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Sökning: (AMNE:(Biokemi och molekylärbiologi)) pers:(Uhlen Mathias)

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1.
  • Schwenk, Jochen M., et al. (författare)
  • Toward Next Generation Plasma Profiling via Heat-induced Epitope Retrieval and Array-based Assays
  • 2010
  • Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 9:11, s. 2497-2507
  • Tidskriftsartikel (refereegranskat)abstract
    • There is a need for high throughput methods for screening patient samples in the quest for potential biomarkers for diagnostics and patient care. Here, we used a combination of undirected target selection, antibody suspension bead arrays, and heat-induced epitope retrieval to allow for protein profiling of human plasma in a novel and systematic manner. Several antibodies were found to reveal altered protein profiles upon epitope retrieval at elevated temperatures with limits of detection improving into lower ng/ml ranges. In a study based on prostate cancer patients, several proteins with differential profiles were discovered and subsequently validated in an independent cohort. For one of the potential biomarkers, the human carnosine dipeptidase 1 protein (CNDP1), the differences were determined to be related to the glycosylation status of the targeted protein. The study shows a path of pursuit for large scale screening of biobank repositories in a flexible and proteome-wide fashion by utilizing heat-induced epitope retrieval and using an antibody suspension bead array format. Molecular & Cellular Proteomics 9:2497-2507, 2010.
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2.
  • Gloriam, David E., et al. (författare)
  • A Community Standard Format for the Representation of Protein Affinity Reagents
  • 2010
  • Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 9:1, s. 1-10
  • Tidskriftsartikel (refereegranskat)abstract
    • Protein affinity reagents (PARs), most commonly antibodies, are essential reagents for protein characterization in basic research, biotechnology, and diagnostics as well as the fastest growing class of therapeutics. Large numbers of PARs are available commercially; however, their quality is often uncertain. In addition, currently available PARs cover only a fraction of the human proteome, and their cost is prohibitive for proteome scale applications. This situation has triggered several initiatives involving large scale generation and validation of antibodies, for example the Swedish Human Protein Atlas and the German Antibody Factory. Antibodies targeting specific subproteomes are being pursued by members of Human Proteome Organisation (plasma and liver proteome projects) and the United States National Cancer Institute (cancer-associated antigens). ProteomeBinders, a European consortium, aims to set up a resource of consistently quality-controlled protein-binding reagents for the whole human proteome. An ultimate PAR database resource would allow consumers to visit one online warehouse and find all available affinity reagents from different providers together with documentation that facilitates easy comparison of their cost and quality. However, in contrast to, for example, nucleotide databases among which data are synchronized between the major data providers, current PAR producers, quality control centers, and commercial companies all use incompatible formats, hindering data exchange. Here we propose Proteomics Standards Initiative (PSI)-PAR as a global community standard format for the representation and exchange of protein affinity reagent data. The PSI-PAR format is maintained by the Human Proteome Organisation PSI and was developed within the context of ProteomeBinders by building on a mature proteomics standard format, PSI-molecular interaction, which is a widely accepted and established community standard for molecular interaction data. Further information and documentation are available on the PSI-PAR web site. Molecular & Cellular Proteomics 9: 1-10, 2010.
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3.
  • Jakobsen, Lis, et al. (författare)
  • Novel asymmetrically localizing components of human centrosomes identified by complementary proteomics methods
  • 2011
  • Ingår i: EMBO Journal. - : Wiley. - 0261-4189 .- 1460-2075. ; 30:8, s. 1520-1535
  • Tidskriftsartikel (refereegranskat)abstract
    • Centrosomes in animal cells are dynamic organelles with a proteinaceous matrix of pericentriolar material assembled around a pair of centrioles. They organize the microtubule cytoskeleton and the mitotic spindle apparatus. Mature centrioles are essential for biogenesis of primary cilia that mediate key signalling events. Despite recent advances, the molecular basis for the plethora of processes coordinated by centrosomes is not fully understood. We have combined protein identification and localization, using PCP-SILAC mass spectrometry, BAC transgeneOmics, and antibodies to define the constituents of human centrosomes. From a background of non-specific proteins, we distinguished 126 known and 40 candidate centrosomal proteins, of which 22 were confirmed as novel components. An antibody screen covering 4000 genes revealed an additional 113 candidates. We illustrate the power of our methods by identifying a novel set of five proteins preferentially associated with mother or daughter centrioles, comprising genes implicated in cell polarity. Pulsed labelling demonstrates a remarkable variation in the stability of centrosomal protein complexes. These spatiotemporal proteomics data provide leads to the further functional characterization of centrosomal proteins.
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4.
  • Fagerberg, Linn, et al. (författare)
  • Prediction of the human membrane proteome
  • 2010
  • Ingår i: Proteomics. - : Wiley. - 1615-9853 .- 1615-9861. ; 10:6, s. 1141-1149
  • Tidskriftsartikel (refereegranskat)abstract
    • Membrane proteins are key molecules in the cell, and are important targets for pharmaceutical drugs. Few three-dimensional structures of membrane proteins have been obtained, which makes computational prediction of membrane proteins crucial for studies of these key molecules. Here, seven membrane protein topology prediction methods based on different underlying algorithms, such as hidden Markov models, neural networks and support vector machines, have been used for analysis of the protein sequences from the 21 416 annotated genes in the human genome. The number of genes coding for a protein with predicted cc-helical transmembrane region(s) ranged from 5508 to 7651, depending on the method used. Based on a majority decision method, we estimate 5539 human genes to code for membrane proteins, corresponding to approximately 26% of the human protein-coding genes. The largest fraction of these proteins has only one predicted transmembrane region, but there are also many proteins with seven predicted transmembrane regions, including the G-protein coupled receptors. A visualization tool displaying the topologies suggested by the eight prediction methods, for all predicted membrane proteins, is available on the public Human Protein Atlas portal (www.proteinatlas.org).
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5.
  • Ågren, Rasmus, 1982, et al. (författare)
  • Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling
  • 2014
  • Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 10:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Synopsis Personalized GEMs for six hepatocellular carcinoma patients are reconstructed using proteomics data and a task-driven model reconstruction algorithm. These GEMs are used to predict antimetabolites preventing tumor growth in all patients or in individual patients. The presence of proteins encoded by 15,841 genes in tumors from 27 HCC patients is evaluated by immunohistochemistry. Personalized GEMs for six HCC patients and GEMs for 83 healthy cell types are reconstructed based on HMR 2.0 and the tINIT algorithm for task-driven model reconstruction. 101 antimetabolites are predicted to inhibit tumor growth in all patients. Antimetabolite toxicity is tested using the 83 cell type-specific GEMs. Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.
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6.
  • Uhlén, Mathias, et al. (författare)
  • The human secretome
  • 2019
  • Ingår i: Science Signaling. - : American Association for the Advancement of Science (AAAS). - 1945-0877 .- 1937-9145. ; 12:609
  • Tidskriftsartikel (refereegranskat)abstract
    • The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.
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7.
  • Zhang, C., et al. (författare)
  • The acute effect of metabolic cofactor supplementation: a potential therapeutic strategy against non-alcoholic fatty liver disease
  • 2020
  • Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 16:4
  • Tidskriftsartikel (refereegranskat)abstract
    • The prevalence of non-alcoholic fatty liver disease (NAFLD) continues to increase dramatically, and there is no approved medication for its treatment. Recently, we predicted the underlying molecular mechanisms involved in the progression of NAFLD using network analysis and identified metabolic cofactors that might be beneficial as supplements to decrease human liver fat. Here, we first assessed the tolerability of the combined metabolic cofactors including l-serine, N-acetyl-l-cysteine (NAC), nicotinamide riboside (NR), and l-carnitine by performing a 7-day rat toxicology study. Second, we performed a human calibration study by supplementing combined metabolic cofactors and a control study to study the kinetics of these metabolites in the plasma of healthy subjects with and without supplementation. We measured clinical parameters and observed no immediate side effects. Next, we generated plasma metabolomics and inflammatory protein markers data to reveal the acute changes associated with the supplementation of the metabolic cofactors. We also integrated metabolomics data using personalized genome-scale metabolic modeling and observed that such supplementation significantly affects the global human lipid, amino acid, and antioxidant metabolism. Finally, we predicted blood concentrations of these compounds during daily long-term supplementation by generating an ordinary differential equation model and liver concentrations of serine by generating a pharmacokinetic model and finally adjusted the doses of individual metabolic cofactors for future human clinical trials.
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8.
  • Lam, S., et al. (författare)
  • Addressing the heterogeneity in liver diseases using biological networks
  • 2021
  • Ingår i: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 22:2, s. 1751-1766
  • Tidskriftsartikel (refereegranskat)abstract
    • The abnormalities in human metabolism have been implicated in the progression of several complex human diseases, including certain cancers. Hence, deciphering the underlying molecular mechanisms associated with metabolic reprogramming in a disease state can greatly assist in elucidating the disease aetiology. An invaluable tool for establishing connections between global metabolic reprogramming and disease development is the genome-scale metabolic model (GEM). Here, we review recent work on the reconstruction of cell/tissue-type and cancer-specific GEMs and their use in identifying metabolic changes occurring in response to liver disease development, stratification of the heterogeneous disease population and discovery of novel drug targets and biomarkers. We also discuss how GEMs can be integrated with other biological networks for generating more comprehensive cell/tissue models. In addition, we review the various biological network analyses that have been employed for the development of efficient treatment strategies. Finally, we present three case studies in which independent studies converged on conclusions underlying liver disease.
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9.
  • Lindskog, Cecilia, et al. (författare)
  • The lung-specific proteome defined by integration of transcriptomics and antibody-based profiling
  • 2014
  • Ingår i: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 28:12, s. 5184-5196
  • Tidskriftsartikel (refereegranskat)abstract
    • The combined action of multiple cell types is essential for the physiological function of the lung, and increased awareness of the molecular constituents characterizing each cell type is likely to advance the understanding of lung biology and disease. In the current study, we used genome-wide RNA sequencing of normal lung parenchyma and 26 additional tissue types, combined with antibody-based protein profiling, to localize the expression to specific cell types. Altogether, 221 genes were found to be elevated in the lung compared with their expression in other analyzed tissues. Among the gene products were several well-known markers, but also several proteins previously not described in the context of the lung. To link the lungspecific molecular repertoire to human disease, survival associations of pneumocyte-specific genes were assessed by using transcriptomics data from 7 non-small-cell lung cancer (NSCLC) cohorts. Transcript levels of 10 genes (SFTPB, SFTPC, SFTPD, SLC34A2, LAMP3, CACNA2D2, AGER, EMP2, NKX2-1, and NAPSA) were significantly associated with survival in the adenocarcinoma subgroup, thus qualifying as promising biomarker candidates. In summary, based on an integrated omics approach, we identified genes with elevated expression in lung and localized corresponding protein expression to different cell types. As biomarker candidates, these proteins may represent intriguing starting points for further exploration in health and disease.-Lindskog, C., Fagerberg, L., Hallstrom, B., Edlund, K., Hellwig, B., Rahnenfuhrer, J., Kampf, C., Uhlen, M., Ponten, F., Micke, P. The lung-specific proteome defined by integration of transcriptomics and antibody-based profiling.
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10.
  • Nain-Perez, Amalyn, et al. (författare)
  • Anthraquinone derivatives as ADP-competitive inhibitors of liver pyruvate kinase
  • 2022
  • Ingår i: European Journal of Medicinal Chemistry. - : Elsevier BV. - 0223-5234 .- 1768-3254. ; 234
  • Tidskriftsartikel (refereegranskat)abstract
    • Liver pyruvate kinase (PKL) is a major regulator of metabolic flux and ATP production during liver cell glycolysis and is considered a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). In this study, we report the first ADP-competitive PKL inhibitors and identify several starting points for the further optimization of these inhibitors. Modeling and structural biology guided the optimization of a PKL-specific anthraquinone-based compound. A structure-activity relationship study of 47 novel synthetic derivatives revealed PKL inhibitors with half-maximal inhibitory concentration (IC50) values in the 200 nM range. Despite the difficulty involved in studying a binding site as exposed as the ADP site, these derivatives feature expanded structural diversity and chemical spaces that may be used to improve their inhibitory activities against PKL. The obtained results expand the knowledge of the structural requirements for interactions with the ADP-binding site of PKL.(C) 2022 The Authors. Published by Elsevier Masson SAS.& nbsp;
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