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What do we measure when we measure cell-associated HIV RNA
Retrovirologyvolume 15, Article number: 13 (2018)
Cell-associated (CA) HIV RNA has received much attention in recent years as a surrogate measure of the efficiency of HIV latency reversion and because it may provide an estimate of the viral reservoir size. This review provides an update on some recent insights in the biology and clinical utility of this biomarker. We discuss a number of important considerations to be taken into account when interpreting CA HIV RNA measurements, as well as different methods to measure this biomarker.
To express all its genes, HIV produces a large number of differentially spliced transcripts collectively termed “cell-associated (CA) HIV RNA” [1, 2]. In HIV-infected individuals, especially those on suppressive antiretroviral therapy (ART), CA HIV RNA is an important surrogate marker of the viral reservoir and the response to ART [3,4,5]. Recent years have seen considerable interest in quantifying CA RNA as a measure of HIV latency reversion, therefore it has been used as a readout in a number of clinical trials aimed at HIV remission [6,7,8,9]. For the correct interpretation of the outcomes of such trials, it is necessary to understand the meaning of CA RNA measurements. In 2013, the significance of CA HIV RNA as a biomarker of viral persistence was summarized in an extensive review article . This review provides an update on some recent insights in the biology and clinical utility of this biomarker.
Transcription versus production versus replication: What do we measure?
By establishing latent infection, HIV forms a long-lived reservoir in infected individuals, which persists despite suppressive ART and is currently considered the main obstacle to an HIV cure [11, 12]. Accordingly, complete eradication of the reservoir would signify a sterilizing cure, and a substantial degree of reservoir depletion would likely be necessary for achieving a state of prolonged ART-free HIV remission, otherwise termed “functional cure” . Depleting the reservoir is therefore the principal goal of HIV curative strategies, of which the so-called “shock-and-kill” approach has received most attention in recent years [14, 15]. The idea behind “shock-and-kill” is to reverse HIV latency with specific compounds, termed “latency-reversing agents” (LRA). The resulting switch to productive infection, or at least the elevated level of HIV protein expression, would then subject the HIV-infected cells to immune-mediated clearance and/or viral cytopathic effects, and the free virions generated in the process would be unable to establish productive infection of new cells in the setting of completely suppressive ART. Because HIV latency has traditionally been understood as transcriptional latency (persistent replication-competent proviruses that are transcriptionally silent but can be reactivated to produce infectious virus particles and reignite viral spread in the absence of ART), most LRAs currently in clinical or preclinical use function by stimulating HIV transcription with minimal cellular activation . Logically, CA HIV RNA has been used as a measure of the potency of these compounds for latency reversion, both ex vivo and in several clinical trials [6,7,8,9, 17, 18]. Modest increases in CA RNA level, sometimes accompanied by elevated cell-free HIV viremia, have indeed been observed in these trials, but despite this, no substantial reservoir reduction has been measured so far in most studies. Here it must be noted that HIV transcription does not necessarily lead to productive infection, consequently an increased CA RNA level does not automatically mean full reversion of latency. Two possible reasons for this are that (1) part of the transcripts is defective at the sequence level for production of active viral proteins and infectious particles (discussed in detail below), and (2) latency might be regulated not only at the transcriptional but also at multiple post-transcriptional levels (e.g. splicing and nuclear export of viral RNA, translation, viral particle assembly and maturation, etc.). For instance, Chun et al. could not detect cell-free virions in ex vivo resting CD4+ T cell cultures from ART-treated individuals, despite the presence of CA RNA . Furthermore, Hong et al. did not find any correlation between CA RNA levels and residual plasma viremia in ART-treated subjects , although a weak correlation was observed by Li et al. . This suggests that in the setting of suppressive ART, at least some HIV transcription events do not result in virus production. This idea is supported by the large disproportion between the decay kinetics of cell-free and CA HIV RNA upon ART initiation [2, 4, 22,23,24,25].
By sensitive methods, CA HIV RNA can be detected in the vast majority of peripheral blood mononuclear cell (PBMC) or CD4+ T-cell samples isolated from HIV-infected individuals on prolonged ART in the absence of any ex vivo stimulation [3,4,5, 26], and the concept of “leaky latency” has recently been put forward to explain these findings (CROI 2015). However, this concept assumes only transcriptional latency (that can occasionally “leak”), ignoring the possibility of post-transcriptional blocks to HIV expression. In general, though, virus latency does not require complete shutdown of viral gene expression, only lack of infectious progeny production . In fact, already in 2011 Pace et al.  proposed the “continuum of latency” with barriers to productive infection at different stages of the viral replication cycle in different populations of latently infected cells, and in 2012 we introduced the concept of the “active HIV reservoir” to describe latently infected cells that are actively transcribing HIV RNA but do not produce infectious virus particles [3, 29]. A question then arises of whether the active reservoir is a true reservoir, in other words how would such cells persist for a long time and escape immune-mediated killing. One simple possibility is that no viral proteins are produced despite ongoing HIV transcription. In a primary CD4+ T-cell model, Mohammadi et al.  observed disproportionally low activation of viral translation compared to activation of viral transcription by the LRA vorinostat. As mentioned above, several mechanisms of post-transcriptional regulation of HIV gene expression are possible. For instance, multiply spliced HIV RNA has been shown to be retained in the nucleus both in resting CD4+ T cells from patients on ART and in a chemokine (CCL19) induced model of HIV latency in primary resting CD4+ T cells [31, 32]. This nuclear localization of multiply spliced RNA precluded high-level transcription and nuclear export of other CA HIV RNA species and protein translation and possibly contributed to the latent state of HIV in these cells. In addition, differential expression of Rev cofactors such as Matrin 3 or PSF in different cell types can contribute to blocking HIV RNA nuclear export [33,34,35]. Furthermore, Li et al.  reported selective inhibition of HIV translation by host factor Schlafen 11 in a codon usage-dependent manner, and inhibition of HIV replication by a number of host microRNAs has been observed, although the precise mechanism of their action is still unclear [37, 38]. However, several groups recently reported the detection of HIV Gag protein expression in ART-treated individuals, albeit Gag-positive cells were much less frequent than cells containing CA RNA [39,40,41]. Future research will reveal whether more sensitive assays are able to detect HIV proteins in a larger proportion of cells. In any case, one mechanism of persistence of such HIV protein-expressing cells could be the large prevalence of CTL escape mutations in the latent reservoir, recently demonstrated for Gag epitopes  but likely present in other HIV proteins as well.
As discussed above, although HIV transcription is a prerequisite for virus production, the mere presence of CA HIV RNA, or an increase in its copy number in a cell from an ART-treated individual does not automatically signify an increase in infectious virus production and this should be taken into account when designing latency reversion experiments. Even less does residual HIV transcription per se mean residual virus replication (discussed in detail in ). The debate about the possibility of residual HIV replication despite ART has been ongoing for a long time , but recently gained some renewed momentum with the publication of an intensive longitudinal study of HIV evolution in lymphoid tissue that revealed a temporal structure of viral populations during early ART , although other investigators challenged that conclusion [45, 46]. Furthermore, two recent reports revealed suboptimal tissue concentrations of antiretroviral drugs that negatively correlated with the slower decay or increases in the follicular dendritic cell network-associated virions and detection of viral RNA in productively infected cells [47, 48]. Combined, this evidence points to the possibility of low-level HIV replication in tissues due to suboptimal ART penetration, even if infection of new cells is completely suppressed in peripheral blood. This possibility also has to be taken into account during LRA clinical trial design. In a number of clinical trials of different LRAs (vorinostat, disulfiram, panobinostat), investigators observed a persistent “post-dosing effect” on CA HIV RNA, with increased CA RNA levels detected long after the measures of LRA pharmacodynamics have returned to baseline levels [6,7,8]. To explain this phenomenon, it has been argued that LRAs could exert a long-lasting effect on host gene expression that could influence viral RNA levels , but given the different mechanisms of action of the LRAs studied, this is unlikely to be the only explanation. An alternative explanation could be that the free virus particle production induced by the LRA treatment could lead to low-frequency de novo infections, at least in tissues and anatomic compartments where ART pressure might be suboptimal. The newly infected, activated CD4+ T cells would in turn produce virus to infect other cells, and in this manner, a limited chain of new infections could continue for some time. If this LRA-induced residual replication occurs, CA RNA, even measured in peripheral blood, is expected to be a very sensitive marker of this process. This is because (1) a productively infected cell can contain hundreds to thousands of HIV unspliced RNA copies at the peak of infection , (2) some cells could be infected by cell-to-cell contact without free virion release , and (3) infected cells can traffic between tissues and periphery [1, 51]. In the disulfiram trial, the highest LRA dose used (2000 mg) caused a significant post-dosing increase not only in CA RNA but in plasma HIV RNA level as well . Interestingly, low-level plasma viremia after recombinant HIV poxvirus vaccination, another intervention that is expected to activate latent HIV, has been shown previously to correlate with HIV sequence evolution, suggesting that HIV activation might cause some residual replication . Another relevant observation is that vorinostat has been shown to increase susceptibility of primary CD4+ cells to HIV infection, whereas the other LRA romidepsin has an opposite effect [53, 54]. Remarkably, the post-dosing effects described above have been observed in the clinical trials of vorinostat but not romidepsin [6, 7, 9, 55]. This putative side-effect of reservoir activation argues for a strict ART adherence during the trials, as small deviations from optimal adherence could lead to residual virus replication, even if plasma viremia stays undetectable by commercial assays [3, 56]. In the worst-case scenario, this residual replication could lead to significant replenishment of the HIV reservoir, compensating for any LRA-induced reservoir depletion, and this might be one of the reasons behind the lack of efficacy in LRA trials so far.
Unspliced versus spliced versus poly(A): What should we measure?
More than 100 different transcripts can be derived from the HIV unspliced (US) genomic RNA by alternative splicing, although it is unclear if all of them are present in infected individuals [57, 58]. These include incompletely, or singly spliced and completely, or multiply spliced (MS) transcripts that can be roughly divided to 1, 2, and 4 kb classes . The 2 kb MS RNAs encode the regulatory proteins Tat, Rev, and Nef. Of these, Tat is necessary for high-level HIV transcription, whereas Rev is needed for efficient nuclear export of US and incompletely spliced HIV RNA species that encode the structural and accessory viral proteins (reviewed in ). The relative abundance of HIV RNA species has been studied in different experimental systems. In H9 cells, MS RNA production has been shown to peak at the early stages of the HIV replication cycle, after which incompletely spliced and US RNA took over . Similar temporal dynamics has been observed after stimulation of ACH-2 cells with PMA . This can be explained by the restriction of Rev function in these cells, so that a high MS RNA (and consequently Rev) level must be achieved before US RNA can be efficiently exported to the cytoplasm, thereby escaping splicing or degradation. More recently, by deep sequencing of RNA derived from primary cells 48 h post-infection with the HIV89.6 strain, the Bushman group could determine that the relative abundance of MS RNA was close to that of US RNA, and Mohammadi et al. observed a similar pattern in their primary CD4+ T-cell model [30, 57, 62]. However, in resting CD4+ T cells directly infected by spinoculation, Pace et al. detected a large excess of US RNA over incompletely spliced and MS RNA species , suggesting a possible limitation in splicing factor availability and/or RNA nuclear export defect in these cells. This complements the reports that described the predominance of short abortive transcripts in resting CD4+ cells [64,65,66], and “long” but incomplete transcripts in CD4+ cells from ART-treated individuals , presumably due to inefficient transcription elongation.
In HIV-infected individuals, ART-treated or not, MS RNA is usually measured to be much less abundant than US RNA [4, 5, 68,69,70], although it is unclear to what extent this reflects underestimation of MS RNA copy numbers by qPCR due to primer/probe-template mismatches that could be more frequent in tat/rev than in gag assays. It should be noted, however, that the difference in relative abundance between US and MS RNA was observed even when patient-matched primers and probes were used for qPCR [5, 71]. In individuals on prolonged ART, US RNA is readily detectable but MS RNA is difficult to detect unless cells are stimulated ex vivo. Nevertheless, MS RNA is detectable early on ART and a higher US/MS RNA ratio at 12 weeks ART was shown to be predictive of a reduced immunological response to therapy at 48 and 96 weeks and correlated with markers of CD4+ T-cell activation and apoptosis . Interestingly, in untreated patients the US/MS ratio is lower in long-term nonprogressors and has been shown to correlate with rapid progression [73,74,75,76]. In light of the temporal shift from the MS to US RNA expression discussed above, a higher US/MS RNA ratio in a patient might reflect the higher frequency of HIV-infected cells in the later stages of viral the replication cycle, which is characterized by expression of viral structural proteins and presentation of antigens. Such cells could exert pressure on the host immune system, causing persistent immune activation and apoptosis and contributing to poor immunological response to ART. Further research will show whether the US/MS RNA ratio could be used as a marker of residual HIV pathogenesis on ART.
Another issue that is relevant to the latency reversal studies is which CA HIV RNA species would be a better surrogate for measuring the LRA efficacy and changes in replication-competent reservoir. Both US and MS RNA have been used in this role in inducible HIV transcription assays (see below and the review article by Plantin et al. in this Special Issue ). It has been argued that MS RNA could be a better surrogate for the replication-competent reservoir as splicing requires the presence of several cis-acting sequences in the HIV genome and therefore the presence of MS RNA reduces the possibility of measuring proviruses with large deletions . The relative decrease in MS RNA level upon ART initiation is more prominent than that of US RNA [79,80,81,82], and cells containing measurable MS RNA are much rarer under ART than those containing US RNA [5, 71]. This suggests that MS RNA-positive cells can indeed be a more proximal surrogate of cells containing HIV proviruses that are reactivated from latency, at least to some extent. This is confirmed by the recent data from Yukl’s group, as they observed much stronger increases in MS RNA than in “long” HIV transcripts upon ex vivo stimulation of CD4+ T cells . However, even despite reactivation, many such proviruses will still be unable to establish the productive infection and release infectious progeny due to various genetic defects. This is the reason why measurements of frequencies of cells that can be induced to express any HIV RNA species will always overestimate the replication-competent reservoir size.
One more issue regarding the choice of which HIV RNA species to measure as a surrogate of latency reversion is whether the transcripts measured by the gag assays represent genuine viral RNA. As HIV preferentially integrates within actively transcribed host genes , Bullen et al. recently proposed that some transcripts detected by the gag-specific assays may not represent bona fide HIV RNA but rather chimeric host-HIV readthrough transcripts that are transcribed from upstream host promoters . They demonstrated that vorinostat could activate such readthrough transcription to the similar levels as gag transcription and proposed to use the polyadenylated HIV mRNA-specific assay to detect genuine HIV RNA [84, 85]. However, neither the absolute copy numbers of readthrough and gag RNA, nor the readthrough/gag RNA ratio was presented and therefore the contribution of host transcripts to the gag RNA pool remained unclear. Subsequently, we and others demonstrated that in ART-suppressed individuals, this contribution is very modest and that the vast majority of HIV gag RNA transcripts represent genuine HIV unspliced RNA [67, 86]. However, recent data from Yukl’s group suggests that most of these transcripts might still be incomplete and therefore an advantage of measuring the poly(A) HIV mRNA would be that such incomplete transcripts are avoided . A disadvantage of the latter assay is that it does not discriminate between unspliced and spliced HIV RNA and therefore is of limited use in HIV reservoir studies.
Early versus late: When should we measure?
It has been firmly established that early initiation of ART limits the HIV reservoir size [87, 88]. HIV-infected individuals who start ART during acute or early infection achieve lower CA RNA levels than those who start therapy during chronic infection [80, 89,90,91]. Early ART preserves immune functions and limits the possibilities for HIV to escape from the host CTL response , providing a likely explanation for the smaller active reservoir under early therapy. However, all these previous studies compared different patients. We recently undertook a longitudinal study to compare viral reservoirs in the same patients treated in two phases during early and chronic HIV infection, and assessed the long-term effects of early therapy on the HIV reservoir during treatment initiated at chronic infection . We quantified levels of CA US RNA and total HIV DNA in HIV-infected individuals who had participated in a randomized controlled trial of 24 or 60 weeks of temporary ART versus no treatment during primary HIV infection (Primo-SHM study; ) and subsequently (re)started therapy during chronic infection after an average of 2 years without treatment. As demonstrated earlier, levels of both US RNA and total DNA during early ART were significantly lower than levels of corresponding markers during ART initiated at chronic infection in patients who were not treated with early ART. Surprisingly, however, no significant difference was found between the levels of CA RNA or DNA measured during early and chronic therapy periods in the same patients, and strong correlations in the HIV RNA and DNA levels between the two therapy periods were observed. Finally, the level of US RNA, measured during chronic infection ART, was significantly lower in patients who had been pre-treated during primary infection than in patients who had not been pre-treated. Taken together, these data suggest that early ART, even when interrupted, has a long-term suppressive effect on the viral reservoir during treatment initiated subsequently during chronic infection. This observation might be reassuring for HIV-infected individuals participating in HIV curative interventions who sometimes have to temporarily interrupt ART .
Another intriguing observation related to the timing of HIV RNA measurement is that CA RNA levels might actually fluctuate with the time of the day. This observation was made during the phase II clinical trial of disulfiram . Significantly higher CA RNA levels have been detected in one out of three baseline samples that was collected earlier in the day than the two others from the same trial participants (all three samples were collected prior to the intervention). To explain this finding, the authors hypothesized that HIV transcription could be influenced either by circadian rhythm or by anticipatory stress (unlike two others, the sample with higher CA RNA levels was collected immediately prior to disulfiram treatment). Recently, data have been presented that indeed confirm the effect of stress on HIV transcription . It is important to understand whether the observed effect was HIV-specific or was reflecting the changes in host transcription in response to either stimulus. HIV RNA is transcribed by RNA polymerase II, which activity is known to fluctuate according to the circadian rhythm ( and references therein). Furthermore, psychosocial stress has been shown to rapidly activate NF-κB [97, 98], and core circadian protein CLOCK is a positive regulator of NF-κB-mediated transcription . As NF-κB is a known HIV transcription factor [100,101,102], this might be the mechanism behind the effect of stress and/or circadian rhythm on CA HIV RNA. In the studies of Elliott et al.  and Hecht et al. , CA RNA levels were normalized to 18S ribosomal RNA, which is transcribed by RNA polymerase I and it is unknown whether this enzyme is regulated by circadian rhythm or stress. Therefore, to disentangle the host- and virus-specific effects, it would be informative to assess the expression of host RNA polymerase II-transcribed genes in parallel with HIV, ideally genes that are responsive to NF-κB. In summary, these findings add another dimension to the longitudinally fluctuating nature of CA HIV RNA levels under ART as shown previously [3, 103], and this has to be taken into account when interpreting the results of latency reversion trials.
Tissue versus periphery: Where should we measure?
Apart from peripheral blood, CA HIV RNA has been measured in human gut-associated lymphatic tissue (GALT), lymph nodes, and tonsil tissue [69, 104,105,106], as well as in various tissues of humanized mice [107, 108]. In addition, CA RNA of SIV or SHIV has been measured in non-human primate models of HIV, by PCR-based or in situ hybridization-based methods [48, 109,110,111,112]. As more than 98% of the body CD4+ T cells are locked in the lymphoid organs, these sites are the primary sites of HIV replication in untreated HIV-infected individuals. It is unclear, however, whether the infection frequency in tissue is higher than in peripheral blood. In ART-treated individuals, Yukl et al. reported significantly higher total HIV DNA levels normalized to CD4+ cells in multiple GALT sites compared to the peripheral blood, whereas for CA RNA, a significantly higher level has been observed for the ileum only . In the subsequent study by the same group, CA RNA levels were reported to be even lower in the rectum than in peripheral blood in CD4+ T cells and total white blood cells, despite higher HIV DNA levels . Interestingly, in these studies, the relative HIV transcription level (RNA/DNA ratio) tended to be higher in peripheral blood than in the rectum, although levels of T-cell activation in the blood were clearly lower. One explanation for these reduced RNA/DNA ratios in the gut might be that the measured total DNA could include a significant portion of incomplete reverse transcripts and complete but unintegrated DNA, reflecting possible recent infections due to suboptimal tissue antiretroviral drug levels and/or cell-to-cell HIV transfer [47, 50, 113, 114]. The distribution of HIV DNA and RNA in T-cell subsets was also different between gut and periphery: most HIV DNA and RNA in the peripheral blood were found in CCR7+ cells, whereas in the gut, most HIV DNA and RNA were found in effector memory cells . This differential HIV distribution was confirmed by an independent study . The latter study did not find a statistically significant difference in infection frequency between GALT and blood. Another study by the same group could not measure a significant difference between the infection frequencies in memory CD4+ cells from lymph nodes and peripheral blood in untreated HIV-infected individuals, although there was a trend to higher infection levels in tissue . However, significantly higher CA US RNA levels were observed in memory CD4+PD-1+ T cells isolated from lymph nodes compared with blood . In the lymph node, cells with high expression of the cell surface receptors CXCR5 and PD-1 correspond to follicular T helper (TFH) cells that are a highly specialized subset of T helper cells that reside in lymph node germinal centers. Both in untreated and treated HIV-infected individuals, TFH cells were shown to harbor higher levels of HIV DNA and RNA than other memory CD4+ T-cell subsets, and CA RNA levels in these cells inversely correlated with the duration of treatment [106, 117]. As germinal centers were shown to be an immunologically privileged site with restricted CTL function , persistent CA RNA transcription there could be a source of infectious virus production and fuel virus rebound upon ART interruption. Indeed, TFH cells were demonstrated to be enriched in replication-competent proviruses in ART-treated individuals , although we still do not know whether the frequency of replication-competent proviruses correlates with CA RNA levels. Further research should reveal whether TFH cells are enriched in “intact” proviruses compared with other T-cell subsets and whether virus evolution continues under ART in these cells in lymph nodes. Finally, it should be noted that for obvious reasons, all studies mentioned above were small and therefore the results should be interpreted with some caution.
Bulk versus single-cell, in situ hybridization versus PCR, digital PCR versus qPCR: How should we measure?
A plethora of different methods have been developed to measure CA HIV RNA (Table 1). The simplest, cheapest, and quickest methods are based on the quantitation of CA RNA in bulk cellular extracts by reverse transcription (RT)-qPCR [5, 85, 119,120,121], to which a nested or seminested pre-amplification step can be added to increase the assay sensitivity [4, 122]. Over the last 10 years, seminested RT-qPCR has been extensively used to measure CA HIV RNA in different clinical cohorts and helped obtain important insights into the clinical value of this biomarker for monitoring ART response and LRA efficiency [3, 4, 6, 8, 29, 68, 72, 86, 92]. Apart from increasing sensitivity, the addition of the pre-amplification step results in higher accuracy in the lower quantitation range and better tolerance of RT or PCR inhibition than single-step qPCR-based assays, while not requiring much extra time and labor . However, the addition of one or two extra primers increases the probability of underestimation of target copy numbers in samples from HIV-infected individuals due to primer/probe-template mismatches. In addition, absolute quantitation by qPCR relies on the external standards and therefore qPCR-based assays are difficult to standardize between different laboratories.
With this in mind, efforts have been made to develop digital PCR-based methods to measure HIV DNA and RNA, as digital PCR is by definition an absolute DNA quantitation method that does not require a standard curve (see the review of Rutsaert et al. in this Special Issue ). For HIV DNA quantitation, Strain et al.  demonstrated the superiority of droplet digital PCR (ddPCR) over single-step qPCR in precision and accuracy, with an added benefit of better tolerance of target sequence variation compared to qPCR. However, for quantitation of CA US and MS HIV RNA, Kiselinova et al.  reported better quantitative linearity, accuracy and sensitivity of seminested qPCR compared to ddPCR, especially in the lower quantitation ranges. On the other hand, ddPCR in that study could detect MS RNA in a larger proportion of samples from ART-treated individuals than qPCR, although the detection rate of MS RNA in samples from untreated individuals was equal between the methods and both methods demonstrated equally high detection rate of US RNA on and off ART. The caveat, though, is that a number of studies, including Kiselinova et al., reported positive droplets in some no-template control wells in digital PCR, undistinguishable by fluorescence from the positive droplets in positive control wells [26, 124, 125]. The origin of these false-positive droplets is presently unclear but they greatly complicate the use of digital PCR for quantitation of extremely low target copy numbers, such as observed for CA HIV RNA from ART-treated individuals. Setting up a detection threshold based on the maximal number of positive droplets in the no-template control wells might alleviate this problem but will substantially compromise the assay sensitivity. For example, in this case, all samples from ART-treated individuals that were scored positive for MS RNA by ddPCR in the study by Kiselinova et al.  would be scored negative. qPCR does not have this issue and therefore is preferable to use when low target copy numbers are expected. Another drawback of digital PCR is possible underestimation of target copy numbers due to molecular dropout, when the target molecule is present in the partition but is not amplified . Finally, it is important to realize that unlike the quantitation of DNA by digital PCR, which is absolute, the quantitation of RNA still needs an external calibrator to account for the yield of the RT reaction which can vary widely depending on the priming strategy, reaction conditions, and the enzyme used [127, 128]. Digital PCR measures cDNA, not RNA, and the absence of such calibrator might cause another significant underestimation of the target RNA copy numbers. This is likely true even for one-step RT-digital PCR methods, where the RNA sample is partitioned prior to RT , and this makes the digital PCR-based quantitation of RNA as dependent on the external standard as the qPCR-based methods.
As discussed above, bulk PCR-based methods of CA HIV RNA measurement are highly sensitive, high-throughput, and inexpensive, and therefore perfectly suited for the analysis of HIV transcription levels in a large number of samples. However, for in-depth dissection of HIV reservoir these assays are of limited use, because they do not allow determining frequencies of HIV RNA+ cells, HIV RNA copy numbers per cell, as well as cellular phenotype and activation level of single HIV-infected cells. A bulk HIV RNA load of 100 copies per million cells can mean that there are either 10 HIV RNA+ cells per million cells with 10 copies HIV RNA per cell, or 1 HIV RNA+ cell with 100 copies per cell. To discriminate between these possibilities, and to determine whether frequencies of HIV RNA+ cells or copy numbers per cell (or both) are changed upon ex vivo virus stimulation, a single-cell approach is necessary. Development of assays that would allow to characterize single HIV-infected cells, including the viral transcription level, is a top priority in the HIV cure field, and several groups recently reported the development of novel single-cell techniques for HIV RNA detection, based on either limiting dilution-PCR or in situ hybridization chemistries. These techniques are discussed below.
In fact, already in 2002 Fischer’s group reported the development of a limiting dilution-PCR-based assay to study the frequencies and expression levels of US and MS CA HIV RNA at the single-cell level , and this assay has been further developed throughout the 2000s [5, 71]. This large and unique body of work resulted in a number of insights into the persistence of viral transcription-active reservoirs in ART-treated individuals including the cellular origin and activation level of HIV RNA+ cells . Notably, all these measurements have been done in the absence of any ex vivo stimulation. More recently, studies of HIV transcription under ART largely shifted to measuring its activation in and ex vivo, as well as estimating the replication-competent reservoir size, and in 2014, Cillo et al. reported the first inducible HIV transcription assay (, also see the review of Plantin et al. in this Special Issue ). This assay, based on limiting dilution-PCR, was primarily designed to measure the frequencies of HIV proviruses that could be reactivated to produce virions upon ex vivo stimulation, but for two donors, frequencies of cells reactivated to transcribe CA US RNA were also reported. These frequencies were 5–24 times higher than those of virion-producing cells, suggesting that most of HIV RNA+ cells cannot be reactivated for virion production due to post-transcriptional blocks or defective proviruses. Subsequently, Procopio et al.  reported the development of the Tat/rev Induced Limiting Dilution Assay, or TILDA, which is based on the modified version of our previously reported seminested RT-qPCR assay for MS RNA . In brief, TILDA measures the frequencies of CD4+ cells that can be induced to produce MS RNA-tat/rev. Because no RNA extraction is performed and RT-PCR is done directly on cells, the assay is relatively fast, and despite its limiting dilution format it does not require large cell numbers. However, the downside of this approach is that because of inhibition of the RT and/or PCR step by cellular proteins, the maximal number of cells that can be assayed in one well is limited to 18,000, compromising the assay sensitivity. The limiting dilution format allows to alleviate this sensitivity issue by combining technical replicates, however this translates into wide confidence intervals for the final output measure, resulting in imprecise estimation of the cell frequencies that are close to the limit of detection. The absence of an RNA extraction step before RT-PCR also precludes the measurement of US RNA by TILDA, because no DNase treatment can be performed, which is necessary to remove the proviral DNA that is collinear with US RNA. The inducible Cell-Associated RNA Expression in Dilution assay (iCARED), developed by Massanella et al. , measures the frequencies of both US and MS RNA+ cells, in addition to virion-producing cells. Confirming the data of Cillo et al., this assay revealed that the frequency of cells producing US and MS RNA are 25- and 5-fold higher than the frequency of virion-producing cells. Interestingly, frequencies of cells that can be activated to produce US or MS RNA measured by TILDA or iCARED did not significantly correlate with virus outgrowth, suggesting that either the inducible HIV transcription assays, or the virus outgrowth assay (or both), are not very reliable as a measure of the replication-competent HIV reservoir. This is because any assay based on the inducible CA RNA+ cell measurement overestimates the reservoir as it still measures some defective proviruses, and the virus outgrowth assay underestimates the reservoir as only a fraction of intact proviruses could be induced at any time [11, 132].
One shortcoming of all the inducible HIV transcription assays described above is that they only report frequencies of HIV RNA+ cells but not HIV RNA copy numbers per cell, which would be useful to evaluate the effects of LRAs on the single-cell level, as it is unknown whether LRAs preferentially activate previously transcriptionally silent proviruses or boost already ongoing transcription. Wiegand et al.  recently developed cell-associated HIV RNA and DNA single-genome sequencing assay (CARD-SGS), which does not use quantitative PCR to directly measure CA RNA but rather estimates the frequencies of CA US RNA+ cells and RNA copy numbers per cell based on the assessment of a sequence match in the p6-PR-RT region of HIV (~ 1.3 kb). Briefly, SGS is performed on CA RNA isolated from aliquots diluted to contain 1–12 HIV RNA+ cells, and identical RNA sequences from the same aliquot are assigned to a single infected cell. By counting the number of different HIV variants in each aliquot, the fraction of infected cells that express HIV RNA is estimated, and the RNA copy numbers per cell are then estimated based on the numbers of identical sequences. Applying these analyses to PBMC isolated from four HIV-infected donors, Wiegand et al. determined that the average fraction of HIV-infected cells that express CA US RNA was 7%, which is close to earlier estimates [5, 71]. Furthermore, in the three ART-treated donors, a median of 29% of the HIV RNA-expressing cells had more than one HIV US RNA molecule detected, but none contained more than 10 molecules per cell. In the untreated participant, 56% of cells had more than one HIV RNA molecule, but only 2% had more than 10 HIV RNA molecules per cell. This per-cell US RNA content is lower than estimated earlier by Fischer et al. , possibly reflecting low donor numbers in both studies and/or different duration of ART. The advantage of this method is that CA RNA is sequenced, which allows determining the intactness/defectiveness, as well as clonal expansion, of the expressed proviruses. A limitation of the assay is that only 15% of HIV genome is sequenced and the rest of the genome might still contain sequence mismatches, therefore one cannot be sure whether the RNA molecules assigned to one cell do not in fact belong to different cells, which could affect the interpretation of the results. However, given the relatively high HIV nucleotide diversity in these donors, such bias might be small .
An extreme “limiting dilution” approach to characterize single HIV RNA+ cells was recently reported by Yucha et al. . They adapted the digital PCR technique to develop an innovative microfluidic single-cell-in-droplet PCR assay to directly quantify the number of US RNA+ and MS RNA+ cells and the changes in these numbers upon reversion of latency. Individual cells are encapsulated into nanoliter-scale reaction droplets, lysed within droplets, and droplets are subjected to PCR amplification and sorted by fluorescence as in regular ddPCR. The results highlighted large inter-patient and inter-assay variation in the response to LRA. Although this assay is expected to be subject to the digital PCR limitations described above, the single-cell-in-droplet technique is promising and further research will show whether US and MS RNA measurements can be multiplexed within the encapsulated cell, and whether per-cell HIV RNA content can be determined in single-cell lysates isolated from positive droplets.
Apart from the PCR-based techniques, in situ hybridization (ISH)-based methods can be used to study HIV transcription (and translation) at the single-cell level. Already in the 1990s, several groups developed ISH-based assays to visualize HIV RNA+ cells [136, 137]. This method was shown to be biologically relevant as Derdeyn et al. demonstrated a near-perfect correlation between the frequencies of cells from HIV-infected donors that could be stimulated ex vivo to transcribe viral RNA, enumerated by ISH, and cells that could be stimulated to produce infectious virus, measured by a coculture assay . At about the same time, Patterson and colleagues developed simultaneous ultrasensitive subpopulation staining/hybridization in situ assay (SUSHI), combining cell surface immunophenotyping with fluorescent ISH for US RNA [137, 138]. This assay has been used in several studies, which demonstrated the correlation of US RNA+ cell frequencies with ex vivo proliferative responses to HIV CA-p24 and confirmed our data on the clinical relevance of US RNA measurement for predicting the response to ART [139, 140]. More recently, next-generation ISH-based assays for HIV RNA detection have been reported, with HIV RNA+ cells either visualized by microscopy in tissue sections (RNAscope, Advanced Cell Diagnostics) or detected by flow in samples from peripheral blood (Human PrimeFlow RNA assay, Affymetrix/eBioscience) [40, 141,142,143]. These methods are reviewed in depth by Baxter et al. and Deleage et al. in this Special Issue [144, 145], therefore here we will not elaborate on the technology. A big advantage of the ISH-based methods is the possibility of phenotypic characterization of single HIV RNA+ cells, for example staining for various cell surface molecules, or even simultaneous detection of HIV proteins . A disadvantage might be lower sensitivity compared to the PCR-based methods, as the presence of several target RNA molecules in a cell is required for that cell to be scored positive by ISH. Therefore, cells with the per-cell RNA content that is lower than the threshold might be missed. Indeed, both Grau-Esposito et al. and Deleage et al. observed 2–3 log10 lower HIV/SIV RNA+ cell numbers measured by their assays than the bulk HIV/SIV RNA levels quantified by qPCR [141, 142], suggesting that only cells with high per-cell viral RNA content are detected. Another disadvantage could be the high background signal level in the HIV RNA channel that can compromise the specificity when measuring rare HIV RNA+ cells in ART-treated individuals [40, 142]. Of note, inducible HIV RNA+ cell frequencies measured by both PrimeFlow-based assays did not correlate with quantitative virus outgrowth values [40, 142].
Defective versus intact: Is it worth measuring at all?
More than 90% of proviruses in ART-treated individuals have been shown to be defective at the sequence level for replication-competent virus production due to large internal deletions, hypermutation, premature stop codons, defects in major splice donor site or packaging signal, etc. [132, 146,147,148]. Moreover, even the small minority of “intact” proviruses might overestimate the size of the replication-competent reservoir as not all defects can be readily determined by sequence analysis (but on the other hand, HIV may overcome some of the defects that are obvious by sequence analysis by using alternative ways to express its genes [149, 150]). For the correct interpretation of CA RNA measurements, it is important to understand whether the fraction of HIV RNA that is defective is smaller or larger than the defective provirus fraction. In other words, it is still unclear to what extent the ability to transcribe HIV RNA is independent of the intactness of the provirus. On one hand, HIV US RNA transcription requires at least a functional LTR, and other cis-acting signals are necessary for production of spliced RNA forms (reviewed in ). On the other hand, cells that produce intact CA RNA, or are capable of doing so upon activation, might be preferentially recognized and eradicated by the host immune system as they can present viral antigens. It has been demonstrated that defective proviruses can be transcribed and translated, which can lead to the CTL recognition [133, 151,152,153]. Two recent studies from Palmer’s group reported larger fractions of defective CA RNA compared to defective DNA in ART-treated individuals before and after LRA treatment [154, 155], indeed suggesting the selective elimination of intact CA RNA-producing cells by host immunity. However, only a small HIV region (V1–V3 region of env) was sequenced in these studies, and therefore only hypermutations and premature stop codons could be assessed, leaving the possibility that the relative ratio between defective CA RNA and defective HIV DNA fractions is different on the full-genome level.
The transcription and translation capability of defective proviruses suggests, in addition to the “continuum of latency” discussed above, an existence of the “continuum of defectiveness”, with some defective proviruses being transcriptionally silent, some transcription-competent but defective for viral protein production, some capable of producing certain viral proteins but not others, some capable of producing all viral proteins but having a defect in the packaging signal, some producing non-infectious viral particles, etc. (Fig. 1). The presence of large deletions in CA RNA also means that any assay based on the measurement of only one genomic region will seriously underestimate the CA RNA level. A possible exception to this are assays based on exon–exon boundary-spanning amplicons that are used for spliced RNA measurements, but even in this case, one must be cautious as HIV can bypass defects in canonical splice sites, including the major splice donor, by using novel alternative spliced sites [149, 152]. Interestingly, Rassler et al.  reported prolonged persistence of an HIV variant with the mutated major splice donor site in plasma of a patient on suppressive ART, suggesting that HIV might have found alternative means to express spliced RNAs needed for virion production.
A very important issue relevant to current discussions on residual HIV pathogenesis in ART-treated individuals, which is only beginning to receive attention, is whether the defective proviruses can be pathogenic. Imamichi et al.  introduced the term “zombie proviruses”, implying that some defective proviruses can still cause harm despite being “dead”. Indeed, a number of studies demonstrated a correlation between the CA RNA levels and markers of immune activation and dysfunction under ART [66, 72, 158, 159], although other investigators challenged this view . Although correlation does not imply causation and increased CA RNA levels might be not only the cause but also the consequence of e.g. increased immune activation, these results are at least suggestive of some biological function of defective proviruses that are expressed. Even if, due to deletions and/or frameshift mutations, no correct HIV proteins can be translated, a cell that expresses a foreign antigen can still be potentially recognized by the host immune system. In theory, persistence and multiplication of such “zombie” proviruses by clonal expansion increases the probability of causing elevated immune activation. In this sense, the “block-and-lock” strategy to permanently suppress CA RNA transcription [161, 162] might be useful even as an addition to conventional ART. Moreover, Li et al.  recently reported that acitretin, a retinoic acid derivative, both increases HIV transcription and induces preferential apoptosis of HIV-infected cells by the RIG-I pathway that involves recognition of HIV RNA. In theory, this strategy should eliminate cells harboring not only intact, but defective proviruses as well, provided the latter are expressed or have an ability to be expressed upon activation. Further research will show whether these strategies will result in decreased residual immune activation and inflammation in ART-treated individuals.
In summary, CA HIV RNA as a biomarker of HIV persistence and latency reversion has received much interest in recent years, but at the same time it has become clear that the size of the HIV transcription-competent reservoir overestimates the size of the replication-competent reservoir as a substantial (but yet unknown) fraction of CA RNA-transcribing proviruses is likely defective for infectious virion production. Does this mean that CA RNA is not informative and that we should stop measuring it? We would argue against such a view, as (1) CA RNA has been shown to be a biomarker that is significantly more sensitive for monitoring ART and predicting virological failure than plasma viremia, at least when the latter is measured by commercial assays [3, 4], (2) even defective expressed proviruses might contribute to residual HIV pathogenesis [151, 152], (3) the “baseline” level of CA RNA correlates with the level upon LRA treatment , suggesting that CA RNA level might serve as a predictor of the efficiency of latency reversal and that future treatments could be tailored to individual patients , (4) transcription-competent proviruses under ART contribute to the virus rebound after therapy interruption, as reported by different groups [153,154,155], (5) in addition to the LRA studies, CA RNA can be used as a surrogate marker of the efficacy of antiviral gene therapy strategies, in particular CRISPR/Cas9 gene editing [165, 166], and (6) probably most importantly, CA RNA levels measured by a simple bulk PCR-based assay (without ex vivo stimulation) at ART interruption are predictive of the duration of post-treatment control, as independently reported by Li et al. and our group [167, 168]. By mathematical modeling, the duration of post-treatment control (ART-free HIV remission) has been shown to be a direct reflection of the size of replication-competent viral reservoir, and probably its best measure that currently exists [169,170,171]. Therefore, any biomarker that reliably correlates with the time to viral rebound should be used as a surrogate marker of the replication-competent reservoir, and as ART interruption is currently the only way to determine whether a patient is cured or whether a curative treatment has been effective, biomarkers that could predict the duration of ART-free remission are urgently needed. Both CA RNA and total HIV DNA have been shown by different groups to predict the time to viral rebound [167, 168, 172] and further research should indicate whether these associations are sufficiently robust for these markers to support the clinical decision-making on the ART interruption during HIV cure-related clinical trials , and to allow initial assessment of novel curative interventions without the need for ART interruption. Without doubt, identifying the predictors of ART-free remission, and therefore the correlates of the replication-competent HIV reservoir size, will greatly facilitate progress in the HIV cure field.
Human immunodeficiency virus
Peripheral blood mononuclear cell
Conference on retroviruses and opportunistic infections
Chemokine (C-C motif) ligand 19
Polypyrimidine tract binding protein associated splicing factor
Cytotoxic T lymphocyte
Phorbol 12-myristate 13-acetate
Reverse transcription-quantitative polymerase chain reaction
Nuclear factor kappa-light-chain-enhancer of activated B cells
Gut-associated lymphatic tissue
Simian immunodeficiency virus
Simian-human immunodeficiency virus
C-C chemokine receptor type 7
Programmed cell death protein 1
C-X-C chemokine receptor type 5
- TFH :
Follicular T helper
Droplet digital PCR
Tat/rev induced limiting dilution assay
Inducible cell-associated RNA expression in dilution assay
Cell-associated HIV RNA and DNA single-genome sequencing assay
In situ hybridization
Simultaneous ultrasensitive subpopulation staining/hybridization in situ assay
Long terminal repeat
Retinoic acid-inducible gene I
Yerly S, Rutschmann OT, Opravil M, Marchal F, Hirschel B, Perrin L. Cell-associated HIV-1 RNA in blood as indicator of virus load in lymph nodes. The Swiss HIV Cohort Study. J Infect Dis. 1999;180:850–3.
Furtado MR, Callaway DS, Phair JP, Kunstman KJ, Stanton JL, Macken CA, Perelson AS, Wolinsky SM. Persistence of HIV-1 transcription in peripheral-blood mononuclear cells in patients receiving potent antiretroviral therapy. N Engl J Med. 1999;340:1614–22.
Pasternak AO, de Bruin M, Jurriaans S, Bakker M, Berkhout B, Prins JM, Lukashov VV. Modest nonadherence to antiretroviral therapy promotes residual HIV-1 replication in the absence of virological rebound in plasma. J Infect Dis. 2012;206:1443–52.
Pasternak AO, Jurriaans S, Bakker M, Prins JM, Berkhout B, Lukashov VV. Cellular levels of HIV unspliced RNA from patients on combination antiretroviral therapy with undetectable plasma viremia predict the therapy outcome. PLoS ONE. 2009;4:e8490.
Kaiser P, Joos B, Niederost B, Weber R, Gunthard HF, Fischer M. Productive human immunodeficiency virus type 1 infection in peripheral blood predominantly takes place in CD4/CD8 double-negative T lymphocytes. J Virol. 2007;81:9693–706.
Elliott JH, Wightman F, Solomon A, Ghneim K, Ahlers J, Cameron MJ, Smith MZ, Spelman T, McMahon J, Velayudham P, et al. Activation of HIV transcription with short-course vorinostat in HIV-infected patients on suppressive antiretroviral therapy. PLoS Pathog. 2014;10:e1004473.
Elliott JH, McMahon JH, Chang CC, Lee SA, Hartogensis W, Bumpus N, Savic R, Roney J, Hoh R, Solomon A, et al. Short-term administration of disulfiram for reversal of latent HIV infection: a phase 2 dose-escalation study. Lancet HIV. 2015;2:e520–9.
Rasmussen TA, Tolstrup M, Brinkmann CR, Olesen R, Erikstrup C, Solomon A, Winckelmann A, Palmer S, Dinarello C, Buzon M, et al. Panobinostat, a histone deacetylase inhibitor, for latent-virus reactivation in HIV-infected patients on suppressive antiretroviral therapy: a phase 1/2, single group, clinical trial. Lancet HIV. 2014;1:e13–21.
Søgaard OS, Graversen ME, Leth S, Olesen R, Brinkmann CR, Nissen SK, Kjaer AS, Schleimann MH, Denton PW, Hey-Cunningham WJ, et al. The depsipeptide romidepsin reverses HIV-1 latency in vivo. PLoS Pathog. 2015;11:e1005142.
Pasternak AO, Lukashov VV, Berkhout B. Cell-associated HIV RNA: a dynamic biomarker of viral persistence. Retrovirology. 2013;10:41.
Pasternak AO, Berkhout B. HIV reservoir: finding the right needles in a needlestack. Cell Host Microbe. 2016;20:280–2.
Darcis G, Van Driessche B, Van Lint C. HIV latency: should we shock or lock? Trends Immunol. 2017;38:217–28.
Deeks SG, Lewin SR, Ross AL, Ananworanich J, Benkirane M, Cannon P, Chomont N, Douek D, Lifson JD, Lo YR, et al. International AIDS Society global scientific strategy: towards an HIV cure 2016. Nat Med. 2016;22:839–50.
Deeks SG. HIV: shock and kill. Nature. 2012;487:439–40.
Spivak AM, Planelles V. HIV-1 eradication: early trials (and tribulations). Trends Mol Med. 2016;22:10–27.
Rasmussen TA, Tolstrup M, Søgaard OS. Reversal of latency as part of a cure for HIV-1. Trends Microbiol. 2016;24:90–7.
Archin NM, Liberty AL, Kashuba AD, Choudhary SK, Kuruc JD, Crooks AM, Parker DC, Anderson EM, Kearney MF, Strain MC, et al. Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy. Nature. 2012;487:482–5.
Laird GM, Bullen CK, Rosenbloom DI, Martin AR, Hill AL, Durand CM, Siliciano JD, Siliciano RF. Ex vivo analysis identifies effective HIV-1 latency-reversing drug combinations. J Clin Invest. 2015;125:1901–12.
Chun TW, Justement JS, Lempicki RA, Yang J, Dennis G Jr, Hallahan CW, Sanford C, Pandya P, Liu S, McLaughlin M, et al. Gene expression and viral prodution in latently infected, resting CD4+ T cells in viremic versus aviremic HIV-infected individuals. Proc Natl Acad Sci USA. 2003;100:1908–13.
Hong F, Fyne E, Cillo AR, Bedison MA, Koontz D, Mellors JW. Characterizing the active HIV reservoir on ART: cell-associated HIV RNA and viremia. In: Conference on retroviruses and opportunistc infections. Seattle, USA; 2015.
Li JZ, Heisey A, Ahmed H, Wang H, Zheng L, Carrington M, Wrin T, Schooley RT, Lederman MM, Kuritzkes DR, Team AAS. Relationship of HIV reservoir characteristics with immune status and viral rebound kinetics in an HIV therapeutic vaccine study. AIDS. 2014;28:2649–57.
Fischer M, Gunthard HF, Opravil M, Joos B, Huber W, Bisset LR, Ott P, Boni J, Weber R, Cone RW. Residual HIV-RNA levels persist for up to 2.5 years in peripheral blood mononuclear cells of patients on potent antiretroviral therapy. AIDS Res Hum Retrovir. 2000;16:1135–40.
Yerly S, Perneger TV, Vora S, Hirschel B, Perrin L. Decay of cell-associated HIV-1 DNA correlates with residual replication in patients treated during acute HIV-1 infection. AIDS. 2000;14:2805–12.
Garrigue I, Pellegrin I, Hoen B, Dumon B, Harzic M, Schrive MH, Sereni D, Fleury H. Cell-associated HIV-1-DNA quantitation after highly active antiretroviral therapy-treated primary infection in patients with persistently undetectable plasma HIV-1 RNA. AIDS. 2000;14:2851–5.
Hoen B, Cooper DA, Lampe FC, Perrin L, Clumeck N, Phillips AN, Goh LE, Lindback S, Sereni D, Gazzard B, et al. Predictors of virological outcome and safety in primary HIV type 1-infected patients initiating quadruple antiretroviral therapy: QUEST GW PROB3005. Clin Infect Dis. 2007;45:381–90.
Kiselinova M, Pasternak AO, De Spiegelaere W, Vogelaers D, Berkhout B, Vandekerckhove L. Comparison of droplet digital PCR and seminested real-time PCR for quantification of cell-associated HIV-1 RNA. PLoS ONE. 2014;9:e85999.
Dimmock N, Easton A, Leppard KN. Introduction to modern virology. 6th ed. Oxford: Blackwell Publishing; 2007.
Pace MJ, Agosto L, Graf EH, O’Doherty U. HIV reservoirs and latency models. Virology. 2011;411:344–54.
Van Gulck E, Bracke L, Heyndrickx L, Coppens S, Atkinson D, Merlin C, Pasternak A, Florence E, Vanham G. Immune and viral correlates of “secondary viral control” after treatment interruption in chronically HIV-1 infected patients. PLoS ONE. 2012;7:e37792.
Mohammadi P, di Iulio J, Munoz M, Martinez R, Bartha I, Cavassini M, Thorball C, Fellay J, Beerenwinkel N, Ciuffi A, Telenti A. Dynamics of HIV latency and reactivation in a primary CD4+ T cell model. PLoS Pathog. 2014;10:e1004156.
Lassen KG, Ramyar KX, Bailey JR, Zhou Y, Siliciano RF. Nuclear retention of multiply spliced HIV-1 RNA in resting CD4+ T cells. PLoS Pathog. 2006;2:e68.
Saleh S, Wightman F, Ramanayake S, Alexander M, Kumar N, Khoury G, Pereira C, Purcell D, Cameron PU, Lewin SR. Expression and reactivation of HIV in a chemokine induced model of HIV latency in primary resting CD4+ T cells. Retrovirology. 2011;8:80.
Kula A, Guerra J, Knezevich A, Kleva D, Myers MP, Marcello A. Characterization of the HIV-1 RNA associated proteome identifies Matrin 3 as a nuclear cofactor of Rev function. Retrovirology. 2011;8:60.
Kula A, Gharu L, Marcello A. HIV-1 pre-mRNA commitment to Rev mediated export through PSF and Matrin 3. Virology. 2013;435:329–40.
Yedavalli VS, Jeang KT. Matrin 3 is a co-factor for HIV-1 Rev in regulating post-transcriptional viral gene expression. Retrovirology. 2011;8:61.
Li M, Kao E, Gao X, Sandig H, Limmer K, Pavon-Eternod M, Jones TE, Landry S, Pan T, Weitzman MD, David M. Codon-usage-based inhibition of HIV protein synthesis by human schlafen 11. Nature. 2012;491:125–8.
Huang J, Wang F, Argyris E, Chen K, Liang Z, Tian H, Huang W, Squires K, Verlinghieri G, Zhang H. Cellular microRNAs contribute to HIV-1 latency in resting primary CD4+ T lymphocytes. Nat Med. 2007;13:1241–7.
Nathans R, Chu CY, Serquina AK, Lu CC, Cao H, Rana TM. Cellular microRNA and P bodies modulate host-HIV-1 interactions. Mol Cell. 2009;34:696–709.
DeMaster LK, Liu XH, VanBelzen DJ, Trinite B, Zheng LJ, Agosto LM, Migueles SA, Connors M, Sambucetti L, Levy DN, et al. A subset of CD4/CD8 double-negative T cells expresses HIV proteins in patients on antiretroviral therapy. J Virol. 2016;90:2165–79.
Baxter AE, Niessl J, Fromentin R, Richard J, Porichis F, Charlebois R, Massanella M, Brassard N, Alsahafi N, Delgado GG, et al. Single-cell characterization of viral translation-competent reservoirs in HIV-infected individuals. Cell Host Microbe. 2016;20:368–80.
Graf EH, Pace MJ, Peterson BA, Lynch LJ, Chukwulebe SB, Mexas AM, Shaheen F, Martin JN, Deeks SG, Connors M, et al. Gag-positive reservoir cells are susceptible to HIV-specific cytotoxic T lymphocyte mediated clearance. PLoS ONE. 2013;8:e71879.
Deng K, Pertea M, Rongvaux A, Wang L, Durand CM, Ghiaur G, Lai J, McHugh HL, Hao H, Zhang H, et al. Broad CTL response is required to clear latent HIV-1 due to dominance of escape mutations. Nature. 2015;517:381–5.
Martinez-Picado J, Deeks SG. Persistent HIV-1 replication during antiretroviral therapy. Curr Opin HIV AIDS. 2016;11:417–23.
Lorenzo-Redondo R, Fryer HR, Bedford T, Kim EY, Archer J, Pond SLK, Chung YS, Penugonda S, Chipman J, Fletcher CV, et al. Persistent HIV-1 replication maintains the tissue reservoir during therapy. Nature. 2016;530:51–6.
Brodin J, Zanini F, Thebo L, Lanz C, Bratt G, Neher RA, Albert J. Establishment and stability of the latent HIV-1 DNA reservoir. Elife. 2016;5:e18889.
Kearney MF, Wiegand A, Shao W, McManus WR, Bale MJ, Luke B, Maldarelli F, Mellors JW, Coffin JM. Ongoing HIV replication during ART reconsidered. Open Forum Infect Dis. 2017;4:ofx173.
Fletcher CV, Staskus K, Wietgrefe SW, Rothenberger M, Reilly C, Chipman JG, Beilman GJ, Khoruts A, Thorkelson A, Schmidt TE, et al. Persistent HIV-1 replication is associated with lower antiretroviral drug concentrations in lymphatic tissues. Proc Natl Acad Sci USA. 2014;111:2307–12.
Estes JD, Kityo C, Ssali F, Swainson L, Makamdop KN, Del Prete GQ, Deeks SG, Luciw PA, Chipman JG, Beilman GJ, et al. Defining total-body AIDS-virus burden with implications for curative strategies. Nat Med. 2017;23:1271–76.
Hockett RD, Kilby JM, Derdeyn CA, Saag MS, Sillers M, Squires K, Chiz S, Nowak MA, Shaw GM, Bucy RP. Constant mean viral copy number per infected cell in tissues regardless of high, low, or undetectable plasma HIV RNA. J Exp Med. 1999;189:1545–54.
Sigal A, Kim JT, Balazs AB, Dekel E, Mayo A, Milo R, Baltimore D. Cell-to-cell spread of HIV permits ongoing replication despite antiretroviral therapy. Nature. 2011;477:95–8.
Imamichi H, Degray G, Dewar RL, Mannon P, Yao M, Chairez C, Sereti I, Kovacs JA. Lack of compartmentalization of HIV-1 quasispecies between the gut and peripheral blood compartments. J Infect Dis. 2011;204:309–14.
Shiu C, Cunningham CK, Greenough T, Muresan P, Sanchez-Merino V, Carey V, Jackson JB, Ziemniak C, Fox L, Belzer M, et al. Identification of ongoing human immunodeficiency virus type 1 (HIV-1) replication in residual viremia during recombinant HIV-1 poxvirus immunizations in patients with clinically undetectable viral loads on durable suppressive highly active antiretroviral therapy. J Virol. 2009;83:9731–42.
Lucera MB, Tilton CA, Mao H, Dobrowolski C, Tabler CO, Haqqani AA, Karn J, Tilton JC. The histone deacetylase inhibitor vorinostat (SAHA) increases the susceptibility of uninfected CD4+ T cells to HIV by increasing the kinetics and efficiency of postentry viral events. J Virol. 2014;88:10803–12.
Jønsson KL, Tolstrup M, Vad-Nielsen J, Kjær K, Laustsen A, Andersen MN, Rasmussen TA, Søgaard OS, Østergaard L, Denton PW, Jakobsen MR. Histone deacetylase inhibitor romidepsin inhibits de novo HIV-1 infections. Antimicrob Agents Chemother. 2015;59:3984–94.
Leth S, Schleimann MH, Nissen SK, Højen JF, Olesen R, Graversen ME, Jørgensen S, Kjær AS, Denton PW, Mørk A, et al. Combined effect of Vacc-4x, recombinant human granulocyte macrophage colony-stimulating factor vaccination, and romidepsin on the HIV-1 reservoir (REDUC): a single-arm, phase 1B/2A trial. Lancet HIV. 2016;3:e463–72.
Li JZ, Gallien S, Ribaudo H, Heisey A, Bangsberg DR, Kuritzkes DR. Incomplete adherence to antiretroviral therapy is associated with higher levels of residual HIV-1 viremia. AIDS. 2014;28:181–6.
Ocwieja KE, Sherrill-Mix S, Mukherjee R, Custers-Allen R, David P, Brown M, Wang S, Link DR, Olson J, Travers K, et al. Dynamic regulation of HIV-1 mRNA populations analyzed by single-molecule enrichment and long-read sequencing. Nucleic Acids Res. 2012;40:10345–55.
Purcell DF, Martin MA. Alternative splicing of human immunodeficiency virus type 1 mRNA modulates viral protein expression, replication, and infectivity. J Virol. 1993;67:6365–78.
Karn J, Stoltzfus CM. Transcriptional and posttranscriptional regulation of HIV-1 gene expression. Cold Spring Harb Perspect Med. 2012;2:a006916.
Kim SY, Byrn R, Groopman J, Baltimore D. Temporal aspects of DNA and RNA synthesis during human immunodeficiency virus infection: evidence for differential gene expression. J Virol. 1989;63:3708–13.
Bagnarelli P, Valenza A, Menzo S, Sampaolesi R, Varaldo PE, Butini L, Montroni M, Perno CF, Aquaro S, Mathez D, et al. Dynamics and modulation of human immunodeficiency virus type 1 transcripts in vitro and in vivo. J Virol. 1996;70:7603–13.
Sherrill-Mix S, Ocwieja KE, Bushman FD. Gene activity in primary T cells infected with HIV89.6: intron retention and induction of genomic repeats. Retrovirology. 2015;12:79.
Pace MJ, Graf EH, Agosto LM, Mexas AM, Male F, Brady T, Bushman FD, O’Doherty U. Directly infected resting CD4+ T cells can produce HIV gag without spreading infection in a model of HIV latency. PLoS Pathog. 2012;8:e1002818.
Lassen KG, Bailey JR, Siliciano RF. Analysis of human immunodeficiency virus type 1 transcriptional elongation in resting CD4+ T cells in vivo. J Virol. 2004;78:9105–14.
Kaiser P, Joshi SK, Kim P, Li P, Liu H, Rice AP, Wong JK, Yukl SA. Assays for precise quantification of total (including short) and elongated HIV-1 transcripts. J Virol Methods. 2017;242:1–8.
Ishizaka A, Sato H, Nakamura H, Koga M, Kikuchi T, Hosoya N, Koibuchi T, Nomoto A, Kawana-Tachikawa A, Mizutani T. Short intracellular HIV-1 transcripts as biomarkers of residual immune activation in patients on antiretroviral therapy. J Virol. 2016;90:5665–76.
Yukl SA, Kaiser P, Kim P, Joshi SK, Kim N, Li P, Lampiris H, Liu H, Rice A, Wong JK. Investigating the mechanisms that control HIV transcription and latency in vivo. In: Conference on retroviruses and opportunistic infections. Boston, USA; 2016.
Pasternak AO, Jurriaans S, Bakker M, Berkhout B, Lukashov VV. Steady increase in cellular HIV-1 load during the asymptomatic phase of untreated infection despite stable plasma viremia. AIDS. 2010;24:1641–9.
Fischer M, Joos B, Wong JK, Ott P, Opravil M, Hirschel B, Weber R, Gunthard HF. Attenuated and nonproductive viral transcription in the lymphatic tissue of HIV-1-infected patients receiving potent antiretroviral therapy. J Infect Dis. 2004;189:273–85.
Fischer M, Wong JK, Russenberger D, Joos B, Opravil M, Hirschel B, Trkola A, Kuster H, Weber R, Gunthard HF. Residual cell-associated unspliced HIV-1 RNA in peripheral blood of patients on potent antiretroviral therapy represents intracellular transcripts. Antivir Ther. 2002;7:91–103.
Fischer M, Joos B, Niederost B, Kaiser P, Hafner R, von Wyl V, Ackermann M, Weber R, Gunthard HF. Biphasic decay kinetics suggest progressive slowing in turnover of latently HIV-1 infected cells during antiretroviral therapy. Retrovirology. 2008;5:107.
Pasternak A, Scherpenisse M, Berkhout B. Cell-associated HIV-1 unspliced to multiply spliced RNA ratio at 12 weeks ART correlates with markers of immune activation and apoptosis and predicts the CD4+ T cell count at 96 weeks ART. In: 8th IAS conference on HIV pathogenesis, treatment and prevention. Vancouver, Canada; 2015.
Seshamma T, Bagasra O, Trono D, Baltimore D, Pomerantz RJ. Blocked early-stage latency in the peripheral blood cells of certain individuals infected with human immunodeficiency virus type 1. Proc Natl Acad Sci USA. 1992;89:10663–7.
Furtado MR, Kingsley LA, Wolinsky SM. Changes in the viral mRNA expression pattern correlate with a rapid rate of CD4+ T-cell number decline in human immunodeficiency virus type 1-infected individuals. J Virol. 1995;69:2092–100.
Michael NL, Mo T, Merzouki A, O’Shaughnessy M, Oster C, Burke DS, Redfield RR, Birx DL, Cassol SA. Human immunodeficiency virus type 1 cellular RNA load and splicing patterns predict disease progression in a longitudinally studied cohort. J Virol. 1995;69:1868–77.
Comar M, Simonelli C, Zanussi S, Paoli P, Vaccher E, Tirelli U, Giacca M. Dynamics of HIV-1 mRNA expression in patients with long-term nonprogressive HIV-1 infection. J Clin Invest. 1997;100:893–903.
Plantin J, Massanella M, Chomont N. Inducible HIV RNA transcription assays to measure HIV persistence: pros and cons of a compromise. Retrovirology. 2018;15:9.
Procopio FA, Fromentin R, Kulpa DA, Brehm JH, Bebin AG, Strain MC, Richman DD, O’Doherty U, Palmer S, Hecht FM, et al. A novel assay to measure the magnitude of the inducible viral reservoir in HIV-infected individuals. EBioMedicine. 2015;2:874–83.
Zanchetta M, Walker S, Burighel N, Bellanova D, Rampon O, Giaquinto C, De RA. Long-term decay of the HIV-1 reservoir in HIV-1-infected children treated with highly active antiretroviral therapy. J Infect Dis. 2006;193:1718–27.
Schmid A, Gianella S, von Wyl V, Metzner KJ, Scherrer AU, Niederost B, Althaus CF, Rieder P, Grube C, Joos B, et al. Profound depletion of HIV-1 transcription in patients initiating antiretroviral therapy during acute infection. PLoS ONE. 2010;5:e13310.
Vesanen M, Markowitz M, Cao Y, Ho DD, Saksela K. Human immunodeficiency virus type-1 mRNA splicing pattern in infected persons is determined by the proportion of newly infected cells. Virology. 1997;236:104–9.
Uprety P, Chadwick EG, Rainwater-Lovett K, Ziemniak C, Luzuriaga K, Capparelli EV, Yenokyan G, Persaud D. Cell-associated HIV-1 DNA and RNA decay dynamics during early combination antiretroviral therapy in HIV-1-infected infants. Clin Infect Dis. 2015;61:1862–70.
Han Y, Lassen K, Monie D, Sedaghat AR, Shimoji S, Liu X, Pierson TC, Margolick JB, Siliciano RF, Siliciano JD. Resting CD4+ T cells from human immunodeficiency virus type 1 (HIV-1)-infected individuals carry integrated HIV-1 genomes within actively transcribed host genes. J Virol. 2004;78:6122–33.
Bullen CK, Laird GM, Durand CM, Siliciano JD, Siliciano RF. New ex vivo approaches distinguish effective and ineffective single agents for reversing HIV-1 latency in vivo. Nat Med. 2014;20:425–9.
Shan L, Rabi SA, Laird GM, Eisele EE, Zhang H, Margolick JB, Siliciano RF. A novel PCR assay for quantification of HIV-1 RNA. J Virol. 2013;87:6521–5.
Pasternak AO, DeMaster LK, Kootstra NA, Reiss P, O’Doherty U, Berkhout B. Minor contribution of chimeric host-HIV readthrough transcripts to the level of HIV cell-associated gag RNA. J Virol. 2015;90:1148–51.
Buzon MJ, Martin-Gayo E, Pereyra F, Ouyang Z, Sun H, Li JZ, Piovoso M, Shaw A, Dalmau J, Zangger N, et al. Long-term antiretroviral treatment initiated at primary HIV-1 infection affects the size, composition, and decay kinetics of the reservoir of HIV-1-infected CD4 T cells. J Virol. 2014;88:10056–65.
Strain MC, Little SJ, Daar ES, Havlir DV, Gunthard HF, Lam RY, Daly OA, Nguyen J, Ignacio CC, Spina CA, et al. Effect of treatment, during primary infection, on establishment and clearance of cellular reservoirs of HIV-1. J Infect Dis. 2005;191:1410–8.
Jain V, Hartogensis W, Bacchetti P, Hunt PW, Hatano H, Sinclair E, Epling L, Lee TH, Busch MP, McCune JM, et al. Antiretroviral therapy initiated within 6 months of HIV infection is associated with lower T-cell activation and smaller HIV reservoir size. J Infect Dis. 2013;208:1202–11.
van Zyl GU, Bedison MA, van Rensburg AJ, Laughton B, Cotton MF, Mellors JW. Early antiretroviral therapy in South African children reduces HIV-1-infected cells and cell-associated HIV-1 RNA in blood mononuclear cells. J Infect Dis. 2015;212:39–43.
Malatinkova E, De Spiegelaere W, Bonczkowski P, Kiselinova M, Vervisch K, Trypsteen W, Johnson M, Verhofstede C, de Looze D, Murray C, et al. Impact of a decade of successful antiretroviral therapy initiated at HIV-1 seroconversion on blood and rectal reservoirs. Elife. 2015;4:e09115.
Pasternak A, Prins JM, Berkhout B. Long-term effect of temporary ART during primary HIV infection on the viral reservoir. In: Conference on retroviruses and opportunistic infections. Seattle, USA; 2015.
Grijsen ML, Steingrover R, Wit FW, Jurriaans S, Verbon A, Brinkman K, van der Ende ME, Soetekouw R, de Wolf F, Lange JM, et al. No treatment versus 24 or 60 weeks of antiretroviral treatment during primary HIV infection: the randomized Primo-SHM trial. PLoS Med. 2012;9:e1001196.
Li JZ, Smith DM, Mellors JW. The need for treatment interruption studies and biomarker identification in the search for an HIV cure. AIDS. 2015;29:1429–32.
Hecht R, Moran P, Mendes W, Cockerham L, Hartogenesis W, Bacchetti P, Chang J, Cameron P, Deeks S, Lewin S. Stress increases HIV transcription in HIV-infected individuals on antiretroviral therapy: implications for biomarkers of HIV persistence. In: 9th IAS conference on HIV science, Paris, France; 2017.
Takahashi JS. Transcriptional architecture of the mammalian circadian clock. Nat Rev Genet. 2017;18:164–79.
Wolf JM, Rohleder N, Bierhaus A, Nawroth PP, Kirschbaum C. Determinants of the NF-kappaB response to acute psychosocial stress in humans. Brain Behav Immun. 2009;23:742–9.
Bierhaus A, Wolf J, Andrassy M, Rohleder N, Humpert PM, Petrov D, Ferstl R, von Eynatten M, Wendt T, Rudofsky G, et al. A mechanism converting psychosocial stress into mononuclear cell activation. Proc Natl Acad Sci USA. 2003;100:1920–5.
Spengler ML, Kuropatwinski KK, Comas M, Gasparian AV, Fedtsova N, Gleiberman AS, Gitlin II, Artemicheva NM, Deluca KA, Gudkov AV, Antoch MP. Core circadian protein CLOCK is a positive regulator of NF-κB-mediated transcription. Proc Natl Acad Sci USA. 2012;109:E2457–65.
Griffin GE, Leung K, Folks TM, Kunkel S, Nabel GJ. Activation of HIV gene expression during monocyte differentiation by induction of NF-kappa B. Nature. 1989;339:70–3.
Nabel G, Baltimore D. An inducible transcription factor activates expression of human immunodeficiency virus in T cells. Nature. 1987;326:711–3.
Berkhout B, Jeang KT. Functional roles for the TATA promoter and enhancers in basal and Tat-induced expression of the human immunodeficiency virus type 1 long terminal repeat. J Virol. 1992;66:139–49.
Leth S, Nymann R, Jørgensen S, Olesen R, Rasmussen TA, Østergaard L, Denton PW, Tolstrup M, Søgaard OS. HIV-1 transcriptional activity during frequent longitudinal sampling in aviremic patients on antiretroviral therapy. AIDS. 2016;30:713–21.
Yukl SA, Shergill AK, Ho T, Killian M, Girling V, Epling L, Li P, Wong LK, Crouch P, Deeks SG, et al. The distribution of HIV DNA and RNA in cell subsets differs in gut and blood of HIV-positive patients on ART: implications for viral persistence. J Infect Dis. 2013;208:1212–20.
Yukl SA, Gianella S, Sinclair E, Epling L, Li Q, Duan L, Choi AL, Girling V, Ho T, Li P, et al. Differences in HIV burden and immune activation within the gut of HIV-positive patients receiving suppressive antiretroviral therapy. J Infect Dis. 2010;202:1553–61.
Banga R, Procopio FA, Noto A, Pollakis G, Cavassini M, Ohmiti K, Corpataux JM, de Leval L, Pantaleo G, Perreau M. PD-1(+) and follicular helper T cells are responsible for persistent HIV-1 transcription in treated aviremic individuals. Nat Med. 2016;22:754–61.
Honeycutt JB, Thayer WO, Baker CE, Ribeiro RM, Lada SM, Cao Y, Cleary RA, Hudgens MG, Richman DD, Garcia JV. HIV persistence in tissue macrophages of humanized myeloid-only mice during antiretroviral therapy. Nat Med. 2017;23:638–43.
Tsai P, Wu G, Baker CE, Thayer WO, Spagnuolo RA, Sanchez R, Barrett S, Howell B, Margolis D, Hazuda DJ, et al. In vivo analysis of the effect of panobinostat on cell-associated HIV RNA and DNA levels and latent HIV infection. Retrovirology. 2016;13:36.
Deere JD, Kauffman RC, Cannavo E, Higgins J, Villalobos A, Adamson L, Schinazi RF, Luciw PA, North TW. Analysis of multiply spliced transcripts in lymphoid tissue reservoirs of rhesus macaques infected with RT-SHIV during HAART. PLoS ONE. 2014;9:e87914.
North TW, Higgins J, Deere JD, Hayes TL, Villalobos A, Adamson L, Shacklett BL, Schinazi RF, Luciw PA. Viral sanctuaries during highly active antiretroviral therapy in a nonhuman primate model for AIDS. J Virol. 2010;84:2913–22.
Kline C, Ndjomou J, Franks T, Kiser R, Coalter V, Smedley J, Piatak M, Mellors JW, Lifson JD, Ambrose Z. Persistence of viral reservoirs in multiple tissues after antiretroviral therapy suppression in a macaque RT-SHIV model. PLoS ONE. 2013;8:e84275.
Bolton DL, McGinnis K, Finak G, Chattopadhyay P, Gottardo R, Roederer M. Combined single-cell quantitation of host and SIV genes and proteins ex vivo reveals host-pathogen interactions in individual cells. PLoS Pathog. 2017;13:e1006445.
Galloway NL, Doitsh G, Monroe KM, Yang Z, Muñoz-Arias I, Levy DN, Greene WC. Cell-to-cell transmission of HIV-1 is required to trigger pyroptotic death of lymphoid-tissue-derived CD4 T cells. Cell Rep. 2015;12:1555–63.
Doitsh G, Cavrois M, Lassen KG, Zepeda O, Yang Z, Santiago ML, Hebbeler AM, Greene WC. Abortive HIV infection mediates CD4 T cell depletion and inflammation in human lymphoid tissue. Cell. 2010;143:789–801.
Josefsson L, von Stockenstrom S, Faria NR, Sinclair E, Bacchetti P, Killian M, Epling L, Tan A, Ho T, Lemey P, et al. The HIV-1 reservoir in eight patients on long-term suppressive antiretroviral therapy is stable with few genetic changes over time. Proc Natl Acad Sci USA. 2013;110:E4987–96.
Josefsson L, Palmer S, Faria NR, Lemey P, Casazza J, Ambrozak D, Kearney M, Shao W, Kottilil S, Sneller M, et al. Single cell analysis of lymph node tissue from HIV-1 infected patients reveals that the majority of CD4+ T-cells contain one HIV-1 DNA molecule. PLoS Pathog. 2013;9:e1003432.
Perreau M, Savoye AL, De Crignis E, Corpataux JM, Cubas R, Haddad EK, De Leval L, Graziosi C, Pantaleo G. Follicular helper T cells serve as the major CD4 T cell compartment for HIV-1 infection, replication, and production. J Exp Med. 2013;210:143–56.
Fukazawa Y, Lum R, Okoye AA, Park H, Matsuda K, Bae JY, Hagen SI, Shoemaker R, Deleage C, Lucero C, et al. B cell follicle sanctuary permits persistent productive simian immunodeficiency virus infection in elite controllers. Nat Med. 2015;21:132–9.
Lewin SR, Vesanen M, Kostrikis L, Hurley A, Duran M, Zhang L, Ho DD, Markowitz M. Use of real-time PCR and molecular beacons to detect virus replication in human immunodeficiency virus type 1-infected individuals on prolonged effective antiretroviral therapy. J Virol. 1999;73:6099–103.
Fischer M, Joos B, Hirschel B, Bleiber G, Weber R, Gunthard HF. Cellular viral rebound after cessation of potent antiretroviral therapy predicted by levels of multiply spliced HIV-1 RNA encoding nef. J Infect Dis. 2004;190:1979–88.
Hong F, Aga E, Cillo AR, Yates AL, Besson G, Fyne E, Koontz DL, Jennings C, Zheng L, Mellors JW. Novel assays for measurement of total cell-associated HIV-1 DNA and RNA. J Clin Microbiol. 2016;54:902–11.
Pasternak AO, Adema KW, Bakker M, Jurriaans S, Berkhout B, Cornelissen M, Lukashov VV. Highly sensitive methods based on seminested real-time reverse transcription-PCR for quantitation of human immunodeficiency virus type 1 unspliced and multiply spliced RNA and proviral DNA. J Clin Microbiol. 2008;46:2206–11.
Rutsaert S, Bosman K, Trypsteen W, Nijhuis M, Vandekerckhove L. Digital PCR as a tool to measure HIV persistence. Retrovirology. 2018. https://doi.org/10.1186/s12977-018-0399-0.
Strain MC, Lada SM, Luong T, Rought SE, Gianella S, Terry VH, Spina CA, Woelk CH, Richman DD. Highly precise measurement of HIV DNA by droplet digital PCR. PLoS ONE. 2013;8:e55943.
Bosman KJ, Nijhuis M, van Ham PM, Wensing AM, Vervisch K, Vandekerckhove L, De Spiegelaere W. Comparison of digital PCR platforms and semi-nested qPCR as a tool to determine the size of the HIV reservoir. Sci Rep. 2015;5:13811.
Whale AS, Cowen S, Foy CA, Huggett JF. Methods for applying accurate digital PCR analysis on low copy DNA samples. PLoS ONE. 2013;8:e58177.
Ståhlberg A, Kubista M, Pfaffl M. Comparison of reverse transcriptases in gene expression analysis. Clin Chem. 2004;50:1678–80.
Stangegaard M, Dufva IH, Dufva M. Reverse transcription using random pentadecamer primers increases yield and quality of resulting cDNA. Biotechniques. 2006;40:649–57.
Sanders R, Mason DJ, Foy CA, Huggett JF. Evaluation of digital PCR for absolute RNA quantification. PLoS ONE. 2013;8:e75296.
Cillo AR, Sobolewski MD, Bosch RJ, Fyne E, Piatak M, Coffin JM, Mellors JW. Quantification of HIV-1 latency reversal in resting CD4+ T cells from patients on suppressive antiretroviral therapy. Proc Natl Acad Sci USA. 2014;111:7078–83.
Massanella M, Yek C, Lada S, Strain MC, Richman DD. Improved assays to measure the inducible latent HIV reservoir. In: 8th IAS conference on HIV pathogenesis, treatment and prevention, Vancouver, Canada; 2015.
Ho YC, Shan L, Hosmane NN, Wang J, Laskey SB, Rosenbloom DI, Lai J, Blankson JN, Siliciano JD, Siliciano RF. Replication-competent noninduced proviruses in the latent reservoir increase barrier to HIV-1 cure. Cell. 2013;155:540–51.
Wiegand A, Spindler J, Hong FF, Shao W, Cyktor JC, Cillo AR, Halvas EK, Coffin JM, Mellors JW, Kearney MF. Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART. Proc Natl Acad Sci USA. 2017;114:E3659–68.
Bui JK, Halvas EK, Fyne E, Sobolewski MD, Koontz D, Shao W, Luke B, Hong FF, Kearney MF, Mellors JW. Ex vivo activation of CD4+ T-cells from donors on suppressive ART can lead to sustained production of infectious HIV-1 from a subset of infected cells. PLoS Pathog. 2017;13:e1006230.
Yucha RW, Hobbs KS, Hanhauser E, Hogan LE, Nieves W, Ozen MO, Inci F, York V, Gibson EA, Thanh C, et al. High-throughput characterization of HIV-1 reservoir reactivation using a single-cell-in-droplet PCR assay. EBioMedicine. 2017;20:217–29.
Derdeyn CA, Kilby JM, Miralles GD, Li LF, Sfakianos G, Saag MS, Hockett RD, Bucy RP. Evaluation of distinct blood lymphocyte populations in human immunodeficiency virus type 1-infected subjects in the absence or presence of effective therapy. J Infect Dis. 1999;180:1851–62.
Patterson BK, Mosiman VL, Cantarero L, Furtado M, Bhattacharya M, Goolsby C. Detection of HIV-RNA-positive monocytes in peripheral blood of HIV-positive patients by simultaneous flow cytometric analysis of intracellular HIV RNA and cellular immunophenotype. Cytometry. 1998;31:265–74.
Patterson BK. Simultaneous ultrasensitive subpopulation staining/hybridization in situ (SUSHI) in HIV-1 disease monitoring. Methods Mol Biol. 2010;659:337–46.
Shults K, Flye-Blakemore L, Patterson BK, Elbeik T. Analysis of multiple cell reservoirs expressing unspliced HIV-1 gag-pol mRNA in patients on antiretroviral therapy. Future Virol. 2012;7:819–32.
Patterson BK, McCallister S, Schutz M, Siegel JN, Shults K, Flener Z, Landay A. Persistence of intracellular HIV-1 mRNA correlates with HIV-1-specific immune responses in infected subjects on stable HAART. AIDS. 2001;15:1635–41.
Deleage C, Wietgrefe SW, Del Prete G, Morcock DR, Hao XP, Piatak M, Bess J, Anderson JL, Perkey KE, Reilly C, et al. Defining HIV and SIV reservoirs in lymphoid tissues. Pathog Immun. 2016;1:68–106.
Grau-Expósito J, Serra-Peinado C, Miguel L, Navarro J, Curran A, Burgos J, Ocaña I, Ribera E, Torrella A, Planas B, et al. A novel single-cell FISH-flow assay identifies effector memory CD4(+) T cells as a major niche for HIV-1 transcription in HIV-infected patients. MBio. 2017;8:e00876-17.
Martrus G, Niehrs A, Cornelis R, Rechtien A, García-Beltran W, Lütgehetmann M, Hoffmann C, Altfeld M. Kinetics of HIV-1 latency reversal quantified on the single-cell level using a novel flow-based technique. J Virol. 2016;90:9018–28.
Baxter AE, O’Doherty U, Kaufmann DE. Beyond the replication-competent HIV reservoir: transcription and translation-competent reservoirs. Retrovirology. 2018. https://doi.org/10.1186/s12977-018-0392-7.
Deleage C, Chan CN, Busman-Sahay K, Estes JD. Next-generation in situ hybridization approaches to define and quantify HIV and SIV reservoirs in tissue microenvironments. Retrovirology. 2018;15:4.
Bruner KM, Murray AJ, Pollack RA, Soliman MG, Laskey SB, Capoferri AA, Lai J, Strain MC, Lada SM, Hoh R, et al. Defective proviruses rapidly accumulate during acute HIV-1 infection. Nat Med. 2016;22:1043–9.
Hiener B, Horsburgh BA, Eden JS, Barton K, Schlub TE, Lee E, von Stockenstrom S, Odevall L, Milush JM, Liegler T, et al. Identification of genetically intact HIV-1 proviruses in specific CD4(+) T cells from effectively treated participants. Cell Rep. 2017;21:813–22.
Lee GQ, Orlova-Fink N, Einkauf K, Chowdhury FZ, Sun X, Harrington S, Kuo HH, Hua S, Chen HR, Ouyang Z, et al. Clonal expansion of genome-intact HIV-1 in functionally polarized Th1 CD4+ T cells. J Clin Invest. 2017;127:2689–96.
Abbink TE, Berkhout B. RNA structure modulates splicing efficiency at the human immunodeficiency virus type 1 major splice donor. J Virol. 2008;82:3090–8.
Huthoff H, Das AT, Vink M, Klaver B, Zorgdrager F, Cornelissen M, Berkhout B. A human immunodeficiency virus type 1-infected individual with low viral load harbors a virus variant that exhibits an in vitro RNA dimerization defect. J Virol. 2004;78:4907–13.
Imamichi H, Dewar RL, Adelsberger JW, Rehm CA, O’Doherty U, Paxinos EE, Fauci AS, Lane HC. Defective HIV-1 proviruses produce novel protein-coding RNA species in HIV-infected patients on combination antiretroviral therapy. Proc Natl Acad Sci USA. 2016;113:8783–8.
Pollack RA, Jones RB, Pertea M, Bruner KM, Martin AR, Thomas AS, Capoferri AA, Beg SA, Huang SH, Karandish S, et al. Defective HIV-1 proviruses are expressed and can be recognized by cytotoxic T lymphocytes, which shape the proviral landscape. Cell Host Microbe. 2017;21(494–506):e494.
Kearney MF, Wiegand A, Shao W, Coffin JM, Mellors JW, Lederman M, Gandhi RT, Keele BF, Li JZ. Origin of rebound plasma HIV includes cells with identical proviruses that are transcriptionally active before stopping of antiretroviral therapy. J Virol. 2015;90:1369–76.
Barton K, Hiener B, Winckelmann A, Rasmussen TA, Shao W, Byth K, Lanfear R, Solomon A, McMahon J, Harrington S, et al. Broad activation of latent HIV-1 in vivo. Nat Commun. 2016;7:12731.
Winckelmann A, Barton K, Hiener B, Schlub TE, Shao W, Rasmussen TA, Østergaard L, Søgaard OS, Tolstrup M, Palmer S. Romidepsin-induced HIV-1 viremia during effective antiretroviral therapy contains identical viral sequences with few deleterious mutations. AIDS. 2017;31:771–9.
Rassler S, Ramirez R, Khoury N, Skowron G, Sahu GK. Prolonged persistence of a novel replication-defective HIV-1 variant in plasma of a patient on suppressive therapy. Virol J. 2016;13:157.
Imamichi H, Dewar RL, Huang DW, Liang D, Rehm CR, Paxinos E, Brown M, Guo Y, Ludka C, Hadigan C, et al. Cryptic transcription of HIV-RNA species from “defective” proviruses: a novel pathway for persistent immune activation in patients with HIV-1 infection and mechanism for persistent seropositivity despite “undetectable” levels of virus. In: 20th International AIDS conference. Melbourne, Australia; 2014.
Hatano H, Jain V, Hunt PW, Lee TH, Sinclair E, Do TD, Hoh R, Martin JN, McCune JM, Hecht F, et al. Cell-based measures of viral persistence are associated with immune activation and programmed cell death protein 1 (PD-1)-expressing CD4+ T cells. J Infect Dis. 2013;208:50–6.
Soares RS, Tendeiro R, Foxall RB, Baptista AP, Cavaleiro R, Gomes P, Camacho R, Valadas E, Doroana M, Lucas M, et al. Cell-associated viral burden provides evidence of ongoing viral replication in aviremic HIV-2-infected patients. J Virol. 2011;85:2429–38.
Gandhi RT, McMahon DK, Bosch RJ, Lalama CM, Cyktor JC, Macatangay BJ, Rinaldo CR, Riddler SA, Hogg E, Godfrey C, et al. Levels of HIV-1 persistence on antiretroviral therapy are not associated with markers of inflammation or activation. PLoS Pathog. 2017;13:e1006285.
Mousseau G, Kessing CF, Fromentin R, Trautmann L, Chomont N, Valente ST. The tat inhibitor didehydro-cortistatin a prevents HIV-1 reactivation from latency. MBio. 2015;6:e00465.
Kessing CF, Nixon CC, Li C, Tsai P, Takata H, Mousseau G, Ho PT, Honeycutt JB, Fallahi M, Trautmann L, et al. In vivo suppression of HIV rebound by didehydro-cortistatin A, a “Block-and-Lock” strategy for HIV-1 treatment. Cell Rep. 2017;21:600–11.
Li P, Kaiser P, Lampiris HW, Kim P, Yukl SA, Havlir DV, Greene WC, Wong JK. Stimulating the RIG-I pathway to kill cells in the latent HIV reservoir following viral reactivation. Nat Med. 2016;22:807–11.
Ke R, Lewin SR, Elliott JH, Perelson AS. Modeling the effects of vorinostat in vivo reveals both transient and delayed HIV transcriptional activation and minimal killing of latently infected cells. PLoS Pathog. 2015;11:e1005237.
Wang G, Zhao N, Berkhout B, Das AT. A combinatorial CRISPR-Cas9 attack on HIV-1 DNA extinguishes all infectious provirus in infected T cell cultures. Cell Rep. 2016;17:2819–26.
Kaminski R, Bella R, Yin C, Otte J, Ferrante P, Gendelman HE, Li H, Booze R, Gordon J, Hu W, et al. Excision of HIV-1 DNA by gene editing: a proof-of-concept in vivo study. Gene Ther. 2016;23:690–5.
Li JZ, Etemad B, Ahmed H, Aga E, Bosch RJ, Mellors JW, Kuritzkes DR, Lederman MM, Para M, Gandhi RT. The size of the expressed HIV reservoir predicts timing of viral rebound after treatment interruption. AIDS. 2016;30:343–53.
Pasternak A, Prins J, Berkhout B. Cell-associated HIV-1 unspliced RNA level predicts both time to virological suppression and duration of post-treatment virological control in patients treated with temporary early ART. In: 21th International AIDS conference. Durban, South Africa; 2016.
Hill AL, Rosenbloom DI, Fu F, Nowak MA, Siliciano RF. Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1. Proc Natl Acad Sci USA. 2014;111:13475–80.
Hill AL, Rosenbloom DI, Goldstein E, Hanhauser E, Kuritzkes DR, Siliciano RF, Henrich TJ. Real-time predictions of reservoir size and rebound time during antiretroviral therapy interruption trials for HIV. PLoS Pathog. 2016;12:e1005535.
Pinkevych M, Cromer D, Tolstrup M, Grimm AJ, Cooper DA, Lewin SR, Søgaard OS, Rasmussen TA, Kent SJ, Kelleher AD, Davenport MP. HIV reactivation from latency after treatment interruption occurs on average every 5–8 days-implications for HIV remission. PLoS Pathog. 2015;11:e1005000.
Williams JP, Hurst J, Stöhr W, Robinson N, Brown H, Fisher M, Kinloch S, Cooper D, Schechter M, Tambussi G, et al. HIV-1 DNA predicts disease progression and post-treatment virological control. Elife. 2014;3:e03821.
AOP and BB wrote the manuscript. Both authors read and approved the final manuscript.
We are thankful to Gilles Darcis for critical reading of the manuscript.
The authors declare that they have no competing interests.
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