Combined single-cell quantitation of host and SIV genes and proteins ex vivo reveals host-pathogen interactions in individual cells

Molecular cytometry for comprehensive immune profiling

Molecular cytometry refers to a group of high-parameter technologies for single-cell analysis that share the following traits: (1) combined (multimodal) measurement of protein and transcripts, (2) medium throughput (10-100K cells), and (3) the use of oligonucleotide-tagged antibodies to detect protein expression. The platform can measure over 100 proteins and either hundreds of targeted genes or the whole transcriptome, on a cell-by-cell basis. It is currently one of the most powerful technologies available for immune monitoring. Here, we describe the technology platform (which includes CITE-Seq, REAP-Seq, and AbSeq), provide guidance for its optimization, and discuss advantages and limitations. Finally, we provide some vignettes from studies that demonstrate the application and potential insight that can be gained from molecular cytometry studies.

AP-1/c-Fos supports SIV and HIV-1 latency in CD4 T cells infected in vivo

Persistent HIV-1 reservoirs of infected CD4 T cells are a major barrier to HIV-1 cure, although the mechanisms by which they are established and maintained in vivo remain poorly characterized. To elucidate host cell gene expression patterns that govern virus gene expression, we analyzed viral RNA+ (vRNA) CD4 T cells of untreated simian immunodeficiency virus (SIV)-infected macaques by single-cell RNA sequencing. A subset of vRNA+ cells distinguished by spliced and high total vRNA (7-10% of reads) expressed diminished FOS, a component of the Activator protein 1 (AP-1) transcription factor, relative to vRNA-low and -negative cells. Conversely, FOS and JUN, another AP-1 component, were upregulated in HIV DNA+ infected cells compared to uninfected cells from people with HIV-1 on suppressive therapy. Inhibiting c-Fos in latently infected primary cells augmented reactivatable HIV-1 infection. These findings implicate AP-1 in latency establishment and maintenance and as a potential therapeutic target to limit HIV-1 reservoirs.

Single-Cell Profiling of Latently SIV-Infected CD4+ T Cells Directly Ex Vivo to Reveal Host Factors Supporting Reservoir Persistence

HIV-1 cure strategies aiming to eliminate persistent infected cell reservoirs are hampered by a poor understanding of cells harboring viral DNA in vivo. We describe a novel method to identify, enumerate, and characterize in detail individual cells infected in vivo using a combination of single-cell multiplexed assays for integrated proviral DNA, quantitative viral and host gene expression, and quantitative surface protein expression without any in vitro manipulation. Latently infected CD4+ T cells, defined as harboring integrated provirus in the absence of spliced viral mRNA, were identified from macaque lymph nodes during acute, chronic, and combination antiretroviral therapy (cART)-suppressed simian immunodeficiency virus (SIV) infection. Latently infected CD4+ T cells were most abundant during acute SIV (~8% of memory CD4+ T cells) and persisted in chronic and cART-suppressed infection. Productively infected cells actively transcribing viral mRNA, by contrast, were much more labile and declined substantially between acute and chronic or cART-suppressed infection. Expression of most surface proteins and host genes was similar between latently infected cells and uninfected cells. Elevated FLIP mRNA and surface CD3 expression among latently infected cells suggest increased survival potential and capacity to respond to T cell receptor stimulation. These findings point to a large pool of latently infected CD4+ T cells established very early in acute infection and upregulated host factors that may facilitate their persistence in vivo, both of which pose potential challenges to eliminating HIV-1 reservoirs. IMPORTANCE Effective combination antiretroviral therapy controls HIV-1 infection but fails to eliminate latent viral reservoirs that give rise to viremia upon treatment interruption. Strategies to eradicate latently infected cells require a better understanding of their biology and distinguishing features to promote their elimination. Tools for studying these cells from patients are currently limited. Here, we developed a single-cell method to identify cells latently infected in vivo and to characterize these cells for expression of surface proteins and host genes without in vitro manipulation, capturing their in vivo state from SIV-infected macaques. Host factors involved in cell survival and proliferation were upregulated in latently infected cells, which were abundant in the earliest stages of acute infection. These studies provide insight into the basic biology of latently infected cells as well as potential mechanisms underlying the persistence of HIV-1/SIV reservoirs to inform development of novel HIV-1 cure strategies.

Cerebrospinal fluid CD4+ T cell infection in humans and macaques during acute HIV-1 and SHIV infection

HIV-1 replication within the central nervous system (CNS) impairs neurocognitive function and has the potential to establish persistent, compartmentalized viral reservoirs. The origins of HIV-1 detected in the CNS compartment are unknown, including whether cells within the cerebrospinal fluid (CSF) produce virus. We measured viral RNA+ cells in CSF from acutely infected macaques longitudinally and people living with early stages of acute HIV-1. Active viral transcription (spliced viral RNA) was present in CSF CD4+ T cells as early as four weeks post-SHIV infection, and among all acute HIV-1 specimens (N = 6; Fiebig III/IV). Replication-inactive CD4+ T cell infection, indicated by unspliced viral RNA in the absence of spliced viral RNA, was even more prevalent, present in CSF of >50% macaques and human CSF at ~10-fold higher frequency than productive infection. Infection levels were similar between CSF and peripheral blood (and lymph nodes in macaques), indicating comparable T cell infection across these compartments. In addition, surface markers of activation were increased on CSF T cells and monocytes and correlated with CSF soluble markers of inflammation. These studies provide direct evidence of HIV-1 replication in CD4+ T cells and broad immune activation in peripheral blood and the CNS during acute infection, likely contributing to early neuroinflammation and reservoir seeding. Thus, early initiation of antiretroviral therapy may not be able to prevent establishment of CNS viral reservoirs and sources of long-term inflammation, important targets for HIV-1 cure and therapeutic strategies.

Neurological pathologies are associated with HIV-1 infection and remain common in the ongoing AIDS epidemic. Despite the advent of successful viremia suppression by anti-retroviral therapy, increased life expectancies and co-morbidities have led to higher prevalence of milder forms of neurocognitive dysfunction. How HIV-1 causes neurocognitive dysfunction is currently unclear, though it is widely believed that viral replication within the central nervous system (CNS) prior to therapy triggers these detrimental processes. The appearance of HIV-1 in the cerebrospinal fluid during the earliest stages of infection suggests that these processes may begin very early. Here, we use novel techniques to probe cells for viral infection during the first few weeks of infection in the CNS of humans and animals to determine the source of this virus. We found HIV-1 replication in T cells in the cerebrospinal fluid during this early window. In addition, infected T cells were present at similar frequencies in the CNS and other anatomic compartments, suggesting equilibration of T cell infection levels across these sites and potential for establishment of long-term reservoirs in the CNS. Our study provides new insights to the early events of viral entry and replication in the CNS with implications for subsequent viral persistence and neuronal injury.

Single-Cell Analysis Reveals Heterogeneity of Virus Infection, Pathogenicity, and Host Responses: HIV as a Pioneering Example

While analyses of cell populations provide averaged information about viral infections, single-cell analyses offer individual consideration, thereby revealing a broad spectrum of diversity as well as identifying extreme phenotypes that can be exploited to further understand the complex virus-host interplay. Single-cell technologies applied in the context of human immunodeficiency virus (HIV) infection proved to be valuable tools to help uncover specific biomarkers as well as novel candidate players in virus-host interactions. This review aims at providing an updated overview of single-cell analyses in the field of HIV and acquired knowledge on HIV infection, latency, and host response. Although HIV is a pioneering example, similar single-cell approaches have proven to be valuable for elucidating the behavior and virus-host interplay in a range of other viruses.

Preferential Infection of α4β7+ Memory CD4+ T Cells During Early Acute Human Immunodeficiency Virus Type 1 Infection

BACKGROUND

Establishment of persistent human immunodeficiency virus type 1 (HIV-1) reservoirs occurs early in infection, and biomarkers of infected CD4+ T cells during acute infection are poorly defined. CD4+ T cells expressing the gut homing integrin complex α4β7 are associated with HIV-1 acquisition, and are rapidly depleted from the periphery and gastrointestinal mucosa during acute HIV-1 infection.

METHODS

Integrated HIV-1 DNA was quantified in peripheral blood mononuclear cells obtained from acutely (Fiebig I-III) and chronically infected individuals by sorting memory CD4+ T-cell subsets lacking or expressing high levels of integrin β7 (β7negative and β7high, respectively). HIV-1 DNA was also assessed after 8 months of combination antiretroviral therapy (cART) initiated in Fiebig II/III individuals. Activation marker and chemokine receptor expression was determined for β7-defined subsets at acute infection and in uninfected controls.

RESULTS

In Fiebig I, memory CD4+ T cells harboring integrated HIV-1 DNA were rare in both β7high and β7negative subsets, with no significant difference in HIV-1 DNA copies. In Fiebig stages II/III and in chronically infected individuals, β7high cells were enriched in integrated and total HIV-1 DNA compared to β7negative cells. During suppressive cART, integrated HIV-1 DNA copies decreased in both β7negative and β7high subsets, which did not differ in DNA copies. In Fiebig II/III, integrated HIV-1 DNA in β7high cells was correlated with their activation.

CONCLUSIONS

β7high memory CD4+ T cells are preferential targets during early HIV-1 infection, which may be due to the increased activation of these cells.

Plasmacytoid dendritic cells sense HIV replication before detectable viremia following treatment interruption

Plasmacytoid dendritic cells (pDCs) are robust producers of IFNα and one of the first immune cells to respond to SIV infection. To elucidate responses to early HIV-1 replication, we studied blood pDCs in 29 HIV-infected participants who initiated antiretroviral therapy during acute infection and underwent analytic treatment interruption (ATI). We observed an increased frequency of partially activated pDCs in the blood before detection of HIV RNA. Concurrent with peak pDC frequency, we detected a transient decline in the ability of pDCs to produce IFNα in vitro, which correlated with decreased phosphorylation of IFN regulatory factory 7 (IRF7) and NF-κB. The levels of phosphorylated IRF7 and NF-κB inversely correlated with plasma IFNα2 levels, implying that pDCs were refractory to in vitro stimulation after IFNα production in vivo. After ATI, decreased expression of IFN genes in pDCs inversely correlated with the time to viral detection, suggesting that pDC IFN loss is part of an effective early immune response. These data from a limited cohort provide a critical first step in understanding the earliest immune response to HIV-1 and suggest that changes in blood pDC frequency and function can be used as an indicator of viral replication before detectable plasma viremia.

Staphylococcus epidermidis Boosts Innate Immune Response by Activation of Gamma Delta T Cells and Induction of Perforin-2 in Human Skin

Perforin-2 (P-2) is an antimicrobial protein with unique properties to kill intracellular bacteria. Gamma delta (GD) T cells, as the major T cell population in epithelial tissues, play a central role in protective and pathogenic immune responses in the skin. However, the tissue-specific mechanisms that control the innate immune response and the effector functions of GD T cells, especially the cross-talk with commensal organisms, are not very well understood. We hypothesized that the most prevalent skin commensal microorganism, Staphylococcus epidermidis, may play a role in regulating GD T cell-mediated cutaneous responses. We analyzed antimicrobial protein P-2 expression in human skin at a single cell resolution using an amplified fluorescence in situ hybridization approach to detect P-2 mRNA in combination with immunophenotyping. We show that S. epidermidis activates GD T cells and upregulates P-2 in human skin ex vivo in a cell-specific manner. Furthermore, P-2 upregulation following S. epidermidis stimulation correlates with increased ability of skin cells to kill intracellular Staphylococcus aureus. Our findings are the first to reveal that skin commensal bacteria induce P-2 expression, which may be utilized beneficially to modulate host innate immune responses and protect from skin infections.

Monocyte and CD4+ T-cell antiviral and innate responses associated with HIV-1 inflammation and cognitive impairment

OBJECTIVE

Mechanisms underlying immune activation and HIV-associated neurocognitive disorders (HAND) in untreated chronic infection remain unclear. The objective of this study was to identify phenotypic and transcriptional changes in blood monocytes and CD4 T cells in HIV-1-infected and uninfected individuals and elucidate processes associated with neurocognitive impairment.

DESIGN

A group of chronically HIV-1-infected Thai individuals (n = 19) were selected for comparison with healthy donor controls (n = 10). Infected participants were further classified as cognitively normal (n = 10) or with HAND (n = 9). Peripheral monocytes and CD4 T cells were phenotyped by flow cytometry and simultaneously isolated for multiplex qPCR-targeted gene expression profiling directly ex vivo. The frequency of HIV-1 RNA-positive cells was estimated by limiting dilution cell sorting.

RESULTS

Expression of genes and proteins involved in cellular activation and proinflammatory immune responses was increased in monocytes and CD4 T cells from HIV-1-infected relative to uninfected individuals. Gene expression profiles of both CD4 T cells and monocytes correlated with soluble markers of inflammation in the periphery (P < 0.05). By contrast, only modest differences in gene programs were observed between cognitively normal and HAND cases. These included increased monocyte surface CD169 protein expression relative to cognitively normal (P = 0.10), decreased surface CD163 expression relative to uninfected (P = 0.02) and cognitively normal (P = 0.06), and downregulation of EMR2 (P = 0.04) and STAT1 (P = 0.02) relative to cognitively normal.

CONCLUSION

Our data support a model of highly activated monocytes and CD4 T cells associated with inflammation in chronic HIV-1 infection, but impaired monocyte anti-inflammatory responses in HAND compared with cognitively normal.

Single-Cell Technologies Applied to HIV-1 Research: Reaching Maturity

The need for definitive answers probably explains our natural tendency to seek simplicity. The reductionist “bulk” approach, in which a mean behavior is attributed to a heterogeneous cell population, fulfills this need by considerably helping the conceptualization of complex biological processes. However, the limits of this methodology are becoming increasingly clear as models seek to explain biological events occurring in vivo, where heterogeneity is the rule. Research in the HIV-1 field is no exception: the challenges encountered in the development of preventive and curative anti-HIV-1 strategies may well originate in part from inadequate assumptions built on bulk technologies, highlighting the need for new perspectives. The emergence of diverse single-cell technologies set the stage for potential breakthrough discoveries, as heterogeneous processes can now be investigated with an unprecedented depth in topics as diverse as HIV-1 tropism, dynamics of the replication cycle, latency, viral reservoirs and immune control. In this review, we summarize recent advances in the HIV-1 field made possible by single-cell technologies, and contextualize their importance.

Single-Cell Analysis of Quiescent HIV Infection Reveals Host Transcriptional Profiles that Regulate Proviral Latency

A detailed understanding of the mechanisms that establish or maintain the latent reservoir of HIV will guide approaches to eliminate persistent infection. We used a cell line and primary cell models of HIV latency to investigate viral RNA (vRNA) expression and the role of the host transcriptome using single-cell approaches. Single-cell vRNA quantitation identified distinct populations of cells expressing various levels of vRNA, including completely silent populations. Strikingly, single-cell RNA-seq of latently infected primary cells demonstrated that HIV downregulation occurred in diverse transcriptomic environments but was significantly associated with expression of a specific set of cellular genes. In particular, latency was more frequent in cells expressing a transcriptional signature that included markers of naive and central memory T cells. These data reveal that expression of HIV proviruses within the latent reservoir are influenced by the host cell transcriptional program. Therapeutic modulation of these programs may reverse or enforce HIV latency.

High-Parameter Single-Cell Analysis

Thousands of transcripts and proteins confer function and discriminate cell types in the body. Using high-parameter technologies, we can now measure many of these markers at once, and multiple platforms are now capable of analysis on a cell-by-cell basis. Three high-parameter single-cell technologies have particular potential for discovering new biomarkers, revealing disease mechanisms, and increasing our fundamental understanding of cell biology. We review these three platforms (high-parameter flow cytometry, mass cytometry, and a new class of technologies called integrated molecular cytometry platforms) in this article. We describe the underlying hardware and instrumentation, the reagents involved, and the limitations and advantages of each platform. We also highlight the emerging field of high-parameter single-cell data analysis, providing an accessible overview of the data analysis process and choice of tools.

Single Cell Profiling Reveals PTEN Overexpression in Influenza-Specific B cells in Aging HIV-infected individuals on Anti-retroviral Therapy

Memory B cells (MBC) respond to secondary antigen challenge to protect against infection and to boost immunity following vaccinations. Despite effective treatment, chronic HIV infection disturbs MBCs by reducing numbers and altering functionality due to hyper-activation and increased apoptosis leading to suboptimal antibody responses against common infectious agents. We used single cell gene expression analysis to evaluate antigen-specific memory B cells in peripheral blood of virally-suppressed HIV-infected individuals and healthy controls stratified by serum H1N1 antibody response 3 weeks post-administration of the seasonal trivalent inactivated influenza vaccine. We used a fluorescent probe to isolate influenza H1N1-specific B cells and a multiplexed and targeted RT-PCR approach to measure expression levels of 96 genes involved in B cell activation and function. Gene profiling revealed a 4-gene predictive signature containing the phosphoinositide-3 kinase (PI3K) inhibitor, PTEN, for identifying antigen-specific MBC from HIV-infected individuals compared to healthy controls. Gene co-expression analysis showed that in addition to overexpression of PTEN, there was increased co-expression of type I interferon-associated genes with PTEN on single cell level in HIV compared to controls. This study highlights the persistent defects in MBC from HIV-infected individuals and points to the PI3K signaling pathway as a target for potential immune intervention.

A deadly dance: the choreography of host-pathogen interactions, as revealed by single-cell technologies

Pathogens have numerous mechanisms by which they replicate within a host, who in turn responds by developing innate and adaptive immune countermeasures to limit disease. The advent of high-content single-cell technologies has facilitated a greater understanding of the properties of host cells harboring infection, the host's pathogen-specific immune responses, and the mechanisms pathogens have evolved to escape host control. Here we review these advances and argue for greater inclusion of higher resolution single-cell technologies into approaches for defining immune evasion mechanisms by pathogens.

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be difficult. To overcome this challenge, a methodology combining indexed flow cytometry and high-throughput multiplexed quantitative polymerase chain reaction (qPCR) was developed. The objective was to identify and characterize simian immunodeficiency virus (SIV)-infected cells present within rhesus macaques. Through quantitation of surface protein by fluorescence-activated cell sorting (FACS) and mRNA by qPCR, virus-infected cells are identified by viral gene expression, which is combined with host gene and protein measurements to create a multidimensional profile. We term the approach, targeted Single-Cell Proteo-transcriptional Evaluation, or tSCEPTRE. To perform the method, viable cells are stained with fluorescent antibodies specific for surface markers used for FACS isolation of a cell subset and/or downstream phenotypic analysis. Single cells are sorted followed by immediate lysis, multiplex reverse transcription (RT), PCR pre-amplification, and high throughput qPCR of up to 96 transcripts. FACS measurements are recorded at the time of sorting and subsequently linked to the gene expression data by well position to create a combined protein and transcriptional profile. To study SIV-infected cells directly ex vivo, cells were identified by qPCR detection of multiple viral RNA species. The combination of viral transcripts and the quantity of each provide a framework for classifying cells into distinct stages of the viral life cycle (e.g., productive versus non-productive). Moreover, tSCEPTRE of SIV⁺ cells were compared to uninfected cells isolated from the same specimen to assess differentially expressed host genes and proteins. The analysis revealed previously unappreciated viral RNA expression heterogeneity among infected cells as well as in vivo SIV-mediated post-transcriptional gene regulation with single-cell resolution. The tSCEPTRE method is relevant for the analysis of any cell population amenable to identification by expression of surface protein marker(s), host or pathogen gene(s), or combinations thereof.

DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis

A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large ’omics’ or systems biology data sets used by teams of analysts working in collaboration. In such instances it is important to ensure all analysts use the same version of a data set for their analyses. Yet, instantiating relational databases and standard operating procedures can be unwieldy, with high "startup" costs and poor adherence to procedures when they deviate substantially from an analyst’s usual work-flow. Ideally a reproducible research work-flow should fit naturally into an individual’s existing work-flow, with minimal disruption. Here, we provide an overview of how we have leveraged popular open source tools, including Bioconductor, Rmarkdown, git version control, R, and specifically R’s package system combined with a new tool DataPackageR, to implement a lightweight reproducible research work-flow for preprocessing large data sets, suitable for sharing among small-to-medium sized teams of computational scientists. Our primary contribution is the DataPackageR tool, which decouples time-consuming data processing from data analysis while leaving a traceable record of how raw data is processed into analysis-ready data sets. The software ensures packaged data objects are properly documented and performs checksum verification of these along with basic package version management, and importantly, leaves a record of data processing code in the form of package vignettes. Our group has implemented this work-flow to manage, analyze and report on pre-clinical immunological trial data from multi-center, multi-assay studies for the past three years.

Rapid HIV RNA rebound after antiretroviral treatment interruption in persons durably suppressed in Fiebig I acute HIV infection

Antiretroviral therapy during the earliest stage of acute HIV infection (Fiebig I) might minimize establishment of a latent HIV reservoir and thereby facilitate viremic control after analytical treatment interruption. We show that 8 participants, who initiated treatment during Fiebig I and were treated for a median of 2.8 years, all experienced rapid viral load rebound following analytical treatment interruption, indicating that additional strategies are required to control or eradicate HIV.

DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis

A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large ’omics’ or systems biology data sets used by teams of analysts working in collaboration. In such instances it is important to ensure all analysts use the same version of a data set for their analyses. Yet, instantiating relational databases and standard operating procedures can be unwieldy, with high "startup" costs and poor adherence to procedures when they deviate substantially from an analyst’s usual work-flow. Ideally a reproducible research work-flow should fit naturally into an individual’s existing work-flow, with minimal disruption. Here, we provide an overview of how we have leveraged popular open source tools, including Bioconductor, Rmarkdown, git version control, R, and specifically R’s package system combined with a new tool DataPackageR, to implement a lightweight reproducible research work-flow for preprocessing large data sets, suitable for sharing among small-to-medium sized teams of computational scientists. Our primary contribution is the DataPackageR tool, which decouples time-consuming data processing from data analysis while leaving a traceable record of how raw data is processed into analysis-ready data sets. The software ensures packaged data objects are properly documented and performs checksum verification of these along with basic package version management, and importantly, leaves a record of data processing code in the form of package vignettes. Our group has implemented this work-flow to manage, analyze and report on pre-clinical immunological trial data from multi-center, multi-assay studies for the past three years.

HLA Class I Downregulation by HIV-1 Variants from Subtype C Transmission Pairs

HIV-1 downregulates human leukocyte antigen A (HLA-A) and HLA-B from the surface of infected cells primarily to evade CD8 T cell recognition. HLA-C was thought to remain on the cell surface and bind inhibitory killer immunoglobulin-like receptors, preventing natural killer (NK) cell-mediated suppression. However, a recent study found HIV-1 primary viruses have the capacity to downregulate HLA-C. The goal of this study was to assess the heterogeneity of HLA-A, HLA-B, and HLA-C downregulation among full-length primary viruses from six chronically infected and six newly infected individuals from transmission pairs and to determine whether transmitted/founder variants exhibit common HLA class I downregulation characteristics. We measured HLA-A, HLA-B, HLA-C, and total HLA class I downregulation by flow cytometry of primary CD4 T cells infected with 40 infectious molecular clones. Primary viruses mediated a range of HLA class I downregulation capacities (1.3- to 6.1-fold) which could differ significantly between transmission pairs. Downregulation of HLA-C surface expression on infected cells correlated with susceptibility to in vitro NK cell suppression of virus release. Despite this, transmitted/founder variants did not share a downregulation signature and instead were more similar to the quasispecies of matched donor partners. These data indicate that a range of viral abilities to downregulate HLA-A, HLA-B, and HLA-C exist within and between individuals that can have functional consequences on immune recognition.IMPORTANCE Subtype C HIV-1 is the predominant subtype involved in heterosexual transmission in sub-Saharan Africa. Authentic subtype C viruses that contain natural sequence variations throughout the genome often are not used in experimental systems due to technical constraints and sample availability. In this study, authentic full-length subtype C viruses, including transmitted/founder viruses, were examined for the ability to disrupt surface expression of HLA class I molecules, which are central to both adaptive and innate immune responses to viral infections. We found that the HLA class I downregulation capacity of primary viruses varied, and HLA-C downregulation capacity impacted viral suppression by natural killer cells. Transmitted viruses were not distinct in the capacity for HLA class I downregulation or natural killer cell evasion. These results enrich our understanding of the phenotypic variation existing among natural HIV-1 viruses and how that might impact the ability of the immune system to recognize infected cells in acute and chronic infection.

Visualizing the Immune System: Providing Key Insights into HIV/SIV Infections

Immunological inductive tissues, such as secondary lymphoid organs, are composed of distinct anatomical microenvironments for the generation of immune responses to pathogens and immunogens. These microenvironments are characterized by the compartmentalization of highly specialized immune and stromal cell populations, as well as the presence of a complex network of soluble factors and chemokines that direct the intra-tissue trafficking of naïve and effector cell populations. Imaging platforms have provided critical contextual information regarding the molecular and cellular interactions that orchestrate the spatial microanatomy of relevant cells and the development of immune responses against pathogens. Particularly in HIV/SIV disease, imaging technologies are of great importance in the investigation of the local interplay between the virus and host cells, with respect to understanding viral dynamics and persistence, immune responses (i.e., adaptive and innate inflammatory responses), tissue structure and pathologies, and changes to the surrounding milieu and function of immune cells. Merging imaging platforms with other cutting-edge technologies could lead to novel findings regarding the phenotype, function, and molecular signatures of particular immune cell targets, further promoting the development of new antiviral treatments and vaccination strategies.

Beyond the replication-competent HIV reservoir: transcription and translation-competent reservoirs

Recent years have seen a substantial increase in the number of tools available to monitor and study HIV reservoirs. Here, we discuss recent technological advances that enable an understanding of reservoir dynamics beyond classical assays to measure the frequency of cells containing provirus able to propagate a spreading infection (replication-competent reservoir). Specifically, we focus on the characterization of cellular reservoirs containing proviruses able to transcribe viral mRNAs (so called transcription-competent) and translate viral proteins (translation-competent). We suggest that the study of these alternative reservoirs provides complementary information to classical approaches, crucially at a single-cell level. This enables an in-depth characterization of the cellular reservoir, both following reactivation from latency and, importantly, directly ex vivo at baseline. Furthermore, we propose that the study of cellular reservoirs that may not contain fully replication-competent virus, but are able to produce HIV mRNAs and proteins, is of biological importance. Lastly, we detail some of the key contributions that the study of these transcription and translation-competent reservoirs has made thus far to investigations into HIV persistence, and outline where these approaches may take the field next.

What do we measure when we measure cell-associated HIV RNA

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.