SummaryThe degradation of aromatic compounds follows different biochemical principles in aerobic and anaerobic microorganisms. While aerobes dearomatize and cleave the aromatic ring by oxygenases, facultative anaerobes utilize an ATP-dependent ring reductase for the dearomatization of the activated key intermediate benzoyl-coenzyme A (CoA). In this work, the aromatic metabolism was studied in the obligately anaerobic model organism Geobacter metallireducens . The gene coding for a putative carboxylic acid-CoA ligase was heterologously overexpressed and the gene product was characterized as a highly specific benzoate-CoA ligase catalysing the initial step of benzoate metabolism. However, no evidence for the presence of an ATP-dependent benzoyl-CoA reductase as observed in facultative anaerobes was obtained. In a proteomic approach benzoate-induced proteins were identified; the corresponding genes are organized in two clusters comprising 44 genes. Induction of representative genes during growth on benzoate was confirmed by reverse transcription polymerase chain reaction. The results obtained suggest that benzoate is activated to benzoyl-CoA, which is then reductively dearomatized to cyclohexa-1,5-diene-1-carbonyl-CoA, followed by β β β β -oxidation reactions to acetyl-CoA units, as in facultatively anaerobic bacteria. However, in G. metallireducens the process of reductive benzene ring dearomatization appears to be catalysed by a set of completely different protein components comprising putative molybdenum and selenocysteine containing enzymes.

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org.

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.

SUMMARYThe moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens.

The moss Physcomitrella patens is suitable for systems biology studies, as it can be grown axenically under standardised conditions in plain mineral medium and comprises only few cell types. We report on metabolite profiling of two major P. patens tissues, filamentous protonema and leafy gametophores, from different culture conditions. A total of 96 compounds were detected, 21 of them as yet unknown in public databases. Protonema and gametophores had distinct metabolic profiles, especially with regard to saccharides, sugar derivates, amino acids, lignin precursors and nitrogen-rich storage compounds. A hydroponic culture was established for P. patens, and was used to apply drought stress under physiological conditions. This treatment led to accumulation of osmoprotectants, such as altrose, maltitol, ascorbic acid and proline. Thus, these osmoprotectants are not unique to seed plants but have evolved at an early phase of the colonization of land by plants.