Leveraging Novel Integrated Single-Cell Analyses to Define HIV

viruses Review Leveraging Novel Integrated Single-Cell Analyses to Define HIV-1 Latency Reversal Suhui Zhao and Athe Tsibris * Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02139, USA; [email protected] * Correspondence: [email protected] Abstract: While suppressive antiretroviral therapy can effectively limit HIV-1 replication and evolu- tion, it leaves behind a residual pool of integrated viral genomes that persist in a state of reversible nonproductive infection, referred to as the HIV-1 reservoir. HIV-1 infection models were established to investigate HIV-1 latency and its reversal; recent work began to probe the dynamics of HIV-1 latency reversal at single-cell resolution. Signals that establish HIV-1 latency and govern its reactivation are complex and may not be completely resolved at the cellular and regulatory levels by the aggregated measurements of bulk cellular-sequencing methods. High-throughput single-cell technologies that characterize and quantify changes to the epigenome, transcriptome, and proteome continue to rapidly evolve. Combinations of single-cell techniques, in conjunction with novel compu- tational approaches to analyze these data, were developed and provide an opportunity to improve the resolution of the heterogeneity that may exist in HIV-1 reactivation. In this review, we summarize the published single-cell HIV-1 transcriptomic work and explore how cutting-edge advances in single-cell techniques and integrative data-analysis tools may be leveraged to define the mechanisms that control the reversal of HIV-1 latency. Keywords: HIV latency; virus reservoir; single-cell RNA-seq; single-cell ATAC-seq; CITE-seq Citation: Zhao, S.; Tsibris, A. Leveraging Novel Integrated Single-Cell Analyses to Define HIV-1 Latency Reversal. Viruses 2021, 13, 1197. https://doi.org/10.3390/ 1. Introduction + v13071197 HIV-1 persists in CD4 T cells and rebounds after antiretroviral therapy (ART) is interrupted or stopped. Viral latency is defined as a state of reversible nonproductive Academic Editor: Alon Herschhorn infection that, in the case of HIV-1, is associated with the use of suppressive ART [1]. Previous work investigated which proportion of integrated sequences are intact, and Received: 29 April 2021 thereby may contribute to the replication-competent HIV-1 reservoir [2–5]. The vast Accepted: 16 June 2021 majority, greater than 90%, of integrated proviruses are defective, accumulate during acute Published: 22 June 2021 HIV-1 infection, and cannot support viral replication [2,4]. However, these “defective” proviruses may still retain HIV-1 transcriptional and translation activity that is relevant to Publisher’s Note: MDPI stays neutral eradication efforts [6,7]. with regard to jurisdictional claims in Cells harboring latent HIV-1 are extremely rare, numbering in the range of 100–103 per published maps and institutional affil- million CD4+ T cells in peripheral blood during treated suppressed infection, and may iations. be heterogenous [8–11]. As few as 100 CD4+ T cells harbor intact HIV-1 proviruses that may contribute to rapid HIV-1 rebound after ART is stopped [2,4,12]. Cells that comprise the HIV-1 reservoir express no known distinguishing markers, making them a challenge to identify [2,7,13–18]. Several approaches were developed to identify cells harboring Copyright: © 2021 by the authors. HIV-1 DNA and measure the frequencies, size, and phenotypes of the HIV-1 reservoir in Licensee MDPI, Basel, Switzerland. ART-suppressed individuals. The tat/rev-induced limiting dilution assay (TILDA) can This article is an open access article measure multiply spliced HIV-1 transcripts after stimulation and has the advantage of distributed under the terms and requiring fewer cells than other methods [19–21], while the quantitative viral outgrowth conditions of the Creative Commons assay (QVOA), a gold standard of estimation of the size of HIV-1 reservoir, quantifies Attribution (CC BY) license (https:// replication-competent proviruses [22–25]. Even the gold standard has limitations: repeated creativecommons.org/licenses/by/ rounds of activation change the result, and a newer QVOA that preferentially differentiates 4.0/). Viruses 2021, 13, 1197. https://doi.org/10.3390/v13071197 https://www.mdpi.com/journal/viruses Viruses 2021, 13, 1197 2 of 18 Viruses 2021, 13, 1197replication-competent proviruses [22–25]. Even the gold standard has limitations: re- 2 of 17 peated rounds of activation change the result, and a newer QVOA that preferentially differentiates T cells to an effector memory phenotype, dQVOA, may be more accurate [26]. The intact proviralT cells DNA to an assay effector (IPDA) memory may phenotype,offer an accurate dQVOA, and mayscalable be more alternative accurate to [ 26]. The intact the more labor-intensiveproviral DNA QVOA assay [12,27]. (IPDA) Full may-length offer sequencing an accurate of the and HIV-1 scalable genome alternative can to the more quantify intact labor-intensivenoninduced genomes QVOA [of12 ,HIV-27]. Full-length1 [3,4]. Cells sequencing expressing of the the HIV-1 HIV-1 capsid genome can quantify protein, p24, thatintact is produced noninduced during genomes viral reactivation of HIV-1 [3, 4can]. Cells be quantified expressing by the flow HIV-1 cytome- capsid protein, p24, try [28–30]. Thesethat approaches is produced should during be viral viewed reactivation as complementary; can be quantified sequencing by flow cannot cytometry [28–30]. determine translationThese approachesor replication should competence, be viewed and as flow complementary; cytometry cannot sequencing assess pro- cannot determine viral deletions and/ortranslation mutations. or replication competence, and flow cytometry cannot assess proviral deletions The rarity and/orof latently mutations. HIV-infected cells in patients makes their reactivation a challenge to study at theThe single-cell rarity of level. latently To address HIV-infected this difficulty, cells in patients in vitro makes and ex their vivo reactivation models a challenge were developedto to study investigate at the single-cell HIV-1 latency, level. To each address with this their difficulty, own uniquein vitro setsand of ex ad- vivo models were vantages and disadvantages.developed to investigateIn vitro models HIV-1 can latency, provide each sufficient with their numbers own unique of cells sets for of advantages analyses, but mayand not disadvantages. recapitulate latencyIn vitro inmodels vivo, and can are provide rarely sufficienttruly latent numbers [31]. Primary of cells for analyses, ex vivo modelsbut that may use notCD4 recapitulate+ T cells are widely latency usedin vivo in ,the and investigation are rarely truly of HIV-1 latent latency [31]. Primary ex vivo and latency reversalmodels [24,32–36]. that use CD4 + T cells are widely used in the investigation of HIV-1 latency and The availabilitylatency of reversal high-resolution [24,32–36 single-cell]. RNA sequencing (scRNA-seq) in com- bination with novelThe technologies availability that of high-resolutionassess the epigenome single-cell and RNAproteome, sequencing such as (scRNA-seq) the in com- assay for transposase-accessiblebination with novel chromatin technologies using thatsequencing assess the (scATAC-seq) epigenome and and Cellular proteome, such as the Indexing of Transcriptomesassay for transposase-accessible and Epitopes by Sequencing chromatin (CITE-seq), using sequencing provides (scATAC-seq) a unique and Cellular opportunity to Indexingstudy the ofheterogeneity Transcriptomes of HIV-1 and Epitopes latency reversal, by Sequencing and more (CITE-seq), precisely providesde- a unique fine the mechanismsopportunity that control to study HIV-1 the heterogeneity transcriptional of reactivation HIV-1 latency (Figure reversal, 1). andIn this more re- precisely define view, we summarizethe mechanisms current approaches that control to HIV-1leverage transcriptional single-cell sequencing reactivation technologies (Figure1). In this review, to study HIV-1we latency. summarize We review current downstream approaches integrative-analysis to leverage single-cell approaches sequencing to technologies iden- to study tify new strategiesHIV-1 that latency. may shed We light review on downstreamthe complexities integrative-analysis of HIV-1 latency approachesand its reac- to identify new tivation. strategies that may shed light on the complexities of HIV-1 latency and its reactivation. Figure 1. Schematic of integrative analysis of HIV-1 latency. (A) Establishment of HIV-1 latency in Figure 1. Schematic of integrative analysis of HIV-1 latency. (A) Establishment of HIV-1 latency in model systems that use model systems that use primary human CD4+ T lymphocytes. Generally, cells are activated, infected primary human CD4+ T lymphocytes. Generally, cells are activated, infected by reporter HIV-1 constructs, and allowed by reporter HIV-1 constructs, and allowed for returning to a quiescent state prior to reactivation for returningwith to apharmacologic quiescent state latency prior to reversal reactivation agents with (LRA). pharmacologic (B) Summary latency of reversalsingle-c agentsell technologies (LRA). (B )to Summary of single-cell technologies to characterize transcriptome, proteome, and regulome. (C) Integration approaches to single-cell datasets that assess transcription and chromatin accessibility. Tn5 transposases, coupled with DNA adapters, fragment and tag accessible genomic DNA. Resulting fragments are amplified and sequenced to generate chromatin accessibility

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