Quantitative analysis of the early steps of virus host cell interaction of human immunodeficiency virus type 1 and hepatitis C virus

Viruses are obligatory intracellular pathogens; hence an essential step of their replication cycle is the entry into a host cell. Enveloped viruses like the human immunodeficiency virus type 1 (HIV-1) and the hepatitis C virus (HCV) enter cells by fusion with cellular membranes. The current knowledge of this process relies mostly on bulk measurements, which often comprise the outcome of several distinct replication steps in a non-synchronized manner. The recent development of novel quantitative approaches has opened the door for deeper understanding of the process by analyses on a single cell and single particle level. Fluorescently labelled viruses allow studying single steps in the interaction of individual virions with the host cell. A strategy for labelling HIV-1 with organic dyes using the recently described SNAP-tag was established and evaluated in this thesis. Introduction of the SNAP-tag did not significantly interfere with virus entry and infectivity and allowed specific labelling of the Gag structural polyprotein in the context of virions and virus producing cells. Combining fluorescently labelled HIV-1 with the HCV pseudoparticle system (HCVpp) allowed the analysis of virion attachment and entry dependent on the envelope protein of HCV on a single particle level. In addition, the -Lactamase virion fusion assay was adapted to and optimized for HCVpp, allowing the detection of virus-cell fusion. The dependency of virus particle binding, endocytic uptake and fusion on various stimulating and inhibiting agents was investigated. The virus binding assay developed for HCVpp was subsequently adapted to HIV-1 and revealed cell-type specific kinetics of virion attachment. Interestingly, the expression level of the cellular virion tethering factor CD317 was shown to have no effect on exogenous virus binding. The main part of this thesis aimed at the acquisition and analysis of quantitative multi-parameter data of HIV-1 entry. Besides the receptor CD4, HIV-1 entry depends on the presence of either one of the two major co-receptors, CXCR4 or CCR5. The ability of a virus variant to use a co-receptor defines the tropism of the virus and is at least in part determined by the sequence of the third variable loop (V3-loop) of the viral envelope protein (Env). In summary, HIV entry efficiency is determined by a complex interplay between Env sequence, receptor and co-receptor densities. A deeper insight into the interdependencies of these critical parameters provides a basis for the understanding of the mechanism of action of HIV entry inhibitors as well as of pathways of resistance development against these compounds. Mathematical models describing the interdependencies will also aid in the refinement of algorithms for the genotypic prediction of co-receptor tropism, which is essential for the use of co-receptor antagonists in antiretroviral therapy. Here, experimental systems were developed which allow acquisition of detailed quantitative data on the interdependencies between these parameters as a basis for a mathematical model of the HIV-1 entry process. This comprised the selection and characterization of suitable model cell lines and experimental conditions, the generation and characterization of defined isogenic virus variants and the establishment and calibration of virological assay systems. Multivariant data sets were acquired under standard conditions and algorithms for multivariant data analysis which have been developed in collaboration with bioinformaticians were evaluated. A comprehensive data set was obtained by studying a subset of viruses carrying patient-derived Env variants which revealed quantitative differences in receptor and co-receptor dependency as well as sensitivity to prototype entry inhibitors beyond the overall results of common phenotyping/genotyping methods

Multiple Routes to Oncogenesis Are Promoted by the Human Papillomavirus-Host Protein Network.

We have mapped a global network of virus-host protein interactions by purification of the complete set of human papillomavirus (HPV) proteins in multiple cell lines followed by mass spectrometry analysis. Integration of this map with tumor genome atlases shows that the virus targets human proteins frequently mutated in HPV- but not HPV+ cancers, providing a unique opportunity to identify novel oncogenic events phenocopied by HPV infection. For example, we find that the NRF2 transcriptional pathway, which protects against oxidative stress, is activated by interaction of the NRF2 regulator KEAP1 with the viral protein E1. We also demonstrate that the L2 HPV protein physically interacts with the RNF20/40 histone ubiquitination complex and promotes tumor cell invasion in an RNF20/40-dependent manner. This combined proteomic and genetic approach provides a systematic means to study the cellular mechanisms hijacked by virally induced cancers.Significance: In this study, we created a protein-protein interaction network between HPV and human proteins. An integrative analysis of this network and 800 tumor mutation profiles identifies multiple oncogenesis pathways promoted by HPV interactions that phenocopy recurrent mutations in cancer, yielding an expanded definition of HPV oncogenic roles. Cancer Discov; 8(11); 1474-89. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1333

Interaction between genetic and epigenetic variation defines gene expression patterns at the asthma-associated locus 17q12-q21 in lymphoblastoid cell lines

Phenotypic variation results from variation in gene expression, which is modulated by genetic and/or epigenetic factors. To understand the molecular basis of human disease, interaction between genetic and epigenetic factors needs to be taken into account. The asthma-associated region 17q12-q21 harbors three genes, the zona pellucida binding protein 2 (ZPBP2), gasdermin B (GSDMB) and ORM1-like 3 (ORMDL3), that show allele-specific differences in expression levels in lymphoblastoid cell lines (LCLs) and CD4+ T cells. Here, we report a molecular dissection of allele-specific transcriptional regulation of the genes within the chromosomal region 17q12-q21 combining in vitro transfection, formaldehyde-assisted isolation of regulatory elements, chromatin immunoprecipitation and DNA methylation assays in LCLs. We found that a single nucleotide polymorphism rs4795397 influences the activity of ZPBP2 promoter in vitro in an allele-dependent fashion, and also leads to nucleosome repositioning on the asthma-associated allele. However, variable methylation of exon 1 of ZPBP2 masks the strong genetic effect on ZPBP2 promoter activity in LCLs. In contrast, the ORMDL3 promoter is fully unmethylated, which allows detection of genetic effects on its transcription. We conclude that the cis-regulatory effects on 17q12-q21 gene expression result from interaction between several regulatory polymorphisms and epigenetic factors within the cis-regulatory haplotype region

A SNAP-Tagged Derivative of HIV-1—A Versatile Tool to Study Virus-Cell Interactions

Fluorescently labeled human immunodeficiency virus (HIV) derivatives, combined with the use of advanced fluorescence microscopy techniques, allow the direct visualization of dynamic events and individual steps in the viral life cycle. HIV proteins tagged with fluorescent proteins (FPs) have been successfully used for live-cell imaging analyses of HIV-cell interactions. However, FPs display limitations with respect to their physicochemical properties, and their maturation kinetics. Furthermore, several independent FP-tagged constructs have to be cloned and characterized in order to obtain spectral variations suitable for multi-color imaging setups. In contrast, the so-called SNAP-tag represents a genetically encoded non-fluorescent tag which mediates specific covalent coupling to fluorescent substrate molecules in a self-labeling reaction. Fusion of the SNAP-tag to the protein of interest allows specific labeling of the fusion protein with a variety of synthetic dyes, thereby offering enhanced flexibility for fluorescence imaging approaches

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19

Mass spectrometry-based protein-protein interaction networks for the study of human diseases.

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

Abstract A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications

Mass spectrometry-based protein-protein interaction networks for the study of human diseases.

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications

Comparative mapping of host-pathogen protein-protein interactions.

Pathogens usurp a variety of host pathways via protein-protein interactions to ensure efficient pathogen replication. Despite the existence of an impressive toolkit of systematic and unbiased approaches, we still lack a comprehensive list of these PPIs and an understanding of their functional implications. Here, we highlight the importance of harnessing genetic diversity of hosts and pathogens for uncovering the biochemical basis of pathogen restriction, virulence, fitness, and pathogenesis. We further suggest that integrating physical interaction data with orthogonal types of data will allow researchers to draw meaningful conclusions both for basic and translational science