MediaDive: the expert-curated cultivation media database.

We present MediaDive (https://mediadive.dsmz.de), a comprehensive and expert-curated cultivation media database, which comprises recipes, instructions and molecular compositions of >3200 standardized cultivation media for >40 000 microbial strains from all domains of life. MediaDive is designed to enable broad range applications from every-day-use in research and diagnostic laboratories to knowledge-driven support of new media design and artificial intelligence-driven data mining. It offers a number of intuitive search functions and comparison tools, for example to identify media for related taxonomic groups and to integrate strain-specific modifications. Besides classical PDF archiving and printing, the state-of-the-art website allows paperless use of media recipes on mobile devices for convenient wet-lab use. In addition, data can be retrieved using a RESTful web service for large-scale data analyses. An internal editor interface ensures continuous extension and curation of media by cultivation experts from the Leibniz Institute DSMZ, which is interlinked with the growing microbial collections at DSMZ. External user engagement is covered by a dedicated media builder tool. The standardized and programmatically accessible data will foster new approaches for the design of cultivation media to target the vast majority of uncultured microorganisms.

Systems Biology of Aromatic Compound Catabolism in Facultative Anaerobic Aromatoleum aromaticum EbN1T.

Members of the genus Aromatoleum thrive in diverse habitats and use a broad range of recalcitrant organic molecules coupled to denitrification or O2 respiration. To gain a holistic understanding of the model organism A. aromaticum EbN1T, we studied its catabolic network dynamics in response to 3-(4-hydroxyphenyl)propanoate, phenylalanine, 3-hydroxybenzoate, benzoate, and acetate utilized under nitrate-reducing versus oxic conditions. Integrated multi-omics (transcriptome, proteome, and metabolome) covered most of the catabolic network (199 genes) and allowed for the refining of knowledge of the degradation modules studied. Their substrate-dependent regulation showed differing degrees of specificity, ranging from high with 3-(4-hydroxyphenyl)propanoate to mostly relaxed with benzoate. For benzoate, the transcript and protein formation were essentially constitutive, contrasted by that of anoxia-specific versus oxia-specific metabolite profiles. The matrix factorization of transcriptomic data revealed that the anaerobic modules accounted for most of the variance across the degradation network. The respiration network appeared to be constitutive, both on the transcript and protein levels, except for nitrate reductase (with narGHI expression occurring only under nitrate-reducing conditions). The anoxia/nitrate-dependent transcription of denitrification genes is apparently controlled by three FNR-type regulators as well as by NarXL (all constitutively formed). The resequencing and functional reannotation of the genome fostered a genome-scale metabolic model, which is comprised of 655 enzyme-catalyzed reactions and 731 distinct metabolites. The model predictions for growth rates and biomass yields agreed well with experimental stoichiometric data, except for 3-(4-hydroxyphenyl)propanoate, with which 4-hydroxybenzoate was exported. Taken together, the combination of multi-omics, growth physiology, and a metabolic model advanced our knowledge of an environmentally relevant microorganism that differs significantly from other bacterial model strains. IMPORTANCE Aromatic compounds are abundant constituents not only of natural organic matter but also of bulk industrial chemicals and fuel components of environmental concern. Considering the widespread occurrence of redox gradients in the biosphere, facultative anaerobic degradation specialists can be assumed to play a prominent role in the natural mineralization of organic matter and in bioremediation at contaminated sites. Surprisingly, differential multi-omics profiling of the A. aromaticum EbN1T studied here revealed relaxed regulatory stringency across its four main physiological modi operandi (i.e., O2-independent and O2-dependent degradation reactions versus denitrification and O2 respiration). Combining multi-omics analyses with a genome-scale metabolic model aligned with measured growth performances establishes A. aromaticum EbN1T as a systems-biology model organism and provides unprecedented insights into how this bacterium functions on a holistic level. Moreover, this experimental platform invites future studies on eco-systems and synthetic biology of the environmentally relevant betaproteobacterial Aromatoleum/Azoarcus/Thauera cluster.

DSMZCellDive: Diving into high-throughput cell line data.

Human and animal cell lines serve as model systems in a wide range of life sciences such as cancer and infection research or drug screening. Reproducible data are highly dependent on authenticated, contaminant-free cell lines, no better delivered than by the official and certified biorepositories. Offering a web portal to high-throughput information on these model systems will facilitate working with and comparing to these references by data otherwise dispersed at different sources. We here provide DSMZCellDive to access a comprehensive data source on human and animal cell lines, freely available at celldive.dsmz.de. A wide variety of data sources are generated such as RNA-seq transcriptome data and STR (short tandem repeats) profiles. Several starting points ease entering the database via browsing, searching or visualising. This web tool is designed for further expansion on meta and high-throughput data to be generated in future. Explicated examples for the power of this novel tool include analysis of B-cell differentiation markers, homeo-oncogene expression, and measurement of genomic loss of heterozygosities by an enlarged STR panel of 17 loci. Sharing the data on cell lines by the biorepository itself will be of benefit to the scientific community  since it (1) supports the selection of appropriate model cell lines, (2) ensures reliability, (3) avoids misleading data, (4) saves on additional experimentals, and (5) serves as reference for genomic and gene expression data.

BacDive in 2022: the knowledge base for standardized bacterial and archaeal data.

The bacterial metadatabase BacDive (https://bacdive.dsmz.de) has developed into a leading database for standardized prokaryotic data on strain level. With its current release (07/2021) the database offers information for 82 892 bacterial and archaeal strains covering taxonomy, morphology, cultivation, metabolism, origin, and sequence information within 1048 data fields. By integrating high-quality data from additional culture collections as well as detailed information from species descriptions, the amount of data provided has increased by 30% over the past three years. A newly developed query builder tool in the advanced search now allows complex database queries. Thereby bacterial strains can be systematically searched based on combinations of their attributes, e.g. growth and metabolic features for biotechnological applications or to identify gaps in the present knowledge about bacteria. A new interactive dashboard provides a statistic overview over the most important data fields. Additional new features are improved genomic sequence data, integrated NCBI TaxIDs and links to BacMedia, the new sister database on cultivation media. To improve the findability and interpretation of data through search engines, data in BacDive are annotated with bioschemas.org terms.

The Metano Modeling Toolbox MMTB: An Intuitive, Web-Based Toolbox Introduced by Two Use Cases.

Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.

BRENDA, the ELIXIR core data resource in 2021: new developments and updates.

The BRENDA enzyme database (https://www.brenda-enzymes.org), established in 1987, has evolved into the main collection of functional enzyme and metabolism data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA provides reliable data, continuous curation and updates of classified enzymes, and the integration of newly discovered enzymes. The main part contains >5 million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted from ∼157 000 primary literature references, combined with information of text and data mining, data integration, and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, genome annotations, ligand information, taxonomic, bibliographic, and kinetic data. BRENDA offers an easy access to enzyme information from quick to advanced searches, text- and structured-based queries for enzyme-ligand interactions, word maps, and visualization of enzyme data. The BRENDA Pathway Maps are completely revised and updated for an enhanced interactive and intuitive usability. The new design of the Enzyme Summary Page provides an improved access to each individual enzyme. A new protein structure 3D viewer was integrated. The prediction of the intracellular localization of eukaryotic enzymes has been implemented. The new EnzymeDetector combines BRENDA enzyme annotations with protein and genome databases for the detection of eukaryotic and prokaryotic enzymes.

MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context.

Metabolic pathways are an important part of systems biology research since they illustrate complex interactions between metabolites, enzymes, and regulators. Pathway maps are drawn to elucidate metabolism or to set data in a metabolic context. We present MetaboMAPS, a web-based platform to visualize numerical data on individual metabolic pathway maps. Metabolic maps can be stored, distributed and downloaded in SVG-format. MetaboMAPS was designed for users without computational background and supports pathway sharing without strict conventions. In addition to existing applications that established standards for well-studied pathways, MetaboMAPS offers a niche for individual, customized pathways beyond common knowledge, supporting ongoing research by creating publication-ready visualizations of experimental data.

Utilization of Phenol as Carbon Source by the Thermoacidophilic Archaeon Saccharolobus solfataricus P2 Is Limited by Oxygen Supply and the Cellular Stress Response.

Present in many industrial effluents and as common degradation product of organic matter, phenol is a widespread compound which may cause serious environmental problems, due to its toxicity to animals and humans. Degradation of phenol from the environment by mesophilic bacteria has been studied extensively over the past decades, but only little is known about phenol biodegradation at high temperatures or low pH. In this work we studied phenol degradation in the thermoacidophilic archaeon Saccharolobus solfataricus P2 (basonym: Sulfolobus solfataricus) under extreme conditions (80°C, pH 3.5). We combined metabolomics and transcriptomics together with metabolic modeling to elucidate the organism's response to growth with phenol as sole carbon source. Although S. solfataricus is able to utilize phenol for biomass production, the carbon source induces profound stress reactions, including genome rearrangement as well as a strong intracellular accumulation of polyamines. Furthermore, computational modeling revealed a 40% higher oxygen demand for substrate oxidation, compared to growth on glucose. However, only 16.5% of oxygen is used for oxidation of phenol to catechol, resulting in a less efficient integration of carbon into the biomass. Finally, our data underlines the importance of the phenol meta-degradation pathway in S. solfataricus and enables us to predict enzyme candidates involved in the degradation processes downstream of 2-hydroxymucconic acid.