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- Ignjatovic, Vera, et al.
(författare)
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Mass Spectrometry-Based Plasma Proteomics : Considerations from Sample Collection to Achieving Translational Data
- 2019
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 18:12, s. 4085-4097
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Forskningsöversikt (refereegranskat)abstract
- The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.
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- Lejaeghere, Kurt, et al.
(författare)
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Reproducibility in density functional theory calculations of solids.
- 2016
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 351:6280, s. 1415-1422
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Tidskriftsartikel (refereegranskat)abstract
- The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.
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- Lenz, Tobias L., et al.
(författare)
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Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases
- 2015
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Ingår i: Nature Genetics. - : Macmillan Publishers Ltd.. - 1061-4036 .- 1546-1718. ; 47:9, s. 1085-1090
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Tidskriftsartikel (refereegranskat)abstract
- Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (n(cases) = 5,337), type 1 diabetes (T1D; n(cases) = 5,567), psoriasis vulgaris (n(cases) = 3,089), idiopathic achalasia (n(cases) = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 x 10(-12); T1D, P = 2.4 x 10(-10); psoriasis, P = 5.9 x 10(-6); celiac disease, P = 1.2 x 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 x 10(-3); T1D, P = 8.6 x 10(-27); celiac disease, P = 6.0 x 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.
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- Martins, I, et al.
(författare)
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Anticancer chemotherapy and radiotherapy trigger both non-cell-autonomous and cell-autonomous death
- 2018
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Ingår i: Cell death & disease. - : Springer Science and Business Media LLC. - 2041-4889. ; 9:7, s. 716-
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Tidskriftsartikel (refereegranskat)abstract
- Even though cell death modalities elicited by anticancer chemotherapy and radiotherapy have been extensively studied, the ability of anticancer treatments to induce non-cell-autonomous death has never been investigated. By means of multispectral imaging flow-cytometry-based technology, we analyzed the lethal fate of cancer cells that were treated with conventional anticancer agents and co-cultured with untreated cells, observing that anticancer agents can simultaneously trigger cell-autonomous and non-cell-autonomous death in treated and untreated cells. After ionizing radiation, oxaliplatin, or cisplatin treatment, fractions of treated cancer cell populations were eliminated through cell-autonomous death mechanisms, while other fractions of the treated cancer cells engulfed and killed neighboring cells through non-cell-autonomous processes, including cellular cannibalism. Under conditions of treatment with paclitaxel, non-cell-autonomous and cell-autonomous death were both detected in the treated cell population, while untreated neighboring cells exhibited features of apoptotic demise. The transcriptional activity of p53 tumor-suppressor protein contributed to the execution of cell-autonomous death, yet failed to affect the non-cell-autonomous death by cannibalism for the majority of tested anticancer agents, indicating that the induction of non-cell-autonomous death can occur under conditions in which cell-autonomous death was impaired. Altogether, these results reveal that chemotherapy and radiotherapy can induce both non-cell-autonomous and cell-autonomous death of cancer cells, highlighting the heterogeneity of cell death responses to anticancer treatments and the unsuspected potential contribution of non-cell-autonomous death to the global effects of anticancer treatment.
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- Omenn, G. S., et al.
(författare)
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Progress on Identifying and Characterizing the Human Proteome : 2019 Metrics from the HUPO Human Proteome Project
- 2019
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Ingår i: Journal of Proteome Research. - : American Chemical Society. - 1535-3893 .- 1535-3907. ; 18:12, s. 4098-4107
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Tidskriftsartikel (refereegranskat)abstract
- The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.
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