolecular structures. However, many compartments have remained refractory to such methods, partly due to lysis and purification artefacts and poor subcompartment resolution. Recently developed proximity-dependent biotinylation approaches such as BioID and APEX provide an alternative avenue for defining the composition of cellular compartments in living cells (e.g. 7-10). Here we report an extensive BioID-based proximity map of a human cell, comprising 192 markers from 32 different compartments that identifies 35,902 unique high confidence proximity interactions and localizes 4,145 proteins expressed in HEK293 cells. The recall of our localization predictions is on par with or better than previous large-scale mass spectrometry and microscopy approaches, but with higher localization specificity. In addition to assigning compartment and subcompartment localization for many previously unlocalized proteins, our data contain fine-grained localization information that, for example, allowed us to identify proteins with novel roles in mitochondrial dynamics. As a community resource, we have created humancellmap.org, a website that allows exploration of our data in detail, and aids with the analysis of BioID experiments.