T Cell Dynamics in HIV-1 Infection

2007

J Virol

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Although CD8 ؉ T cells play an important role in controlling viral infections, boosting specific CD8 ؉ T cells by prophylactic vaccination with simian immunodeficiency virus (SIV) epitopes fails to provide sterilizing immunity. Viral replication rates and viral contraction rates after the peak viremia hardly depend on the presence of memory CD8 ؉ T cells. To study these paradoxical findings, we parameterize novel mathematical models for acute SIV and human immunodeficiency virus infection. These models explain that failure of vaccination is due to the fact that effector/target ratios are too low during the viral expansion phase. Because CD8 ؉ T cells require cell-to-cell contacts, immune protection requires high effector/target ratios at the primary site of infection. Effector/target ratios become favorable for immune control at the time of the peak in the viral load when the virus becomes limited by other factors, such as the availability of uninfected target cells. At the viral set point, effector/target ratios are much higher, and perturbations of the number of CD8 ؉ effector cells have a large impact on the viral load. Such protective effector/target ratios are difficult to achieve with nucleic acid-or protein-based vaccines.

supporting

confidence: 73%

Understanding the Failure of CD8⁺T-Cell Vaccination against Simian/Human Immunodeficiency Virus

2007

J Virol

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“…3a) (29). The RTE pool decreases proportionally to the thymic output, which decreases Ͼ100-fold and is close to the previously estimated 10 8 cells d Ϫ1 at age 30 (30). Because the naive T cell population rapidly fills up by renewal, we find that, even at very young age, only 10% of the total naive T cells is an RTE.…”

Section: Model Behaviorsupporting

confidence: 86%

“…Steinmann et al (7) showed that the involution of the thymus is ϳ0.05 y Ϫ1 , which is about 100-fold over a human lifetime. The thymic output of a healthy 30-year-old adult was estimated to be ϳ10 8 cells per day (30).…”

Section: Parametersmentioning

confidence: 99%

“…To obtain such a decrease in this ratio, and the observed decrease in thymic output, the thymocyte proliferation rate, t , is reduced at a rate ϭ 5 ϫ 10 Ϫ5 d Ϫ1 , i.e., the proliferation rate halves in ϳ40 years. The initial thymocyte proliferation rate was assumed to be t0 ϭ 0.6 d Ϫ1 , and the daily production of TCR␤ ϩ thymocytes was set to ϭ 4.48 ϫ 10 8 cell per day, which in combination delivered the measured thymic output of 10 8 cells per day at the age of 30 (30).…”

Section: Parametersmentioning

confidence: 99%

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The Effects of Age, Thymectomy, and HIV Infection on α and β TCR Excision Circles in Naive T Cells

Dool

The Journal of Immunology

2006

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Due to homeostasis total naive T cell numbers remain fairly constant over life despite a gradual involution of the thymus. The contribution of the thymus to maintaining naive T cell pools is typically measured with TCR excision circles (TRECs) that are formed in thymocytes. The mechanisms underlying thymic involution are poorly understood. Some data suggest that thymocytes undergo fewer divisions in old (small) than young (large) thymi, and other data suggest that the number of TRECs per thymocyte is independent of age. If thymic involution were associated with a decreased number of divisions of the thymocytes, this would markedly complicate the interpretation of TREC data. To study this we develop a mathematical model in which the division rate of thymocytes decreases with increasing age. We describe the dilution of TRECs formed during the arrangement of both chains of the TCR by division of thymocytes, recent thymic emigrants, and mature naive T cells. The model behavior is complicated as TREC contents in naive T cells can increase with age due to decreased dilution in the thymus. Because our model is consistent with current data on the effects of age and thymectomy on TRECs in peripheral T cells, we conclude that aging may well affect thymocyte division, which markedly complicates the interpretation of TREC data. It is possible, but more difficult, to let the model be consistent with the rapid changes in α and β TRECs observed shortly after HIV infection.

“…The five monkeys with a low viral load have an intermediate average death rate. This twofold difference between uninfected monkeys and monkeys with a high viral load is considerably smaller than the sevenfold increase in d, and than the more than 10-fold increase in r in table 1 (and that in Mohri et al (1998)), but is in good agreement with human data (Clark et al 1999). We conclude that these BrdU data allow one to estimate reliably only the average rate of death.…”

Section: One-compartment Modelssupporting

confidence: 75%

Estimating average cellular turnover from 5–bromo–2'–deoxyuridine (BrdU) measurements

Mohri

et al. 2003

Proc. R. Soc. Lond. B

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Cellular turnover rates in the immune system can be determined by labelling dividing cells with 5-bromo-29-deoxyuridine (BrdU) or deuterated glucose ( 2 H-glucose). To estimate the turnover rate from such measurements one has to fit a particular mathematical model to the data. The biological assumptions underlying various models developed for this purpose are controversial. Here, we fit a series of different models to BrdU data on CD4 1 T cells from SIV 2 and SIV 1 rhesus macaques. We first show that the parameter estimates obtained using these models depend strongly on the details of the model. To resolve this lack of generality we introduce a new parameter for each model, the 'average turnover rate', defined as the cellular death rate averaged over all subpopulations in the model. We show that very different models yield similar estimates of the average turnover rate, i.e. ca. 1% day 2 1 in uninfected monkeys and ca. 2% day 2 1 in SIV-infected monkeys. Thus, we show that one can use BrdU data from a possibly heterogeneous population of cells to estimate the average turnover rate of that population in a robust manner.