An Atlas of Immune Cell Exhaustion in HIV-Infected Individuals Revealed by Single-Cell Transcriptomics

Abstract

Chronic infection with human immunodeficiency virus (HIV) can cause progressive loss of immune cell function, or exhaustion, which impairs control of virus replication. However, little is known about the development and maintenance, as well as heterogeneity of immune cell exhaustion. Here, we investigated the effects of HIV infection on immune cell exhaustion at the transcriptomic level by analyzing single-cell RNA sequencing of peripheral blood mononuclear cells from two healthy subjects (15,121 cells) and six HIV-infected donors (28,610 cells). We identified nine immune cell clusters and eight T cell subclusters according to their unique gene expression programs; three of these (exhausted CD4 + and CD8 + T cells and interferonresponsive CD8 + T cells) were detected only in samples from HIV-infected donors. An inhibitory receptor KLRG1 was identified in the exhausted T cell populations and further characterized in HIV infected individuals. We identified a novel HIV-1 specific exhausted CD8 + T cell population expressing KLRG1, TIGIT, and T-bet dim Eomes hi markers. Ex-vivo antibody blockade of KLRG1 restored the function of HIV-specific exhausted CD8 + T cells demonstrating the contribution of KLRG1 + population to T cell exhaustion and providing a novel target for developing immunotherapy to treat HIV chronic infection. Analysis of gene signatures also revealed impairment of B cell and NK cell function in HIVinfected donors. These data provide a comprehensive analysis of gene signatures associated with immune cell exhaustion during HIV infection, which could be useful in understanding exhaustion mechanisms and developing new cure therapies. We thank Drs. Doug Richman, Mario Stevenson, and Jon Karn for helpful discussions, Kristen Jepsen at the IGM Genomics Center for help with scRNA-seq, Celsa Spina of UCSD CFAR for flow analysis and members of the Rana lab for helpful discussions and advice. We also thank Dr. Song Chen for advice and help in sample preparation and data analysis.

Interactions of Monocytes, HIV, and ART Identified by an Innovative scRNAseq Pipeline: Pathways to Reservoirs and HIV-Associated Comorbidities

“…They have also used latency-reversing agents and cell lines transfected with virus, having a larger percentage of transcriptionally active cells than is found physiologically. Some groups examined only the total population of cells and did not evaluate differences between the cells harboring virus and those that remained uninfected in studies of host-virus interactions (22,70,(74)(75)(76)(77)(78)(79). In this report, we describe what is, to our knowledge, the first time HIV has been detected by scRNAseq in primary human cells, even with ART, and without use of modifications described above.…”

“…These reservoirs are a major obstacle to eradication and cure of HIV. Recent advances in scRNAseq have been used to examine transcriptional complexities associated with viral infection, viral latency, and cellular components associated with HIV-associated comorbidities (22,70,(74)(75)(76)(77)(78). However, understanding host-HIV interactions at the single-cell level has been a distinct hurdle because only a small percentage of cells harbor HIV, and an even smaller number are transcriptionally active with ART, thus hindering the ability to capture and study reservoirs.…”

Host variation in type I interferon signaling genes (MX1),CCR5Δ32, and MHC class I alleles in treated HIV+ non-controllers predict viral reservoir size

“…These include several SNPs in the MX1 gene, which encodes a potent IFN-induced host restriction factor that is upregulated in HIV-infected compared to uninfected individuals [74] and in HIV-infected participants receiving a toll-like receptor 9 agonist (a potent stimulator of type I IFN) [75, 76]. MX1 has also been associated with higher viremia among HIV-infected individuals [77], HIV-1 persistence in latently infected cell lines [78], immune cell exhaustion [79] and T cell persistence [80]. Genetic variants in two other type I IFN-related genes were statistically significantly associated with HIV total DNA in our study: DDX3X , an X-chromosome-encoded RNA helicase which regulates the production of type I IFNs [51] and PPP1CB , for which the encoded protein regulates the antiviral potency of MX2 [52] (closely related to MX1 which directly inhibits HIV infection prior to integration [52]).…”

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

“…As single cell omics tools are mostly in its naïve stage, thus ample evidences of their application at virus host interface is currently lacking but surely not too far in future which can be easily predicted from the bulk of omics interventions in terms of genomics, transcriptomics, proteomics, metabolomics and interactomics in the current perspective. Other single cell omics techniques have been employed to explore virus-host interaction in recent years (Dhillon and Li, 2015;Labonté et al, 2015;Drayman et al, 2017Drayman et al, , 2019Zanini et al, 2018;Rosenwasser et al, 2019;Russell et al, 2019;Wang S. et al, 2019). However SCM techniques are yet to start contributing significantly in understanding virushost interaction.…”