{"type": "FeatureCollection", "features": [{"id": "10.1093/nar/gkz378", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:18:22Z", "type": "Journal Article", "created": "2019-05-06", "title": "Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport", "description": "Abstract

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands\uffe2\uff80\uff99 transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands\uffe2\uff80\uff99 passages can be calculated and visualized. The tool is very fast (2\uffe2\uff80\uff9320 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.

", "keywords": ["0301 basic medicine", "Internet", "0303 health sciences", "Binding Sites", "BINDING; STABILITY; MECHANISM; MYOGLOBIN; MIGRATION; DYNAMICS; KINETICS; PATHWAY; ENZYMES; SERVER", "Computational Biology", "Ligands", "Protein Structure", " Tertiary", "3. Good health", "Molecular Docking Simulation", "Benchmarking", "User-Computer Interface", "03 medical and health sciences", "Web Server Issue", "Animals", "Humans", "Protein Interaction Domains and Motifs", "Amino Acid Sequence", "Carrier Proteins", "Protein Structure", " Quaternary", "Algorithms", "Protein Binding"]}, "links": [{"href": "http://academic.oup.com/nar/article-pdf/47/W1/W414/28880050/gkz378.pdf"}, {"href": "https://doi.org/10.1093/nar/gkz378"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nucleic%20Acids%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/nar/gkz378", "name": "item", "description": "10.1093/nar/gkz378", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/nar/gkz378"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-22T00:00:00Z"}}, {"id": "10.1101/2023.10.03.560709", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-28T16:18:27Z", "type": "Journal Article", "created": "2023-10-04", "title": "Bacteria face trade-offs in the decomposition of complex biopolymers", "description": "Abstract

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of system\uffe2\uff80\uff99s complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low- or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes.

Author summary

The decomposition of polysaccharides by microbes is a key process in the global carbon cycle. It requires the joint action of a variety of microbially-produced extracellular enzymes. They can be broadly classified into endo-enzymes, that act in the middle of polymers, and exo-enzymes, that cleave units from polymer ends. Little is known about the benefits for microbes producing a certain enzyme type and the interplay between enzyme producing strategies in mixed communities. This hampers our comprehensive understanding of decomposition in terrestrial and marine ecosystems and thus limits the prediction of decomposition processes, for example in a changing climate.

Based on theoretical modelling, we revealed a fundamental trade-off in the action of these enzymes. While exo-enzymes are more efficient at high substrate conditions, endo-enzymes perform better when substrate is low. Generalists producing both enzymes expand their ecological niche of substrate availability compared to specialists only producing one of the two types. Complementary specialists only co-exist in oligotrophic conditions. We conclude that producing enzymes for specific steps within polymer degradation represents relevant ecological strategies for microbes in decomposer communities.Enzymes are on high demand for very diverse biotechnological applications. However, natural biocatalysts often need to be engineered for fine-tuning their properties towards the end applications, such as the activity, selectivity, stability to temperature or co-solvents, and solubility. Computational methods are increasingly used in this task, providing predictions that narrow down the space of possible mutations significantly and can enormously reduce the experimental burden. Many computational tools are available as web-based platforms, making them accessible to non-expert users. These platforms are typically user-friendly, contain walk-throughs, and do not require deep expertise and installations. Here we describe some of the most recent outstanding web-tools for enzyme engineering and formulate future perspectives in this field.

", "keywords": ["0301 basic medicine", "Internet", "0303 health sciences", "03 medical and health sciences", "Solubility", "biochemistry", "Computational Biology", "PROTEIN; STABILITY; DYNAMICS; VIEW", "Biotechnology"]}, "links": [{"href": "https://doi.org/10.1016/j.sbi.2021.01.010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Current%20Opinion%20in%20Structural%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.sbi.2021.01.010", "name": "item", "description": "10.1016/j.sbi.2021.01.010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.sbi.2021.01.010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-03T00:00:00Z"}}, {"id": "10.1021/acs.est.0c06687", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:17:26Z", "type": "Journal Article", "created": "2021-02-10", "title": "Microbial Interactions Drive the Complete Catabolism of the Antibiotic Sulfamethoxazole in Activated Sludge Microbiomes", "description": "Microbial communities are believed to outperform monocultures in the complete catabolism of organic pollutants via reduced metabolic burden and increased robustness to environmental challenges; however, the interaction mechanism in functional microbiomes remains poorly understood. Here, three functionally differentiated activated sludge microbiomes (S1: complete catabolism of sulfamethoxazole (SMX); S2: complete catabolism of the phenyl part of SMX ([phenyl]-SMX) with stable accumulation of its heterocyclic product 3-amino-5-methylisoxazole (3A5MI); A: complete catabolism of 3A5MI rather than [phenyl]-SMX) were enriched. Combining time-series cultivation-independent microbial community analysis, DNA-stable isotope probing, molecular ecological network analysis, and cultivation-dependent function verification, we identified key players involved in the SMX degradation process. Paenarthrobacter and Nocardioides were primary degraders for the initial cleavage of the sulfonamide functional group (-C-S-N- bond) and 3A5MI degradation, respectively. Complete catabolism of SMX was achieved by their cross-feeding. The co-culture of Nocardioides, Acidovorax, and Sphingobium demonstrated that the nondegraders Acidovorax and Sphingobium were involved in the enhancement of 3A5MI degradation. Moreover, we unraveled the internal labor division patterns and connections among the active members centered on the two primary degraders. Overall, the proposed methodology is promisingly applicable and would help generate mechanistic, predictive, and operational understanding of the collaborative biodegradation of various contaminants. This study provides useful information for synthetic activated sludge microbiomes with optimized environmental functions.", "keywords": ["Sulfamethoxazole", "Physiology", "Science Policy", "analysis", "0211 other engineering and technologies", "02 engineering and technology", "Microbiology", "Environmental Sciences not elsewhere classified", "heterocyclic product 3-", "11. Sustainability", "Activated Sludge Microbiomes Microb.", "Acidovorax", "SMX degradation process", "Molecular Biology", "cultivation-dependent function veri.", "phenyl", "Ecology", "Sewage", "Microbiota", "catabolism", "Nocardioide", "Computational Biology", "Cell Biology", "6. Clean water", "Sphingobium", "Anti-Bacterial Agents", "sludge microbiomes", "Infectious Diseases", "Complete", "Biodegradation", " Environmental", "Microbial Interactions Drive", "degrader", "Microbial Interactions", "labor division patterns", "5MI degradation", "Water Pollutants", " Chemical", "Developmental Biology", "Biological Sciences not elsewhere classified"]}, "links": [{"href": "https://pubs.acs.org/doi/pdf/10.1021/acs.est.0c06687"}, {"href": "https://doi.org/10.1021/acs.est.0c06687"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/acs.est.0c06687", "name": "item", "description": "10.1021/acs.est.0c06687", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/acs.est.0c06687"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-10T00:00:00Z"}}, {"id": "10.1038/s41598-020-58025-3", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:17:47Z", "type": "Journal Article", "created": "2020-01-28", "title": "Building de novo reference genome assemblies of complex eukaryotic microorganisms from single nuclei", "description": "Abstract

The advent of novel sequencing techniques has unraveled a tremendous diversity on Earth. Genomic data allow us to understand ecology and function of organisms that we would not otherwise know existed. However, major methodological challenges remain, in particular for multicellular organisms with large genomes. Arbuscular mycorrhizal (AM) fungi are important plant symbionts with cryptic and complex multicellular life cycles, thus representing a suitable model system for method development. Here, we report a novel method for large scale, unbiased nuclear sorting, sequencing, and de novo assembling of AM fungal genomes. After comparative analyses of three assembly workflows we discuss how sequence data from single nuclei can best be used for different downstream analyses such as phylogenomics and comparative genomics of single nuclei. Based on analysis of completeness, we conclude that comprehensive de novo genome assemblies can be produced from six to seven nuclei. The method is highly applicable for a broad range of taxa, and will greatly improve our ability to study multicellular eukaryotes with complex life cycles.

", "keywords": ["0301 basic medicine", "Evolutionary Biology", "0303 health sciences", "Genome", "Fungi", "Computational Biology", "Eukaryota", "Genomics", "Article", "Workflow", "Evolutionsbiologi", "03 medical and health sciences", "13. Climate action", "Algorithms"]}, "links": [{"href": "https://www.nature.com/articles/s41598-020-58025-3.pdf"}, {"href": "https://doi.org/10.1038/s41598-020-58025-3"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41598-020-58025-3", "name": "item", "description": "10.1038/s41598-020-58025-3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-020-58025-3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-28T00:00:00Z"}}, {"id": "10.1080/1040841x.2022.2132850", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:18:13Z", "type": "Journal Article", "created": "2022-10-26", "title": "Bioinformatic approaches for studying the microbiome of fermented food", "description": "High-throughput DNA sequencing-based approaches continue to revolutionise our understanding of microbial ecosystems, including those associated with fermented foods. Metagenomic and metatranscriptomic approaches are state-of-the-art biological profiling methods and are employed to investigate a wide variety of characteristics of microbial communities, such as taxonomic membership, gene content and the range and level at which these genes are expressed. Individual groups and consortia of researchers are utilising these approaches to produce increasingly large and complex datasets, representing vast populations of microorganisms. There is a corresponding requirement for the development and application of appropriate bioinformatic tools and pipelines to interpret this data. This review critically analyses the tools and pipelines that have been used or that could be applied to the analysis of metagenomic and metatranscriptomic data from fermented foods. In addition, we critically analyse a number of studies of fermented foods in which these tools have previously been applied, to highlight the insights that these approaches can provide.", "keywords": ["2. Zero hunger", "0301 basic medicine", "metatranscriptomics", "Microbiota", "0206 medical engineering", "high-throughput sequencing", "Computational Biology", "High-Throughput Nucleotide Sequencing", "bioinformatics", "02 engineering and technology", "fermented foods", "03 medical and health sciences", "Metagenome", "Metagenomics", "Fermented Foods"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/1040841X.2022.2132850"}, {"href": "https://doi.org/10.1080/1040841x.2022.2132850"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Critical%20Reviews%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1080/1040841x.2022.2132850", "name": "item", "description": "10.1080/1040841x.2022.2132850", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1080/1040841x.2022.2132850"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-26T00:00:00Z"}}, {"id": "10.1093/bioinformatics/btz584", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:18:19Z", "type": "Journal Article", "created": "2019-08-19", "title": "MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network", "description": "Abstract Motivation

Analysis of differential expression of genes is often performed to understand how the metabolic activity of an organism is impacted by a perturbation. However, because the system of metabolic regulation is complex and all changes are not directly reflected in the expression levels, interpreting these data can be difficult.

Results

In this work, we present a new algorithm and computational tool that uses a genome-scale metabolic reconstruction to infer metabolic changes from differential expression data. Using the framework of constraint-based analysis, our method produces a qualitative hypothesis of a change in metabolic activity. In other words, each reaction of the network is inferred to have increased, decreased, or remained unchanged in flux. In contrast to similar previous approaches, our method does not require a biological objective function and does not assign on/off activity states to genes. An implementation is provided and it is available online. We apply the method to three published datasets to show that it successfully accomplishes its two main goals: confirming or rejecting metabolic changes suggested by differentially expressed genes based on how well they fit in as parts of a coordinated metabolic change, as well as inferring changes in reactions whose genes did not undergo differential expression.

Availability and implementation

github.com/htpusa/moomin.

Supplementary information

Supplementary data are available at Bioinformatics online.

", "keywords": ["0301 basic medicine", "570", "[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]", "Metabolic networks; omics data", "Genome", "[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]", "0206 medical engineering", "610", "Computational Biology", "[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]", "02 engineering and technology", "[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]", "Original Papers", "Models", " Biological", "03 medical and health sciences", "[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]", "Algorithms", "Metabolic Networks and Pathways", "[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]"]}, "links": [{"href": "https://iris.uniroma1.it/bitstream/11573/1321358/5/Pusa_MOOMIN_2020.pdf"}, {"href": "https://academic.oup.com/bioinformatics/article-pdf/36/2/514/48991611/btz584.pdf"}, {"href": "https://doi.org/10.1093/bioinformatics/btz584"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bioinformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/bioinformatics/btz584", "name": "item", "description": "10.1093/bioinformatics/btz584", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/bioinformatics/btz584"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-08-22T00:00:00Z"}}, {"id": "10.1093/bioinformatics/btad407", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:18:19Z", "type": "Journal Article", "created": "2023-06-24", "title": "enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways", "description": "Abstract Motivation

Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions.

Results

We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule\uffe2\uff80\uff99s strengths for both automatic extraction of optimized reactions rules and automated updating thereof.

Availability and implementation

enviRule code is freely available at https://github.com/zhangky12/enviRule.

", "keywords": ["10120 Department of Chemistry", "Statistics and Probability", "Original Paper", "1303 Biochemistry", "Computational Biology", "Biochemistry", "Computer Science Applications", "Computational Mathematics", "Computational Theory and Mathematics", "13. Climate action", "540 Chemistry", "1312 Molecular Biology", "1706 Computer Science Applications", "2613 Statistics and Probability", "2605 Computational Mathematics", "Molecular Biology", "Biotransformation", "1703 Computational Theory and Mathematics"]}, "links": [{"href": "https://doi.org/10.1093/bioinformatics/btad407"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bioinformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/bioinformatics/btad407", "name": "item", "description": "10.1093/bioinformatics/btad407", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/bioinformatics/btad407"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-06-24T00:00:00Z"}}, {"id": "10.1105/tpc.20.00318", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:18:29Z", "type": "Journal Article", "created": "2020-10-10", "title": "ARADEEPOPSIS, an Automated Workflow for Top-View Plant Phenomics using Semantic Segmentation of Leaf States", "description": "Linking plant phenotype to genotype is a common goal to both plant breeders and geneticists. However, collecting phenotypic data for large numbers of plants remain a bottleneck. Plant phenotyping is mostly image based and therefore requires rapid and robust extraction of phenotypic measurements from image data. However, because segmentation tools usually rely on color information, they are sensitive to background or plant color deviations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner. ARADEEPOPSIS (https://github.com/Gregor-Mendel-Institute/aradeepopsis) uses semantic segmentation of top-view images to classify leaf tissue into three categories: healthy, anthocyanin rich, and senescent. This makes it particularly powerful at quantitative phenotyping of different developmental stages, mutants with aberrant leaf color and/or phenotype, and plants growing in stressful conditions. On a panel of 210 natural Arabidopsis (Arabidopsis thaliana) accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to identify known loci related to anthocyanin production and early necrosis in genome-wide association analyses. Our pipeline accurately processed images of diverse origin, quality, and background composition, and of a distantly related Brassicaceae. ARADEEPOPSIS is deployable on most operating systems and high-performance computing environments and can be used independently of bioinformatics expertise and resources.", "keywords": ["0301 basic medicine", "0303 health sciences", "Genotype", "Large-Scale Biology Articles", "Arabidopsis", "Computational Biology", "Semantics", "Workflow", "Plant Leaves", "03 medical and health sciences", "Phenotype", "Image Processing", " Computer-Assisted", "Phenomics", "Software", "Genome-Wide Association Study"]}, "links": [{"href": "https://doi.org/10.1105/tpc.20.00318"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Plant%20Cell", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1105/tpc.20.00318", "name": "item", "description": "10.1105/tpc.20.00318", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1105/tpc.20.00318"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-09T00:00:00Z"}}, {"id": "10.3389/fmicb.2019.01347", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:20:30Z", "type": "Journal Article", "created": "2019-06-25", "title": "Finding Functional Differences Between Species in a Microbial Community: Case Studies in Wine Fermentation and Kefir Culture", "description": "Microbial life usually takes place in a community where individuals interact, by competition for nutrients, cross-feeding, inhibition by end-products, but also by their spatial distribution. Lactic acid bacteria are prominent members of microbial communities responsible for food fermentations. Their niche in a community depends on their own properties as well as those of the other species. Here, we apply a computational approach, which uses only genomic and metagenomic information and functional annotation of genes, to find properties that distinguish a species from others in the community, as well as to follow individual species in a community. We analyzed isolated and sequenced strains from a kefir community, and metagenomes from wine fermentations. We demonstrate how the distinguishing properties of an organism lead to experimentally testable hypotheses concerning the niche and the interactions with other species. We observe, for example, that L. kefiranofaciens, a dominant organism in kefir, stands out among the Lactobacilli because it potentially has more amino acid auxotrophies. Using metagenomic analysis of industrial wine fermentations we investigate the role of an inoculated L. plantarum in malolactic fermentation. We observed that L. plantarum thrives better on white than on red wine fermentations and has the largest number of phosphotransferase system among the bacteria observed in the wine communities. Also, L. plantarum together with Pantoea, Erwinia, Asaia, Gluconobacter, and Komagataeibacter genera had the highest number of genes involved in biosynthesis of amino acids.", "keywords": ["0301 basic medicine", "metagenomics", "0303 health sciences", "microbial communities", "Microbial communities", "Wine", "Microbiology", "QR1-502", "Computational biology", "lactic acid bacteria", "03 medical and health sciences", "Kefir", "computational biology", "Lactic acid bacteria", "Metagenomics", "Genomes", "wine", "genomes"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2019.01347"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2019.01347", "name": "item", "description": "10.3389/fmicb.2019.01347", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2019.01347"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-06-25T00:00:00Z"}}, {"id": "10.3390/cells9092026", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-28T16:20:38Z", "type": "Journal Article", "created": "2020-09-03", "title": "Chemical Genetics Approach Identifies Abnormal Inflorescence Meristem 1 as a Putative Target of a Novel Sulfonamide That Protects Catalase2-Deficient Arabidopsis against Photorespiratory Stress", "description": "

Alterations of hydrogen peroxide (H2O2) levels have a profound impact on numerous signaling cascades orchestrating plant growth, development, and stress signaling, including programmed cell death. To expand the repertoire of known molecular mechanisms implicated in H2O2 signaling, we performed a forward chemical screen to identify small molecules that could alleviate the photorespiratory-induced cell death phenotype of Arabidopsisthaliana mutants lacking H2O2-scavenging capacity by peroxisomal catalase2. Here, we report the characterization of pakerine, an m-sulfamoyl benzamide from the sulfonamide family. Pakerine alleviates the cell death phenotype of cat2 mutants exposed to photorespiration-promoting conditions and delays dark-induced senescence in wild-type Arabidopsis leaves. By using a combination of transcriptomics, metabolomics, and affinity purification, we identified abnormal inflorescence meristem 1 (AIM1) as a putative protein target of pakerine. AIM1 is a 3-hydroxyacyl-CoA dehydrogenase involved in fatty acid \u03b2-oxidation that contributes to jasmonic acid (JA) and salicylic acid (SA) biosynthesis. Whereas intact JA biosynthesis was not required for pakerine bioactivity, our results point toward a role for \u03b2-oxidation-dependent SA production in the execution of H2O2-mediated cell death.

", "keywords": ["EXPRESSION", "0106 biological sciences", "0301 basic medicine", "photorespiration", "Cell Respiration", "Meristem", "Arabidopsis", "Cyclopentanes", "catalase2-deficient Arabidopsis", "01 natural sciences", "Article", "ACTIVATION", "catalase2-deficient Arabidopsis", "03 medical and health sciences", "HYDROGEN-PEROXIDE", "Hydroponics", "Gene Expression Regulation", " Plant", "Multienzyme Complexes", "Stress", " Physiological", "Plant Cells", "SALICYLIC-ACID BIOSYNTHESIS", "H2O2 signaling", "Medicine and Health Sciences", "abnormal inflorescence meristem 1", "LEAF SENESCENCE", "Oxylipins", "Photosynthesis", "2. Zero hunger", "QH573-671", "Cell Death", "Arabidopsis Proteins", "Gene Expression Profiling", "Biology and Life Sciences", "Computational Biology", "Hydrogen Peroxide", "ARABIDOPSIS", "MULTIFUNCTIONAL PROTEIN", "3. Good health", "PEROXISOMAL BETA-OXIDATION", "Plant Leaves", "chemical genetics", "CELL-DEATH", "PHENYLALANINE AMMONIA-LYASE", "Seeds", "Cytology", "Salicylic Acid", "H2O2 signaling", "Signal Transduction"]}, "links": [{"href": "http://www.mdpi.com/2073-4409/9/9/2026/pdf"}, {"href": "https://doi.org/10.3390/cells9092026"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Cells", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/cells9092026", "name": "item", "description": "10.3390/cells9092026", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/cells9092026"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-02T00:00:00Z"}}, {"id": "11353/10.2115948", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-28T16:24:04Z", "type": "Journal Article", "created": "2023-10-04", "title": "Bacteria face trade-offs in the decomposition of complex biopolymers", "description": "Abstract

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of system\uffe2\uff80\uff99s complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low- or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes.

Author summary

The decomposition of polysaccharides by microbes is a key process in the global carbon cycle. It requires the joint action of a variety of microbially-produced extracellular enzymes. They can be broadly classified into endo-enzymes, that act in the middle of polymers, and exo-enzymes, that cleave units from polymer ends. Little is known about the benefits for microbes producing a certain enzyme type and the interplay between enzyme producing strategies in mixed communities. This hampers our comprehensive understanding of decomposition in terrestrial and marine ecosystems and thus limits the prediction of decomposition processes, for example in a changing climate.

Based on theoretical modelling, we revealed a fundamental trade-off in the action of these enzymes. While exo-enzymes are more efficient at high substrate conditions, endo-enzymes perform better when substrate is low. Generalists producing both enzymes expand their ecological niche of substrate availability compared to specialists only producing one of the two types. Complementary specialists only co-exist in oligotrophic conditions. We conclude that producing enzymes for specific steps within polymer degradation represents relevant ecological strategies for microbes in decomposer communities.

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups\u2019 biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils.

", "keywords": ["Soil matrix", "2. Zero hunger", "Soil organic matter", "Root Water Uptake", "Trophic cascades", "Ecosystem models", "Computational Biology", "04 agricultural and veterinary sciences", "15. Life on land", "12. Responsible consumption", "Soil food web", "13. Climate action", "Growth rates", "Soil structure", "0401 agriculture", " forestry", " and fisheries", "Ecosystem engineering", "Predator exclusion", "Hydrology", "Engineering sciences. Technology", "info:eu-repo/classification/ddc/610"]}, "links": [{"href": "https://peerj.com/articles/10707.pdf"}, {"href": "https://doi.org/10.7717/peerj.10707"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PeerJ", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.7717/peerj.10707", "name": "item", "description": "10.7717/peerj.10707", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7717/peerj.10707"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-15T00:00:00Z"}}, {"id": "10067/1760850151162165141", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:23:42Z", "type": "Journal Article", "created": "2021-01-15", "title": "KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models\u2014II: model description, implementation and testing", "description": "

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups\u2019 biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils.

", "keywords": ["Soil matrix", "2. Zero hunger", "Soil organic matter", "Root Water Uptake", "Trophic cascades", "Ecosystem models", "Computational Biology", "04 agricultural and veterinary sciences", "15. Life on land", "12. Responsible consumption", "Soil food web", "13. Climate action", "Growth rates", "Soil structure", "0401 agriculture", " forestry", " and fisheries", "Ecosystem engineering", "Predator exclusion", "Hydrology", "Engineering sciences. Technology", "info:eu-repo/classification/ddc/610"]}, "links": [{"href": "https://peerj.com/articles/10707.pdf"}, {"href": "https://doi.org/10067/1760850151162165141"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PeerJ", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10067/1760850151162165141", "name": "item", "description": "10067/1760850151162165141", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10067/1760850151162165141"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-15T00:00:00Z"}}, {"id": "1854/LU-8674409", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-28T16:24:16Z", "type": "Journal Article", "created": "2020-09-03", "title": "Chemical Genetics Approach Identifies Abnormal Inflorescence Meristem 1 as a Putative Target of a Novel Sulfonamide That Protects Catalase2-Deficient Arabidopsis against Photorespiratory Stress", "description": "

Alterations of hydrogen peroxide (H2O2) levels have a profound impact on numerous signaling cascades orchestrating plant growth, development, and stress signaling, including programmed cell death. To expand the repertoire of known molecular mechanisms implicated in H2O2 signaling, we performed a forward chemical screen to identify small molecules that could alleviate the photorespiratory-induced cell death phenotype of Arabidopsisthaliana mutants lacking H2O2-scavenging capacity by peroxisomal catalase2. Here, we report the characterization of pakerine, an m-sulfamoyl benzamide from the sulfonamide family. Pakerine alleviates the cell death phenotype of cat2 mutants exposed to photorespiration-promoting conditions and delays dark-induced senescence in wild-type Arabidopsis leaves. By using a combination of transcriptomics, metabolomics, and affinity purification, we identified abnormal inflorescence meristem 1 (AIM1) as a putative protein target of pakerine. AIM1 is a 3-hydroxyacyl-CoA dehydrogenase involved in fatty acid \u03b2-oxidation that contributes to jasmonic acid (JA) and salicylic acid (SA) biosynthesis. Whereas intact JA biosynthesis was not required for pakerine bioactivity, our results point toward a role for \u03b2-oxidation-dependent SA production in the execution of H2O2-mediated cell death.

", "keywords": ["EXPRESSION", "0106 biological sciences", "0301 basic medicine", "photorespiration", "Cell Respiration", "Meristem", "Arabidopsis", "Cyclopentanes", "catalase2-deficient Arabidopsis", "01 natural sciences", "Article", "ACTIVATION", "catalase2-deficient Arabidopsis", "03 medical and health sciences", "HYDROGEN-PEROXIDE", "Hydroponics", "Gene Expression Regulation", " Plant", "Multienzyme Complexes", "Stress", " Physiological", "Plant Cells", "SALICYLIC-ACID BIOSYNTHESIS", "H2O2 signaling", "Medicine and Health Sciences", "abnormal inflorescence meristem 1", "LEAF SENESCENCE", "Oxylipins", "Photosynthesis", "2. Zero hunger", "QH573-671", "Cell Death", "Arabidopsis Proteins", "Gene Expression Profiling", "Biology and Life Sciences", "Computational Biology", "Hydrogen Peroxide", "ARABIDOPSIS", "MULTIFUNCTIONAL PROTEIN", "3. Good health", "PEROXISOMAL BETA-OXIDATION", "Plant Leaves", "chemical genetics", "CELL-DEATH", "PHENYLALANINE AMMONIA-LYASE", "Seeds", "Cytology", "Salicylic Acid", "H2O2 signaling", "Signal Transduction"]}, "links": [{"href": "http://www.mdpi.com/2073-4409/9/9/2026/pdf"}, {"href": "https://doi.org/1854/LU-8674409"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Cells", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8674409", "name": "item", "description": "1854/LU-8674409", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8674409"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-02T00:00:00Z"}}, {"id": "PMC10322654", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:27:10Z", "type": "Journal Article", "created": "2023-06-24", "title": "enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways", "description": "Abstract Motivation

Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions.

Results

We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule\uffe2\uff80\uff99s strengths for both automatic extraction of optimized reactions rules and automated updating thereof.

Availability and implementation

enviRule code is freely available at https://github.com/zhangky12/enviRule.

", "keywords": ["10120 Department of Chemistry", "Statistics and Probability", "Original Paper", "1303 Biochemistry", "Computational Biology", "Biochemistry", "Computer Science Applications", "Computational Mathematics", "Computational Theory and Mathematics", "13. Climate action", "540 Chemistry", "1312 Molecular Biology", "1706 Computer Science Applications", "2613 Statistics and Probability", "2605 Computational Mathematics", "Molecular Biology", "Biotransformation", "1703 Computational Theory and Mathematics"]}, "links": [{"href": "https://doi.org/PMC10322654"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bioinformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC10322654", "name": "item", "description": "PMC10322654", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC10322654"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-06-24T00:00:00Z"}}, {"id": "PMC5679399", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-28T16:27:14Z", "type": "Journal Article", "created": "2017-11-01", "title": "NDEx 2.0: A Clearinghouse for Research on Cancer Pathways", "description": "Abstract

We present NDEx 2.0, the latest release of the Network Data Exchange (NDEx) online data commons (www.ndexbio.org) and the ways in which it can be used to (i) improve the quality and abundance of biological networks relevant to the cancer research community; (ii) provide a medium for collaboration involving networks; and (iii) facilitate the review and dissemination of networks. We describe innovations addressing the challenges of an online data commons: scalability, data integration, data standardization, control of content and format by authors, and decentralized mechanisms for review. The practical use of NDEx is presented in the context of a novel strategy to foster network-oriented communities of interest in cancer research by adapting methods from academic publishing and social media. Cancer Res; 77(21); e58\uffe2\uff80\uff9361. \uffc2\uffa92017 AACR.