A novel method to detect interactions between proteins of viruses and their hosts with more precision than current methodologies may improve the understanding of viral mutations, as well as the design of future antiviral drugs and therapeutic strategies, according to recent findings published in Nature Communications.
The method, called mRNA display with library of even-distribution (md-LED), offers investigators the opportunity to identify the functional consequences of protein mutations in viruses with higher sensitivity, according to Judd Hultquist, PhD, assistant professor of Medicine in the Division of Infectious Diseases and a co-author of the study.
“It’s easy for us to track viral mutations in their genomes; it’s much harder to say what that mutation does, and this approach helps us do just that,” Hultquist said.
Viruses rely on interactions between their own proteins and proteins of the host to replicate. These interactions allow the virus to hijack an infected cell to essentially become a virus producing factory. They are also important in allowing a virus to evade the body’s immune response and defining the interactions that occur during infection is not only important in understanding the mechanisms of viral disease, but also in designing new antiviral treatments.
Current methodologies to examine these protein interactions have limited sensitivity and several inherent biases that restrict their utility, according to Hultquist. In response, Hultquist and his collaborators developed md-LED, an improved approach to identify low-abundance binders of target proteins with high specificity and sensitivity. This approach also allows for the direct comparison of single point changes in a protein, enabling rapid analysis of viral mutations.
Essentially, md-LED involves extracting all the exons in the human genome and converting them into small protein fragments in vitro. These protein fragments are directly linked to the messages that encoded them. This library of proteins can then be analyzed for binding to a protein of interest, such as a viral protein, with deep sequencing of the linked messages as a readout.
The method ultimately provides investigators with a comprehensive library of every portion of every protein expressed by the human genome. In this way, investigators can accurately determine not only what interactions are occurring, but where they are occurring in the protein, Hultquist said.
“This method offers a large number of advantages based on what’s currently being done. Deep sequencing is also relatively cheap and easy to perform as a readout, so that makes this kind of work more accessible for everybody,” Hultquist said.
To demonstrate the feasibility of md-LED, the investigators applied the method to develop high-sensitivity maps of the multifunctional influenza A virus protein, NS1. The NS1 protein in flu viruses is primarily used for evading the early immune response to infection. The ability of NS1 to counteract the immune response is also what helps makes the influenza virus so successful as a pathogen.
“We knew normal methods weren’t capturing all of the interactions NS1 was making, and the virus is mutating NS1 constantly, so we wanted a better way to explore these interactions,” Hultquist said.
The method was not only able to recapitulate several known interactions, but also unexpectedly revealed a new interaction between the NS1 protein and human fatty acid synthetase, which is responsible for making fat molecules in the cell. This protein is expressed at low levels in the cell, so this new interaction was missed in prior studies using other methods and by using md-LED, was found to be essential for the virus to replicate successfully in human cells.
According to Hultquist, their method could even be used to better understand the protein interactions behind the SARS-CoV-2 virus, the strain of coronavirus that causes COVID-19. Like other viruses, SARS-CoV-2 encodes many proteins that are able to evade or shut down the immune system, enhancing the virus’ ability to spread at an unprecedented rate and cause disease.
“We think this approach could be useful in exploring how these proteins are interacting within the cell to shut off the immune response,” Hultquist said.
As for next steps, Hultquist said his team is planning to use the approach to compare how different viral protein mutations influence virus replication and result in different levels of disease severity, which could ultimately aid in risk stratification and inform clinical management and treatment.
This work was supported by the Nationals Institutes of Health Grants PO1 CA177322 and U19 AI135972.