Analysis of mutational history of multidrug‐resistant genotypes with a mutagenetic tree model

Abstract

Human immunodeficiency virus (HIV) can develop resistance to all antiretroviral drugs. Multidrug 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 multidrug resistance, we analyzed the EuResist database to uncover the accumulation of mutations over time. We hypothesize that the 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 multidrug resistance. Our evolutionary model shows an almost monotonic increase of resistance with each acquired mutation, including less well‐known nucleoside reverse transcriptase (RT) inhibitor‐related mutations like K223Q, L228H, and Q242H. Mutations within the integrase (IN) (T97A, E138A/K G140S, Q148H, N155H) indicate high probability of multidrug resistance. Hence, these IN mutations also tend to be observed together with mutations in the protease (PR) and 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 multidrug resistance.

Incorporating temporal dynamics of mutations to enhance the prediction capability of antiretroviral therapy’s outcome for HIV-1

“…Our study’s implications align with a concept emerging from a recent study conducted by part of our team to study mutational history in a different context ( Pirkl et al 2023 ). In this work, data from various patients are used cross-sectionally rather than longitudinally to infer the accumulation of mutations in multidrug-resistant patients, i.e.…”

“…Therefore, the respective model can predict aspects of mutational history from current genotypes. For example, if we observe a genotype with the X mutation and not with the Y mutation, but in the mutational history, Y was observed before X, Pirkl et al (2023) hypothesize that the Y mutation may now be present only in the latent reservoir genotypes and not in the blood serum and that mutations are still present in the latent reservoir and thus have an impact on future therapies. Both studies emphasize the importance of mutations that occurred in the past for future therapies and drug resistance, respectively.…”

Alterations of SARS-CoV-2 Evolutionary Dynamics by Pharmaceutical Factors

“…Multidrug combinations may be a useful approach for reducing the spread of drug-resistant variants. [111] These approaches may be used to mitigate the impact of drug resistance in the future.…”