On the contribution of Angola to the initial spread of HIV-1

Authors: Abecasis AB, Bártolo I, Leitner T, Pineda-Peña AC, Sousa JD, Taveira N, Theys K, Vandamme AM, Varanda J
Publication Year: 2016
Journal: Infection Genetics and Evolution
Link: https://www.ncbi.nlm.nih.gov/pubmed/27521160

Angola borders and has long-term links with Democratic Republic of Congo (DRC) as well as high levels of Human Immunodeficiency Virus (HIV) genetic diversity, indicating a potential role in the initial spread of the HIV-1 pandemic. Herein, we analyze 564 C2V3 and 354 pol publicly available sequences from DRC, Republic of Congo (RC) and Angola […]
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HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

Authors: Beheydt G, Bruzzone B, Camacho RJ, De Luca A, Deforche K, Grossman Z, Imbrechts S, Incardona F, Libin P, Pironti A, Rhee SY, Ruiz L, Sangeda RZ, Shafer RW, Sönnerborg A, Theys K, Torti C, Van de Vijver DA, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vercauteren J, Zazzi M
Journal: Infection Genetics and Evolution
Link: http://www.ncbi.nlm.nih.gov/pubmed/23523594

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment.
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RegaDB: Community-driven data management and analysis for infectious diseases

Authors: Alcantara LC, Assel M, Ayouba A, Beheydt G, Boucher C, Camacho RJ, Carvalho AP, Cavaco-Silva J, De Bel A, De Munter P, De Oliveira T, Deforche K, Ferreira F, Grossman Z, Imbrechts S, Kaiser R, Lacor P, Lapadula G, Libin P, Otelea D, Paraschiv S, Peeters M, Ruelle J, Sloot P, Snoeck J, Theys K, Torti C, Van Laethem K, Van Wijngaerden E, Vandamme AM, Wesner S, Zazzi M
Journal: Bioinformatics
Link: http://www.ncbi.nlm.nih.gov/pubmed/23645815

RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.
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Structural modifications induced by specific HIV-1 protease-compensatory mutations have an impact on the virological response to a first-line lopinavir/ritonavir-containing regimen

Authors: Alcaro S, Alteri C, Antinori A, Artese A, Beheydt G, Bertoli A, Ceccherini-Silberstein F, Costa G, d’Arminio Monforte A, Girardi E, Gori C, Orchi N, Parrotta L, Perno CF, Santoro MM, Svicher V, Theys K, Vandamme AM
Publication Year: 2013
Journal: Journal of Antimicrobial Chemotherapy
Link: http://www.ncbi.nlm.nih.gov/pubmed/23687186

This study evaluates the impact of specific HIV-1 protease-compensatory mutations (wild-type amino acids in non-B subtypes) on virological response to a first-line lopinavir/ritonavir-containing regimen in an HIV-1 subtype B-infected population.
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Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

BACKGROUND:
The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission.
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On the contribution of Angola to the initial spread of HIV-1

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

RegaDB: Community-driven data management and analysis for infectious diseases

Structural modifications induced by specific HIV-1 protease-compensatory mutations have an impact on the virological response to a first-line lopinavir/ritonavir-containing regimen

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

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