A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Six Highly Conserved Targets of RNAi Revealed in HIV-1-Infected Patients from Russia Are Also Present in Many HIV-1 Strains Worldwide

RNAi has been suggested for use in gene therapy of HIV/AIDS, but the main problem is that HIV-1 is highly variable and could escape attack from the small interfering RNAs (siRNAs) due to even single nucleotide substitutions in the potential targets. To exhaustively check the variability in selected RNA targets of HIV-1, we used ultra-deep sequencing of six regions of HIV-1 from the plasma of two independent cohorts of patients from Russia. Six RNAi targets were found that are invariable in 82%-97% of viruses in both cohorts and are located inside the domains specifying reverse transcriptase (RT), integrase, vpu, gp120, and p17. The analysis of mutation frequencies and their characteristics inside the targets suggests a likely role for APOBEC3G (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G, A3G) in G-to-A mutations and a predominant effect of RT biases in the detected variability of the virus. The lowest frequency of mutations was detected in the central part of all six targets. We also discovered that the identical RNAi targets are present in many HIV-1 strains from many countries and from all continents. The data are important for both the understanding of the patterns of HIV-1 mutability and properties of RT and for the development of gene therapy approaches using RNAi for the treatment of HIV/AIDS.

Analysis of Variability in HIV-1 Subtype A Strains in Russia Suggests a Combination of Deep Sequencing and Multitarget RNA Interference for Silencing of the Virus

Any method for silencing the activity of the HIV-1 retrovirus should tackle the extremely high variability of HIV-1 sequences and mutational escape. We studied sequence variability in the vicinity of selected RNA interference (RNAi) targets from isolates of HIV-1 subtype A in Russia, and we propose that using artificial RNAi is a potential alternative to traditional antiretroviral therapy. We prove that using multiple RNAi targets overcomes the variability in HIV-1 isolates. The optimal number of targets critically depends on the conservation of the target sequences. The total number of targets that are conserved with a probability of 0.7-0.8 should exceed at least 2. Combining deep sequencing and multitarget RNAi may provide an efficient approach to cure HIV/AIDS.