NEW YORK – An international team led by investigators at the Dana-Farber Cancer Institute and the University of Toronto has established a network that encompasses interactions for thousands of human proteins, highlighting widespread as well as more tissue-specific protein subnetworks to inform future protein analyses.
"We can use our human interactome map to predict protein function," co-senior and co-corresponding author Frederick Roth, a researcher at the University of Toronto's Donnelly Centre for Cellular and Biomolecular Research and at Sinai Health System's Lunenfeld-Tanenbaum Research Institute, said in a statement. "People can look up their favourite protein and get clues about its function from the proteins it interacts with."
As they reported in Nature on Wednesday, the researchers brought together several types of yeast two-hybrid assays to map protein-protein interactions, ultimately identifying more than 52,500 interactions for some 8,300 human proteins in a so-called "Human Reference Interactome" (HuRI) map. HuRI data was initially released through a preprint article on BioRxiv last spring.
The current version of HuRI "has approximately four times as many [protein-protein] interactions as there are high-quality curated interactions from small-scale studies," the authors wrote, noting that the resulting network "is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes."
The team noted that the availability of large-scale protein-protein interaction data builds on and begins to clarify some of the information that can be drawn from genetic sequence, RNA sequence, regulatory, and other genomic data that is routinely generated from human tissues or individual cells.
"Genome sequencing can identify the variants carried by an individual that make them susceptible to disease, but it doesn't reveal how the disease is caused," co-senior and co-corresponding author Michael Calderwood, scientific director of the Dana-Farber Cancer Institute's Center for Cancer Systems Biology (CCSB) and a genetics researcher at Harvard Medical School, explained in a statement.
"Changes in the interactions of a protein is one possible mechanism of disease, and this map provides a starting point to study the impact of disease-associated variants on protein-protein interactions," Calderwood said.
The researchers started with some 17,408 human protein-coding genes found in the ORFeome database and performed a total of nine "all-by-all" pairwise screens with three different yeast two-hybrid assays, complemented by information from a series of validation experiments and analyses. The resulting network contained 52,569 interactions involving 8,275 human proteins, which they expanded to include nearly 9,100 proteins and more than 64,000 protein-protein interactions by incorporating additional published data.
The team went on to explore protein functions, tissue specificity, disease-related insights, and other analyses that could be informed by the HuRI protein-protein interactions.
While they cautioned that there are many more human protein-protein interactions yet to be identified, which impacts the sensitivity of analyses that hinge on such networks, the authors suggested that "the uniform proteome and interactome coverage of HuRI enable its use as a reference for the study of most aspects of human cellular function."