Prevent the evolution of SARS-CoV-2 by targeting low probability stochastic events

The rapidity with which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are emerging poses a threat to obtaining herd immunity against coronavirus disease 2019 (COVID-19). Multiple point mutations are often responsible for the emergence of these new variants of SARS-CoV-2 which are associated with traits such as increased duration of infection, 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 shown that people with impaired immune function can create a favorable environment by eliminating high levels of SARS-CoV-2 for weeks. This allows the virus to undergo beneficial phenotypic changes that allow it to evade the immune response.

To study: Long-term control of SARS-CoV-2 infections may slow viral progression and reduce the risk of treatment failure. Image Credit: PHOTOCREO Michal Bednarek /

About the study

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

In the present study, several different steps were used to generate new advantageous variants which are stochastic and occur largely by chance. The first step involved creating genetic diversity within infected individuals through stochastic events.

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

Genetic diversity helps the development and expansion of beneficial mutations due to natural selection in individuals infected with SARS-CoV-2. Comparatively, genetic drift hampers the expansion of beneficial viral mutations to 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 trigger infection in a new host by the low number of viral particles, thus creating a tight transmission bottleneck. Intervention studies can be designed to slow viral progression by viewing these stochastic factors as a potential weakness.

Study results

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

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

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

Conclusion and limits

The results of the present study suggest practical methods for controlling long-term SARS-CoV-2 infections that will be important in slowing the rate of viral progression. Here, the authors also show that the expected frequency of variant generation events will be sufficient to cause a substantial threat to public health.

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

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

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