RESUMEN
The HIV reservoir is a population of 1-10 million anatomically dispersed, latently infected memory CD4+ T cells in which HIV DNA is quiescently integrated into human chromosomal DNA. When antiretroviral therapy (ART) is stopped and HIV replication initiates in one of these cells, systemic viral spread resumes, rekindling progression to AIDS. Therefore, HIV latency prevents cure. The detection of many populations of identical HIV sequences at unique integration sites implicates CD4+ T cell proliferation as the critical driver of reservoir sustainment after a prolonged period of effective ART. Initial reservoir formation occurs during the first week of primary infection usually before ART is started. While empirical data indicates that both de novo infection and cellular proliferation generate latently infected cells during early untreated infection, it is not known which of these mechanisms is predominant. We developed a mathematical model that recapitulates the profound depletion and brisk recovery of CD4+ T cells, reservoir creation, and viral load trajectory during primary HIV infection. We extended the model to stochastically simulate individual HIV reservoir clones. This model predicts the first detection of HIV infected clones approximately 5 weeks after infection as has recently been shown in vivo and suggests that substantial, uneven proliferation among clones during the recovery from CD4+ lymphopenia is the most plausible explanation for the observed clonal reservoir distribution during the first year of infection.
RESUMEN
Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentrations of individual bacterial species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We sought to determine the accuracy of an inferred measure of bacterial concentration using total bacterial load and relative abundance. We analyzed 1,320 samples from 20 women with a history of frequent bacterial vaginosis who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and bacterial load (measured by broad-range 16S rRNA gene qPCR). Log10-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, P < 2.2e-16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacteria associated with larger errors. A total of 92% of the >0.5-log10 errors occurred when the relative abundance was <10%. Many errors occurred during early bacterial expansion from or late contraction to low abundance. When the relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR in the vaginal microbiome. However, targeted qPCR is required to capture bacteria at low relative abundance and is preferable for characterizing growth and decay kinetics of single species.IMPORTANCE Microbiome studies primarily use 16S rRNA gene amplicon sequencing to assess the relative abundance of bacterial taxa in a community. However, these measurements do not accurately reflect absolute taxon concentrations. We sought to determine whether the product of species' relative abundance and total bacterial load measured by broad-range qPCR is an accurate proxy for individual species' concentrations, as measured by taxon-specific qPCR assays. Overall, the inferred bacterial concentrations were a reasonable proxy of species-specific qPCR values, particularly when bacteria are present at a higher relative abundance. This approach offers an opportunity to assess the concentrations of bacterial species and how they change in a community over time without developing individual qPCR assays for each taxon.
