RESUMEN
Influenza viruses undergo frequent genomic mutations, leading to potential cross-species transmission, phenotypic changes, and challenges in diagnostic reagents and vaccines. Accurately evaluating and predicting the risk of such variations remain significant challenges. To address this, we developed the VarEPS-Influ database, an influenza virus variations risk evaluation system (VarEPS-Influ). This database employs a 'multi-dimensional evaluation of mutations' strategy, utilizing various tools to assess the physical and chemical properties, primary, secondary, and tertiary structures, receptor affinity, antibody binding capacity, antigen epitopes, and other aspects of the variation's impact. Additionally, we consider space-time distribution, host species distribution, pedigree analysis, and frequency of mutations to provide a comprehensive risk evaluation of mutations and viruses. The VarEPS-Influ database evaluates both observed variations and virtual variations (variations that have not yet occurred), thereby addressing the time-lag issue in risk predictions. Our current one-stop evaluation system for influenza virus genomic variation integrates 1065290 sequences from 224 927 Influenza A, B and C isolates retrieved from public resources. Researchers can freely access the data at https://nmdc.cn/influvar/.
Asunto(s)
Bases de Datos Genéticas , Gripe Humana , Orthomyxoviridae , Humanos , Anticuerpos/genética , Epítopos , Glicoproteínas Hemaglutininas del Virus de la Influenza/genética , Gripe Humana/epidemiología , Gripe Humana/virología , Mutación , Orthomyxoviridae/genética , Variación Genética , Genoma Viral , Medición de RiesgoRESUMEN
Here, we present the manually curated Global Catalogue of Pathogens (gcPathogen), an extensive genomic resource designed to facilitate rapid and accurate pathogen analysis, epidemiological exploration and monitoring of antibiotic resistance features and virulence factors. The catalogue seamlessly integrates and analyzes genomic data and associated metadata for human pathogens isolated from infected patients, animal hosts, food and the environment. The pathogen list is supported by evidence from medical or government pathogenic lists and publications. The current version of gcPathogen boasts an impressive collection of 1 164 974 assemblies comprising 986 044 strains from 497 bacterial taxa, 4794 assemblies encompassing 4319 strains from 265 fungal taxa, 89 965 assemblies featuring 13 687 strains from 222 viral taxa, and 646 assemblies including 387 strains from 159 parasitic taxa. Through this database, researchers gain access to a comprehensive 'one-stop shop' that facilitates global, long-term public health surveillance while enabling in-depth analysis of genomes, sequence types, antibiotic resistance genes, virulence factors and mobile genetic elements across different countries, diseases and hosts. To access and explore the data and statistics, an interactive web interface has been developed, which can be accessed at https://nmdc.cn/gcpathogen/. This user-friendly platform allows seamless querying and exploration of the extensive information housed within the gcPathogen database.
Asunto(s)
Bases de Datos Genéticas , Infecciones , Salud Pública , Humanos , Genoma Bacteriano/genética , Genómica , Factores de Virulencia/genética , Infecciones/microbiología , Infecciones/parasitología , Infecciones/virología , AnimalesRESUMEN
Fungal taxonomy is a complex and rapidly changing subject, which makes proper naming of fungi challenging for taxonomists. A registration platform with a standardized and information-integrated database is a powerful tool for efficient research on fungal taxonomy. Fungal Names (FN, https://nmdc.cn/fungalnames/; launched in 2011) is one of the three official fungal nomenclatural repositories authorized by the International Nomenclature Committee for Fungi (NCF). Currently, FN includes >567 000 taxon names from >10 000 related journals and books published since 1596 and covers >147 000 collection records of type specimens/illustrations from >5000 preserving agencies. FN is also a knowledge base that integrates nomenclature information with specimens, culture collections and herbaria/fungaria, publications and taxonomists, and represents a summary of the history and recent advances in fungal taxonomy. Published fungal names are categorized based on well-accepted nomenclature rules and can be readily searched with different keywords and strategies. In combination with a standardized name checking tool and a sequence alignment-based identification package, FN makes the registration and typification of nomenclatural novelties of fungi convenient and accurate.
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Hongos , Bases del Conocimiento , Manejo de Datos , Bases de Datos Factuales , Alineación de Secuencia , Hongos/clasificación , Terminología como AsuntoRESUMEN
The genomic variations of SARS-CoV-2 continue to emerge and spread worldwide. Some mutant strains show increased transmissibility and virulence, which may cause reduced protection provided by vaccines. Thus, it is necessary to continuously monitor and analyze the genomic variations of SARS-COV-2 genomes. We established an evaluation and prewarning system, SARS-CoV-2 variations evaluation and prewarning system (VarEPS), including known and virtual mutations of SARS-CoV-2 genomes to achieve rapid evaluation of the risks posed by mutant strains. From the perspective of genomics and structural biology, the database comprehensively analyzes the effects of known variations and virtual variations on physicochemical properties, translation efficiency, secondary structure, and binding capacity of ACE2 and neutralizing antibodies. An AI-based algorithm was used to verify the effectiveness of these genomics and structural biology characteristic quantities for risk prediction. This classifier could be further used to group viral strains by their transmissibility and affinity to neutralizing antibodies. This unique resource makes it possible to quickly evaluate the variation risks of key sites, and guide the research and development of vaccines and drugs. The database is freely accessible at www.nmdc.cn/ncovn.
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COVID-19/virología , Bases de Datos Factuales , Mutación , SARS-CoV-2/genética , Algoritmos , Enzima Convertidora de Angiotensina 2/metabolismo , Anticuerpos Neutralizantes/metabolismo , Inteligencia Artificial , Cartilla de ADN , Genoma Viral , HumanosRESUMEN
Taxonomic and functional research of microorganisms has increasingly relied upon genome-based data and methods. As the depository of the Global Catalogue of Microorganisms (GCM) 10K prokaryotic type strain sequencing project, Global Catalogue of Type Strain (gcType) has published 1049 type strain genomes sequenced by the GCM 10K project which are preserved in global culture collections with a valid published status. Additionally, the information provided through gcType includes >12 000 publicly available type strain genome sequences from GenBank incorporated using quality control criteria and standard data annotation pipelines to form a high-quality reference database. This database integrates type strain sequences with their phenotypic information to facilitate phenotypic and genotypic analyses. Multiple formats of cross-genome searches and interactive interfaces have allowed extensive exploration of the database's resources. In this study, we describe web-based data analysis pipelines for genomic analyses and genome-based taxonomy, which could serve as a one-stop platform for the identification of prokaryotic species. The number of type strain genomes that are published will continue to increase as the GCM 10K project increases its collaboration with culture collections worldwide. Data of this project is shared with the International Nucleotide Sequence Database Collaboration. Access to gcType is free at http://gctype.wdcm.org/.
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Bases de Datos Genéticas , Genoma , Filogenia , Células Procariotas/metabolismo , Investigación , Secuencia de Bases , Análisis de Datos , ARN Ribosómico 16S/genéticaRESUMEN
Meta-omics approaches have been increasingly used to study the structure and function of the microbial communities. A variety of large-scale collaborative projects are being conducted to encompass samples from diverse environments and habitats. This change has resulted in enormous demands for long-term data maintenance and capacity for data analysis. The Global Catalogue of Metagenomics (gcMeta) is a part of the 'Chinese Academy of Sciences Initiative of Microbiome (CAS-CMI)', which focuses on studying the human and environmental microbiome, establishing depositories of samples, strains and data, as well as promoting international collaboration. To accommodate and rationally organize massive datasets derived from several thousands of human and environmental microbiome samples, gcMeta features a database management system for archiving and publishing data in a standardized way. Another main feature is the integration of more than ninety web-based data analysis tools and workflows through a Docker platform which enables data analysis by using various operating systems. This platform has been rapidly expanding, and now hosts data from the CAS-CMI and a number of other ongoing research projects. In conclusion, this platform presents a powerful and user-friendly service to support worldwide collaborative efforts in the field of meta-omics research. This platform is freely accessible at https://gcmeta.wdcm.org/.
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Bases de Datos Genéticas , Metagenoma , Metagenómica/métodos , Microbiota , Programas Informáticos , Metagenómica/normas , Estándares de ReferenciaRESUMEN
The World Data Centre for Microorganisms (WDCM) was established 50 years ago as the data center of the World Federation for Culture Collections (WFCC)-Microbial Resource Center (MIRCEN). WDCM aims to provide integrated information services using big data technology for microbial resource centers and microbiologists all over the world. Here, we provide an overview of WDCM including all of its integrated services. Culture Collections Information Worldwide (CCINFO) provides metadata information on 708 culture collections from 72 countries and regions. Global Catalogue of Microorganism (GCM) gathers strain catalogue information and provides a data retrieval, analysis, and visualization system of microbial resources. Currently, GCM includes >368 000 strains from 103 culture collections in 43 countries and regions. Analyzer of Bioresource Citation (ABC) is a data mining tool extracting strain related publications, patents, nucleotide sequences and genome information from public data sources to form a knowledge base. Reference Strain Catalogue (RSC) maintains a database of strains listed in International Standards Organization (ISO) and other international or regional standards. RSC allocates a unique identifier to strains recommended for use in diagnosis and quality control, and hence serves as a valuable cross-platform reference. WDCM provides free access to all these services at www.wdcm.org.
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Biología Computacional/métodos , Bases de Datos Factuales , Microbiología , Microbiota , Programas Informáticos , Biodiversidad , Minería de Datos , Metagenómica/métodos , Filogenia , Navegador Web , Flujo de TrabajoRESUMEN
Pan-genomics is one of the most powerful means to study genomic variation and obtain a sketch of genes within a defined clade of species. Though there are a lot of computational tools to achieve this, an integrated framework to evaluate their performance and offer the best choice to users has never been achieved. To ease the process of large-scale prokaryotic genome analysis, we introduce Integrated Prokaryotes Genome and pan-genome Analysis (IPGA), a one-stop web service to analyze, compare, and visualize pan-genome as well as individual genomes, that rids users of installing any specific tools. IPGA features a scoring system that helps users to evaluate the reliability of pan-genome profiles generated by different packages. Thus, IPGA can help users ascertain the profiling method that is most suitable for their data set for the following analysis. In addition, IPGA integrates several downstream comparative analysis and genome analysis modules to make users achieve diverse targets.
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We present a method of mapping data from publicly available genomics and publication resources to the Resource Description Framework (RDF) and implement a server to publish linked open data (LOD). As one of the largest and most comprehensive semantic databases about coronaviruses, the resulted gcCov database demonstrates the capability of using data in the LOD framework to promote correlations between genotypes and phenotypes. These correlations will be helpful for future research on fundamental viral mechanisms and drug and vaccine designs. These LOD with 62,168,127 semantic triplets and their visualizations are freely accessible through gcCov at https://nmdc.cn/gccov/.
RESUMEN
Genomic information is essential for taxonomic, phylogenetic, and functional studies to comprehensively decipher the characteristics of microorganisms, to explore microbiomes through metagenomics, and to answer fundamental questions of nature and human life. However, large gaps remain in the available genomic sequencing information published for bacterial and archaeal species, and the gaps are even larger for fungal type strains. The Global Catalogue of Microorganisms (GCM) leads an internationally coordinated effort to sequence type strains and close gaps in the genomic maps of microorganisms. Hence, the GCM aims to promote research by deep-mining genomic data.