Publications by authors named "Lars J Jensen"

75 Publications

Human pathways in animal models: possibilities and limitations.

Nucleic Acids Res 2021 02;49(4):1859-1871

Center for non-coding RNA in Technology and Health, University of Copenhagen, 1871 Frederiksberg, Denmark.

Animal models are crucial for advancing our knowledge about the molecular pathways involved in human diseases. However, it remains unclear to what extent tissue expression of pathways in healthy individuals is conserved between species. In addition, organism-specific information on pathways in animal models is often lacking. Within these limitations, we explore the possibilities that arise from publicly available data for the animal models mouse, rat, and pig. We approximate the animal pathways activity by integrating the human counterparts of curated pathways with tissue expression data from the models. Specifically, we compare whether the animal orthologs of the human genes are expressed in the same tissue. This is complicated by the lower coverage and worse quality of data in rat and pig as compared to mouse. Despite that, from 203 human KEGG pathways and the seven tissues with best experimental coverage, we identify 95 distinct pathways, for which the tissue expression in one animal model agrees better with human than the others. Our systematic pathway-tissue comparison between human and three animal modes points to specific similarities with human and to distinct differences among the animal models, thereby suggesting the most suitable organism for modeling a human pathway or tissue.
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http://dx.doi.org/10.1093/nar/gkab012DOI Listing
February 2021

The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets.

Nucleic Acids Res 2021 01;49(D1):D605-D612

Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.

Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein-protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.
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http://dx.doi.org/10.1093/nar/gkaa1074DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779004PMC
January 2021

A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research.

bioRxiv 2020 Nov 5. Epub 2020 Nov 5.

Motivation: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, hostpathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy.

Results: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.

Availability: https://neo4covid19.ncats.io.
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http://dx.doi.org/10.1101/2020.11.04.369041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654851PMC
November 2020

Comparing 22 Popular Phosphoproteomics Pipelines for Peptide Identification and Site Localization.

J Proteome Res 2020 03 4;19(3):1338-1345. Epub 2020 Feb 4.

Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.

Phosphorylation-driven cell signaling governs most biological functions and is widely studied using mass-spectrometry-based phosphoproteomics. Identifying the peptides and localizing the phosphorylation sites within them from the raw data is challenging and can be performed by several algorithms that return scores that are not directly comparable. This increases the heterogeneity among published phosphoproteomics data sets and prevents their direct integration. Here we compare 22 pipelines implemented in the main software tools used for bottom-up phosphoproteomics analysis (MaxQuant, Proteome Discoverer, PeptideShaker). We test six search engines (Andromeda, Comet, Mascot, MS Amanda, SequestHT, and X!Tandem) in combination with several localization scoring algorithms (delta score, D-score, PTM-score, phosphoRS, and Ascore). We show that these follow very different score distributions, which can lead to different false localization rates for the same threshold. We provide a strategy to discriminate correctly from incorrectly localized phosphorylation sites in a consistent manner across the tested pipelines. The results presented here can help users choose the most appropriate pipeline and cutoffs for their phosphoproteomics analysis.
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http://dx.doi.org/10.1021/acs.jproteome.9b00679DOI Listing
March 2020

Oncogenic Mutations Rewire Signaling Pathways by Switching Protein Recruitment to Phosphotyrosine Sites.

Cell 2019 10;179(2):543-560.e26

Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health and Medical Sciences, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark. Electronic address:

Tyrosine phosphorylation regulates multi-layered signaling networks with broad implications in (patho)physiology, but high-throughput methods for functional annotation of phosphotyrosine sites are lacking. To decipher phosphotyrosine signaling directly in tissue samples, we developed a mass-spectrometry-based interaction proteomics approach. We measured the in vivo EGF-dependent signaling network in lung tissue quantifying >1,000 phosphotyrosine sites. To assign function to all EGF-regulated sites, we determined their recruited protein signaling complexes in lung tissue by interaction proteomics. We demonstrated how mutations near tyrosine residues introduce molecular switches that rewire cancer signaling networks, and we revealed oncogenic properties of such a lung cancer EGFR mutant. To demonstrate the scalability of the approach, we performed >1,000 phosphopeptide pulldowns and analyzed them by rapid mass spectrometric analysis, revealing tissue-specific differences in interactors. Our approach is a general strategy for functional annotation of phosphorylation sites in tissues, enabling in-depth mechanistic insights into oncogenic rewiring of signaling networks.
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http://dx.doi.org/10.1016/j.cell.2019.09.008DOI Listing
October 2019

Improving Peptide-Spectrum Matching by Fragmentation Prediction Using Hidden Markov Models.

J Proteome Res 2019 06 22;18(6):2385-2396. Epub 2019 May 22.

Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Science , University of Copenhagen , Blegdamsvej 3B , DK-2200 Copenhagen , Denmark.

Tandem mass spectrometry has become the method of choice for high-throughput, quantitative analysis in proteomics. Peptide spectrum matching algorithms score the concordance between the experimental and the theoretical spectra of candidate peptides by evaluating the number (or proportion) of theoretically possible fragment ions observed in the experimental spectra without any discrimination. However, the assumption that each theoretical fragment is just as likely to be observed is inaccurate. On the contrary, MS2 spectra often have few dominant fragments. Using millions of MS/MS spectra we show that there is high reproducibility across different fragmentation spectra given the precursor peptide and charge state, implying that there is a pattern to fragmentation. To capture this pattern we propose a novel prediction algorithm based on hidden Markov models with an efficient training process. We investigated the performance of our interpolated-HMM model, trained on millions of MS2 spectra, and found that our model picks up meaningful patterns in peptide fragmentation. Second, looking at the variability of the prediction performance by varying the train/test data split, we observed that our model performs well independent of the specific peptides that are present in the training data. Furthermore, we propose that the real value of this model is as a preprocessing step in the peptide identification process. The model can discern fragment ions that are unlikely to be intense for a given candidate peptide rather than using the actual predicted intensities. As such, probabilistic measures of concordance between experimental and theoretical spectra will leverage better statistics.
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http://dx.doi.org/10.1021/acs.jproteome.8b00499DOI Listing
June 2019

Analysis of Predicted Host-Parasite Interactomes Reveals Commonalities and Specificities Related to Parasitic Lifestyle and Tissues Tropism.

Front Immunol 2019 13;10:212. Epub 2019 Feb 13.

Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

The study of molecular host-parasite interactions is essential to understand parasitic infection and adaptation within the host system. As well, prevention and treatment of infectious diseases require a clear understanding of the molecular crosstalk between parasites and their hosts. Yet, large-scale experimental identification of host-parasite molecular interactions remains challenging, and the use of computational predictions becomes then necessary. Here, we propose a computational integrative approach to predict host-parasite protein-protein interaction (PPI) networks resulting from the human infection by 15 different eukaryotic parasites. We used an orthology-based approach to transfer high-confidence intraspecies interactions obtained from the STRING database to the corresponding interspecies homolog protein pairs in the host-parasite system. Our approach uses either the parasites predicted secretome and membrane proteins, or only the secretome, depending on whether they are uni- or multi-cellular, respectively, to reduce the number of false predictions. Moreover, the host proteome is filtered for proteins expressed in selected cellular localizations and tissues supporting the parasite growth. We evaluated the inferred interactions by analyzing the enriched biological processes and pathways in the predicted networks and their association with known parasitic invasion and evasion mechanisms. The resulting PPI networks were compared across parasites to identify common mechanisms that may define a global pathogenic hallmark. We also provided a study case focusing on a closer examination of the human- predicted interactome, detecting central proteins that have relevant roles in the human- network, and identifying tissue-specific interactions with key roles in the life cycle of the parasite. The predicted PPI networks can be visualized and downloaded at http://orthohpi.jensenlab.org.
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http://dx.doi.org/10.3389/fimmu.2019.00212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6381214PMC
January 2020

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Nucleic Acids Res 2019 01;47(D1):D607-D613

Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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http://dx.doi.org/10.1093/nar/gky1131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323986PMC
January 2019

Quantitative metaproteomics of medieval dental calculus reveals individual oral health status.

Nat Commun 2018 11 20;9(1):4744. Epub 2018 Nov 20.

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200, Copenhagen N, Denmark.

The composition of ancient oral microbiomes has recently become accessible owing to advanced biomolecular methods such as metagenomics and metaproteomics, but the utility of metaproteomics for such analyses is less explored. Here, we use quantitative metaproteomics to characterize the dental calculus associated with the remains of 21 humans retrieved during the archeological excavation of the medieval (ca. 1100-1450 CE) cemetery of Tjærby, Denmark. We identify 3671 protein groups, covering 220 bacterial species and 81 genera across all medieval samples. The metaproteome profiles of bacterial and human proteins suggest two distinct groups of archeological remains corresponding to health-predisposed and oral disease-susceptible individuals, which is supported by comparison to the calculus metaproteomes of healthy living individuals. Notably, the groupings identified by metaproteomics are not apparent from the bioarchaeological analysis, illustrating that quantitative metaproteomics has the potential to provide additional levels of molecular information about the oral health status of individuals from archeological contexts.
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http://dx.doi.org/10.1038/s41467-018-07148-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6246597PMC
November 2018

Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data.

J Proteome Res 2019 02 5;18(2):623-632. Epub 2018 Dec 5.

Novo Nordisk Foundation Center for Protein Research , University of Copenhagen , 2200 Copenhagen N, Denmark.

Protein networks have become a popular tool for analyzing and visualizing the often long lists of proteins or genes obtained from proteomics and other high-throughput technologies. One of the most popular sources of such networks is the STRING database, which provides protein networks for more than 2000 organisms, including both physical interactions from experimental data and functional associations from curated pathways, automatic text mining, and prediction methods. However, its web interface is mainly intended for inspection of small networks and their underlying evidence. The Cytoscape software, on the other hand, is much better suited for working with large networks and offers greater flexibility in terms of network analysis, import, and visualization of additional data. To include both resources in the same workflow, we created stringApp, a Cytoscape app that makes it easy to import STRING networks into Cytoscape, retains the appearance and many of the features of STRING, and integrates data from associated databases. Here, we introduce many of the stringApp features and show how they can be used to carry out complex network analysis and visualization tasks on a typical proteomics data set, all through the Cytoscape user interface. stringApp is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/stringapp .
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http://dx.doi.org/10.1021/acs.jproteome.8b00702DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800166PMC
February 2019

eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses.

Nucleic Acids Res 2019 01;47(D1):D309-D314

Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.

eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de.
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http://dx.doi.org/10.1093/nar/gky1085DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324079PMC
January 2019

Role of age, Rho-kinase 2 expression, and G protein-mediated signaling in the myogenic response in mouse small mesenteric arteries.

Physiol Rep 2018 09;6(17):e13863

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Copenhagen, Denmark.

The myogenic response (MR) and myogenic tone (MT) in resistance vessels is crucial for maintaining peripheral vascular resistance and blood flow autoregulation. Development of MT involves G protein-coupled receptors, and may be affected by aging.

Aims: (1) to estimate the mesenteric blood flow in myogenically active small mesenteric arteries; (2) to investigate the signaling from G and/or G activation to MT development; (3) to investigate the role of Rho-kinase 2 and aging on MT in mesenteric resistance arteries.

Methods: we used pressure myography, quantitative real-time PCR, and immunolocalization to study small (<200 μm) mesenteric arteries (SMA) from young, mature adult, and middle aged mice.

Results: Poiseuille flow calculations indicated autoregulation of blood flow at 60-120 mm Hg arterial pressure. G and G were abundantly expressed at the mRNA and protein levels in SMA. The G inhibitor YM-254890 suppressed MT development, and the Phosholipase C inhibitors U73122 and ET-18-OCH3 robustly inhibited it. We found an age-dependent increase in ROCK2 mRNA expression, and in basal MT. The specific ROCK2 inhibitor KD025 robustly inhibited MT in SMAs in all mice with an age-dependent variation in KD025 sensitivity. The inhibitory effect of KD025 was not prevented by the L-type Ca channel activator BayK 8644. KD025 reversibly inhibited MT and endothelin-1 vasoconstriction in small pial arteries from Göttingen minipigs.

Conclusions: MT development in SMAs occurs through a G /PLC/Ca -dependent pathway, and is maintained via ROCK2-mediated Ca sensitization. Increased MT at mature adulthood can be explained by increased ROCK2 expression/activity.
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http://dx.doi.org/10.14814/phy2.13863DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129776PMC
September 2018

Systems-wide Analysis of Serine ADP-Ribosylation Reveals Widespread Occurrence and Site-Specific Overlap with Phosphorylation.

Cell Rep 2018 08;24(9):2493-2505.e4

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark. Electronic address:

ADP-ribosylation (ADPr) is a reversible posttranslational modification involved in a range of cellular processes. Here, we report system-wide identification of serine ADPr in human cells upon oxidative stress. High-resolution mass spectrometry and unrestricted data processing confirm that serine residues are the major target of ADPr in HeLa cells. Proteome-wide analysis identifies 3,090 serine ADPr sites, with 97% of acceptor sites modulating more than 2-fold upon oxidative stress, while treatment with the poly (ADP-ribose) polymerase (PARP) inhibitor olaparib abrogates this induction. Serine ADPr predominantly targets nuclear proteins, while structural-predictive analyses reveal that serine ADPr preferentially targets disordered protein regions. The identified ADP-ribosylated serines significantly overlap with known phosphorylated serines, and large-scale phosphoproteomics analysis provides evidence for site-specific crosstalk between serine ADPr and phosphorylation. Collectively, we demonstrate that serine ADPr is a widespread modification and a major nuclear signaling response to oxidative stress, with a regulatory scope comparable to other extensive posttranslational modifications.
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http://dx.doi.org/10.1016/j.celrep.2018.07.083DOI Listing
August 2018

Site-specific characterization of endogenous SUMOylation across species and organs.

Nat Commun 2018 06 25;9(1):2456. Epub 2018 Jun 25.

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200, Copenhagen, Denmark.

Small ubiquitin-like modifiers (SUMOs) are post-translational modifications that play crucial roles in most cellular processes. While methods exist to study exogenous SUMOylation, large-scale characterization of endogenous SUMO2/3 has remained technically daunting. Here, we describe a proteomics approach facilitating system-wide and in vivo identification of lysines modified by endogenous and native SUMO2. Using a peptide-level immunoprecipitation enrichment strategy, we identify 14,869 endogenous SUMO2/3 sites in human cells during heat stress and proteasomal inhibition, and quantitatively map 1963 SUMO sites across eight mouse tissues. Characterization of the SUMO equilibrium highlights striking differences in SUMO metabolism between cultured cancer cells and normal tissues. Targeting preferences of SUMO2/3 vary across different organ types, coinciding with markedly differential SUMOylation states of all enzymes involved in the SUMO conjugation cascade. Collectively, our systemic investigation details the SUMOylation architecture across species and organs and provides a resource of endogenous SUMOylation sites on factors important in organ-specific functions.
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http://dx.doi.org/10.1038/s41467-018-04957-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018634PMC
June 2018

miRandola 2017: a curated knowledge base of non-invasive biomarkers.

Nucleic Acids Res 2018 01;46(D1):D354-D359

Department of Clinical and Experimental Medicine, University of Catania, Catania, 95125, Italy.

miRandola (http://mirandola.iit.cnr.it/) is a database of extracellular non-coding RNAs (ncRNAs) that was initially published in 2012, foreseeing the relevance of ncRNAs as non-invasive biomarkers. An increasing amount of experimental evidence shows that ncRNAs are frequently dysregulated in diseases. Further, ncRNAs have been discovered in different extracellular forms, such as exosomes, which circulate in human body fluids. Thus, miRandola 2017 is an effort to update and collect the accumulating information on extracellular ncRNAs that is spread across scientific publications and different databases. Data are manually curated from 314 articles that describe miRNAs, long non-coding RNAs and circular RNAs. Fourteen organisms are now included in the database, and associations of ncRNAs with 25 drugs, 47 sample types and 197 diseases. miRandola also classifies extracellular RNAs based on their extracellular form: Argonaute2 protein, exosome, microvesicle, microparticle, membrane vesicle, high density lipoprotein and circulating. We also implemented a new web interface to improve the user experience.
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http://dx.doi.org/10.1093/nar/gkx854DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753291PMC
January 2018

Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer.

Cell Rep 2017 03;18(13):3242-3256

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark. Electronic address:

Our understanding of the molecular determinants of cancer is still inadequate because of cancer heterogeneity. Here, using epithelial ovarian cancer (EOC) as a model system, we analyzed a minute amount of patient-derived epithelial cells from either healthy or cancerous tissues by single-shot mass-spectrometry-based phosphoproteomics. Using a multi-disciplinary approach, we demonstrated that primary cells recapitulate tissue complexity and represent a valuable source of differentially expressed proteins and phosphorylation sites that discriminate cancer from healthy cells. Furthermore, we uncovered kinase signatures associated with EOC. In particular, CDK7 targets were characterized in both EOC primary cells and ovarian cancer cell lines. We showed that CDK7 controls cell proliferation and that pharmacological inhibition of CDK7 selectively represses EOC cell proliferation. Our approach defines the molecular landscape of EOC, paving the way for efficient therapeutic approaches for patients. Finally, we highlight the potential of phosphoproteomics to identify clinically relevant and druggable pathways in cancer.
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http://dx.doi.org/10.1016/j.celrep.2017.03.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382236PMC
March 2017

miRNAs in human subcutaneous adipose tissue: Effects of weight loss induced by hypocaloric diet and exercise.

Obesity (Silver Spring) 2017 03 3;25(3):572-580. Epub 2017 Feb 3.

Xlab, Center for Healthy Aging, Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Objective: Obesity is central in the development of insulin resistance. However, the underlying mechanisms still need elucidation. Dysregulated microRNAs (miRNAs; post-transcriptional regulators) in adipose tissue may present an important link.

Methods: The miRNA expression in subcutaneous adipose tissue from 19 individuals with severe obesity (10 women and 9 men) before and after a 15-week weight loss intervention was studied using genome-wide microarray analysis. The microarray results were validated with RT-qPCR, and pathway enrichment analysis of in silico predicted targets was performed to elucidate the biological consequences of the miRNA dysregulation. Lastly, the messenger RNA (mRNA) and/or protein expression of multiple predicted targets as well as several proteins involved in lipolysis were investigated.

Results: The intervention led to upregulation of miR-29a-3p and miR-29a-5p and downregulation of miR-20b-5p. The mRNA and protein expression of predicted targets was not significantly affected by the intervention. However, negative correlations between miR-20b-5p and the protein levels of its predicted target, acyl-CoA synthetase long-chain family member 1, were observed. Several other miRNA-target relationships correlated negatively, indicating possible miRNA regulation, including miR-29a-3p and lipoprotein lipase mRNA levels. Proteins involved in lipolysis were not affected by the intervention.

Conclusions: Weight loss influenced several miRNAs, some of which were negatively correlated with predicted targets. These dysregulated miRNAs may affect adipocytokine signaling and forkhead box protein O signaling.
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http://dx.doi.org/10.1002/oby.21765DOI Listing
March 2017

Site-specific mapping of the human SUMO proteome reveals co-modification with phosphorylation.

Nat Struct Mol Biol 2017 03 23;24(3):325-336. Epub 2017 Jan 23.

Department of Proteomics, Novo Nordisk Foundation Center for Protein Research (NNF-CPR), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Small ubiquitin-like modifiers (SUMOs) are post-translational modifications (PTMs) that regulate nuclear cellular processes. Here we used an augmented K0-SUMO proteomics strategy to identify 40,765 SUMO acceptor sites and quantify their fractional contribution for 6,747 human proteins. Structural-predictive analyses revealed that lysines residing in disordered regions are preferentially targeted by SUMO, in notable contrast to other widespread lysine modifications. In our data set, we identified 807 SUMOylated peptides that were co-modified by phosphorylation, along with dozens of SUMOylated peptides that were co-modified by ubiquitylation, acetylation and methylation. Notably, 9% of the identified SUMOylome occurred proximal to phosphorylation, and numerous SUMOylation sites were found to be fully dependent on prior phosphorylation events. SUMO-proximal phosphorylation occurred primarily in a proline-directed manner, and inhibition of cyclin-dependent kinases dynamically affected co-modification. Collectively, we present a comprehensive analysis of the SUMOylated proteome, uncovering the structural preferences for SUMO and providing system-wide evidence for a remarkable degree of cross-talk between SUMOylation and other major PTMs.
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http://dx.doi.org/10.1038/nsmb.3366DOI Listing
March 2017

The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Nucleic Acids Res 2017 01 18;45(D1):D362-D368. Epub 2016 Oct 18.

Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland

A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
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http://dx.doi.org/10.1093/nar/gkw937DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210637PMC
January 2017

Metaproteomics of saliva identifies human protein markers specific for individuals with periodontitis and dental caries compared to orally healthy controls.

PeerJ 2016 14;4:e2433. Epub 2016 Sep 14.

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Background: The composition of the salivary microbiota has been reported to differentiate between patients with periodontitis, dental caries and orally healthy individuals. To identify characteristics of diseased and healthy saliva we thus wanted to compare saliva metaproteomes from patients with periodontitis and dental caries to healthy individuals.

Methods: Stimulated saliva samples were collected from 10 patients with periodontitis, 10 patients with dental caries and 10 orally healthy individuals. The proteins in the saliva samples were subjected to denaturing buffer and digested enzymatically with LysC and trypsin. The resulting peptide mixtures were cleaned up by solid-phase extraction and separated online with 2 h gradients by nano-scale C18 reversed-phase chromatography connected to a mass spectrometer through an electrospray source. The eluting peptides were analyzed on a tandem mass spectrometer operated in data-dependent acquisition mode.

Results: We identified a total of 35,664 unique peptides from 4,161 different proteins, of which 1,946 and 2,090 were of bacterial and human origin, respectively. The human protein profiles displayed significant overexpression of the complement system and inflammatory markers in periodontitis and dental caries compared to healthy controls. Bacterial proteome profiles and functional annotation were very similar in health and disease.

Conclusions: Overexpression of proteins related to the complement system and inflammation seems to correlate with oral disease status. Similar bacterial proteomes in healthy and diseased individuals suggests that the salivary microbiota predominantly thrives in a planktonic state expressing no disease-associated characteristics of metabolic activity.
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http://dx.doi.org/10.7717/peerj.2433DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5028799PMC
September 2016

Overview of the interactive task in BioCreative V.

Database (Oxford) 2016 1;2016. Epub 2016 Sep 1.

Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, 19711, USA Department of Computer and Information Sciences, University of Delaware, Newark, DE, 19711, USA

Fully automated text mining (TM) systems promote efficient literature searching, retrieval, and review but are not sufficient to produce ready-to-consume curated documents. These systems are not meant to replace biocurators, but instead to assist them in one or more literature curation steps. To do so, the user interface is an important aspect that needs to be considered for tool adoption. The BioCreative Interactive task (IAT) is a track designed for exploring user-system interactions, promoting development of useful TM tools, and providing a communication channel between the biocuration and the TM communities. In BioCreative V, the IAT track followed a format similar to previous interactive tracks, where the utility and usability of TM tools, as well as the generation of use cases, have been the focal points. The proposed curation tasks are user-centric and formally evaluated by biocurators. In BioCreative V IAT, seven TM systems and 43 biocurators participated. Two levels of user participation were offered to broaden curator involvement and obtain more feedback on usability aspects. The full level participation involved training on the system, curation of a set of documents with and without TM assistance, tracking of time-on-task, and completion of a user survey. The partial level participation was designed to focus on usability aspects of the interface and not the performance per se In this case, biocurators navigated the system by performing pre-designed tasks and then were asked whether they were able to achieve the task and the level of difficulty in completing the task. In this manuscript, we describe the development of the interactive task, from planning to execution and discuss major findings for the systems tested.Database URL: http://www.biocreative.org.
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http://dx.doi.org/10.1093/database/baw119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009325PMC
November 2017

Proteome-wide analysis of arginine monomethylation reveals widespread occurrence in human cells.

Sci Signal 2016 08 30;9(443):rs9. Epub 2016 Aug 30.

Department of Proteomics, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark.

The posttranslational modification of proteins by arginine methylation is functionally important, yet the breadth of this modification is not well characterized. Using high-resolution mass spectrometry, we identified 8030 arginine methylation sites within 3300 human proteins in human embryonic kidney 293 cells, indicating that the occurrence of this modification is comparable to phosphorylation and ubiquitylation. A site-level conservation analysis revealed that arginine methylation sites are less evolutionarily conserved compared to arginines that were not identified as modified by methylation. Through quantitative proteomics and RNA interference to examine arginine methylation stoichiometry, we unexpectedly found that the protein arginine methyltransferase (PRMT) family of arginine methyltransferases catalyzed methylation independently of arginine sequence context. In contrast to the frequency of somatic mutations at arginine methylation sites throughout the proteome, we observed that somatic mutations were common at arginine methylation sites in proteins involved in mRNA splicing. Furthermore, in HeLa and U2OS cells, we found that distinct arginine methyltransferases differentially regulated the functions of the pre-mRNA splicing factor SRSF2 (serine/arginine-rich splicing factor 2) and the RNA transport ribonucleoprotein HNRNPUL1 (heterogeneous nuclear ribonucleoprotein U-like 1). Knocking down PRMT5 impaired the RNA binding function of SRSF2, whereas knocking down PRMT4 [also known as coactivator-associated arginine methyltransferase 1 (CARM1)] or PRMT1 increased the RNA binding function of HNRNPUL1. High-content single-cell imaging additionally revealed that knocking down CARM1 promoted the nuclear accumulation of SRSF2, independent of cell cycle phase. Collectively, the presented human arginine methylome provides a missing piece in the global and integrative view of cellular physiology and protein regulation.
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http://dx.doi.org/10.1126/scisignal.aaf7329DOI Listing
August 2016

Structure-based discovery of novel US28 small molecule ligands with different modes of action.

Chem Biol Drug Des 2017 03 28;89(3):289-296. Epub 2016 Sep 28.

Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.

The human cytomegalovirus-encoded G protein-coupled receptor US28 is a constitutively active receptor, which can recognize various chemokines. Despite the recent determination of its 2.9 Å crystal structure, potent and US28-specific tool compounds are still scarce. Here, we used structural information from a refined US28:VUF2274 complex for virtual screening of >12 million commercially available small molecule compounds. Using a combined receptor- and ligand-based approach, we tested 98 of the top 0.1% ranked compounds, revealing novel chemotypes as compared to the ~1.45 million known ligands in the ChEMBL database. Two compounds were confirmed as agonist and inverse agonist, respectively, in both IP accumulation and Ca mobilization assays. The screening setup presented in this work is computationally inexpensive and therefore particularly useful in an academic setting as it enables simultaneous testing in binding as well as in different functional assays and/or species without actual chemical synthesis.
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http://dx.doi.org/10.1111/cbdd.12848DOI Listing
March 2017

No apparent role for T-type Ca²⁺ channels in renal autoregulation.

Pflugers Arch 2016 Apr 14;468(4):541-50. Epub 2015 Dec 14.

Department of Biomedical Sciences, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200, Copenhagen N, Denmark.

Renal autoregulation protects glomerular capillaries against increases in renal perfusion pressure (RPP). In the mesentery, both L- and T-type calcium channels are involved in autoregulation. L-type calcium channels participate in renal autoregulation, but the role of T-type channels is not fully elucidated due to lack of selective pharmacological inhibitors. The role of T- and L-type calcium channels in the response to acute increases in RPP in T-type channel knockout mice (CaV3.1) and normo- and hypertensive rats was examined. Changes in afferent arteriolar diameter in the kidneys from wild-type and CaV3.1 knockout mice were assessed. Autoregulation of renal blood flow was examined during acute increases in RPP in normo- and hypertensive rats under pharmacological blockade of T- and L-type calcium channels using mibefradil (0.1 μM) and nifedipine (1 μM). In contrast to the results from previous pharmacological studies, genetic deletion of T-type channels CaV3.1 did not affect renal autoregulation. Pharmacological blockade of T-type channels using concentrations of mibefradil which specifically blocks T-type channels also had no effect in wild-type or knockout mice. Blockade of L-type channels significantly attenuated renal autoregulation in both strains. These findings are supported by in vivo studies where blockade of T-type channels had no effect on changes in the renal vascular resistance after acute increases in RPP in normo- and hypertensive rats. These findings show that genetic deletion of T-type channels CaV3.1 or treatment with low concentrations of mibefradil does not affect renal autoregulation. Thus, T-type calcium channels are not involved in renal autoregulation in response to acute increases in RPP.
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http://dx.doi.org/10.1007/s00424-015-1770-9DOI Listing
April 2016

Search Databases and Statistics: Pitfalls and Best Practices in Phosphoproteomics.

Methods Mol Biol 2016 ;1355:323-39

Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, Bldg. 6.2, 2200, Copenhagen, Denmark.

Advances in mass spectrometric instrumentation in the past 15 years have resulted in an explosion in the raw data yield from typical phosphoproteomics workflows. This poses the challenge of confidently identifying peptide sequences, localizing phosphosites to proteins and quantifying these from the vast amounts of raw data. This task is tackled by computational tools implementing algorithms that match the experimental data to databases, providing the user with lists for downstream analysis. Several platforms for such automated interpretation of mass spectrometric data have been developed, each having strengths and weaknesses that must be considered for the individual needs. These are reviewed in this chapter. Equally critical for generating highly confident output datasets is the application of sound statistical criteria to limit the inclusion of incorrect peptide identifications from database searches. Additionally, careful filtering and use of appropriate statistical tests on the output datasets affects the quality of all downstream analyses and interpretation of the data. Our considerations and general practices on these aspects of phosphoproteomics data processing are presented here.
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http://dx.doi.org/10.1007/978-1-4939-3049-4_22DOI Listing
August 2016

From Phosphosites to Kinases.

Methods Mol Biol 2016 ;1355:307-21

Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, Bldg. 6.2, 2200, Copenhagen, Denmark.

Kinases play a pivotal role in propagating the phosphorylation-mediated signaling networks in living cells. With the overwhelming quantities of phosphoproteomics data being generated, the number of identified phosphorylation sites (phosphosites) is ever increasing. Often, proteomics investigations aim to understand the global signaling modulation that takes place in different biological conditions investigated. For phosphoproteomics data, identifying the kinases central to mediating this response is key. This has prompted several efforts to catalogue the immense amounts of phosphorylation data and known or predicted kinases responsible for the modifications. However, barely 20 % of the known phosphosites are assigned to a kinase, initiating various bioinformatics efforts that attempt to predict the responsible kinases. These algorithms employ different approaches to predict kinase consensus sequence motifs, mostly based on large scale in vivo and in vitro experiments. The context of the kinase and the phosphorylated proteins in a biological system is equally important for predicting association between the enzymes and substrates, an aspect that is also being tackled with available bioinformatics tools. This chapter summarizes the use of the larger phosphorylation databases, and approaches that can be applied to predict kinases that phosphorylate individual sites or that are globally modulated in phosphoproteomics datasets.
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http://dx.doi.org/10.1007/978-1-4939-3049-4_21DOI Listing
August 2016

HOODS: finding context-specific neighborhoods of proteins, chemicals and diseases.

PeerJ 2015 30;3:e1057. Epub 2015 Jun 30.

The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen N , Denmark.

Clustering algorithms are often used to find groups relevant in a specific context; however, they are not informed about this context. We present a simple algorithm, HOODS, which identifies context-specific neighborhoods of entities from a similarity matrix and a list of entities specifying the context. We illustrate its applicability by finding disease-specific neighborhoods of functionally associated proteins, kinase-specific neighborhoods of structurally similar inhibitors, and physiological-system-specific neighborhoods of interconnected diseases. HOODS can be used via a simple interface at http://hoods.jensenlab.org, from where the source code can also be downloaded.
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http://dx.doi.org/10.7717/peerj.1057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493695PMC
July 2015

Temporal proteomics of NGF-TrkA signaling identifies an inhibitory role for the E3 ligase Cbl-b in neuroblastoma cell differentiation.

Sci Signal 2015 Apr 28;8(374):ra40. Epub 2015 Apr 28.

Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.

SH-SY5Y neuroblastoma cells respond to nerve growth factor (NGF)-mediated activation of the tropomyosin-related kinase A (TrkA) with neurite outgrowth, thereby providing a model to study neuronal differentiation. We performed a time-resolved analysis of NGF-TrkA signaling in neuroblastoma cells using mass spectrometry-based quantitative proteomics. The combination of interactome, phosphoproteome, and proteome data provided temporal insights into the molecular events downstream of NGF binding to TrkA. We showed that upon NGF stimulation, TrkA recruits the E3 ubiquitin ligase Cbl-b, which then becomes phosphorylated and ubiquitylated and decreases in abundance. We also found that recruitment of Cbl-b promotes TrkA ubiquitylation and degradation. Furthermore, the amount of phosphorylation of the kinase ERK and neurite outgrowth increased upon Cbl-b depletion in several neuroblastoma cell lines. Our findings suggest that Cbl-b limits NGF-TrkA signaling to control the length of neurites.
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http://dx.doi.org/10.1126/scisignal.2005769DOI Listing
April 2015

Acetylation site specificities of lysine deacetylase inhibitors in human cells.

Nat Biotechnol 2015 Apr 9;33(4):415-23. Epub 2015 Mar 9.

Department of Proteomics, The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Lysine deacetylases inhibitors (KDACIs) are used in basic research, and many are being investigated in clinical trials for treatment of cancer and other diseases. However, their specificities in cells are incompletely characterized. Here we used quantitative mass spectrometry (MS) to obtain acetylation signatures for 19 different KDACIs, covering all 18 human lysine deacetylases. Most KDACIs increased acetylation of a small, specific subset of the acetylome, including sites on histones and other chromatin-associated proteins. Inhibitor treatment combined with genetic deletion showed that the effects of the pan-sirtuin inhibitor nicotinamide are primarily mediated by SIRT1 inhibition. Furthermore, we confirmed that the effects of tubacin and bufexamac on cytoplasmic proteins result from inhibition of HDAC6. Bufexamac also triggered an HDAC6-independent, hypoxia-like response by stabilizing HIF1-α, providing a possible mechanistic explanation of its adverse, pro-inflammatory effects. Our results offer a systems view of KDACI specificities, providing a framework for studying function of acetylation and deacetylases.
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http://dx.doi.org/10.1038/nbt.3130DOI Listing
April 2015

Hepatic oxidative stress, genotoxicity and vascular dysfunction in lean or obese Zucker rats.

PLoS One 2015 4;10(3):e0118773. Epub 2015 Mar 4.

Section of Environmental Health, Department of Public Health, University of Copenhagen, Øster Farimagsgade 5A, DK-1014 Copenhagen K, Denmark.

Metabolic syndrome is associated with increased risk of cardiovascular disease, which could be related to oxidative stress. Here, we investigated the associations between hepatic oxidative stress and vascular function in pressurized mesenteric arteries from lean and obese Zucker rats at 14, 24 and 37 weeks of age. Obese Zucker rats had more hepatic fat accumulation than their lean counterparts. Nevertheless, the obese rats had unaltered age-related level of hepatic oxidatively damaged DNA in terms of formamidopyrimidine DNA glycosylase (FPG) or human oxoguanine DNA glycosylase (hOGG1) sensitive sites as measured by the comet assay. There were decreasing levels of oxidatively damaged DNA with age in the liver of lean rats, which occurred concurrently with increased expression of Ogg1. The 37 week old lean rats also had higher expression level of Hmox1 and elevated levels of DNA strand breaks in the liver. Still, both strain of rats had increased protein level of HMOX-1 in the liver at 37 weeks. The external and lumen diameters of mesenteric arteries increased with age in obese Zucker rats with no change in media cross-sectional area, indicating outward re-modelling without hypertrophy of the vascular wall. There was increased maximal response to acetylcholine-mediated endothelium-dependent vasodilatation in both strains of rats. Collectively, the results indicate that obese Zucker rats only displayed a modest mesenteric vascular dysfunction, with no increase in hepatic oxidative stress-generated DNA damage despite substantial hepatic steatosis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118773PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349582PMC
December 2015