Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes

Author:

Cesnik Anthony1,Schaffer Leah V.2,Gaur Ishan1,Jain Mayank2,Ideker Trey32,Lundberg Emma4561

Affiliation:

1. 1Department of Bioengineering, Stanford University, Stanford, California, USA; email: emmalu@stanford.edu

2. 2Department of Medicine, University of California San Diego, La Jolla, California, USA; email: tideker@health.ucsd.edu

3. 3Departments of Computer Science and Engineering and Bioengineering, University of California San Diego, La Jolla, California, USA

4. 6Chan Zuckerberg Biohub, San Francisco, California, USA

5. 5Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden

6. 4Department of Pathology, Stanford University, Palo Alto, California, USA

Abstract

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Publisher

Annual Reviews

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