Researchers adapt social network analysis to model virus evolution

Researchers adapt social network analysis to model virus evolution

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Western University researchers may have discovered a new meaning for the social media phrase, “viral spread.”


New research from Western University indicates that some viruses evolve much like a dynamic social network – rather than a rigid tree, as previously thought – combining with one another to create a network of intersecting subspecies. This work has epidemiology and public health implications, not only for HIV-1 but for other viruses as well, as it affects how we track the way viruses are transmitted through populations.

Previously, when epidemiologists looked at the evolution of viruses, they would classify variants like a growing tree – each variant with one or more mutations from its origin branching out into new variants.

By studying the complete genomes of HIV-1 from around the world, particularly regions where sequencing was less common, a team at the Schulich School of Medicine and Dentistry in the West, led by Art Bohn, showed that recombination is more widespread than previously thought.

“If people are infected with two or more HIV subtypes, they exchange parts of their genome to create mosaic shapes that we call ‘recombinant,'” said Abayomi Olabode, lead author and postdoctoral partner in Poon’s lab at Western. Our research and our approach, we’ve found that this recombination is not just a curiosity but is happening a lot more than we originally thought.”

The study, “Revisiting the recombinant history of HIV-1 M cluster with discovery of a dynamic network community” was published this week in PNAS.

Viruses such as HIV-1 are usually classified by comparing only a portion of the virus’ genome to a reference genome. However, Bohn and his team developed a new computational method of looking instead at the entire genome and discovered much greater diversity within the subspecies. This result demonstrates the existence of extensive recombination throughout HIV-1 evolution, including evidence that even the reference genomes of the virus may have been recombinant.

“This discovery was made possible because we now have more full-length genome data available now than in the past, and there are more global initiatives for sequencing populations that have been neglected in the past,” said Poon, associate professor of pathology and laboratory medicine. In Schulich Medicine and Dentistry.

With this data in hand, the team was inspired by social network analysis to look at the data in a new way. When researchers analyze data from social networks such as Facebook or Twitter, they have to consider the intersecting and changing connections between people. “The analogy we make is that similar to dynamic social network analysis, when we go through the genome, parts of the genome will become more similar to a completely different set of other genomes due to recombination.”

The team says this new approach has implications for how viruses are classified, and for tracking and understanding how viruses travel through populations.

“Currently, if we want to figure out how the epidemic spreads in populations, we compare sequences, build a tree, and then use that tree to try to determine what’s going on; where the virus is spreading faster than other parts of the population, for example,” Boone said. “What we found is that recombination breaks these methods — so now we have to work on the assumption that there is not just one tree, there is an entire forest that depends on which part of the virus genome you are looking at.”


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more information:
Abayomi S. Olabode et al, Revisiting the recombinant history of the HIV-1 M cluster with the discovery of the dynamic network community, Proceedings of the National Academy of Sciences (2022). DOI: 10.1073/pnas.2108815119

Offered by University of Western Ontario

the quote: Researchers adapted social network analysis to model virus evolution (2022, May 5) Retrieved May 5, 2022 from https://phys.org/news/2022-05-social-network-analysis-virus-evolution.html

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2022-05-05 15:02:38

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