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“Super-strong” antibody against isolated COVID-19 mutant | Health care




Technology developed at Vanderbilt University Medical Center has discovered “super-strong” monoclonal antibodies against multiple variants of SARS-CoV-2, the virus responsible for COVID-19, including delta variants. ..

Antibodies have rare properties that make a valuable addition to a limited set of widely responsive antibody therapeutic candidates, researchers reported in the journal Cell Reports.

This technique, called LIBRA-seq, has helped speed up the discovery of antibodies that can neutralize SARS-CoV-2. Researchers can also screen for antibodies to other viruses that have not yet caused human illness but are likely to do so.

“This is one way to actively build a repertoire of potential treatments for future outbreaks,” said Vanderbilt Computational Microbiology and Immunology Program Director, Vanderbilt Infection and Immunology and Inflammation. Dr. Ivelin Georgiev, Deputy Director of the Institute, said.

“Pathogens continue to evolve and we are basically catching up,” said Georgiev, an associate professor of pathology, microbiology, immunology and computer science and a member of the Vanderbild Vaccine Center. Stated.

He said that to prevent the recurrence of COVID-19, or “worse things happen in the future,” a more aggressive approach is needed to predict future outbreaks before they occur.

In their report, Georgiev and his colleagues describe the isolation of monoclonal antibodies from patients who have recovered from COVID-19, which “shows strong neutralization” against SARS-CoV-2. It is also effective against viral variants that are delaying efforts to control the pandemic.

This antibody has unusual genetic and structural characteristics that distinguish it from other monoclonal antibodies commonly used to treat COVID-19. SARS-CoV-2 is thought to be less likely to mutate to escape previously “unseen” antibodies.

LIBRA-seq means linking B cell receptors to antigen specificity through sequencing. It was developed in 2019 by Dr. Ian Setriff, a former graduate student in Georgiev’s lab, who is currently working in the biotechnology industry, and Andrea Siacolas, a current graduate student at Vanderbilt University.

Setliff wondered if the antibody’s gene sequence could be simultaneously mapped at high throughput to the identity of a particular viral antigen, a protein marker that the antibody recognizes and attacks. The goal was to find a faster way to identify antibodies that focus on a particular viral antigen.

With the help of VUMC’s Core Genomics Institute, Vanderbilt Technologies for Advanced Genomics (VANTAGE), Vanderbilt Flow Cytometry Shared Resource, and Vanderbilt University’s Advanced Computing Center for Research and Education (ACCRE), Georgiev tries out Setliff’s ideas. I did. done.

The efforts led by Setliff and Shiakolas culminated in a 2019 proof-of-concept manuscript of LIBRA-seq technology published in the journal Cell.

“Three or four years ago, it was impossible to move at current speeds,” said Georgiev. “There have been many changes in the very short period of time regarding the discovery of monoclonal antibodies and the development of vaccines.”

I have no time to lose. “If you give the virus enough time, many other variants will occur,” he said. One or more of them can be even worse than the Delta variant by avoiding current vaccines.

“That’s why we need as many options as possible,” said Georgiev. The antibodies described in this white paper “basically provide another tool in the toolbox.”

Georgiev and Jason McLellan, PhD at the University of Texas at Austin are the corresponding authors of this treatise. VUMC and UTAustin graduate students Kevin Kramer and Nicole Johnson are the first authors of this treatise, respectively.

In addition to Ciacolas, other VUMC co-authors include Naveen Suryadevara, PhD, Nagarajan Raju, PhD, Seth Zost, PhD, Lauren Walker, Steven Wall, Clinton Holt, Rachel Sutton, Ariana Paulo, James Crowe, Jr., MD, This is Robert Carnahan. ,doctorate

This study was partially funded by the National Institutes of Health grants AI131722, AI157155, AI127521, AI095202, Hayes Foundation COVID-19 Research Fund, Vanderbilt Dolly Parton COVID-19 Research Fund, Fast Grant, Welch Foundation, Mercatus Center. Was supported by. Of George Mason University.





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