Study evaluates how rapid tests will perform when challenged with future SARS-CoV-2 variants

The availability of rapid antigen tests has significantly advanced efforts to contain the spread of COVID-19, but every new variant of concern raises questions about whether diagnostic tests will still be effective. A new study published in Cell attempts to address these questions by evaluating how rapid tests will perform when challenged with future SARS-CoV-2 variants.

The research team, led by Emory University and funded by the National Institute of Health's (NIH) Rapid Acceleration of Diagnostics (RADx) Tech program, developed a novel method for evaluating how mutations to SARS-CoV-2 can affect recognition by antibodies used in rapid antigen tests. Because most rapid antigen tests detect the SARS-CoV-2 nucleocapsid protein (N protein), the team directly measured how mutations to the N protein impacted diagnostic antibodies' ability to recognize their target.

"Based on our findings, none of the major past and present SARS-CoV-2 variants of concern contain mutations that would affect the capability of current rapid antigen tests to detect antibodies," says first study author Filipp Frank, Ph.D., an assistant professor in the department of biochemistry at Emory University. "Further, these data allow us to look one step ahead and predict test performance against almost any variant that may arise."

The study used a method called deep mutational scanning to evaluate all possible mutations in the N protein in a single, high-throughput experiment. Researchers then measured the impact of the mutations on their interaction with antibodies used in 11 commercially available rapid antigen tests and identified mutations that may allow for antibody escape.

Accurate and efficient identification of infected individuals remains a critically important strategy for COVID-19 mitigation, and our study provides information about future SARS-CoV-2 mutations that may interfere with detection. The results outlined here can allow us to quickly adapt to the virus as new variants continue to emerge, representing an immediate clinical and public health impact."

Eric Ortlund, Ph.D., senior study author, professor, department of biochemistry, Emory University

Findings show that it's relatively rare for variants to have mutations to the N protein that allow them to evade diagnostic tests, but there are a small proportion of sequences that could impact detection. Researchers, public health officials, and test manufacturers can use these data to determine if a diagnostic test needs to be evaluated for its ability to detect these mutations or to inform future test design.

"Considering the endless cycle of new variants, the data from this study will be useful for years to come," says Bruce J. Tromberg, Ph.D., director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and lead for the RADx® Tech program at NIH.

While many variants of concern contain multiple mutations to the N protein, the study authors note that their method does not evaluate how multiple mutations could affect diagnostic antibody recognition, representing a limitation of the study.

The project was supported by NIBIB under award numbers 75N92019P00328, U54EB015408, and U54EB027690 as part of the RADx initiative, launched to speed innovation in the development, commercialization and implementation of technologies for COVID-19 testing.

Source:
Journal reference:

Frank, F., et al. (2022) Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests. Cell. doi.org/10.1016/j.cell.2022.08.010.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Mucosal COVID-19 vaccine prevents airborne transmission of SARS-CoV-2