| 1. |
- Baumgartner, Stefan, et al.
(författare)
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The discoidin domain family revisited : new members from prokaryotes and a homology-based fold prediction
- 1998
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Ingår i: Protein Science. - : Wiley. - 0961-8368 .- 1469-896X. ; 7:7, s. 31-1626
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Tidskriftsartikel (refereegranskat)abstract
- Members of the discoidin (DS) domain family, which includes the C1 and C2 repeats of blood coagulation factors V and VIII, occur in a great variety of eukaryotic proteins, most of which have been implicated in cell-adhesion or developmental processes. So far, no three-dimensional structure of a known example of this extracellular module has been determined, limiting the usefulness of identifying a new sequence as member of this family. Here, we present results of a recent search of the protein sequence database for new DS domains using generalized profiles, a sensitive multiple alignment-based search technique. Several previously unrecognized DS domains could be identified by this method, including the first examples from prokaryotic species. More importantly, we present statistical, structural, and functional evidence that the D1 domain of galactose oxidase whose three-dimensional structure has been determined at 1.7 A resolution, is a distant member of this family. Taken together, these findings significantly expand the concept of the DS domain, by extending its taxonomic range and by implying a fold prediction for all its members. The proposed alignment with the galactose oxidase sequence makes it possible to construct homology-based three-dimensional models for the most interesting examples, as illustrated by an accompanying paper on the C1 and C2 domains of factor V.
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| 2. |
- Braun, Bernhard, et al.
(författare)
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Gid9, a second RING finger protein contributes to the ubiquitin ligase activity of the Gid complex required for catabolite degradation
- 2011
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Ingår i: FEBS Letters. - : Wiley. - 0014-5793 .- 1873-3468. ; 585:24, s. 3856-3861
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Tidskriftsartikel (refereegranskat)abstract
- The two major antagonistic pathways of carbon metabolism in cells, glycolysis and gluconeogenesis, are tightly regulated. In the eukaryotic model organism Saccharomyces cerevisiae the switch from gluconeogenesis to glycolysis is brought about by proteasomal degradation of the gluconeogenic enzyme fructose-1,6-bisphosphatase. The ubiquitin ligase responsible for polyubiquitylation of fructose-1,6-bisphosphatase is the Gid complex. This complex consists of seven subunits of which subunit Gid2/Rmd5 contains a RING finger domain providing E3 ligase activity. Here we identify an additional subunit containing a degenerated RING finger, Gid9/Fyv10. This subunit binds to Gid2/Rmd5. A mutation in the degenerated RING finger of Gid9/Fyv10 abolishes polyubiquitylation and degradation of three enzymes specific for gluconeogenesis. Structured summary of protein interactions: Gid2 physically interacts with Gid9 by anti tag coimmunoprecipitation (View interaction) (C) 2011 Federation of European Biochemical Societies.
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| 3. |
- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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| 4. |
- Klionsky, Daniel J., et al.
(författare)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Forskningsöversikt (refereegranskat)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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| 5. |
- MacKay, Craig, et al.
(författare)
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Identification of KIAA1018/FAN1, a DNA Repair Nuclease Recruited to DNA Damage by Monoubiquitinated FANCD2
- 2010
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Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 142:1, s. 65-76
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Tidskriftsartikel (refereegranskat)abstract
- DNA interstrand crosslinks (ICLs) are highly toxic because they block the progression of replisomes. The Fanconi Anemia (FA) proteins, encoded by genes that are mutated in FA, are important for repair of ICLs. The FA core complex catalyzes the monoubiquitination of FANCD2, and this event is essential for several steps of ICL repair. However, how monoubiquitination of FANCD2 promotes ICL repair at the molecular level is unknown. Here, we describe a highly conserved protein, KIAA1018/MTMR15/FAN1, that interacts with, and is recruited to sites of DNA damage by, the monoubiquitinated form of FANCD2. FAN1 exhibits endonuclease activity toward 50 flaps and has 5' exonuclease activity, and these activities are mediated by an ancient VRR_nuc domain. Depletion of FAN1 from human cells causes hypersensitivity to ICLs, defects in ICL repair, and genome instability. These data at least partly explain how ubiquitination of FANCD2 promotes DNA repair.
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| 6. |
- Scelo, Ghislaine, et al.
(författare)
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Genome-wide association study identifies multiple risk loci for renal cell carcinoma.
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10-10), 3p22.1 (rs67311347, P=2.5 × 10-8), 3q26.2 (rs10936602, P=8.8 × 10-9), 8p21.3 (rs2241261, P=5.8 × 10-9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10-8), 11q22.3 (rs74911261, P=2.1 × 10-10) and 14q24.2 (rs4903064, P=2.2 × 10-24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.
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