The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.
Due to popular successes (e.g., ChatGPT) Artificial Intelligence (AI) is on everyone's lips today. When advances in biotechnology are combined with advances in AI unprecedented new potential solutions become available. This can help with many global problems and contribute to important Sustainability Development Goals. Current examples include Food Security, Health and Well-being, Clean Water, Clean Energy, Responsible Consumption and Production, Climate Action, Life below Water, or protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. AI is ubiquitous in the life sciences today. Topics include a wide range from machine learning and Big Data analytics, knowledge discovery and data mining, biomedical ontologies, knowledge-based reasoning, natural language processing, decision support and reasoning under uncertainty, temporal and spatial representation and inference, and methodological aspects of explainable AI (XAI) with applications of biotechnology. In this pre-Editorial paper, we provide an overview of open research issues and challenges for each of the topics addressed in this special issue. Potential authors can directly use this as a guideline for developing their paper.
- Klíčová slova
- Artificial Intelligence, Biotechnology, Deep Learning, Digital Transformation, Machine Learning,
- MeSH
- biotechnologie MeSH
- data mining MeSH
- ekosystém * MeSH
- umělá inteligence * MeSH
- znalostní báze MeSH
- Publikační typ
- úvodní články MeSH
MOTIVATION: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only. RESULTS: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network's topology and the update logic (obtained through, e.g. a biological knowledge base or a literature search), as well as further assumptions about the properties of the network's transitions (e.g. the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an 'initial' sketch, which is extended by adding restrictions representing experimental data to a 'data-informed' sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data. AVAILABILITY AND IMPLEMENTATION: All software and data are freely available as a reproducible artefact at https://doi.org/10.5281/zenodo.7688740.
The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard.
- Klíčová slova
- Data management plan, Machine-actionable data management plan, Ontology, Semantic web technologies,
- MeSH
- bio-ontologie * MeSH
- data management * MeSH
- řízený slovník MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Verticillium nonalfalfae (V. nonalfalfae) is one of the most problematic hop (Humulus lupulus L.) pathogens, as the highly virulent fungal pathotypes cause severe annual yield losses due to infections of entire hop fields. In recent years, the RNA interference (RNAi) mechanism has become one of the main areas of focus in plant-fungal pathogen interaction studies and has been implicated as one of the major contributors to fungal pathogenicity. MicroRNA-like RNAs (milRNAs) have been identified in several important plant pathogenic fungi; however, to date, no milRNA has been reported in the V. nonalfalfae species. In the present study, using a high-throughput sequencing approach and extensive bioinformatics analysis, a total of 156 milRNA precursors were identified in the annotated V. nonalfalfae genome, and 27 of these milRNA precursors were selected as true milRNA candidates, with appropriate microRNA hairpin secondary structures. The stem-loop RT-qPCR assay was used for milRNA validation; a total of nine V. nonalfalfae milRNAs were detected, and their expression was confirmed. The milRNA expression patterns, determined by the absolute quantification approach, imply that milRNAs play an important role in the pathogenicity of highly virulent V. nonalfalfae pathotypes. Computational analysis predicted milRNA targets in the V. nonalfalfae genome and in the host hop transcriptome, and the activity of milRNA-mediated RNAi target cleavage was subsequently confirmed for two selected endogenous fungal target gene models using the 5' RLM-RACE approach.
- Klíčová slova
- RNA interference, Verticillium nonalfalfae, fungal pathogen, microRNA-like RNAs, plant-pathogen interactions,
- MeSH
- Ascomycota genetika MeSH
- fungální RNA * MeSH
- fylogeneze MeSH
- genová ontologie MeSH
- interakce hostitele a patogenu MeSH
- konformace nukleové kyseliny MeSH
- kvantitativní polymerázová řetězová reakce MeSH
- malá nekódující RNA genetika MeSH
- mikro RNA genetika MeSH
- nemoci rostlin mikrobiologie MeSH
- regulace genové exprese u hub MeSH
- reprodukovatelnost výsledků MeSH
- stanovení celkové genové exprese MeSH
- výpočetní biologie metody MeSH
- vysoce účinné nukleotidové sekvenování * MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- fungální RNA * MeSH
- malá nekódující RNA MeSH
- mikro RNA MeSH
The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.
- MeSH
- anotace sekvence * MeSH
- databáze proteinů * MeSH
- datové soubory jako téma MeSH
- DNA genetika metabolismus MeSH
- genová ontologie MeSH
- internet MeSH
- lidé MeSH
- RNA genetika metabolismus MeSH
- sekvence aminokyselin MeSH
- software * MeSH
- vazba proteinů MeSH
- vnitřně neuspořádané proteiny chemie genetika metabolismus MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Názvy látek
- DNA MeSH
- RNA MeSH
- vnitřně neuspořádané proteiny MeSH
Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.
- MeSH
- anotace sekvence MeSH
- B-lymfocyty cytologie metabolismus MeSH
- dendritické buňky cytologie metabolismus MeSH
- endoteliální buňky cytologie metabolismus MeSH
- erytroblasty cytologie metabolismus MeSH
- genetická heterogenita * MeSH
- genová ontologie MeSH
- hepatocyty cytologie metabolismus MeSH
- játra cytologie metabolismus MeSH
- Kupfferovy buňky cytologie metabolismus MeSH
- makrofágy cytologie metabolismus MeSH
- myši inbrední C57BL MeSH
- myši MeSH
- neutrofily cytologie metabolismus MeSH
- stanovení celkové genové exprese MeSH
- transkriptom * MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
N6-methyladenosine (m6A) and N6,2'-O-dimethyladenosine (m6Am) are two abundant modifications found in mRNAs and ncRNAs that can regulate multiple aspects of RNA biology. They function mainly by regulating interactions with specific RNA-binding proteins. Both modifications are linked to development, disease and stress response. To date, three methyltransferases and two demethylases have been identified that modify adenosines in mammalian mRNAs. Here, we present a comprehensive analysis of the interactomes of these enzymes. PCIF1 protein network comprises mostly factors involved in nascent RNA synthesis by RNA polymerase II, whereas ALKBH5 is closely linked with most aspects of pre-mRNA processing and mRNA export to the cytoplasm. METTL16 resides in subcellular compartments co-inhabited by several other RNA modifiers and processing factors. FTO interactome positions this demethylase at a crossroad between RNA transcription, RNA processing and DNA replication and repair. Altogether, these enzymes share limited spatial interactomes, pointing to specific molecular mechanisms of their regulation.
- MeSH
- adaptorové proteiny signální transdukční genetika metabolismus MeSH
- adenosin analogy a deriváty metabolismus MeSH
- alfa-ketoglutarát-dependentní dioxygenasa, AlkB homolog 5 genetika metabolismus MeSH
- anotace sekvence MeSH
- gen pro FTO genetika metabolismus MeSH
- genetická transkripce MeSH
- genová ontologie MeSH
- HEK293 buňky MeSH
- jaderné proteiny genetika metabolismus MeSH
- lidé MeSH
- mapování interakce mezi proteiny MeSH
- messenger RNA genetika metabolismus MeSH
- methyltransferasy genetika metabolismus MeSH
- N-demethylasy genetika metabolismus MeSH
- nekódující RNA genetika metabolismus MeSH
- oprava DNA MeSH
- protein - isoformy genetika metabolismus MeSH
- replikace DNA MeSH
- vazba proteinů MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- adaptorové proteiny signální transdukční MeSH
- adenosin MeSH
- alfa-ketoglutarát-dependentní dioxygenasa, AlkB homolog 5 MeSH
- ALKBH5 protein, human MeSH Prohlížeč
- FTO protein, human MeSH Prohlížeč
- gen pro FTO MeSH
- jaderné proteiny MeSH
- messenger RNA MeSH
- methyltransferasy MeSH
- METTL16 protein, human MeSH Prohlížeč
- N-demethylasy MeSH
- N-methyladenosine MeSH Prohlížeč
- N(6),N(6)-dimethyladenosine MeSH Prohlížeč
- nekódující RNA MeSH
- PCIF1 protein, human MeSH Prohlížeč
- protein - isoformy MeSH
The wide-spread use of Common Data Models and information models in biomedical informatics encourages assumptions that those models could provide the entirety of what is needed for knowledge representation purposes. Based on the lack of computable semantics in frequently used Common Data Models, there appears to be a gap between knowledge representation requirements and these models. In this use-case oriented approach, we explore how a system-theoretic, architecture-centric, ontology-based methodology can help to better understand this gap. We show how using the Generic Component Model helps to analyze the data management system in a way that allows accounting for data management procedures inside the system and knowledge representation of the real world at the same time.
- Klíčová slova
- Biomedical Ontologies, Information Models, Knowledge Representation, Systems Theory, eHealth,
- MeSH
- bio-ontologie * MeSH
- data management MeSH
- sémantika * MeSH
- Publikační typ
- časopisecké články MeSH
Extracellular vesicles are thought to facilitate pathogen transmission from arthropods to humans and other animals. Here, we reveal that pathogen spreading from arthropods to the mammalian host is multifaceted. Extracellular vesicles from Ixodes scapularis enable tick feeding and promote infection of the mildly virulent rickettsial agent Anaplasma phagocytophilum through the SNARE proteins Vamp33 and Synaptobrevin 2 and dendritic epidermal T cells. However, extracellular vesicles from the tick Dermacentor andersoni mitigate microbial spreading caused by the lethal pathogen Francisella tularensis. Collectively, we establish that tick extracellular vesicles foster distinct outcomes of bacterial infection and assist in vector feeding by acting on skin immunity. Thus, the biology of arthropods should be taken into consideration when developing strategies to control vector-borne diseases.
- MeSH
- Anaplasma phagocytophilum patogenita MeSH
- bakteriální infekce imunologie metabolismus MeSH
- buněčné linie MeSH
- členovci metabolismus mikrobiologie fyziologie MeSH
- Dermacentor metabolismus mikrobiologie fyziologie MeSH
- extracelulární vezikuly metabolismus ultrastruktura MeSH
- Francisella tularensis patogenita MeSH
- genová ontologie MeSH
- intravitální mikroskopie MeSH
- klíšťata metabolismus mikrobiologie MeSH
- klíště metabolismus mikrobiologie fyziologie MeSH
- kůže imunologie mikrobiologie parazitologie MeSH
- lidé MeSH
- membránový protein 2 asociovaný s vezikuly metabolismus MeSH
- myši inbrední C57BL MeSH
- myši knockoutované MeSH
- myši MeSH
- proteiny R-SNARE metabolismus MeSH
- proteomika MeSH
- T-lymfocyty metabolismus MeSH
- tandemová hmotnostní spektrometrie MeSH
- transmisní elektronová mikroskopie MeSH
- zánět imunologie metabolismus parazitologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Názvy látek
- membránový protein 2 asociovaný s vezikuly MeSH
- proteiny R-SNARE MeSH
