CORUM: the comprehensive resource of mammalian protein complexes—2009

CORUM is a database that provides a manually curated repository of experimentally characterized protein complexes from mammalian organisms, mainly human (64%), mouse (16%) and rat (12%). Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The new CORUM 2.0 release encompasses 2837 protein complexes offering the largest and most comprehensive publicly available dataset of mammalian protein complexes. The CORUM dataset is built from 3198 different genes, representing ∼16% of the protein coding genes in humans. Each protein complex is described by a protein complex name, subunit composition, function as well as the literature reference that characterizes the respective protein complex. Recent developments include mapping of functional annotation to Gene Ontology terms as well as cross-references to Entrez Gene identifiers. In addition, a ‘Phylogenetic Conservation’ analysis tool was implemented that analyses the potential occurrence of orthologous protein complex subunits in mammals and other selected groups of organisms. This allows one to predict the occurrence of protein complexes in different phylogenetic groups. CORUM is freely accessible at (http://mips.helmholtz-muenchen.de/genre/proj/corum/index.html)

PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes

PhenomiR is a comprehensive database of 542 studies reporting deregulation of miRNAs allowing large-scale statistical analysis of miRNA expression changes

FUS/TLS contributes to replication-dependent histone gene expression by interaction with U7 snRNPs and histone-specific transcription factors

Replication-dependent histone genes are up-regulated during the G1/S phase transition to meet the requirement for histones to package the newly synthesized DNA. In mammalian cells, this increment is achieved by enhanced transcription and 3′ end processing. The non-polyadenylated histone mRNA 3′ ends are generated by a unique mechanism involving the U7 small ribonucleoprotein (U7 snRNP). By using affinity purification methods to enrich U7 snRNA, we identified FUS/TLS as a novel U7 snRNP interacting protein. Both U7 snRNA and histone transcripts can be precipitated by FUS antibodies predominantly in the S phase of the cell cycle. Moreover, FUS depletion leads to decreased levels of correctly processed histone mRNAs and increased levels of extended transcripts. Interestingly, FUS antibodies also co-immunoprecipitate histone transcriptional activator NPAT and transcriptional repressor hnRNP UL1 in different phases of the cell cycle. We further show that FUS binds to histone genes in S phase, promotes the recruitment of RNA polymerase II and is important for the activity of histone gene promoters. Thus, FUS may serve as a linking factor that positively regulates histone gene transcription and 3′ end processing by interacting with the U7 snRNP and other factors involved in replication-dependent histone gene expressio

The Negatome database: a reference set of non-interacting protein pairs

The Negatome is a collection of protein and domain pairs that are unlikely to be engaged in direct physical interactions. The database currently contains experimentally supported non-interacting protein pairs derived from two distinct sources: by manual curation of literature and by analyzing protein complexes with known 3D structure. More stringent lists of non-interacting pairs were derived from these two datasets by excluding interactions detected by high-throughput approaches. Additionally, non-interacting protein domains have been derived from the stringent manual and structural data, respectively. The Negatome is much less biased toward functionally dissimilar proteins than the negative data derived by randomly selecting proteins from different cellular locations. It can be used to evaluate protein and domain interactions from new experiments and improve the training of interaction prediction algorithms. The Negatome database is available at http://mips.helmholtz-muenchen.de/proj/ppi/negatome

The Mouse Functional Genome Database (MfunGD): functional annotation of proteins in the light of their cellular context

MfunGD () provides a resource for annotated mouse proteins and their occurrence in protein networks. Manual annotation concentrates on proteins which are found to interact physically with other proteins. Accordingly, manually curated information from a protein–protein interaction database (MPPI) and a database of mammalian protein complexes is interconnected with MfunGD. Protein function annotation is performed using the Functional Catalogue (FunCat) annotation scheme which is widely used for the analysis of protein networks. The dataset is also supplemented with information about the literature that was used in the annotation process as well as links to the SIMAP Fasta database, the Pedant protein analysis system and cross-references to external resources. Proteins that so far were not manually inspected are annotated automatically by a graphical probabilistic model and/or superparamagnetic clustering. The database is continuously expanding to include the rapidly growing amount of functional information about gene products from mouse. MfunGD is implemented in GenRE, a J2EE-based component-oriented multi-tier architecture following the separation of concern principle

FUS/TLS contributes to replication-dependent histone gene expression by interaction with U7 snRNPs and histone-specific transcription factors.

Replication-dependent histone genes are up-regulated during the G1/S phase transition to meet the requirement for histones to package the newly synthesized DNA. In mammalian cells, this increment is achieved by enhanced transcription and 3' end processing. The non-polyadenylated histone mRNA 3' ends are generated by a unique mechanism involving the U7 small ribonucleoprotein (U7 snRNP). By using affinity purification methods to enrich U7 snRNA, we identified FUS/TLS as a novel U7 snRNP interacting protein. Both U7 snRNA and histone transcripts can be precipitated by FUS antibodies predominantly in the S phase of the cell cycle. Moreover, FUS depletion leads to decreased levels of correctly processed histone mRNAs and increased levels of extended transcripts. Interestingly, FUS antibodies also co-immunoprecipitate histone transcriptional activator NPAT and transcriptional repressor hnRNP UL1 in different phases of the cell cycle. We further show that FUS binds to histone genes in S phase, promotes the recruitment of RNA polymerase II and is important for the activity of histone gene promoters. Thus, FUS may serve as a linking factor that positively regulates histone gene transcription and 3' end processing by interacting with the U7 snRNP and other factors involved in replication-dependent histone gene expression

Expression of phosphorylated ribosomal protein S6 in mesothelioma patients - correlation with clinico-pathological characteristics and outcome: results from the European Thoracic Oncology Platform (ETOP) Mesoscape project

Pleural mesothelioma (PM) is an aggressive malignancy with poor prognosis. Although histology and pathologic stage are important prognostic factors, better prognostic biomarkers are needed. The ribosomal protein S6 is a downstream target of the phosphatidylinositol 3-kinase (PI3K) pathway involved in protein synthesis and cell proliferation. In previous studies, low phosphorylated S6 (pS6) immunoreactivity was significantly correlated with longer progression-free survival (PFS) and overall survival (OS) in PM patients. We aimed to correlate pS6 expression to clinical data in a large multi-centre PM cohort as part of the European Thoracic Oncology Platform (ETOP) Mesoscape project. Tissue Micro Arrays (TMAs) of PM were constructed and expression of pS6 was evaluated by a semiquantitatively aggregate H-score. Expression results were correlated to patient characteristics as well as OS/PFS. pS6 IHC results of 364 patients from 9 centres, diagnosed between 1999 and 2017 were available. The primary histology of included tumours was epithelioid (70.3%), followed by biphasic (24.2%) and sarcomatoid (5.5%). TMAs included both treatment-naive and tumour tissue taken after induction chemotherapy. High pS6 expression (181 patients with H-score>1.41) was significantly associated with less complete resection. In the overall cohort, OS/PFS were not significantly different between pS6-low and pS6-high patients. In a subgroup analysis nonepithelioid (biphasic and sarcomatoid) patients with high pS6 expression showed a significantly shorter OS (p< 0.001, 10.7 versus 16.9 months) and PFS (p < 0.001, 6.2 versus 10.8 months). In subgroup analysis, in non-epithelioid PM patients high pS6 expression was associated with significantly shorter OS and PFS. These exploratory findings suggest a clinically relevant PI3K pathway activation in non-epithelioid PM which might lay the foundation for future targeted treatment strategies

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Funder: Bundesministerium für Bildung und ForschungFunder: Bundesministerium für Bildung und Forschung (BMBF)We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective