Format

Send to

Choose Destination
Nat Rev Mol Cell Biol. 2019 May;20(5):285-302. doi: 10.1038/s41580-018-0094-y.

Spatial proteomics: a powerful discovery tool for cell biology.

Author information

1
Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden. emma.lundberg@scilifelab.se.
2
Department of Genetics, Stanford University, Stanford, CA, USA. emma.lundberg@scilifelab.se.
3
Chan Zuckerberg Biohub, San Francisco, CA, USA. emma.lundberg@scilifelab.se.
4
Max Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Martinsried, Germany. borner@biochem.mpg.de.

Abstract

Protein subcellular localization is tightly controlled and intimately linked to protein function in health and disease. Capturing the spatial proteome - that is, the localizations of proteins and their dynamics at the subcellular level - is therefore essential for a complete understanding of cell biology. Owing to substantial advances in microscopy, mass spectrometry and machine learning applications for data analysis, the field is now mature for proteome-wide investigations of spatial cellular regulation. Studies of the human proteome have begun to reveal a complex architecture, including single-cell variations, dynamic protein translocations, changing interaction networks and proteins localizing to multiple compartments. Furthermore, several studies have successfully harnessed the power of comparative spatial proteomics as a discovery tool to unravel disease mechanisms. We are at the beginning of an era in which spatial proteomics finally integrates with cell biology and medical research, thereby paving the way for unbiased systems-level insights into cellular processes. Here, we discuss current methods for spatial proteomics using imaging or mass spectrometry and specifically highlight global comparative applications. The aim of this Review is to survey the state of the field and also to encourage more cell biologists to apply spatial proteomics approaches.

PMID:
30659282
DOI:
10.1038/s41580-018-0094-y

Supplemental Content

Full text links

Icon for Nature Publishing Group
Loading ...
Support Center