Quantifying the turnover of transcriptional subclasses of HIV-1-infected cells

Abstract

HIV-1-infected cells in peripheral blood can be grouped into different transcriptional subclasses. Quantifying the turnover of these cellular subclasses can provide important insights into the viral life cycle and the generation and maintenance of latently infected cells. We used previously published data from five patients chronically infected with HIV-1 that initiated combination antiretroviral therapy (cART).Patient-matched PCR for unspliced and multiply spliced viral RNAs combined with limiting dilution analysis provided measurements of transcriptional profiles at the single cell level. Furthermore, measurement of intracellular transcripts and extracellular virion-enclosed HIV-1 RNA allowed us to distinguish productive from non-productive cells. We developed a mathematical model describing the dynamics of plasma virus and the transcriptional subclasses of HIV-1-infected cells. Fitting the model to the data allowed us to better understand the phenotype of different transcriptional subclasses and their contribution to the overall turnover of HIV-1 before and during cART. The average number of virus-producing cells in peripheral blood is small during chronic infection (25.7 cells ml −1 ). We find that 14.0%, 0.3% and 21.2% of infected cells become defectively, latently and persistently infected cells, respectively. Assuming that the infection is homogenous throughout the body, we estimate an average in vivo viral burst size of 2.1 × 10 4 virions per cell. Our study provides novel quantitative insights into the turnover and develop-

Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART

“…In this initial study, the fraction of proviruses expressing HIV RNA was not obviously different between donors on and off ART. Possibly, the low levels of expression occur for two different reasons: selection for cells containing inactive proviruses in donors on ART (33)(34)(35)(36)(37)(38) and large amounts of unintegrated and nontranscribed viral DNA in donors not on ART (39)(40)(41). In either case, establishing the generality of this unexpected finding will require confirmation and further investigation in larger numbers of individuals both on and off ART.…”

What do mathematical models tell us about killing rates during HIV-1 infection?

“…The two-stage model is a simple extension of the basic model, and underlines how the rate limiting step alters the interpretation of the initial viral decay. More sophisticated models either with multiple cellular compartments [52,43], or with n stages from infection to viral production [53,54] have been proposed for a complete description of all three phases of viral decay. Nevertheless, the two-stage model with CTL-mediated killing of infected cells either in the early or late stage can qualitatively explain the results from ART studies (phase I) with or without CD8-depletion.…”

Antiretroviral drug exposure in lymph nodes is heterogeneous and drug dependent

“…Under these conditions, we observed active recruitment of CD4 + T cells within B cell follicles, where vRNA was predominately trapped within the FDC network. Previous studies estimated the average viral burst size to be 3–4 log10 virions/cell in a lifetime [53] and that virion production after T cell activation from individual proviruses varies by 10,000‐fold to 100,000‐fold [54], given a vast range of virion production per cell. We estimate that up to 99% of total vRNA was attributable to free virions.…”