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      Phylogenetic Diversity in Core Region of Hepatitis C Virus Genotype 1a as a Factor Associated with Fibrosis Severity in HIV-1-Coinfected Patients

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          Abstract

          High hepatitis C virus (HCV) genetic diversity impacts infectivity/pathogenicity, influencing chronic liver disease progression associated with fibrosis degrees and hepatocellular carcinoma. HCV core protein is crucial in cell-growth regulation and host-gene expression. Liver fibrosis is accelerated by unknown mechanisms in human immunodeficiency virus-1- (HIV-1-) coinfected individuals. We aimed to study whether well-defined HCV-1a core polymorphisms and genetic heterogeneity are related to fibrosis in a highly homogeneous group of interferon-treated HIV-HCV-coinfected patients. Genetic heterogeneity was weighed by Faith's phylogenetic diversity (PD), which has been little studied in HCV. Eighteen HCV/HIV-coinfected patients presenting different liver fibrosis stages before anti-HCV treatment-initiation were recruited. Sampling at baseline and during and after treatment was performed up to 72 weeks. At inter/intrahost level, HCV-1a populations were studied using molecular cloning and Sanger sequencing. Over 400 complete HCV-1a core sequences encompassing 573 positions of C were obtained. Amino acid substitutions found previously at positions 70 and 91 of HCV-1b core region were not observed. However, HCV genetic heterogeneity was higher in mild than in severe fibrosis cases. These results suggest a potential utility of PD as a virus-related factor associated with chronic hepatitis C progression. These observations should be reassessed in larger cohorts to corroborate our findings and assess other potential covariates.

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          Most cited references48

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          Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology.

          Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.
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            Skylign: a tool for creating informative, interactive logos representing sequence alignments and profile hidden Markov models

            Background Logos are commonly used in molecular biology to provide a compact graphical representation of the conservation pattern of a set of sequences. They render the information contained in sequence alignments or profile hidden Markov models by drawing a stack of letters for each position, where the height of the stack corresponds to the conservation at that position, and the height of each letter within a stack depends on the frequency of that letter at that position. Results We present a new tool and web server, called Skylign, which provides a unified framework for creating logos for both sequence alignments and profile hidden Markov models. In addition to static image files, Skylign creates a novel interactive logo plot for inclusion in web pages. These interactive logos enable scrolling, zooming, and inspection of underlying values. Skylign can avoid sampling bias in sequence alignments by down-weighting redundant sequences and by combining observed counts with informed priors. It also simplifies the representation of gap parameters, and can optionally scale letter heights based on alternate calculations of the conservation of a position. Conclusion Skylign is available as a website, a scriptable web service with a RESTful interface, and as a software package for download. Skylign’s interactive logos are easily incorporated into a web page with just a few lines of HTML markup. Skylign may be found at http://skylign.org.
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              Hepatitis C virus infection protein network

              A proteome-wide mapping of interactions between hepatitis C virus (HCV) and human proteins was performed to provide a comprehensive view of the cellular infection. A total of 314 protein–protein interactions between HCV and human proteins was identified by yeast two-hybrid and 170 by literature mining. Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HCV are enriched in highly central and interconnected proteins. A global analysis on the basis of functional annotation highlighted the enrichment of cellular pathways targeted by HCV. A network of proteins associated with frequent clinical disorders of chronically infected patients was constructed by connecting the insulin, Jak/STAT and TGFβ pathways with cellular proteins targeted by HCV. CORE protein appeared as a major perturbator of this network. Focal adhesion was identified as a new function affected by HCV, mainly by NS3 and NS5A proteins.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2017
                12 November 2017
                : 2017
                : 1728456
                Affiliations
                1Instituto de Investigaciones Biomédicas en Retrovirus y Sida (INBIRS), Facultad de Medicina, Universidad de Buenos Aires, Paraguay 2155, Piso 11, C1121ABG Buenos Aires, Argentina
                2Laboratorio de Virología y Genética Molecular (LVGM), Facultad de Ciencias Naturales y Ciencias de la Salud Sede Trelew, Universidad Nacional de la Patagonia San Juan Bosco, 9 de Julio y Belgrano S/N, Chubut, 9100 Trelew, Argentina
                3Consejo Nacional de Investigaciones Científicas y Técnicas, Av. Rivadavia 1917, C1083ACA Buenos Aires, Argentina
                Author notes

                Academic Editor: Fumio Imazeki

                Author information
                http://orcid.org/0000-0001-5110-8773
                Article
                10.1155/2017/1728456
                5702417
                bdf4c386-4927-4bcd-9828-591812fcfc65
                Copyright © 2017 Micaela Parra et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 August 2017
                : 19 October 2017
                Funding
                Funded by: University of Buenos Aires
                Award ID: 20020150100033BA
                Funded by: Argentinean National Scientific and Technical Research Council
                Award ID: PIP-11220110101089
                Categories
                Research Article

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