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Comparative host protein interactions with HTLV-1 p30 and HTLV-2 p28: insights into difference in pathobiology of human retroviruses.

ABSTRACT: Human T lymphotropic virus type-1 (HTLV-1) and type 2 (HTLV-2) are closely related human retroviruses, but have unique disease associations. HTLV-1 is the causative agent of an aggressive T-cell leukemia known as adult T-cell leukemia (ATL), HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP), and other inflammatory diseases. HTLV-2 infection has not been clearly associated with any disease condition. Although both viruses can transform T cells in vitro, the HTLV-1 provirus is mainly detected in CD4+ T cells whereas HTLV-2 is mainly detected in CD8+ T cells of infected individuals. HTLV-1 and HTLV-2 encode accessory proteins p30 and p28, respectively, which share partial amino acid homology and are required for viral persistence in vivo. The goal of this study was to identify host proteins interacting with p30 and p28 in order to understand their role in pathogenesis.Affinity-tag purification coupled with mass spectrometric (MS) analyses revealed 42 and 22 potential interacting cellular partners of p30 and p28, respectively. Of these, only three cellular proteins, protein arginine methyltransferase 5 (PRMT5), hnRNP K and 60?S ribosomal protein L8 were detected in both p30 and p28 fractions. To validate the proteomic results, four interacting proteins were selected for further analyses using immunoblot assays. In full agreement with the MS analysis two cellular proteins REG? and NEAF-interacting protein 30 (NIP30) selectively interacted with p30 and not with p28; heterogeneous nuclear ribonucleoprotein H1 (hnRNP H1) bound to p28 and not to p30; and PRMT5 interacted with both p30 and p28. Further studies demonstrated that reduced levels of PRMT5 resulted in decreased HTLV-2 viral gene expression whereas the viral gene expression of HTLV-1 was unchanged.The comparisons of p30 and p28 host protein interaction proteome showed striking differences with some degree of overlap. PRMT5, one of the host proteins that interacted with both p30 and p28 differentially affected HTLV-1 and HTLV-2 viral gene expression suggesting that PRMT5 is involved at different stages of HTLV-1 and HTLV-2 biology. These findings suggest that distinct host protein interaction profiles of p30 and p28 could, in part, be responsible for differences in HTLV-1 and HTLV-2 pathobiology. This study provides new avenues of investigation into mechanisms of viral infection, tropism and persistence.

SUBMITTER: Doueiri R

PROVIDER: S-EPMC3464894 | biostudies-other | 2012 Aug

REPOSITORIES: biostudies-other

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Comparative host protein interactions with HTLV-1 p30 and HTLV-2 p28: insights into difference in pathobiology of human retroviruses.

Doueiri Rami R Anupam Rajaneesh R Kvaratskhelia Mamuka M Green Kari B KB Lairmore Michael D MD Green Patrick L PL

Retrovirology 20120809

<h4>Background</h4>Human T lymphotropic virus type-1 (HTLV-1) and type 2 (HTLV-2) are closely related human retroviruses, but have unique disease associations. HTLV-1 is the causative agent of an aggressive T-cell leukemia known as adult T-cell leukemia (ATL), HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP), and other inflammatory diseases. HTLV-2 infection has not been clearly associated with any disease condition. Although both viruses can transform T cells in vitro, the HT ...[more]

PMID: 22876852

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Project description:BackgroundHuman T-cell leukemia viruses (HTLV) tend to induce some fatal human diseases like Adult T-cell Leukemia (ATL) by targeting human T lymphocytes. To indentify the protein-protein interactions (PPI) between HTLV viruses and Homo sapiens is one of the significant approaches to reveal the underlying mechanism of HTLV infection and host defence. At present, as biological experiments are labor-intensive and expensive, the identified part of the HTLV-human PPI networks is rather small. Although recent years have witnessed much progress in computational modeling for reconstructing pathogen-host PPI networks, data scarcity and data unavailability are two major challenges to be effectively addressed. To our knowledge, no computational method for proteome-wide HTLV-human PPI networks reconstruction has been reported.ResultsIn this work we develop Multi-instance Adaboost method to conduct homolog knowledge transfer for computationally reconstructing proteome-wide HTLV-human PPI networks. In this method, the homolog knowledge in the form of gene ontology (GO) is treated as auxiliary homolog instance to address the problems of data scarcity and data unavailability, while the potential negative knowledge transfer is automatically attenuated by AdaBoost instance reweighting. The cross validation experiments show that the homolog knowledge transfer in the form of independent homolog instances can effectively enrich the feature information and substitute for the missing GO information. Moreover, the independent tests show that the method can validate 70.3% of the recently curated interactions, significantly exceeding the 2.1% recognition rate by the HT-Y2H experiment. We have used the method to reconstruct the proteome-wide HTLV-human PPI networks and further conducted gene ontology based clustering of the predicted networks for further biomedical research. The gene ontology based clustering analysis of the predictions provides much biological insight into the pathogenesis of HTLV retroviruses.ConclusionsThe Multi-instance AdaBoost method can effectively address the problems of data scarcity and data unavailability for the proteome-wide HTLV-human PPI interaction networks reconstruction. The gene ontology based clustering analysis of the predictions reveals some important signaling pathways and biological modules that HTLV retroviruses are likely to target.

Project description:Physical interactions between viral and host proteins are responsible for almost all aspects of the viral life cycle and the host's immune response. Studying viral-host protein-protein interactions is thus crucial for identifying strategies for treatment and prevention of viral infection. Here, we use high-throughput yeast two-hybrid and affinity purification followed by mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of both binary and co-complex interactions. We report a total of 739 high-confidence interactions, showing the highest overlap of interaction partners among published datasets as well as the highest overlap with genes differentially expressed in samples (such as upper airway and bronchial epithelial cells) from patients with SARS-CoV-2 infection. Showcasing the utility of our network, we describe a novel interaction between the viral accessory protein ORF3a and the host zinc finger transcription factor ZNF579 to illustrate a SARS-CoV-2 factor mediating a direct impact on host transcription. Leveraging our interactome, we performed network-based drug screens for over 2,900 FDA-approved/investigational drugs and obtained a curated list of 23 drugs that had significant network proximities to SARS-CoV-2 host factors, one of which, carvedilol, showed promising antiviral properties. We performed electronic health record-based validation using two independent large-scale, longitudinal COVID-19 patient databases and found that carvedilol usage was associated with a significantly lowered probability (17%-20%, P < 0.001) of obtaining a SARS-CoV-2 positive test after adjusting various confounding factors. Carvedilol additionally showed anti-viral activity against SARS-CoV-2 in a human lung epithelial cell line [half maximal effective concentration (EC 50 ) value of 4.1 µM], suggesting a mechanism for its beneficial effect in COVID-19. Our study demonstrates the value of large-scale network systems biology approaches for extracting biological insight from complex biological processes.

Dataset Information

Comparative host protein interactions with HTLV-1 p30 and HTLV-2 p28: insights into difference in pathobiology of human retroviruses.

Publications

Comparative host protein interactions with HTLV-1 p30 and HTLV-2 p28: insights into difference in pathobiology of human retroviruses.

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