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Argonne’s computational resources have supported the largest comprehensive analysis of COVID-19 genomic sequences in the United States and helped confirm growing evidence of a protein mutation.
Before COVID-19 was first introduced in the United States in March, Houston Methodist Hospital had already begun preparations to test and sequence the virus on a large scale, in light of news from Wuhan, China.
Between March 5, when the first case emerged in the greater Houston area, and July 7, doctors / researchers at Houston Methodist Hospital sequenced the genomes of more than 5,085 strains of the virus. These accounted for nearly 10% of the COVID-19 cases that the Houston Methodist health system, with its 2,400 beds, experienced during two different waves that occurred during that time.
“99 percent is not 100 percent. If there is a mutation that is only one percent of the population and you suppress or exterminate the majority, you can increase any trait by that percentage, be it virulence or transmissibility, and then it’s another game. ” – James Davis, Argonne staff scientist
Staff from the University of Texas at Austin, Weill Cornell Medical College, the University of Chicago and the United States Department of Energy (DOE) Argonne National Laboratory collaborated to analyze the data and try to discover patients with viral traits correlate.
“This is currently the largest virus sequence analysis in the United States and one of the most complete and continuous snapshots of sequences dating back to the beginning of the outbreak,” said James Davis, a scientist in Argonne’s Data Science and Learning division. “It also provides a much clearer picture of how the strains are developing.”
As research progressed, the group helped solidify growing international observations and fears that a mutation in the virus’s spike protein had become dominant, increasing transmission rates of COVID-19, the second wave showed in mid-May scattered around. Houston.
An article about their methods and results was published in the mBio journal on October 30, 2020.
This mutation in the peak – responsible for infiltrating the human immune system and current target of vaccine research – was in an amino acid called Gly614 and was the result of the mutation of a protein, aspartic acid, into another protein, glycine. .
During the first phase of the pandemic, from March to April, Gly614 was just one variant among many others. But during the second wave in May, Davis recalls, all cases sequenced in the Houston Methodist showed that Gly614 had reproduced so much that it became the dominant amino acid in the spike protein.
In fact, it was found in over 99 percent of the sequenced variants.
“The SARS-CoV-2 virus is remarkably conserved. So when you see changes like this, it’s even more remarkable because you don’t tend to see so many mutations, “he said. I’m not sure if that makes the virus more virulent or more easily transmitted, but the study shows some data that suggests that patients with the Gly614 mutation have a higher viral load, although they are not necessarily sicker.
Coinciding with the second wave of adoption of Gly614, patients tended to be younger, less severe, more likely to be Hispanic / Latino and to live in areas with lower median incomes. However, the reasons for this were unclear and it was hoped that Argonne’s computer resources would open a door to causes.
The Houston Methodist, a pre-existing employment relationship, contacted Argonne for help with genomic sequence analysis of more than 5,000 COVID strains, as well as phylogenetic analyzes that look at changes in a specific organism or trait over time.
Argonne provides computational and technical resources to employees conducting large bio-based data projects through its Bioinformatics Resource Center project, supported by the National Institute of Allergy and Infectious Diseases. In this case, he managed the sequencing components and included quality control, genome alignment, and phylogenetic tree construction.
“For a virus, it has a fairly large genome,” Davis noted, “so the process became computationally expensive. But with its arsenal of computers, both large and supercomputers, Argonne was ready to handle. the influx of data.
Another aspect of this work concerned the technology of artificial intelligence, the so-called machine learning. While the focus of machine learning at many research institutes, including Argonne, was to understand how drugs might interact with COVID-19, Marcus Nguyen hoped to predict whether the sequence of the virus could ultimately predict outcome or patient demographics.
Nguyen, a research specialist with a joint appointment at Argonne and the University of Chicago, studied the correlations between genome sequences and patient information.
The process trained a machine learning algorithm on the Houston Methodist genomic sequences, as well as previous ones
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