Tyrosine kinase inhibitors can activate the NLRP3 inflammasome in myeloid cells through lysosomal damage and cell lysis.

Inflammasomes are intracellular protein complexes that promote an inflammatory host defense in response to pathogens and damaged or neoplastic tissues and are implicated in inflammatory disorders and therapeutic-induced toxicity. We investigated the mechanisms of activation for inflammasomes nucleated by NOD-like receptor (NLR) protiens. A screen of a small-molecule library revealed that several tyrosine kinase inhibitors (TKIs)-including those that are clinically approved (such as imatinib and crizotinib) or are in clinical trials (such as masitinib)-activated the NLRP3 inflammasome. Furthermore, imatinib and masitinib caused lysosomal swelling and damage independently of their kinase target, leading to cathepsin-mediated destabilization of myeloid cell membranes and, ultimately, cell lysis that was accompanied by potassium (K+) efflux, which activated NLRP3. This effect was specific to primary myeloid cells (such as peripheral blood mononuclear cells and mouse bone marrow-derived dendritic cells) and did not occur in other primary cell types or various cell lines. TKI-induced lytic cell death and NLRP3 activation, but not lysosomal damage, were prevented by stabilizing cell membranes. Our findings reveal a potential immunological off-target of some TKIs that may contribute to their clinical efficacy or to their adverse effects.

Draft Genome Sequence of Marine Actinobacterium Streptomyces spinoverrucosus SNB-032.

Actinobacteria represent a large source of diverse bioactive compounds of medical and economic importance. Here, we report the 8.8-Mb draft genome of the marine bacterium Streptomyces spinoverrucosus SNB-032. Bioinformatic sequence analysis proved similarities to known Streptomyces strains and revealed the capacity for the production of various secondary metabolites.

NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy.

BACKGROUND: Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies-based long-read sequencing "nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers. RESULTS: The Galaxy platform provides a user-friendly interface to computational command line-based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed "NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads. CONCLUSIONS: A range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

Disease relevant modifications of the methylome and transcriptome by particulate matter (PM2.5) from biomass combustion.

Exposure to particulate matter (PM) is recognized as a major health hazard, but molecular responses are still insufficiently described. We analyzed the epigenetic impact of ambient PM2.5 from biomass combustion on the methylome of primary human bronchial epithelial BEAS-2B cells using the Illumina HumanMethylation450 BeadChip. The transcriptome was determined by the Affymetrix HG-U133 Plus 2.0 Array. PM2.5 induced genome wide alterations of the DNA methylation pattern, including differentially methylated CpGs in the promoter region associated with CpG islands. Gene ontology analysis revealed that differentially methylated genes were significantly clustered in pathways associated with the extracellular matrix, cellular adhesion, function of GTPases, and responses to extracellular stimuli, or were involved in ion binding and shuttling. Differential methylations also affected tandem repeats. Additionally, 45 different miRNA CpG loci showed differential DNA methylation, most of them proximal to their promoter. These miRNAs are functionally relevant for lung cancer, inflammation, asthma, and other PM-associated diseases. Correlation of the methylome and transcriptome demonstrated a clear bias toward transcriptional activation by hypomethylation. Genes that exhibited both differential methylation and expression were functionally linked to cytokine and immune responses, cellular motility, angiogenesis, inflammation, wound healing, cell growth, differentiation and development, or responses to exogenous matter. Disease ontology of differentially methylated and expressed genes indicated their prominent role in lung cancer and their participation in dominant cancer related signaling pathways. Thus, in lung epithelial cells, PM2.5 alters the methylome of genes and noncoding transcripts or elements that might be relevant for PM- and lung-associated diseases.

The Draft Genome Sequence of Actinokineospora bangkokensis 44EHWT Reveals the Biosynthetic Pathway of the Antifungal Thailandin Compounds with Unusual Butylmalonyl-CoA Extender Units.

We report the draft genome sequence of Actinokineospora bangkokensis 44EHWT, the producer of the antifungal polyene compounds, thailandins A and B. The sequence contains 7.45 Mb, 74.1% GC content and 35 putative gene clusters for the biosynthesis of secondary metabolites. There are three gene clusters encoding large polyketide synthases of type I. Annotation of the ORF functions and targeted gene disruption enabled us to identify the cluster for thailandin biosynthesis. We propose a plausible biosynthetic pathway for thailandin, where the unusual butylmalonyl-CoA extender unit is incorporated and results in an untypical side chain.

StreptomeDB: a resource for natural compounds isolated from Streptomyces species.

Bacteria from the genus Streptomyces are very important for the production of natural bioactive compounds such as antibiotic, antitumour or immunosuppressant drugs. Around two-thirds of all known natural antibiotics are produced by these bacteria. An enormous quantity of crucial data related to this genus has been generated and published, but so far no freely available and comprehensive database exists. Here, we present StreptomeDB (http://www.pharmaceutical-bioinformatics.de/streptomedb/). To the best of our knowledge, this is the largest database of natural products isolated from Streptomyces. It contains >2400 unique and diverse compounds from >1900 different Streptomyces strains and substrains. In addition to names and molecular structures of the compounds, information about source organisms, references, biological role, activities and synthesis routes (e.g. polyketide synthase derived and non-ribosomal peptides derived) is included. Data can be accessed through queries on compound names, chemical structures or organisms. Extraction from the literature was performed through automatic text mining of thousands of articles from PubMed, followed by manual curation. All annotated compound structures can be downloaded from the website and applied for in silico screenings for identifying new active molecules with undiscovered properties.

Tetrahydroxynaphthalene reductase: catalytic properties of an enzyme involved in reductive asymmetric naphthol dearomatization.

In reduced circumstances: tetrahydroxynaphthalene reductase shows a broad substrate range including alternate phenolic compounds and cyclic ketones. Structural modeling reveals major enzyme-substrate interactions; C-terminal truncation of the enzyme causes an altered substrate preference, in accordance with stabilization of the substrate by the C-terminal carboxylate. This effect allows the identification of a homologous enzyme.

Mining and evaluation of molecular relationships in literature.

MOTIVATION: Specific information on newly discovered proteins is often difficult to find in literature. Particularly if only sequences and no common names of proteins or genes are available, preceding sequence similarity searches can be crucial for the process of information collection. In drug research, it is important to know whether a small molecule targets only one specific protein or whether similar or homologous proteins are also influenced that may account for possible side effects. RESULTS: prolific (protein-literature investigation for interacting compounds) provides a one-step solution to investigate available information on given protein names, sequences, similar proteins or sequences on the gene level. Co-occurrences of UniProtKB/Swiss-Prot proteins and PubChem compounds in all PubMed abstracts are retrievable. Concise 'heat-maps' and tables display frequencies of co-occurrences. They provide links to processed literature with highlighted found protein and compound synonyms. Evaluation with manually curated drug-protein relationships showed that up to 69% could be discovered by automatic text-processing. Examples are presented to demonstrate the capabilities of prolific. AVAILABILITY: The web-application is available at http://prolific.pharmaceutical-bioinformatics.de and a web service at http://www.pharmaceutical-bioinformatics.de/prolific/soap/prolific.wsdl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Compounds In Literature (CIL): screening for compounds and relatives in PubMed.

SUMMARY: Searching for certain compounds in literature can be an elaborate task, with many compounds having several different synonyms. Often, only the structure is known but not its name. Furthermore, rarely investigated compounds may not be described in the available literature at all. In such cases, preceding searches for described similar compounds facilitate literature mining. Highlighted names of proteins in selected texts may further accelerate the time-consuming process of literary research. Compounds In Literature (CIL) provides a web interface to automatically find names, structures, and similar structures in over 28 million compounds of PubChem and more than 18 million citations provided by the PubMed service. CIL's pre-calculated database contains more than 56 million parent compound-abstract relations. Found compounds, relatives and abstracts are related to proteins in a concise 'heat map'-like overview. Compounds and proteins are highlighted in their respective abstracts, and are provided with links to PubChem and UniProt. AVAILABILITY: An easy-to-use web interface with detailed descriptions, help and statistics is available from http://cil.pharmaceutical-bioinformatics.de. CONTACT: stefan.guenther@pharmazie.uni-freiburg.de.