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


Autoria(s): Althaus, Christian L.; Joos, Beda; Perelson, Alan S.; Günthard, Huldrych F.
Data(s)

01/10/2014

Resumo

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. We find that a substantial fraction of cells can become defectively infected. Assuming that the infection is homogenous throughout the body, we estimate an average in vivo viral burst size on the order of 104 virions per cell. Our study provides novel quantitative insights into the turnover and development of different subclasses of HIV-1-infected cells, and indicates that cells containing solely unspliced viral RNA are a good marker for viral latency. The model illustrates how the pool of latently infected cells becomes rapidly established during the first months of acute infection and continues to increase slowly during the first years of chronic infection. Having a detailed understanding of this process will be useful for the evaluation of viral eradication strategies that aim to deplete the latent reservoir of HIV-1.

Formato

application/pdf

Identificador

http://boris.unibe.ch/61459/1/Althaus%20PLoSComputBiol%202014.pdf

Althaus, Christian L.; Joos, Beda; Perelson, Alan S.; Günthard, Huldrych F. (2014). Quantifying the turnover of transcriptional subclasses of HIV-1-infected cells. PLoS computational biology, 10(10), e1003871. Public Library of Science 10.1371/journal.pcbi.1003871 <http://dx.doi.org/10.1371/journal.pcbi.1003871>

doi:10.7892/boris.61459

info:doi:10.1371/journal.pcbi.1003871

info:pmid:25340797

urn:issn:1553-734X

Idioma(s)

eng

Publicador

Public Library of Science

Relação

http://boris.unibe.ch/61459/

Direitos

info:eu-repo/semantics/openAccess

Fonte

Althaus, Christian L.; Joos, Beda; Perelson, Alan S.; Günthard, Huldrych F. (2014). Quantifying the turnover of transcriptional subclasses of HIV-1-infected cells. PLoS computational biology, 10(10), e1003871. Public Library of Science 10.1371/journal.pcbi.1003871 <http://dx.doi.org/10.1371/journal.pcbi.1003871>

Palavras-Chave #610 Medicine & health #360 Social problems & social services
Tipo

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

PeerReviewed