XVIII International AIDS Conference


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Development of a bioinformatic tool for analysis of HIV-1 drug resistance mutations

D.R.M. Cunha1, J.C. Couto-Fernandez1, T. Oliveira2, B. Galvão-Castro3, L.C. Alcantara3

1Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Rio de Janeiro, Brazil, 2South African National AIDS Council Secretariat Bioinformatics Institute, Cape Town, South Africa, 3Oswaldo Cruz Foundation - Gonçalo Moniz Research Center, Advanced Laboratory of Public Health, Salvador, Brazil

Background: Bioinformatic tools are useful in the analysis of the drug resistance mutations identified bygenerated from genotyping HIV-1. However, each analytic tool uses different logistics, difficulting interpretation and comparison of results. To streamline and systematize the analyses, we developed a bioinformatic tool for easy handling, allowing the identification of antiretroviral resistance mutations, in addition to possible post-translational glycosylation and phosphorylation sites in HIV-1 derived sequences.
Methods: We created a script to classify the HIV-1 pol sequences of different subtypes and recombinant forms using a local database on Mysql. We used the PHP (PHP: Hypertext Preprocessor) program languag, in an environment oriented through the Internet. It is a free public tool available on the web, hosted on a Linux server, hosted in the Laboratório Avançado de Saúde Pública-LASP/FIOCRUZ.
Results: Currently, 8.058 HIV-1 Brazilian sequences available in the database (Los Alamos) and 1.656 pol sequences derived from genotyping, were stored, in the script that organized and inserted the information in the database. The sequences were classified according to access number, country of origin, subtype, year of sampling. The analysis tool accesses the database and identifies the site mutations that confer-drug resistance, both in the sequences stored and in the sequences submitted by users to the bioinformatic tool. The system displays a screen with the overall result of the analysis and providing a link to access the data in XML format.
Conclusions: Our bioinformatic tool could perform the analysis of HIV-1 sequences of different subtypes and recombinant forms, also providing the results of their analysis in XML format to be transported and stored or used in different systems. Our results are in agreement with other tools for this type of analysis, demonstrating its applicability for the evaluation of HIV-1 drug resistance and as a additional support for AIDS vaccine trials.

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