CROI 2018 Abstract eBook

Abstract eBook

Poster Abstracts

standards. One p24 assay detected HIV protein in virus-spiked samples, with observed specificity of 90%. Conclusion: p24 assays can detect virus in seronegative plasma without virus enrichment, but dynamic sensitivity was lacking at <45 copies/mL. Ultrasensitive RNA-amplification assays following virus enrichment or with replicate testing can quantitatively measure HIV RNA down to ~1 copy/mL, which is necessary to assess the impact of experimental curative interventions on residual viremia. 394 QUANTIFYING THE TURNOVER OF LATENT HIV: APPLICATIONS TO ANTI- PROLIFERATIVE THERAPY Jeffrey Gerold 1 , Michael J. Bale 2 , Zheng Wang 3 , Guinevere Q. Lee 4 , Mathias Lichterfeld 4 , Robert Siliciano 3 , Mary F. Kearney 5 , Alison L. Hill 1 1 Harvard University, Cambridge, MA, USA, 2 NIH, Frederick, MD, USA, 3 Johns Hopkins University, Baltimore, MD, USA, 4 Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA, 5 NIH, Bethesda, MD, USA Background: The latent reservoir for HIV consists of provirus stably integrated into long-lived lymphocytes and represents a barrier to a cure. This reservoir decays with a half-life of ~44 months during long-term suppressive ART, but the relative role of intrinsic T cell longevity vs proliferation in this persistence is unknown. Recent characterization of integration sites and full-genome sequences has suggested that clonal proliferation contributes to reservoir stability, but this rate has yet to be quantified. Estimating the value of this turnover rate is necessary to understand whether anti-proliferative therapy is a viable treatment option. Methods: Here we develop a method to infer the underlying dynamics of cells in the latent reservoir from clone size distributions in sampled cells. We created a dynamic, stochastic mathematical model for cells in the latent reservoir, and fit this model to data using a Bayesian Markov Chain Monte Carlo estimation procedure that includes the size of the latent reservoir before ART initiation, the time on ART, and the later sampling of infected cells. The inference algorithm was applied to two sources of data: HIV integration site frequencies and intact provirus determined by full-genome sequencing. Results: Using HIV DNA integration site data and a simple homogeneous model of latent cell division and death, we estimated that on average latent cells divide around 10 times/yr [95% CI 5-20/yr], a much higher turnover than predicted by the total decay rate of 0.2/yr (e.g. half-life 44 months). For individual patients, the best-estimated turnover rate varied by up to an order of magnitude [2-30/ yr]. Results were similar using intact virus only, though more uncertain due to smaller sample sizes. We used simulated populations to confirm our inference method was unbiased and required ~500 samples from each patient to reduce the uncertainty in turnover rate to +/-40% (95% CI). We found that an augmented model which also allowed for rare, burst-like proliferation could explain the clone size distribution better than the simple model. These findings suggest that therapy which reduced proliferation by 50% could reduce reservoir half-life to a fewmonths, raising the potential for eradication with a few years of ART. Conclusion: Our findings suggest that proliferation of latently-infected cells is a major contributor to the stability of the total and intact DNA reservoir and that reducing this proliferation may have potential as a curative intervention. 395 SINGLE CELL ANALYSIS OF HIV LATENCY REVEALS DIVERSE PROVIRAL AND HOST CELL BEHAVIOR Edward P. Browne 1 , Todd Bradley 2 , Guido Ferrari 2 , Barton F. Haynes 2 , David M. Margolis 1 1 University of North Carolina Chapel Hill, Chapel Hill, NC, USA, 2 Duke Human Vaccine Institute, Durham, NC, USA Background: The latent reservoir is inherently diverse with each infected cell exhibiting a potentially unique combination of integration site, epigenetic modifications, and host cell phenotype. However, most studies of HIV latency have relied on assays of bulk cultures in which information about the behavior of individual cells is lost. As such, the application of single cell level methods to HIV latency model systems may reveal previously unappreciated levels of heterogeneity. We hypothesized that latently infected cells exhibit diverse characteristics with respect to proviral reactivation and host cell phenotype, and that characterizing this diversity will be important for optimizing approaches for clearing the latent reservoir. Methods: We have characterized a cell line model and a novel primary cell model of HIV latency with two single cell assays – single cell qPCR (sc-qPCR)

for viral RNA (vRNA), and single cell RNAseq (scRNAseq). These systems were examined both at rest, and after stimulation with two latency reversing agents (LRAs)– vorinostat, and prostratin. Results: sc-qPCR for vRNA revealed that a subset of latently infected cells transcribe detectable viral RNA in the absence of stimulation, and that stimulation with LRAs induces a wide range of vRNA levels in infected cells. For transformed cell lines, an apparent threshold of ~500 copies of vRNA was required before virally encoded antigen was detected by flow cytometry, while primary cells exhibited a more complex relationship between vRNA and viral protein expression. Compared to prostratin, vorinostat induced lower levels of viral antigen expression, even in cells with equivalent expression of vRNA, suggesting a post-transcriptional block to viral gene expression. Single cell RNAseq of >2000 latently infected primary cells using the 10x Genomics platform revealed diverse transcriptomic profiles within the infected cell population. Interestingly, cells which exhibited the greatest levels of HIV silencing were enriched for a specific set of host genes that define naïve and central memory T cells, suggesting a role for T cell subset identity in the establishment of latency. Conclusion: Altogether, these data reveal heterogeneous behaviors of HIV proviruses and host cells at rest, and after stimulation with LRAs, and illustrate the power of single cell methods to provide insights into HIV latency. 396 ULTRASENSITIVE P24 DIGITAL ELISA CAN LEAD TO AN OVERESTIMATE OF HIV RESERVOIR SIZE Francesco R. Simonetti 1 , Subul A. Beg 2 , Jun Lai 2 , Purvish Patel 3 , Hao Zhang 2 , Gregory Laird 2 , Lynn N. Bertagnolli 2 , David Kulick 3 , Robert Siliciano 2 , Janet Siliciano 2 1 The Johns Hopkins University, Baltimore, MD, USA, 2 Johns Hopkins University, Baltimore, MD, USA, 3 Quanterix Corporation, Lexington, MA, USA Background: The quantitative viral outgrowth assay (qVOA) estimates the size of the HIV reservoir based on the frequency of cells harboring inducible, replication-competent proviruses. The ultrasensitive SIMOA p24 assay, developed by Quanterix, can quantify p24 with a limit of detection up to 1000 times lower than standard ELISA. We investigated whether SIMOA can be used as a reliable read out to calculate the frequency of infected cells in qVOA experiments. In addition, we tested if SIMOA can be biased by defective proviruses still capable of producing p24. Methods: Total CD4+ T-cells from 3 patients on suppressive ART were sorted based on CD32, recently characterized by Descours et al. CD4+CD32- cells (14-24x10^6) were plated in 5-fold dilutions. CD4+CD32+ cells, present at very low frequency, were plated in replicate with low cell input (2.2-62 x 10^3 total cells). qVOAs were conducted as described by Laird et al, 2014. The SIMOA p24 2.0 commercial kit was used to assay supernatants collected at days 5, 9, 14 and 21. We used droplet digital PCR to quantify HIV RNA from cells and supernatants, and performed RNA single genome sequencing from U5 to gag (HXB2 nt 551- 1330). Results: The lower limit of quantification of SIMOA (0.01 pg/ml) allowed earlier p24 detection in CD32- wells that were positive by ELISA at day 21 (63% positive wells at day 5, 95% at day 9, 100% at day 14, n=19). However, of these wells positive by SIMOA, only 53% (19/36) showed exponential viral outgrowth from day 5 to 21, while the others had stable, low p24 levels (mean 0.21 pg/ ml). In two of these wells with no outgrowth we found high HIV RNA copies in both cells and supernatants. SGS revealed 3 variants with an intact gag ORF, 2 of them carrying defects in the major splice donor site. The extreme sensitivity of SIMOA allowed detection of low level of p24 released from cells with defective proviruses. The frequency of latently infected cells showed a 4-fold increase when the assay had high cell input. However, in 2 out of the 3 qVOAs with a low input of CD32+ cells (all negative by ELISA), SIMOA caused a dramatic overestimate of infected cell frequency (554 and 3184 IUPM). Conclusion: SIMOA allows earlier detection of p24 compared to ELISA. However, longitudinal sampling is necessary to distinguish viral outgrowth from low-level p24 likely produced by defective proviruses. Our results advice caution in using SIMOA on a single timepoint, as it can lead to an overestimate of IUPM, particularly for qVOA with low cell input.

Poster Abstracts

CROI 2018 138