The social life of proteins is easily as complex and full of drama as the latest Instagram celebrities. However, unlike a rising social network star, understanding how and with whom various proteins interact with inside the cell can ultimately provide useful information about general biology and disease development. Yet, mapping this network of interactions, or “interactome,” has been slow going in the past because the number of interactions that could be tested at once was limited.
Now, a team of investigators at the Salk Institute have developed a new high-throughput technique to understand better the “social network” of cellular proteins, in addition to allowing researchers test millions of relationships between thousands of proteins in a single experiment. Findings from the new study were published recently in Nature Methods in an article entitled “CrY2H-seq: A Massively Multiplexed Assay for Deep-Coverage Interactome Mapping.”
The interactome of a cell, much like a map of social networks, lets scientists see who's working with whom in the world of proteins. This helps them figure out the roles of different proteins and piece together the different players in molecular pathways and processes. If a newly discovered protein interacts with lots of other proteins involved in cellular metabolism, for instance, researchers can deduce that's a likely role for the new protein and potentially target it for treatments related to metabolic dysfunction.
“The power of this new approach is in the ability we now have to scale it up,” explained senior study author and Howard Hughes investigator Joseph Ecker, Ph.D., professor, and director of Salk's Genomic Analysis Laboratory. “This assay has the potential to begin addressing questions about fundamental biological interactions that we haven't been able to address before.”
Previously, researchers typically relied on standard high-throughput yeast two-hybrid (Y2H) assays to determine the interactions between proteins. The system requires using a single known protein—known as the bait—to screen against a pool of prey proteins. But finding all the interactions between, for instance, 1000 proteins would require 1000 separate experiments to screen once for each bait's interaction partners.
“Current technologies essentially require that interactions detected in primary screening get retested individually,” noted lead study investigator Shelly Trigg, an NSF graduate research fellow at the University of California, San Diego and a member of Dr. Ecker’s lab. “That may no longer be necessary with the screening depth this new approach achieves.”
In the new approach, the researchers added a twist to the standard Y2H assay for a much more effective way of measuring the interactome. The genes for two proteins, each on their own circle of DNA, are added to the same cell. If the proteins of interest interact inside the cell, a gene called Cre is activated. When turned on, Cre physically splices the two individual circles of DNA together, thus pairing the genes of interacting proteins together so the team can easily find them through sequencing.
The team can generate a massive library of yeast cells—each containing different pairs of proteins by introducing random combinations of genes on circular DNA molecules called plasmids. When cells are positive for a protein interaction, the researchers can use genetic sequencing to figure out what the two proteins interacting are, using new high-throughput DNA sequencing technologies similar to those used for human genome sequencing. This way, they're no longer limited to testing one “bait” protein at a time but could test the interactions between all the proteins in a library at once.
We used “a massively multiplexed yeast two-hybrid method, CrY2H-seq, which uses a Cre recombinase interaction reporter to intracellularly fuse the coding sequences of two interacting proteins and next-generation DNA sequencing to identify these interactions en masse,” the authors wrote. “We applied CrY2H-seq to investigate sparsely annotated Arabidopsis thaliana transcription factors interactions. By performing ten independent screens testing a total of 36 million binary interaction combinations, and uncovering a network of 8,577 interactions among 1,453 transcription factors, we demonstrate CrY2H-seq′s improved screening capacity, efficiency, and sensitivity over those of existing technologies.”
The Salk team tested the new method, dubbed CrY2H-seq, on all the transcription factors within the plant model Arabidopsis. “When you take 1800 proteins and test the interactions among them, that's nearly 4 million combinations,” Dr. Ecker remarked. “We did that ten times in a matter of a month.”
The scientists uncovered more than 8000 interactions among those proteins tested, giving them new insight into which Arabidopsis transcription factors interact with each other. The researchers are optimistic that the data will answer longstanding questions about whether certain groups of transcription factors have set functions. In the future, the method could be scaled up to test larger sets of proteins—human cells, for instance, contain about 20,000 different proteins.