Proteins are the chief effectors of cellular processes. Within the context of the living cell, proteins form networks of interactions to exert their functions through both stable and transient macromolecular complexes. These protein-protein interactions (PPIs), and interactions with other biomolecules, constitute the interactome of a cell. Alterations in proteins, including changes to protein length, amino acid sequence, expression level, and subcellular localization, can lead to the formation of altered protein interaction networks that cause cellular dysfunction and disease. Therefore, to understand molecular and cellular function and dysfunction, to understand health and disease, we must understand interactomes, creating a need for methods that detect and dissect interactomes and any such alterations. This project will significantly advance a proof-of-concept method to produce a mature platform technology aimed at revealing the compositions of interactomes and behaviors of PPIs at previously unrealized depth and accuracy. The approach taken is akin to a crystallographic screen, except applied to the affinity capture of endogenous protein complexes, optimizing sample preparation in conjunction with initial characterization by mass spectrometry. This project will demonstrate the application of the platform beyond detecting protein interactions, to include biochemical and structural characterization of macromolecular complexes (among other possibilities).
Three Aims, composed of an innovative synthesis of methods and technologies, will permit us to achieve our goals: we will (1) optimize access to interactomes, (2) preserve interactomes for bioanalytical assays, and (3) interpret interactomes aided by computational tools. The knowledge generated will improve success rates in affinity capture experimental design and find applications in basic, biomedical, and biotechnology research, from protein complex discovery and characterization, to sample storage, basic and clinical assay development, and industrial engineering.

Public Health Relevance

Within the living cell, proteins form networks of interactions to exert their functions. Alterations in healthy networks of protein interactions can lead to dysfunctional networks and cause human disease, creating a need for methods that detect and dissect such alterations. This project will advance a technology platform aimed at revealing the compositions of protein networks and the behaviors of network constituents at previously unrealized depth and accuracy.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM126170-01
Application #
9426374
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Smith, Ward
Project Start
2017-12-01
Project End
2021-11-30
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Rockefeller University
Department
Biology
Type
Graduate Schools
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065