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Reviews of "Identification of a Molnupiravir-associated Mutational Signature in SARS-CoV-2 Sequencing Databases"

Reviewers: R Neher (University of Basel) | 📘📘📘📘📘

Published onApr 25, 2023
Reviews of "Identification of a Molnupiravir-associated Mutational Signature in SARS-CoV-2 Sequencing Databases"
key-enterThis Pub is a Review of
Identification of a molnupiravir-associated mutational signature in SARS-CoV-2 sequencing databases
Identification of a molnupiravir-associated mutational signature in SARS-CoV-2 sequencing databases
Description

Molnupiravir, an antiviral medication that has been widely used against SARS-CoV-2, acts by inducing mutations in the virus genome during replication. Most random mutations are likely to be deleterious to the virus, and many will be lethal. Molnupiravir-induced elevated mutation rates have been shown to decrease viral load in animal models. However, it is possible that some patients treated with molnupiravir might not fully clear SARS-CoV-2 infections, with the potential for onward transmission of molnupiravir-mutated viruses. We set out to systematically investigate global sequencing databases for a signature of molnupiravir mutagenesis. We find that a specific class of long phylogenetic branches appear almost exclusively in sequences from 2022, after the introduction of molnupiravir treatment, and in countries and age-groups with widespread usage of the drug. We calculate a mutational spectrum from the AGILE placebo-controlled clinical trial of molnupiravir and show that its signature, with elevated G-to-A and C-to-T rates, largely corresponds to the mutational spectrum seen in these long branches. Our data suggest a signature of molnupiravir mutagenesis can be seen in global sequencing databases, in some cases with onwards transmission.

To read the original manuscript, click the link above.

Reviewer 1 (Richard N…) | 📘📘📘📘📘

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the reviews, click the links below. 


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