Network-Based Analysis of OMICs Data to Understand the HIV-Host Interaction

HIV-2 mediated effects on target and bystander cells induce plasma proteome remodeling

Despite low or undetectable plasma viral load, people living with HIV-2 (PLWH2) typically progress toward AIDS. The driving forces behind HIV-2 disease progression and the role of viremia are still not known, but low-level replication in tissues is believed to play a role. To investigate the impact of viremic and aviremic HIV-2 infection on target and bystander cell pathology, we used data-independent acquisition mass spectrometry to determine plasma signatures of tissue and cell type engagement. Proteins derived from target and bystander cells in multiple tissues, such as the gastrointestinal tract and brain, were detected at elevated levels in plasma of PLWH2, compared with HIV negative controls. Moreover, viremic HIV-2 infection appeared to induce enhanced release of proteins from a broader range of tissues compared to aviremic HIV-2 infection. This study expands the knowledge on the link between plasma proteome remodeling and the pathological cell engagement in tissues during HIV-2 infection.

Transcriptome-based analysis of human peripheral blood reveals regulators of immune response in different viral infections

Introduction

There are difficulties in creating direct antiviral drugs for all viruses, including new, suddenly arising infections, such as COVID-19. Therefore, pathogenesis-directed therapy is often necessary to treat severe viral infections and comorbidities associated with them. Despite significant differences in the etiopathogenesis of viral diseases, in general, they are associated with significant dysfunction of the immune system. Study of common mechanisms of immune dysfunction caused by different viral infections can help develop novel therapeutic strategies to combat infections and associated comorbidities.

Methods

To identify common mechanisms of immune functions disruption during infection by nine different viruses (cytomegalovirus, Ebstein-Barr virus, human T-cell leukemia virus type 1, Hepatitis B and C viruses, human immunodeficiency virus, Dengue virus, SARS-CoV, and SARS-CoV-2), we analyzed the corresponding transcription profiles from peripheral blood mononuclear cells (PBMC) using the originally developed pipeline that include transcriptome data collection, processing, normalization, analysis and search for master regulators of several viral infections. The ten datasets containing transcription data from patients infected by nine viruses and healthy people were obtained from Gene Expression Omnibus. The analysis of the data was performed by Genome Enhancer pipeline.

Results

We revealed common pathways, cellular processes, and master regulators for studied viral infections. We found that all nine viral infections cause immune activation, exhaustion, cell proliferation disruption, and increased susceptibility to apoptosis. Using network analysis, we identified PBMC receptors, representing proteins at the top of signaling pathways that may be responsible for the observed transcriptional changes and maintain the current functional state of cells.

Discussion

The identified relationships between some of them and virus-induced alteration of immune functions are new and have not been found earlier, e.g., receptors for autocrine motility factor, insulin, prolactin, angiotensin II, and immunoglobulin epsilon. Modulation of the identified receptors can be investigated as one of therapeutic strategies for the treatment of severe viral infections.

Network for network concept offers new insights into host- SARS-CoV-2 protein interactions and potential novel targets for developing antiviral drugs

SARS-CoV-2, the causal agent of COVID-19, is primarily a pulmonary virus that can directly or indirectly infect several organs. Despite many studies carried out during the current COVID-19 pandemic, some pathological features of SARS-CoV-2 have remained unclear. It has been recently attempted to address the current knowledge gaps on the viral pathogenicity and pathological mechanisms via cellular-level tropism of SARS-CoV-2 using human proteomics, visualization of virus-host protein-protein interactions (PPIs), and enrichment analysis of experimental results. The synergistic use of models and methods that rely on graph theory has enabled the visualization and analysis of the molecular context of virus/host PPIs. We review current knowledge on the SARS-COV-2/host interactome cascade involved in the viral pathogenicity through the graph theory concept and highlight the hub proteins in the intra-viral network that create a subnet with a small number of host central proteins, leading to cell disintegration and infectivity. Then we discuss the putative principle of the "gene-for-gene and "network for network" concepts as platforms for future directions toward designing efficient anti-viral therapies.

Recent Advances in Influenza, HIV and SARS-CoV-2 Infection Prevention and Drug Treatment—The Need for Precision Medicine

Viruses, and in particular, RNA viruses, dominate the WHO’s current list of ten global health threats. Of these, we review the widespread and most common HIV, influenza virus, and SARS-CoV-2 infections, as well as their possible prevention by vaccination and treatments by pharmacotherapeutic approaches. Beyond the vaccination, we discuss the virus-targeting and host-targeting drugs approved in the last five years, in the case of SARS-CoV-2 in the last one year, as well as new drug candidates and lead molecules that have been published in the same periods. We share our views on vaccination and pharmacotherapy, their mutually reinforcing strategic significance in combating pandemics, and the pros and cons of host and virus-targeted drug therapy. The COVID-19 pandemic has provided evidence of our limited armamentarium to fight emerging viral diseases. Novel broad-spectrum vaccines as well as drugs that could even be applied as prophylactic treatments or in early phases of the viremia, possibly through oral administration, are needed in all three areas. To meet these needs, the use of multi-data-based precision medicine in the practice and innovation of vaccination and drug therapy is inevitable.

Cellular Proteo-Transcriptomic Changes in the Immediate Early-Phase of Lentiviral Transduction

Lentivirus-based vectors derived from human immunodeficiency viruses type 1 and 2 (HIV-1 and 2) are widely used tools in research and may also be utilized in clinical settings. Like their parental virions, they are known to depend on the cellular machinery for successful gene delivery and integration. While most of the studies on cellular proteomic and transcriptomic changes have focused on the late phase of the transduction, studies of those changes in early time-points, especially in the case of HIV-2 based vectors, are widely lacking. Using second generation HIV-1 and 2 vesicular stomatitis virus G protein (VSV-G) pseudotyped lentiviral vectors, we transduced HEK-293T human embryonic kidney cells and carried out transcriptomic profiling at 0 and 2 h time points, with accompanying proteomic analysis at 2 h following transduction. Significant variations were observed in gene expression profile between HIV-1 and HIV-2 transduced samples. Thrombospondin 1 (THBS1), collagens (COL1A2, COL3A1), and eukaryotic translation factors (EIF3CL) in addition to various genes coding for long non-coding RNA (lncRNA) were significantly upregulated 2 h after HIV-2 transduction compared to HIV-1. Label-free quantification mass spectrometry (MS) indicated that seven proteins involved in RNA binding, mRNA transport, and chaperoning were significantly downregulated. The identification of cellular protein targets of lentiviral vectors and their effect on the cellular transcriptome will undoubtedly shed more light on their complex life cycle and may be utilized against infection by their parental lentiviruses. Furthermore, characterizing the early phase of HIV-2 infection may aid in the understanding of its pathomechanism and long incubation period.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

HIV-1 Vpr Induces Widespread Transcriptomic Changes in CD4+ T Cells Early Postinfection

The interactions between a virus and its host are complex but can be broadly categorized as either viral manipulation of cellular functions or cellular responses to infection. These processes begin at the earliest point of contact between virus and cell and frequently result in changes to cellular gene expression, making genome-wide transcriptomics a useful tool to study them. Several previous studies have used transcriptomics to evaluate the cellular responses to human immunodeficiency virus type 1 (HIV-1) infection; however, none have examined events in primary CD4+ T cells during the first 24 h of infection. Here, we analyzed CD4+ T cells at 4.5, 8, 12, 24, and 48 h following infection. We describe global changes to host gene expression commencing at 4.5 h postinfection and evolving over the ensuing time points. We identify upregulation of genes related to innate immunity, cytokine production, and apoptosis and downregulation of those involved in transcription and translation. We further demonstrate that the viral accessory protein Vpr is necessary for almost all gene expression changes seen at 12 h postinfection and the majority of those seen at 48 h. Identifying this new role for Vpr not only provides fresh perspective on its possible function but also adds further insight into the interplay between HIV-1 and its host at the cellular level. IMPORTANCE HIV-1, while now treatable, remains an important human pathogen causing significant morbidity and mortality globally. The virus predominantly infects CD4+ T cells and, if not treated with medication, ultimately causes their depletion, resulting in AIDS and death. Further refining our understanding of the interaction between HIV-1 and these cells has the potential to inform further therapeutic development. Previous studies have used transcriptomics to assess gene expression changes in CD4+ T cells following HIV-1 infection; here, we provide a detailed examination of changes occurring in the first 24 h of infection. Importantly, we define the viral protein Vpr as essential for the changes observed at this early stage. This finding has significance for understanding the role of Vpr in infection and pathogenesis and also for interpreting previous transcriptomic analyses of HIV-1 infection.

RHIVDB: A Freely Accessible Database of HIV Amino Acid Sequences and Clinical Data of Infected Patients

Human immunodeficiency virus (HIV) infection remains one of the most severe problems for humanity, particularly due to the development of HIV resistance. To evaluate an association between viral sequence data and drug combinations and to estimate an effect of a particular drug combination on the treatment results, collection of the most representative drug combinations used to cure HIV and the biological data on amino acid sequences of HIV proteins is essential. We have created a new, freely available web database containing 1,651 amino acid sequences of HIV structural proteins [reverse transcriptase (RT), protease (PR), integrase (IN), and envelope protein (ENV)], treatment history information, and CD4+ cell count and viral load data available by the user's query. Additionally, the biological data on new HIV sequences and treatment data can be stored in the database by any user followed by an expert's verification. The database is available on the web at http://www.way2drug.com/rhivdb.

Machine Learning in Discovery of New Antivirals and Optimization of Viral Infections Therapy

Nowadays, computational approaches play an important role in the design of new drug-like compounds and optimization of pharmacotherapeutic treatment of diseases. The emerging growth of viral infections, including those caused by the Human Immunodeficiency Virus (HIV), Ebola virus, recently detected coronavirus, and some others, leads to many newly infected people with a high risk of death or severe complications. A huge amount of chemical, biological, clinical data is at the disposal of the researchers. Therefore, there are many opportunities to find the relationships between the particular features of chemical data and the antiviral activity of biologically active compounds based on machine learning approaches. Biological and clinical data can also be used for building models to predict relationships between viral genotype and drug resistance, which might help determine the clinical outcome of treatment. In the current study, we consider machine-learning approaches in the antiviral research carried out during the past decade. We overview in detail the application of machine-learning methods for the design of new potential antiviral agents and vaccines, drug resistance prediction, and analysis of virus-host interactions. Our review also covers the perspectives of using the machine-learning approaches for antiviral research, including Dengue, Ebola viruses, Influenza A, Human Immunodeficiency Virus, coronaviruses, and some others.

A computational analysis of transcriptional profiles from CD8(+) T lymphocytes reveals potential mechanisms of HIV/AIDS control and progression

Cytotoxic and noncytotoxic CD8+ T lymphocyte responses are essential for the control of HIV infection. Understanding the mechanisms underlying HIV control in elite controllers (ECs), which maintain undetectable viral load in the absence of antiretroviral therapy, may facilitate the development of new effective therapeutic strategies. We developed an original pipeline for an analysis of the transcriptional profiles of CD8+ cells from ECs, treated and untreated progressors. Hierarchical cluster analysis of CD8+ cells' transcription profiles allowed us to identify five distinct groups (EC groups 1-5) of ECs. The transcriptional profiles of EC group 1 were opposite to those of groups 2-4 and similar to those of the treated progressors, which can be associated with residual activation and dysfunction of CD8+ T-lymphocytes. The profiles of groups 2-4 were associated with different numbers of differentially expressed genes compared to healthy controls, but the corresponding genes shared the same cellular processes. These three groups were associated with increased metabolism, survival, proliferation, and the absence of an "exhausted" phenotype, compared to both untreated progressors and healthy controls. The CD8+ lymphocytes from these groups of ECs may contribute to the control under HIV replication and slower disease progression. The EC group 5 was indistinguishable from normal. Application of master regulator analysis allowed us to identify 22 receptors, including interferon-gamma, interleukin-2, and androgen receptors, which may be responsible for the observed expression changes and the functional states of CD8+ cells from ECs. These receptors can be considered potential targets of therapeutic intervention, which may decelerate disease progression.

Interactions of HIV-1 Capsid with Host Factors and Their Implications for Developing Novel Therapeutics

The Human Immunodeficiency Virus type 1 (HIV-1) virion contains a conical shell, termed capsid, encasing the viral RNA genome. After cellular entry of the virion, the capsid is released and ensures the protection and delivery of the HIV-1 genome to the host nucleus for integration. The capsid relies on many virus-host factor interactions which are regulated spatiotemporally throughout the course of infection. In this paper, we will review the current understanding of the highly dynamic HIV-1 capsid-host interplay during the early stages of viral replication, namely intracellular capsid trafficking after viral fusion, nuclear import, uncoating, and integration of the viral genome into host chromatin. Conventional anti-retroviral therapies primarily target HIV-1 enzymes. Insights of capsid structure have resulted in a first-in-class, long-acting capsid-targeting inhibitor, GS-6207 (Lenacapavir). This inhibitor binds at the interface between capsid protein subunits, a site known to bind host factors, interferes with capsid nuclear import, HIV particle assembly, and ordered assembly. Our review will highlight capsid structure, the host factors that interact with capsid, and high-throughput screening techniques, specifically genomic and proteomic approaches, that have been and can be used to identify host factors that interact with capsid. Better structural and mechanistic insights into the capsid-host factor interactions will significantly inform the understanding of HIV-1 pathogenesis and the development of capsid-centric antiretroviral therapeutics.