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This article is part of the supplement: Second Congress of Italian Evolutionary Biologists (First Congress of the Italian Society for Evolutionary Biology)

Open Access Research

Modeling HIV quasispecies evolutionary dynamics

Luca Sguanci12, Franco Bagnoli134 and Pietro Liò2*

Author Affiliations

1 CSDC, Center for the Study of Complex Systems, Firenze, Italy

2 Computer Laboratory, University of Cambridge, CB3 0FD Cambridge, UK

3 Dipartimento di Energetica, Università di Firenze, Via S. Marta 3, 50139 Firenze, Italy

4 INFN, sezione di Firenze, Italy

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BMC Evolutionary Biology 2007, 7(Suppl 2):S5  doi:10.1186/1471-2148-7-S2-S5

Published: 16 August 2007

Abstract

Background

During the HIV infection several quasispecies of the virus arise, which are able to use different coreceptors, in particular the CCR5 and CXCR4 coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor usage has been correlated with a faster progression of the disease to the AIDS phase. As several pharmaceutical companies are starting large phase III trials for R5 and X4 drugs, models are needed to predict the co-evolutionary and competitive dynamics of virus strains.

Results

We present a model of HIV early infection which describes the dynamics of R5 quasispecies and a model of HIV late infection which describes the R5 to X4 switch. We report the following findings: after superinfection (multiple infections at different times) or coinfection (simultaneous infection by different strains), quasispecies dynamics has time scales of several months and becomes even slower at low number of CD4+ T cells. Phylogenetic inference of chemokine receptors suggests that viral mutational pathway may generate a large variety of R5 variants able to interact with chemokine receptors different from CXCR4. The decrease of CD4+ T cells, during AIDS late stage, can be described taking into account the X4-related Tumor Necrosis Factor dynamics.

Conclusion

The results of this study bridge the gap between the within-patient and the inter-patients (i.e. world-wide) evolutionary processes during HIV infection and may represent a framework relevant for modeling vaccination and therapy.