Analysis of mutational history of multi-drug resistant genotypes with a mutagenetic tree model

Martin Pirkl*, Joachim Büch, Carole Devaux, Michael Böhm, Anders Sönnerborg, Francesca Incardona, Ana Abecasis, Anne-Mieke Vandamme, Maurizio Zazzi, Rolf Kaiser, Thomas Lengauer, The EuResist Network Study Group

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multi-drug resistance however is a rare event in modern HIV treatment, but can be life-threatening, particular in patients with very long therapy histories and in areas with limited access to novel drugs. To understand the evolution of multi-drug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that accumulation of resistance mutations is not acquired simultaneously and randomly across viral genotypes but rather tends to follow a predetermined order. The knowledge of this order might help to elucidate potential mechanisms of multi-drug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well known NRTI-related mutations like K223Q, L228H and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multi-drug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and reverse transcriptase (RT). We followed up with an analysis of the mutation-specific error rates of our model given the data. We identified several mutations with unusual rates (PR: M41L, L33F, IN: G140S). This could imply the existence of previously unknown virus variants in the viral quasispecies. In conclusion, our bioinformatics model supports the analysis and understanding of multi-drug resistance. This article is protected by copyright. All rights reserved.

Original languageEnglish
Article numbere28389
JournalJournal of Medical Virology
Volume95
Issue number1
Early online date9 Dec 2022
DOIs
Publication statusPublished - Jan 2023

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