Does antiretroviral treatment change HIV-1 codon usage patterns in its genes: a preliminary bioinformatics study
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AIDS Research and Therapy Open Access
RESEARCH
Does antiretroviral treatment change HIV‑1 codon usage patterns in its genes: a preliminary bioinformatics study Navaneethan Palanisamy1,2,3,4*, Nathan Osman1,2, Frédéric Ohnona1, Hong‑Tao Xu1, Bluma Brenner1, Thibault Mesplède1 and Mark A. Wainberg1,2
Abstract Background: Codon usage bias has been described for various organisms and is thought to contribute to the regulation of numerous biological processes including viral infections. HIV-1 codon usage has been previously shown to be different from that of other viruses and man. It is evident that the antiretroviral drugs used to restrict HIV-1 replication also select for resistance variants. We wanted to test whether codon frequencies in HIV-1 sequences from treatment-experienced patients differ from those of treatment-naive individuals due to drug pressure affecting codon usage bias. Results: We developed a JavaScript to determine the codon frequencies of aligned nucleotide sequences. Irre‑ spective of subtypes, using HIV-1 pol sequences from 532 treatment-naive and 52 treatment-experienced individu‑ als, we found that pol sequences from treatment-experienced patients had significantly increased AGA (arginine; p = 0.0002***) and GGU (glycine; p = 0.0001***), and decreased AGG (arginine; p = 0.0001***) codon frequencies. The same pattern was not observed when subtypes B and C sequences were analyzed separately. Additionally, irre‑ spective of subtypes, using HIV-1 gag sequences from 524 treatment-naive and 54 treatment-experienced individuals, gag sequences from treatment-experienced patients had significantly increased CUA (leucine; p twofold more common within the HIV-1 than in the human genome (Fig. 1, represented by *). UGG (tryptophan) was also overrepresented in HIV-1 compared to humans; however, given that UGG is the only codon for tryptophan, this observation simply indicates that this amino acid is more prevalent in HIV-1 than in human proteins (Fig. 1, represented by #). An earlier study also reported differences in codon usage patterns between HIV-1 and humans using HIV sequences obtained over 23 years [11]. Phylogeny and resistance analysis of studied sequences
First, we wanted to evaluate evolutionary relationships among the sequences used in this study. pol gene
Palanisamy et al. AIDS Res Ther (2017) 14:2
sequences from 532 treatment-naive and 52 treatmentexperienced HIV-1 samples were studied. For the construction of a phylogenetic tree, MEGA6 (http://www. megasoftware.net/) software was used [18]. The tree construction parameters included: Maximum Likelihood (for statistical analysis), Bootstrap method (for testing of phylogeny), 1000 (for number of Bootstrap replications), nucleotides (for substitution type), Tamura-Nei model (for model) while others were set to default parameters. From the phylogenetic tree, we found that the sequences formed distinct diverse clusters, thereby making their sequences ideal for further analysis (Fig. 2). We also evaluated resistance mutations in treatmentna
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