exploring-m6a-m5c-epitranscriptomes-upon-viral-infection-an-example

Exploring m<sup>6</sup>A and m<sup>5</sup>C Epitranscriptomes upon Viral Infection: an Example with HIV

The role of RNA modifications in biological processes has been the focus of an increasing number of studies in the last few years and is known nowadays as ...

Lausanne University Hospital and University of Lausanne

An essential step of the life cycle of retroviruses is the stable insertion of a copy of their DNA genome into the host cell genome, and lentiviruses are no exception. This integration step, catalyzed by the viral-encoded integrase, ensures long-term expression of the viral genes, thus allowing a productive viral replication and rendering retroviral vectors also attractive for the field of gene therapy. At the same time, this ability to integrate into the host genome raises safety concerns regarding the use of retroviral-based gene therapy vectors, due to the genomic locations of integration sites. The availability of the human genome sequence made possible the analysis of the integration site preferences, which revealed to be nonrandom and retrovirus-specific, i.e. all lentiviruses studied so far favor integration in active transcription units, while other retroviruses have a different integration site distribution. Several mechanisms have been proposed that may influence integration targeting, which include (i) chromatin accessibility, (ii) cell cycle effects, and (iii) tethering proteins. Recent data provide evidence that integration site selection can occur via a tethering mechanism, through the recruitment of the lentiviral integrase by the cellular LEDGF/p75 protein, both proteins being the two major players in lentiviral integration targeting.

Mechanisms governing lentivirus integration site selection.

One of the seven key scientific priorities identified in the road map on HIV cure research is to 'determine the host mechanisms that control HIV replication in the absence of therapy'. This review summarizes the recent work in genomics and in epigenetic control of viral replication that is relevant for this mission.

State of genomics and epigenomics research in the perspective of HIV cure.

Numerous in vitro studies attribute to human TRIM5Î± some modest anti-HIV-1 activity and human population studies suggest some differential effect of TRIM5Î± polymorphisms on disease progression. If the activity of TRIM5Î± were relevant in vivo, it could result in positive selection on the viral capsid. To address this issue, we identified 10 positively selected sites in HIV-1 capsid from multiple viral strains and generated 17 clade B viruses carrying a minor (i.e. low frequency) residue or an alanine at those positions. All recombinant viruses were susceptible to the modest effect of common human TRIM5Î± and allelic variants R136Q, and H419Y; H43Y and G249D TRIM5Î± were generally inactive. Increased sensitivity to TRIM5Î± was observed for some capsid variants, suggesting that minor residues are selected against in human populations. On the other hand, the modest potency of human TRIM5Î± does not translate in escape mutations in the viral capsid.

Susceptibility and adaptation to human TRIM5Î± alleles at positive selected sites in HIV-1 capsid.

Despite effective treatment, HIV is not completely eliminated from the infected organism because of the existence of viral reservoirs. A major reservoir consists of infected resting CD4+ T cells, mostly of memory type, that persist over time due to the stable proviral insertion and a long cellular lifespan. Resting cells do not produce viral particles and are protected from viral-induced cytotoxicity or immune killing. However, these latently infected cells can be reactivated by stochastic events or by external stimuli. The present review focuses on novel genome-wide technologies applied to the study of integration, transcriptome, and proteome characteristics and their recent contribution to the understanding of HIV latency. 

Bioinformatics and HIV latency.

Myeloid cells are key players in the recognition and response of the host against invading viruses. Paradoxically, upon HIV-1 infection, myeloid cells might also promote viral pathogenesis through trans-infection, a mechanism that promotes HIV-1 transmission to target cells via viral capture and storage. The receptor Siglec-1 (CD169) potently enhances HIV-1 trans-infection and is regulated by immune activating signals present throughout the course of HIV-1 infection, such as interferon α (IFNα).

HIV-1 immune activation induces Siglec-1 expression and enhances viral trans-infection in blood and tissue myeloid cells.

Known antiretroviral restriction factors are encoded by genes that are under positive selection pressure, induced during HIV-1 infection, up-regulated by interferons, and/or interact with viral proteins. To identify potential novel restriction factors, we performed genome-wide scans for human genes sharing molecular and evolutionary signatures of known restriction factors and tested the anti-HIV-1 activity of the most promising candidates.

Identification of potential HIV restriction factors by combining evolutionary genomic signatures with functional analyses.

Retroviruses, including the human immunodeficiency virus (HIV), are notorious for two essential steps of their viral replication: reverse transcription and integration. This latter property is considered to be essential for productive replication and ensures the stable long-term insertion of the viral genome sequence in the host chromatin, thereby leading to the life-long association of the virus with the infected cell. Using HIV as a prototypic example, the present review aims to provide an overview of how and where integration occurs, as well as presenting general consequences for both the virus and the infected host. 

The benefits of integration.

Single-cell sequencing technologies, i.e., single cell analysis followed by deep sequencing investigate cellular heterogeneity in many biological settings. It was only in the past year that single-cell sequencing analyses has been applied in the field of virology, providing new ways to explore viral diversity and cell response to viral infection, which are summarized in the present review.

Single-Cell Genomics for Virology.

Studying the effects of HIV infection on the host transcriptome has typically focused on protein-coding genes. However, recent advances in the field of RNA sequencing revealed that long non-coding RNAs (lncRNAs) add an extensive additional layer to the cell's molecular network. Here, we performed transcriptome profiling throughout a primary HIV infection in vitro to investigate lncRNA expression at the different HIV replication cycle processes (reverse transcription, integration and particle production). Subsequently, guilt-by-association, transcription factor and co-expression analysis were performed to infer biological roles for the lncRNAs identified in the HIV-host interplay. Many lncRNAs were suggested to play a role in mechanisms relying on proteasomal and ubiquitination pathways, apoptosis, DNA damage responses and cell cycle regulation. Through transcription factor binding analysis, we found that lncRNAs display a distinct transcriptional regulation profile as compared to protein coding mRNAs, suggesting that mRNAs and lncRNAs are independently modulated. In addition, we identified five differentially expressed lncRNA-mRNA pairs with mRNA involvement in HIV pathogenesis with possible cis regulatory lncRNAs that control nearby mRNA expression and function. Altogether, the present study demonstrates that lncRNAs add a new dimension to the HIV-host interplay and should be further investigated as they may represent targets for controlling HIV replication.

Differential expression of lncRNAs during the HIV replication cycle: an underestimated layer in the HIV-host interplay.

Single-cell sequencing (SCS) has emerged as a valuable tool to study cellular heterogeneity in diverse fields, including virology. By studying the viral and cellular genome and/or transcriptome, the dynamics of viral infection can be investigated at single cell level. Most studies have explored the impact of cell-to-cell variation on the viral life cycle from the point of view of the virus, by analyzing viral sequences, and from the point of view of the cell, mainly by analyzing the cellular host transcriptome. In this review, we will focus on recent studies that use single-cell sequencing to explore viral diversity and cell variability in response to viral replication.

Exploring viral infection using single-cell sequencing.

Cellular permissiveness to HIV infection is highly heterogeneous across individuals. Heterogeneity is also found across CD4+ T cells from the same individual, where only a fraction of cells gets infected. To explore the basis of permissiveness, we performed single-cell RNA-seq analysis of non-infected CD4+ T cells from high and low permissive individuals. Transcriptional heterogeneity translated in a continuum of cell states, driven by T-cell receptor-mediated cell activation and was strongly linked to permissiveness. Proteins expressed at the cell surface and displaying the highest correlation with T cell activation were tested as biomarkers of cellular permissiveness to HIV. FACS sorting using antibodies against several biomarkers of permissiveness led to an increase of HIV cellular infection rates. Top candidate biomarkers included CD25, a canonical activation marker. The combination of CD25 high expression with other candidate biomarkers led to the identification of CD298, CD63 and CD317 as the best biomarkers for permissiveness. CD25highCD298highCD63highCD317high cell population showed an enrichment of HIV-infection of up to 28 fold as compared to the unsorted cell population. The purified hyper-permissive cell subpopulation was characterized by a downregulation of interferon-induced genes and several known restriction factors. Single-cell RNA-seq analysis coupled with functional characterization of cell biomarkers provides signatures of the "HIV-permissive cell".

Single-cell analysis identifies cellular markers of the HIV permissive cell.

Single-cell analyses allow uncovering cellular heterogeneity, not only per se, but also in response to viral infection. Similarly, single cell transcriptome analyses (scRNA-Seq) can highlight specific signatures, identifying cell subsets with particular phenotypes, which are relevant in the understanding of virus-host interactions.

The use of single-cell RNA-Seq to understand virus-host interactions.

Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle toward HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV-infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression.

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells.

Throughout the HIV-1 replication cycle, complex host-pathogen interactions take place in the infected cell, leading to the production of new virions. The virus modulates the host cellular machinery in order to support its life cycle, while counteracting intracellular defense mechanisms. We investigated the dynamic host response to HIV-1 infection by systematically measuring transcriptomic, proteomic, and phosphoproteomic expression changes in infected and uninfected SupT1 CD4+ T cells at five time points of the viral replication process. By means of a Gaussian mixed-effects model implemented in the new R/Bioconductor package TMixClust, we clustered host genes based on their temporal expression patterns. We identified a proteo-transcriptomic gene expression signature of 388 host genes specific for HIV-1 replication. Comprehensive functional analyses of these genes confirmed the previously described roles of some of the genes and revealed novel key virus-host interactions affecting multiple molecular processes within the host cell, including signal transduction, metabolism, cell cycle, and immune system. The results of our analysis are accessible through a freely available, dedicated and user-friendly R/Shiny application, called PEACHi2.0. This resource constitutes a catalogue of dynamic host responses to HIV-1 infection that provides a basis for a more comprehensive understanding of virus-host interactions.

Proteo-Transcriptomic Dynamics of Cellular Response to HIV-1 Infection.

The latent HIV reservoir is generated following HIV infection of activated effector CD4 T cells, which then transition to a memory phenotype. Here, we describe an  method, called QUECEL (iescent ffector ll atency), that mimics this process efficiently and allows production of large numbers of latently infected CD4 T cells. Naïve CD4 T cells were polarized into the four major T cell subsets (Th1, Th2, Th17, and Treg) and subsequently infected with a single-round reporter virus which expressed GFP/CD8a. The infected cells were purified and coerced into quiescence using a defined cocktail of cytokines, including tumor growth factor beta, interleukin-10 (IL-10), and IL-8, producing a homogeneous population of latently infected cells. Flow cytometry and transcriptome sequencing (RNA-Seq) demonstrated that the cells maintained the correct polarization phenotypes and had withdrawn from the cell cycle. Key pathways and gene sets enriched during transition from quiescence to reactivation include E2F targets, GM checkpoint, estrogen response late gene expression, and c-myc targets. Reactivation of HIV by latency-reversing agents (LRAs) closely mimics RNA induction profiles seen in cells from well-suppressed HIV patient samples using the envelope detection of  transcription sequencing (EDITS) assay. Since homogeneous populations of latently infected cells can be recovered, the QUECEL model has an excellent signal-to-noise ratio and has been extremely consistent and reproducible in numerous experiments performed during the last 4 years. The ease, efficiency, and accuracy of the mimicking of physiological conditions make the QUECEL model a robust and reproducible tool to study the molecular mechanisms underlying HIV latency. Current primary cell models for HIV latency correlate poorly with the reactivation behavior of patient cells. We have developed a new model, called QUECEL, which generates a large and homogenous population of latently infected CD4 memory cells. By purifying HIV-infected cells and inducing cell quiescence with a defined cocktail of cytokines, we have eliminated the largest problems with previous primary cell models of HIV latency: variable infection levels, ill-defined polarization states, and inefficient shutdown of cellular transcription. Latency reversal in the QUECEL model by a wide range of agents correlates strongly with RNA induction in patient samples. This scalable and highly reproducible model of HIV latency will permit detailed analysis of cellular mechanisms controlling HIV latency and reactivation.

Entry of Polarized Effector Cells into Quiescence Forces HIV Latency.

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.

Article	Year
Mechanisms governing lentivirus integration site selection. Current gene therapy\| PubMed ID: 19075625	2008
State of genomics and epigenomics research in the perspective of HIV cure. Current opinion in HIV and AIDS\| PubMed ID: 23426238	2013
Susceptibility and adaptation to human TRIM5Î± alleles at positive selected sites in HIV-1 capsid. Virology\| PubMed ID: 23601783	2013
Bioinformatics and HIV latency. Current HIV/AIDS reports\| PubMed ID: 25586146	2015
HIV-1 immune activation induces Siglec-1 expression and enhances viral trans-infection in blood and tissue myeloid cells. Retrovirology\| PubMed ID: 25947229	2015
Identification of potential HIV restriction factors by combining evolutionary genomic signatures with functional analyses. Retrovirology\| PubMed ID: 25980612	2015
The benefits of integration. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases\| PubMed ID: 27107301	2016
Single-Cell Genomics for Virology. Viruses\| PubMed ID: 27153082	2016
Differential expression of lncRNAs during the HIV replication cycle: an underestimated layer in the HIV-host interplay. Scientific reports\| PubMed ID: 27782208	2016
Exploring viral infection using single-cell sequencing. Virus research\| PubMed ID: 27816430	2017
Single-cell analysis identifies cellular markers of the HIV permissive cell. PLoS pathogens\| PubMed ID: 29073251	2017
The use of single-cell RNA-Seq to understand virus-host interactions. Current opinion in virology\| PubMed ID: 29558678	2018
Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells. Cell reports\| PubMed ID: 29694901	2018
Proteo-Transcriptomic Dynamics of Cellular Response to HIV-1 Infection. Scientific reports\| PubMed ID: 30659199	2019
Entry of Polarized Effector Cells into Quiescence Forces HIV Latency. mBio\| PubMed ID: 30914509	2019
Single-Cell Analysis Reveals Heterogeneity of Virus Infection, Pathogenicity, and Host Responses: HIV as a Pioneering Example. Annual review of virology\| PubMed ID: 32991268	2020

Angela Ciuffi

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