Limits...
Dynamic correlation between intrahost HIV-1 quasispecies evolution and disease progression.

Lee HY, Perelson AS, Park SC, Leitner T - PLoS Comput. Biol. (2008)

Bottom Line: We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants.The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces.In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu

ABSTRACT
Quantifying the dynamics of intrahost HIV-1 sequence evolution is one means of uncovering information about the interaction between HIV-1 and the host immune system. In the chronic phase of infection, common dynamics of sequence divergence and diversity have been reported. We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants. The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces. Analysis of the model suggested that the previously observed saturation of divergence and decrease of diversity in later stages of infection can be explained by a decrease in the proportion of offspring that are mutants as the distance from the founder strain increases rather than due to an increase of viral fitness. The prediction of the model was examined by performing phylogenetic analysis to estimate the change in the rate of evolution during infection. In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline. The correlation between the dynamics of the evolutionary rate and the rate of CD4+ T-cell decline, coupled with our HIV-1 sequence evolution model, explains previously conflicting observations of the relationships between the rate of HIV-1 quasispecies evolution and disease progression.

Show MeSH

Related in: MedlinePlus

Dynamics of divergence and diversity with emergence of X4                                viruses.Dynamics of divergence and diversity when imposing a greater level of                                fitness for certain types of viruses which emerge and persist, for                                example, by acquiring X4 tropism. The X4 viruses appear at                                d = 50 with                                greater level of fitness                                Fhigh = 1.5                                in comparison to R5 viruses with fitness                                F = 1. The                                fraction of X4 viruses out of the total virus population with                                    d≥50 is given by                                    α. The rapid transient increases                                both in divergence and diversity upon the emergence of X4 viruses                                are observed. The scale factor for the divergence is 500, that for                                the diversity is 100, and                                M(d) = 0.5                                for all d.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2602878&req=5

pcbi-1000240-g006: Dynamics of divergence and diversity with emergence of X4 viruses.Dynamics of divergence and diversity when imposing a greater level of fitness for certain types of viruses which emerge and persist, for example, by acquiring X4 tropism. The X4 viruses appear at d = 50 with greater level of fitness Fhigh = 1.5 in comparison to R5 viruses with fitness F = 1. The fraction of X4 viruses out of the total virus population with d≥50 is given by α. The rapid transient increases both in divergence and diversity upon the emergence of X4 viruses are observed. The scale factor for the divergence is 500, that for the diversity is 100, and M(d) = 0.5 for all d.

Mentions: Figure 6 plots the dynamics of divergence and diversity by changing the fraction (α) of X4 viruses that have a 50% increase of fitness at distance dc = 50 mutations. As we increase the value of α, we observe an increase in divergence, then a transient rapid increase followed again by the inital slope of linear increase. The emergence and persistency of X4 viruses in the population leads to a rapid increase of diversity followed by a decline of diversity. Then at the final stage, diversity starts to increase again. This trend is robust to both the amount of fitness increase and the value of dc. For example, when we chose dc = 30, the transient rapid increases in the divergence and diversity still occur, but were shifted to 4.2 years. An initial rapid increase both in diversity and divergence due to the emergence of more fit virus is not compatible with the in vivo measurements from HIV-1 infected patients (Figure 3).


Dynamic correlation between intrahost HIV-1 quasispecies evolution and disease progression.

Lee HY, Perelson AS, Park SC, Leitner T - PLoS Comput. Biol. (2008)

Dynamics of divergence and diversity with emergence of X4                                viruses.Dynamics of divergence and diversity when imposing a greater level of                                fitness for certain types of viruses which emerge and persist, for                                example, by acquiring X4 tropism. The X4 viruses appear at                                d = 50 with                                greater level of fitness                                Fhigh = 1.5                                in comparison to R5 viruses with fitness                                F = 1. The                                fraction of X4 viruses out of the total virus population with                                    d≥50 is given by                                    α. The rapid transient increases                                both in divergence and diversity upon the emergence of X4 viruses                                are observed. The scale factor for the divergence is 500, that for                                the diversity is 100, and                                M(d) = 0.5                                for all d.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2602878&req=5

pcbi-1000240-g006: Dynamics of divergence and diversity with emergence of X4 viruses.Dynamics of divergence and diversity when imposing a greater level of fitness for certain types of viruses which emerge and persist, for example, by acquiring X4 tropism. The X4 viruses appear at d = 50 with greater level of fitness Fhigh = 1.5 in comparison to R5 viruses with fitness F = 1. The fraction of X4 viruses out of the total virus population with d≥50 is given by α. The rapid transient increases both in divergence and diversity upon the emergence of X4 viruses are observed. The scale factor for the divergence is 500, that for the diversity is 100, and M(d) = 0.5 for all d.
Mentions: Figure 6 plots the dynamics of divergence and diversity by changing the fraction (α) of X4 viruses that have a 50% increase of fitness at distance dc = 50 mutations. As we increase the value of α, we observe an increase in divergence, then a transient rapid increase followed again by the inital slope of linear increase. The emergence and persistency of X4 viruses in the population leads to a rapid increase of diversity followed by a decline of diversity. Then at the final stage, diversity starts to increase again. This trend is robust to both the amount of fitness increase and the value of dc. For example, when we chose dc = 30, the transient rapid increases in the divergence and diversity still occur, but were shifted to 4.2 years. An initial rapid increase both in diversity and divergence due to the emergence of more fit virus is not compatible with the in vivo measurements from HIV-1 infected patients (Figure 3).

Bottom Line: We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants.The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces.In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu

ABSTRACT
Quantifying the dynamics of intrahost HIV-1 sequence evolution is one means of uncovering information about the interaction between HIV-1 and the host immune system. In the chronic phase of infection, common dynamics of sequence divergence and diversity have been reported. We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants. The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces. Analysis of the model suggested that the previously observed saturation of divergence and decrease of diversity in later stages of infection can be explained by a decrease in the proportion of offspring that are mutants as the distance from the founder strain increases rather than due to an increase of viral fitness. The prediction of the model was examined by performing phylogenetic analysis to estimate the change in the rate of evolution during infection. In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline. The correlation between the dynamics of the evolutionary rate and the rate of CD4+ T-cell decline, coupled with our HIV-1 sequence evolution model, explains previously conflicting observations of the relationships between the rate of HIV-1 quasispecies evolution and disease progression.

Show MeSH
Related in: MedlinePlus