WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.

WikiPathways (https://www.wikipathways.org) is a biological pathway database known for its collaborative nature and open science approaches. With the core idea of the scientific community developing and curating biological knowledge in pathway models, WikiPathways lowers all barriers for accessing and using its content. Increasingly more content creators, initiatives, projects and tools have started using WikiPathways. Central in this growth and increased use of WikiPathways are the various communities that focus on particular subsets of molecular pathways such as for rare diseases and lipid metabolism. Knowledge from published pathway figures helps prioritize pathway development, using optical character and named entity recognition. We show the growth of WikiPathways over the last three years, highlight the new communities and collaborations of pathway authors and curators, and describe various technologies to connect to external resources and initiatives. The road toward a sustainable, community-driven pathway database goes through integration with other resources such as Wikidata and allowing more use, curation and redistribution of WikiPathways content.

The concept of encapsulated-cell therapy is very appealing, but in practice a great deal of technology and know-how is needed for the production of long-term functional transplants. Alginate is one of the most promising biomaterials for immunoisolation of allogeneic and xenogeneic cells and tissues (such as Langerhans islets). Although great advances in alginate-based cell encapsulation have been reported, several improvements need to be made before routine clinical applications can be considered. Among these is the production of purified alginates with consistently high transplantation-grade quality. This depends to a great extent on the purity of the input algal source as well as on the development of alginate extraction and purification processes that can be validated. A key engineering challenge in designing immunoisolating alginate-based microcapsules is that of maintaining unimpeded exchange of nutrients, oxygen and therapeutic factors (released by the encapsulated cells), while simultaneously avoiding swelling and subsequent rupture of the microcapsules. This requires the development of efficient, validated and well-documented technology for cross-linking alginates with divalent cations. Clinical applications also require validated technology for long-term cryopreservation of encapsulated cells to maintaining a product inventory in order to meet end-user demands. As shown here these demands could be met by the development of novel, validated technologies for production of transplantation-grade alginate and microcapsule engineering and storage. The advances in alginate-based therapy are demonstrated by transplantation of encapsulated rat and human islet grafts that functioned properly for about 1 year in diabetic mice.

Volume changes of human T-lymphocytes (Jurkat line) exposed to hypotonic carbohydrate-substituted solutions of different composition and osmolality were studied by videomicroscopy. In 200 mOsm media the cells first swelled within 1-2 min and then underwent regulatory volume decrease (RVD) to their original isotonic volume within 10-15 min. RVD also occurred in strongly hypotonic 100 mOsm solutions of di- and trisaccharides (trehalose, sucrose, raffinose). In contrast to oligosaccharide media, 100 mOsm solutions of monomeric carbohydrates (glucose, galactose, inositol and sorbitol) inhibited RVD. The complex volumetric data were analyzed with a membrane transport model that allowed the estimation of the hydraulic conductivity and volume-dependent solute permeabilities. We found that under slightly hypotonic stress (200 mOsm) the cell membrane was impermeable to all carbohydrates studied here. Upon osmolality decrease to 100 mOsm, the membrane permeability to monomeric carbohydrates increased dramatically (apparently due to channel activation caused by extensive cell swelling), whereas oligosaccharide permeability remained very poor. The size-selectivity of the swelling-activated sugar permeation was confirmed by direct chromatographic measurements of intracellular sugars. The results of this study are of interest for biotechnology, where sugars and related compounds are increasingly being used as potential cryo- and lyoprotective agents for preservation of rare and valuable mammalian cells and tissues.

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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.

Rett syndrome (RTT) is a rare disease but still one of the most abundant causes for intellectual disability in females. Typical symptoms are onset at month 6–18 after normal pre- and postnatal development, loss of acquired skills and severe intellectual disability. The type and severity of symptoms are individually highly different. A single mutation in one gene, coding for methyl-CpG-binding protein 2 (MECP2), is responsible for the disease. The most important action of MECP2 is regulating epigenetic imprinting and chromatin condensation, but MECP2 influences many different biological pathways on multiple levels although the molecular pathways from gene to phenotype are currently not fully understood. In this review the known changes in metabolite levels, gene expression and biological pathways in RTT are summarized, discussed how they are leading to some characteristic RTT phenotypes and therefore the gaps of knowledge are identified. Namely, which phenotypes have currently no mechanistic explanation leading back to MECP2 related pathways? As a result of this review the visualization of the biologic pathways showing MECP2 up- and downstream regulation was developed and published on WikiPathways which will serve as template for future omics data driven research. This pathway driven approach may serve as a use case for other rare diseases, too.

Increasing amounts of systems toxicology data, including omics results, are becoming publically available and accessible in databases. Data-driven and informatics-tool supported pipeline schemas for fitting such data into Adverse Outcome Pathway (AOP) descriptions could potentially aid the development of nonanimal-based hazard and risk assessment methods. We devised a 6-step workflow that integrated diverse types of toxicology data into a novel AOP scheme for pulmonary fibrosis. Mining of literature references and diverse data sources covering previous pathway descriptions and molecular results were coupled in a stepwise manner with informatics tools applications that enabled gene linkage and pathway identification in molecular interaction maps. Ultimately, a network of functional elements coupled 64 pulmonary fibrosis-associated genes into a novel, open-source AOP-linked molecular pathway, now available for commenting and improvements in WikiPathways (WP3624). Applying in silico-based knowledge extraction and modeling, the pipeline enabled screening and fusion of many different complex data types, including the integration of omics results. Overall, the taken, stepwise approach should be generally useful to construct novel AOP descriptions as well as to enrich developing AOP descriptions in progress.