Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV

Abstract

HIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutations in vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.

An Evolutionary Model-Based Approach To Quantify the Genetic Barrier to Drug Resistance in Fast-Evolving Viruses and Its Application to HIV-1 Subtypes and Integrase Inhibitors

“…The A49P, M50I, V54I, L68I/V, L74I/M, T97A, S119R, V151I, M154I, K156N, E157Q, K160N, G163K/R, V165I, I203M, S230N, and D232N mutations were observed with a frequency above 1% in at least one subtype. 7 subtypes (49,54,74,92,118,148,153,157,160,170, and 263), 9 positions showed a consensus among 6 subtypes observed (68, 95, 119, 128, 140, 147, 156, 165, and 166), and, finally, 5 positions (114, 125, 151, 163, and 232) showed a consensus at 5 subtypes. These results illustrate well the extent of relevant integrase diversity within and between subtypes, encompassing varied entropy, resistance mutations, and codon predominance.…”

CpG Dinucleotides Inhibit HIV-1 Replication through Zinc Finger Antiviral Protein (ZAP)-Dependent and -Independent Mechanisms

“…CpG dinucleotides are suppressed throughout the HIV-1 genomic RNA (gRNA), and introducing CpGs into gag or env inhibits viral replication (12)(13)(14)(15)(16). Furthermore, analysis of clinical HIV-1 samples found that mutations that create new CpG dinucleotides in HIV-1 are twice as costly as those that do not and that increased CpG dinucleotide abundance in env may predict disease progression (17,18). There are at least four mechanisms by which CpG dinucleotides could inhibit HIV-1.…”

Drug resistance evolution in HIV in the late 1990s: hard sweeps, soft sweeps, clonal interference and the accumulation of drug resistance mutations

“…The samples were cloned and Sanger-sequenced so that we multiple independent viral sequences from each time point. We have previously used part of this dataset to study soft and hard selective sweeps (Pennings et al, 2014) and to study fitness costs of transition mutations (Theys et al, 2018).…”

“…Drug resistance in HIV provides great examples of evolutionary phenomena such as selective sweeps (Messer and Neher, 2012;Pennings et al, 2014), standing genetic variation (Li et al, 2011;Paredes et al, 2010;Pennings, 2012) and mutation-selection balance (Theys et al, 2018;Zanini et al, 2017). Even though HIV has been the subject of intensive research and studied by evolutionary biologists for decades, we are still often limited by the availability of high-quality data.…”

“…Another exception, and the only one that focuses on treated patients, is the dataset from Bacheler et al (2000), which we use in this paper. We have used this dataset for two previous studies (Pennings et al, 2014;Theys et al, 2018). In this manuscript, we show the many different patterns of drug resistance evolution observed in 1 the Bacheler dataset.…”