RT Journal Article
SR Electronic
T1 A proximity biotinylation map of a human cell
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 796391
DO 10.1101/796391
A1 Christopher D. Go
A1 James D.R. Knight
A1 Archita Rajasekharan
A1 Bhavisha Rathod
A1 Geoffrey G. Hesketh
A1 Kento T. Abe
A1 Ji-Young Youn
A1 Payman Samavarchi-Tehrani
A1 Hui Zhang
A1 Lucie Y. Zhu
A1 Evelyn Popiel
A1 Jean-Philippe Lambert
A1 Étienne Coyaud
A1 Sally W.T. Cheung
A1 Dushyandi Rajendran
A1 Cassandra J. Wong
A1 Hana Antonicka
A1 Laurence Pelletier
A1 Brian Raught
A1 Alexander F. Palazzo
A1 Eric A. Shoubridge
A1 Anne-Claude Gingras
YR 2019
UL http://biorxiv.org/content/early/2019/10/07/796391.abstract
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.