| 1. |
- Bonnardel, Francois, et al.
(författare)
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Architecture and Evolution of Blade Assembly in beta-propeller Lectins
- 2019
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Ingår i: Structure. - : Elsevier BV. - 0969-2126 .- 1878-4186. ; 27:5, s. 764-
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Tidskriftsartikel (refereegranskat)abstract
- Lectins with a beta-propeller fold bind glycans on the cell surface through multivalent binding sites and appropriate directionality. These proteins are formed by repeats of short domains, raising questions about evolutionary duplication. However, these repeats are difficult to detect in translated genomes and seldom correctly annotated in sequence databases. To address these issues, we defined the blade signature of the five types of beta-propellers using 3D-structural data. With these templates, we predicted 3,887 beta-propeller lectins in 1,889 species and organized this information in a searchable online database. The data reveal a widespread distribution of beta-propeller lectins across species. Prediction also emphasizes multiple architectures and led to the discovery of a beta-propeller assembly scenario. This was confirmed by producing and characterizing a predicted protein coded in the genome of Kordia zhangzhouensis. The crystal structure uncovers an intermediate in the evolution of beta-propeller assembly and demonstrates the power of our tools.
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| 2. |
- Campbell, Matthew P, et al.
(författare)
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Toolboxes for a standardised and systematic study of glycans
- 2014
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Ingår i: BMC Bioinformatics. - 1471-2105. ; 15:Suppl. 1
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Tidskriftsartikel (refereegranskat)abstract
- Abstract Background Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. Methods Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the "objective" difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. Results Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. Conclusions Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics.
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| 3. |
- Horlacher, Oliver, et al.
(författare)
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Glycoforest 1.0.
- 2017
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Ingår i: Analytical chemistry. - : American Chemical Society (ACS). - 1520-6882 .- 0003-2700. ; 89:20, s. 10932-10940
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Tidskriftsartikel (refereegranskat)abstract
- Tandem mass spectrometry, when combined with liquid chromatography and applied to complex mixtures, produces large amounts of raw data, which needs to be analyzed to identify molecular structures. This technique is widely used, particularly in glycomics. Due to a lack of high throughput glycan sequencing software, glycan spectra are predominantly sequenced manually. A challenge for writing glycan-sequencing software is that there is no direct template that can be used to infer structures detectable in an organism. To help alleviate this bottleneck, we present Glycoforest 1.0, a partial de novo algorithm for sequencing glycan structures based on MS/MS spectra. Glycoforest was tested on two data sets (human gastric and salmon mucosa O-linked glycomes) for which MS/MS spectra were annotated manually. Glycoforest generated the human validated structure for 92% of test cases. The correct structure was found as the best scoring match for 70% and among the top 3 matches for 83% of test cases. In addition, the Glycoforest algorithm detected glycan structures from MS/MS spectra missing a manual annotation. In total 1532 MS/MS previously unannotated spectra were annotated by Glycoforest. A portion containing 521 spectra was manually checked confirming that Glycoforest annotated an additional 50 MS/MS spectra overlooked during manual annotation.
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| 4. |
- Jin, Chunsheng, et al.
(författare)
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UniCarb-DB: An MS/MS Experimental Glycomic Fragmentation Database
- 2024
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Ingår i: Methods in molecular biology (Clifton, N.J.). - 1940-6029. ; 2836, s. 77-96
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Tidskriftsartikel (refereegranskat)abstract
- Glycosylation is a unique posttranslational modification that dynamically shapes the surface of cells. Glycans attached to proteins or lipids in a cell or tissue are studied as a whole and collectively designated as a glycome. UniCarb-DB is a glycomic spectral library of tandem mass spectrometry (MS/MS) fragment data. The current version of the database consists of over 1500 entries and over 1000 unique structures. Each entry contains parent ion information with associated MS/MS spectra, metadata about the original publication, experimental conditions, and biological origin. Each structure is also associated with the GlyTouCan glycan structure repository allowing easy access to other glycomic resources. The database can be directly utilized by mass spectrometry (MS) experimentalists through the conversion of data generated by MS into structural information. Flexible online search tools along with a downloadable version of the database are easily incorporated in either commercial or open-access MS software. This chapter highlights UniCarb-DB online search tool to browse differences of isomeric structures between spectra, a peak matching search between user-generated MS/MS spectra and spectra stored in UniCarb-DB and more advanced MS tools for combined quantitative and qualitative glycomics.
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| 5. |
- Mariethoz, Julien, et al.
(författare)
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SugarBindDB, a resource of glycan-mediated host-pathogen interactions.
- 2016
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Ingår i: Nucleic acids research. - : Oxford University Press (OUP). - 1362-4962 .- 0305-1048. ; 44:D1
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Tidskriftsartikel (refereegranskat)abstract
- The SugarBind Database (SugarBindDB) covers knowledge of glycan binding of human pathogen lectins and adhesins. It is a curated database; each glycan-protein binding pair is associated with at least one published reference. The core data element of SugarBindDB is a set of three inseparable components: the pathogenic agent, a lectin/adhesin and a glycan ligand. Each entity (agent, lectin or ligand) is described by a range of properties that are summarized in an entity-dedicated page. Several search, navigation and visualisation tools are implemented to investigate the functional role of glycans in pathogen binding. The database is cross-linked to protein and glycan-relaled resources such as UniProtKB and UniCarbKB. It is tightly bound to the latter via a substructure search tool that maps each ligand to full structures where it occurs. Thus, a glycan-lectin binding pair of SugarBindDB can lead to the identification of a glycan-mediated protein-protein interaction, that is, a lectin-glycoprotein interaction, via substructure search and the knowledge of site-specific glycosylation stored in UniCarbKB. SugarBindDB is accessible at: http://sugarbind.expasy.org.
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| 6. |
- Masseroli, Marco, et al.
(författare)
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Integrated Bio-Search : challenges and trends for the integration, search and comprehensive processing of biological information
- 2014
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Ingår i: BMC Bioinformatics. - 1471-2105. ; 15:S1, s. S2-
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Forskningsöversikt (refereegranskat)abstract
- Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information sources, but also the danger of producing too many solutions for the same problem. Methodological, technological, infrastructural and social aspects appear to be essential for the development of a new generation of best practices and tools. In this paper, we analyse and discuss these aspects from different perspectives, by extending some of the ideas that arose during the NETTAB 2012 Workshop, making reference especially to the European context. First, relevance of using data and software models for the management and analysis of biological data is stressed. Second, some of the most relevant community achievements of the recent years, which should be taken as a starting point for future efforts in this research domain, are presented. Third, some of the main outstanding issues, challenges and trends are analysed. The challenges related to the tendency to fund and create large scale international research infrastructures and public-private partnerships in order to address the complex challenges of data intensive science are especially discussed. The needs and opportunities of Genomic Computing (the integration, search and display of genomic information at a very specific level, e.g. at the level of a single DNA region) are then considered. In the current data and network-driven era, social aspects can become crucial bottlenecks. How these may best be tackled to unleash the technical abilities for effective data integration and validation efforts is then discussed. Especially the apparent lack of incentives for already overwhelmed researchers appears to be a limitation for sharing information and knowledge with other scientists. We point out as well how the bioinformatics market is growing at an unprecedented speed due to the impact that new powerful in silico analysis promises to have on better diagnosis, prognosis, drug discovery and treatment, towards personalized medicine. An open business model for bioinformatics, which appears to be able to reduce undue duplication of efforts and support the increased reuse of valuable data sets, tools and platforms, is finally discussed.
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| 7. |
- Shen, Qiujin, et al.
(författare)
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A targeted proteomics approach reveals a serum protein signature as diagnostic biomarker for resectable gastric cancer
- 2019
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 44, s. 322-333
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gastric cancer (GC) is the third leading cause of cancer death. Early detection is a key factor to reduce its mortality. Methods: We retrospectively collected pre- and postoperative serum samples as well as tumour tissues and adjacent normal tissues from 100 GC patients. Serum samples from non-cancerous patients were served as controls (n = 50). A high-throughput protein detection technology, multiplex proximity extension assays (PEA), was applied to measure levels of over 300 proteins. Alteration of each protein was analysed by univariate analysis. Elastic-net logistic regression was performed to select serum proteins into the diagnostic model. Findings: We identified 19 serum proteins (CEACAM5, CA9, MSLN, CCL20, SCF, TGF-alpha, MMP-1, MMP-10, IGF-1, CDCPI, PPIA, DDAH-1, HMOX-1, FLI1, IL-7, ZBTB-17, APBB1IP, KAZALD-1, and ADAMTS-15) that together distinguish GC cases from controls with a diagnostic sensitivity of 93%, specificity of 100%, and area under receiver operating characteristic curve (AUC) of 0.99 (95% CI: 0.98-1). Moreover, the 19-serum protein signature pro-vided an increased diagnostic capacity in patients at TNMI-II stage (sensitivity 89%, specificity 100%, AUC 0.99) and in patients with high miaosatellite instability (MSI) (91%. 98%, and 0.99) compared to individual proteins. These promising results will inspire a large-scale independent cohort study to be pursued for validating the proposed protein signature. Interpretation: Based on targeted proteomics and elastic-net logistic regression, we identified a 19-serum protein signature which could contribute to clinical GC diagnosis, especially for patients at early stage and those with high MSI. (C) 2019 The Authors. Published by Elsevier B.V.
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| 8. |
- Tiemeyer, Michael, et al.
(författare)
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GlyTouCan: an accessible glycan structure repository.
- 2017
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Ingår i: Glycobiology. - : Oxford University Press (OUP). - 1460-2423 .- 0959-6658. ; 27:10, s. 915-919
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Tidskriftsartikel (refereegranskat)abstract
- Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.
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| 9. |
- Vizcaíno, Juan Antonio, et al.
(författare)
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A community proposal to integrate proteomics activities in ELIXIR
- 2017
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Ingår i: F1000Research. - : F1000 Research Ltd. - 2046-1402. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.
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