Impeding SARS‑CoV‑2 evolution by targeting low-probability stochastic events

The rapid rate at which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerge poses a threat to attaining herd immunity against the coronavirus disease 2019 (COVID-19). Multiple point mutations are often responsible for the emergence of these novel SARS-CoV-2 variants that are associated with traits like increased infection duration, transmissibility, and immune evasion. In many cases, the emergence of variants has been associated with a longer duration of infections in immunocompromised individuals and patients treated with convalescent plasma.

Various previous studies have depicted that individuals with impaired immune function can create a favorable environment by shedding high levels of SARS-CoV-2 for weeks. This enables the virus to undergo advantageous phenotypic changes that allow for its ability to escape the immune response.

Study: Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure. Image Credit: PHOTOCREO Michal Bednarek / Shutterstock.com

About the study

In a recent Scientific Reports article, the authors explored the emergence of more fit SARS-CoV-2 variants using a stochastic evolutionary modeling framework during long-term infections. By discerning the factors responsible for the evolutionary process for SARS-CoV-2, the authors of this study anticipate that their findings could assist in the development of biomedical interventions that can control the pandemic.

In the current study, several different steps were utilized to generate novel advantageous variants that are stochastic and occur largely by random chance. The first step involved the creation of genetic diversity within infected individuals through stochastic events.

Deep sequencing studies have shown that within the host, the SARS-CoV-2 viral population exists as a quasi-species due to de novo mutations during the infection. These studies have also established the role of genetic drift and intrahost transmission bottlenecks in the movement of the virus from one region of the body to another.

Genetic diversity helps in the development and expansion of advantageous mutations due to natural selection within individuals infected with SARS-CoV-2. Comparatively, genetic drift hinders the expansion of advantageous viral mutations at small population sizes.

The next step involved the transmission of viral variants generated in a COVID-19 patient to new hosts. Stochasticity was introduced during this process to start an infection in a new host by the low numbers of viral particles, thus creating a narrow transmission bottleneck. Intervention studies can be designed to slow viral evolution considering these stochastic factors as a potential weakness.

Study findings

The authors simulated stochastic viral evolution using a modified Wright-Fisher model and observed that over the course of a typical-length SARS-CoV-2 infection, which typically lasts around 23 days, viral variants with point mutations increased the replication probability by 20–50%. Their expansion was also higher than variants with neutral or weakly deleterious fitness effects, thus leading to an increase in the probability of transmission of at least one viral particle with a specific beneficial mutation to a new host.

These results suggest that new SARS-CoV-2 lineages with advantageous single mutations are rapidly established at the population level due to the selection for beneficial single-point mutations within COVID-19 patients. The data also showed that patients with longer periods of higher viral load were able to transmit more fit SARS-CoV-2 variants more effectively.

It was observed that as the number of COVID-19 patients with longer SARS-CoV-2 infections increases, the rate at which novel and more fit variants with two mutations also increases. Overall, the simulation results depicted that SARS-CoV-2 evolution can be hindered by targeting the various low-probability stochastic events that are crucial for SARS-CoV-2 variant emergence.

Conclusion and limitations

The findings of the current study suggest practical methods to attain control of long-term SARS-CoV-2 infections that will be important for slowing the rate of viral evolution. Herein, the authors also show that the expected frequency of variant-generation events will be sufficient to cause a substantial public health threat.

There are a few limitations associated with this model. The authors supposed that patients were initially infected with only wild-type viruses and did not consider the existing genetic variation in the population that might be responsible for advantageous viral mutations. The model also did not consider the variation in some parts of the viral replication cycle, which may act as additional stochastic events that could affect viral evolution.

Understanding the mechanism of SARS-CoV-2 evolution allows us to design strategies that can tip the balance in this evolutionary arms race and ultimately allow us to control the spread of SARS-CoV-2”

Journal reference:
Saurabh Chaturvedi

Written by

Saurabh Chaturvedi

Saurabh Chaturvedi is a freelance writer from Jaipur, India. He is a gold medalist in Masters in Pharmaceutical Chemistry and has extensive experience in medical writing. He is passionate about reading and enjoys watching sci-fi movies.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Chaturvedi, Saurabh. (2021, November 24). Impeding SARS‑CoV‑2 evolution by targeting low-probability stochastic events. News-Medical. Retrieved on November 18, 2024 from https://www.news-medical.net/news/20211124/Impeding-SARSe28091CoVe280912-evolution-by-targeting-low-probability-stochastic-events.aspx.

  • MLA

    Chaturvedi, Saurabh. "Impeding SARS‑CoV‑2 evolution by targeting low-probability stochastic events". News-Medical. 18 November 2024. <https://www.news-medical.net/news/20211124/Impeding-SARSe28091CoVe280912-evolution-by-targeting-low-probability-stochastic-events.aspx>.

  • Chicago

    Chaturvedi, Saurabh. "Impeding SARS‑CoV‑2 evolution by targeting low-probability stochastic events". News-Medical. https://www.news-medical.net/news/20211124/Impeding-SARSe28091CoVe280912-evolution-by-targeting-low-probability-stochastic-events.aspx. (accessed November 18, 2024).

  • Harvard

    Chaturvedi, Saurabh. 2021. Impeding SARS‑CoV‑2 evolution by targeting low-probability stochastic events. News-Medical, viewed 18 November 2024, https://www.news-medical.net/news/20211124/Impeding-SARSe28091CoVe280912-evolution-by-targeting-low-probability-stochastic-events.aspx.

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...
Phase 2 study evaluates safety and efficacy of asunercept in COVID-19 patients