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Sökning: WFRF:(Bruening Thomas)

  • Resultat 11-17 av 17
  • Föregående 1[2]
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11.
  • Banse, Pia, et al. (författare)
  • CD81 receptor regions outside the large extracellular loop determine hepatitis C virus entry into hepatoma cells
  • 2018
  • Ingår i: Viruses. - 1999-4915 .- 1999-4915. ; 10:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Hepatitis C virus (HCV) enters human hepatocytes using four essential entry factors, one of which is human CD81 (hCD81). The tetraspanin hCD81 contains a large extracellular loop (LEL), which interacts with the E2 glycoprotein of HCV. The role of the non-LEL regions of hCD81 (intracellular tails, four transmembrane domains, small extracellular loop and intracellular loop) is poorly understood. Here, we studied the contribution of these domains to HCV susceptibility of hepatoma cells by generating chimeras of related tetraspanins with the hCD81 LEL. Our results show that non-LEL regions in addition to the LEL determine susceptibility of cells to HCV. While closely related tetraspanins (X. tropicalis CD81 and D. rerio CD81) functionally complement hCD81 non-LEL regions, distantly related tetraspanins (C. elegans TSP9 amd D. melanogaster TSP96F) do not and tetraspanins with intermediate homology (hCD9) show an intermediate phenotype. Tetraspanin homology and susceptibility to HCV correlate positively. For some chimeras, infectivity correlates with surface expression. In contrast, the hCD9 chimera is fully surface expressed, binds HCV E2 glycoprotein but is impaired in HCV receptor function. We demonstrate that a cholesterol-coordinating glutamate residue in CD81, which hCD9 lacks, promotes HCV infection. This work highlights the hCD81 non-LEL regions as additional HCV susceptibility-determining factors.
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12.
  • Bruening, Janina, et al. (författare)
  • Hepatitis C virus enters liver cells using the CD81 receptor complex proteins calpain-5 and CBLB
  • 2018
  • Ingår i: PLoS Pathogens. - 1553-7366 .- 1553-7374. ; 14:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Hepatitis C virus (HCV) and the malaria parasite Plasmodium use the membrane protein CD81 to invade human liver cells. Here we mapped 33 host protein interactions of CD81 in primary human liver and hepatoma cells using high-resolution quantitative proteomics. In the CD81 protein network, we identified five proteins which are HCV entry factors or facilitators including epidermal growth factor receptor (EGFR). Notably, we discovered calpain-5 (CAPN5) and the ubiquitin ligase Casitas B-lineage lymphoma proto-oncogene B (CBLB) to form a complex with CD81 and support HCV entry. CAPN5 and CBLB were required for a post-binding and pre-replication step in the HCV life cycle. Knockout of CAPN5 and CBLB reduced susceptibility to all tested HCV genotypes, but not to other enveloped viruses such as vesicular stomatitis virus and human coronavirus. Furthermore, Plasmodium sporozoites relied on a distinct set of CD81 interaction partners for liver cell entry. Our findings reveal a comprehensive CD81 network in human liver cells and show that HCV and Plasmodium highjack selective CD81 interactions, including CAPN5 and CBLB for HCV, to invade cells.
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13.
  • Gerold, Gisa, 1979-, et al. (författare)
  • Decoding protein networks during virus entry by quantitative proteomics
  • 2016
  • Ingår i: Virus Research. - : Elsevier. - 0168-1702 .- 1872-7492. ; 218, s. 25-39
  • Tidskriftsartikel (refereegranskat)abstract
    • Virus entry into host cells relies on interactions between viral and host structures including lipids, carbohydrates and proteins. Particularly, protein-protein interactions between viral surface proteins and host proteins as well as secondary host protein-protein interactions play a pivotal role in coordinating virus binding and uptake. These interactions are dynamic and frequently involve multiprotein complexes. In the past decade mass spectrometry based proteomics methods have reached sensitivities and high throughput compatibilities of genomics methods and now allow the reliable quantitation of proteins in complex samples from limited material. As proteomics provides essential information on the biologically active entity namely the protein, including its posttranslational modifications and its interactions with other proteins, it is an indispensable method in the virologist's toolbox. Here we review protein interactions during virus entry and compare classical biochemical methods to study entry with novel technically advanced quantitative proteomics techniques. We highlight the value of quantitative proteomics in mapping functional virus entry networks, discuss the benefits and limitations and illustrate how the methodology will help resolve unsettled questions in virus entry research in the future.
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16.
  • Mavaddat, Nasim, et al. (författare)
  • Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
  • 2015
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 1460-2105. ; 107:5, s. 036-036
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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17.
  • Michailidou, Kyriaki, et al. (författare)
  • Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer
  • 2015
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 47:4, s. 373-U127
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining similar to 14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 x 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
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  • Resultat 11-17 av 17
  • Föregående 1[2]

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