Researchers of the Yu Lab, led by Principal Investigator Haiyuan Yu, recently published a study revealing a comprehensive list of SARS-CoV-2-viral and human proteins that interact with each other in the pathobiology of COVID-19. These findings open doors to new research avenues for identifying potential treatments for the virus that can target protein-binding sites.
Mauricio Paramo grad and Shagun Gupta grad, both members of the Yu Lab who contributed to the study, began their studies in pathobiology to broaden their understanding of the relationship between the SARS CoV-2 virus and its host cells.
When viruses enter a cell, they are able to replicate themselves and evade the body’s immune response by interacting with proteins. Studying the mechanisms of these interactions is key in understanding how the SARS-CoV-2 virus affects human bodily responses.
Prior to this study, information about protein interaction networks for COVID-19 was scarce. To create a more complete and precise database, the authors applied two cutting-edge complementary methods: high-throughput yeast two-hybrid and a combination of tandem mass tag affinity purification and mass spectrometry. Y2H is a technique that detects interacting proteins in living yeast cells. TMT-AP-MS is a technique that isolates and identifies protein complexes.
The researchers used Y2H to observe the affinity between viral and human proteins by providing a binary interactome, which highlighted important connections between different protein complexes and pathways. A binary interactome describes an interaction between two proteins.
“You’re doing pairwise testing of all viral factors across all host proteins. There are about 20 viral proteins that make up SARS-CoV-2, so we did pairwise testing across almost 16,000 human factors. This method will give you interactions where only the two factors — one viral and one host protein — are interacting,” Paramo said.
Based on the interactomes identified by Y2H, researchers used TMT-AP-MS to label binary and co-complex proteins and their interactions by breaking down proteins into their peptide components to put them into a mass spec machine.
“For example, to test the effect of a specific drug, you can track how much of the peptide you find with no drug treatment and how much you find with drug treatment. This allows us to have more precise measurements,” Gupta said.
The combination of these two novel methods enabled researchers to generate high-quality protein interactome networks. To assess the quality of the data, they performed orthogonal methods with co-immunoprecipitation assays, a technique that evaluates the relevance of reported protein interactions using human immune proteins called antibodies.
Once the researchers were able to validate their findings, they confirmed that there were 739 high-confidence protein-protein interactions among 579 human proteins and 28 SARS-CoV-2 proteins. This validated 218 known human proteins that interact with SARS-CoV-2 and revealed 361 novel ones.
Based on this interactome, it was possible to identify 23 candidate drugs to target COVID-19. The final results indicated carvedilol, usually used to treat heart failure and high blood pressure, as the drug with the most potential for treatment because of its strong network proximity to SARS-CoV-2 host factors.
“Carvedilol had a strong network proximity in that it directly influenced the network of human proteins and was a short distance away from a viral protein. The assumption is that it is more likely to have an influence on a viral protein and its effect in the cell and is, therefore, a strong drug candidate,” Gupta said.
The researchers extracted further biological information from the data with the help of fellow researchers at Cornell, including Profs. Cédric Feschotte and John T. Lis, molecular biology and genetics.
Researchers learned more about transcription, the process of converting genetic instructions into a form that can be directly used to make proteins.
“We learned that one of the viral proteins was interacting with human transcription factors. From this, we were able to demonstrate direct viral impact on host transcription. This was previously unknown about SARS-CoV-2 proteins and offers a pathway to learn about how viruses evade host immunity,” Paramo said.
There are a number of pathways for future research to gain more insight into how SARS-CoV-2 works in the body and its implications for other viruses.
“There are two people in the lab who are working on a viral human interactome study to examine a broad range of viruses and interacting interfaces on human protein. Also, when we were looking at direct drug binding targets based on our networks, we found some other interesting targets that we are looking to patent,” Gupta said.
Reflecting back on the study process and results, Paramo highlighted the importance of collaboration as a driver of scientific discovery, especially in pioneering COVID-19 research.
“This study really shows how these large scale efforts are driven by collaboration with other groups,” Paramo said. “We came in with a network systems biology perspective, and we worked with people with many different backgrounds to ultimately make very important discoveries that have real-world applications.”