World Data Centre for Microorganisms: an information infrastructure to explore and utilize preserved microbial strains worldwide

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 more than 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.National High Technology Research and Development Program of China [2014AA021501, 2014AA021503, 2015AA020108]; International S&T Cooperation Program of China (ISTCP) [2015DFG32550]; Bureau of Science & Technology for Development of Chinese Academy of Sciences (Strategic bio-resources information center) and Field Cloud Project of Chinese Academy of Sciences [XXH12503-05-01]. Funding for open access charge: National High Technology Research and Development Program of China [2014AA021501, 2014AA021503, 2015AA020108]; International S&T Cooperation Program of China (ISTCP) [2015DFG32550] ; Bureau of Science & Technology for Development of Chinese Academy of Sciences [Strategic bio-resources information center]; Field Cloud Project of Chinese Academy of Sciences [XXH12503-05-01]

Global catalogue of microorganisms (gcm): a comprehensive database and information retrieval, analysis, and visualization system for microbial resources

Abstract Background Throughout the long history of industrial and academic research, many microbes have been isolated, characterized and preserved (whenever possible) in culture collections. With the steady accumulation in observational data of biodiversity as well as microbial sequencing data, bio-resource centers have to function as data and information repositories to serve academia, industry, and regulators on behalf of and for the general public. Hence, the World Data Centre for Microorganisms (WDCM) started to take its responsibility for constructing an effective information environment that would promote and sustain microbial research data activities, and bridge the gaps currently present within and outside the microbiology communities. Description Strain catalogue information was collected from collections by online submission. We developed tools for automatic extraction of strain numbers and species names from various sources, including Genbank, Pubmed, and SwissProt. These new tools connect strain catalogue information with the corresponding nucleotide and protein sequences, as well as to genome sequence and references citing a particular strain. All information has been processed and compiled in order to create a comprehensive database of microbial resources, and was named Global Catalogue of Microorganisms (GCM). The current version of GCM contains information of over 273,933 strains, which includes 43,436bacterial, fungal and archaea species from 52 collections in 25 countries and regions.A number of online analysis and statistical tools have been integrated, together with advanced search functions, which should greatly facilitate the exploration of the content of GCM. Conclusion A comprehensive dynamic database of microbial resources has been created, which unveils the resources preserved in culture collections especially for those whose informatics infrastructures are still under development, which should foster cumulative research, facilitating the activities of microbiologists world-wide, who work in both public and industrial research centres. This database is available from http://gcm.wfcc.info.Peer Reviewe

The global catalogue of microorganisms 10K type strain sequencing project: closing the genomic gaps for the validly published prokaryotic and fungi species

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 microbes. Hence, the GCM aims to promote research by deep-mining genomic data.This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDA19050301), the Bureau of International Cooperation of the Chinese Academy of Sciences (grants 153211KYSB20160029 and 153211KYSB20150010), the National Key Research Program of China (grants 2017YFC1201202, 2016YFC1201303, and 2016YFC0901702), the 13th Five-year Informatization Plan of the Chinese Academy of Sciences (grant XXH13506), and the National Science Foundation for Young Scientists of China (grant 31701157).info:eu-repo/semantics/publishedVersio

Identification of Phase-Separation-Protein-Related Function Based on Gene Ontology by Using Machine Learning Methods

Phase-separation proteins (PSPs) are a class of proteins that play a role in the process of liquid–liquid phase separation, which is a mechanism that mediates the formation of membranelle compartments in cells. Identifying phase separation proteins and their associated function could provide insights into cellular biology and the development of diseases, such as neurodegenerative diseases and cancer. Here, PSPs and non-PSPs that have been experimentally validated in earlier studies were gathered as positive and negative samples. Each protein’s corresponding Gene Ontology (GO) terms were extracted and used to create a 24,907-dimensional binary vector. The purpose was to extract essential GO terms that can describe essential functions of PSPs and build efficient classifiers to identify PSPs with these GO terms at the same time. To this end, the incremental feature selection computational framework and an integrated feature analysis scheme, containing categorical boosting, least absolute shrinkage and selection operator, light gradient-boosting machine, extreme gradient boosting, and permutation feature importance, were used to build efficient classifiers and identify GO terms with classification-related importance. A set of random forest (RF) classifiers with F1 scores over 0.960 were established to distinguish PSPs from non-PSPs. A number of GO terms that are crucial for distinguishing between PSPs and non-PSPs were found, including GO:0003723, which is related to a biological process involving RNA binding; GO:0016020, which is related to membrane formation; and GO:0045202, which is related to the function of synapses. This study offered recommendations for future research aimed at determining the functional roles of PSPs in cellular processes by developing efficient RF classifiers and identifying the representative GO terms related to PSPs

Effects of Cu2O morphology on the performance of CO self-sustained catalytic combustion

Self-sustained catalytic combustion is a sustainable approach to deal with exhaust gas with high concentration CO, and revealing its reaction process is necessary and challenging. Herein, cube (Cu2O-C), octahedron (Cu2O-O) and dodecahedron (Cu2O-D) exposing different crystal planes were used to explore the catalytic combustion mechanism. The catalytic combustion can be self-sustained on the Cu2O surface and the activities decrease in the order of Cu2O-O > Cu2O-D > Cu2O-C, contributing to the different exposing planes with (1 1 1), (1 1 0) and (1 0 0), respectively. In-situ DRIFTS results prove that the catalytic combustion of CO to CO2 on Cu2O is prone to follow the MvK mechanism. Comparing with Cu2O-D and Cu2O-C, the relatively open surface of Cu2O-O plane composed of unsaturated copper and oxygen atoms facilitates the CO adsorption on Cu (I) and the mobility of lattice oxygen, leading to the highest low temperature reducibility and catalytic activity

Self-sustained combustion of CO with transient changes and reaction mechanism over CuCe0.75Zr0.25O delta powder for honeycomb ceramic catalyst

A CuCe0.75Zr0.25O delta catalyst was prepared by the sol-gel method and successfully coated on honeycomb ceramic (HC) carrier. The activity of CuCe0.75Zr0.25O delta/HC was determined by the CO-TPO + FLIR, with the results performing that the critical condition for CO self-sustained combustion is 3 vol% CO + 3 vol% O-2/N-2 at 0.5 L/min. As the CO concentration increases from 1 vol% CO to 3 vol% CO, the induction process ( T-15) shifts to rapid ignition with a transient change for the CO oxidation reaction. The furnace temperature for CO self-sustained combustion decreases with increasing the CO and O-2 concentrations. Upon increasing the CO2 concentration, however, furnace temperature is needed to increase and realize CO complete conversion. The thermal stability test combined with SEM + EDX results indicate that the CuCe0.75Zr0.25O delta/HC retains an excellent thermal stability after a 200 h, and the high-temperature region remains at 225 +/- 1 degrees C during the CO self-combustion reaction. The activity of catalyst is reduced slightly after the 200 h test because of the carbon deposition on the catalyst surface, but such a slight deactivation can be eliminated by the air oxidation method. In situ IR results show a competitive adsorption of CO/O-2 and CO2 on the Cu-Ce active sites, indicating that the addition of gaseous CO2 performs an inhibition of CO oxidation. CO preferentially adsorbs linearly at Cu+ sites to form carbonyls that react with lattice oxygen to produce CO2 to release, which can be ascribed to M-K mechanism. The L-H mechanism is less important, which involves the relatively weak reaction of adsorbed CO and adsorbed oxygen on the Cu-Ce active sites to form carbonate species

Effects of precursor concentration on morphologies of Cu2O micro/nanocrystals and properties of CO self-sustained catalytic combustion

The self-sustained catalytic combustion is one of the most effective ways to remove high concentration CO at low temperature. In this paper, Cu2O micro/nanocrystals with different morphologies were successfully synthesized by changing the precursor concentration using liquid phase reduction method. The obtained Cu2O were characterized using SEM, XRD, XPS, H-2-TPR and O-2-TPD, and the relationship between the catalytic performance and morphology was analyzed based on CO-TPD-MS and activity evaluation results. It was found that high precursor concentration leads to more exposure of active crystal planes of Cu2O. Compared with Cu2O-1 exposing only (100) crystal planes, Cu2O-5, the precursor concentration of which is 5 times of Cu2O-1, exposes (100) and (110) crystal planes. Cu2O-9, with 9 times of precursor concentration of Cu2O-1, exposes (100), (110) and (1 1 1) crystal planes simultaneously. All the obtained Cu2O with different precursor concentrations can achieve self-sustained CO catalytic combustion, and the catalytic activity increases with increasing precursor concentration (Cu2O-1 < Cu2O-5 < Cu2O-9). The results prove that unsaturated coordination of Cu and O on the (1 1 1) and (1 1 0) planes can enhance the corresponding reducibility, adsorption and activation of gaseous oxygen, consequently promoting the CO oxidation to CO2 over Cu2O-9

Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods

Long-term cigarette smoking causes various human diseases, including respiratory disease, cancer, and gastrointestinal (GI) disorders. Alterations in gene expression and variable splicing processes induced by smoking are associated with the development of diseases. This study applied advanced machine learning methods to identify the isoforms with important roles in distinguishing smokers from former smokers based on the expression profile of isoforms from current and former smokers collected in one previous study. These isoforms were deemed as features, which were first analyzed by the Boruta to select features highly correlated with the target variables. Then, the selected features were evaluated by four feature ranking algorithms, resulting in four feature lists. The incremental feature selection method was applied to each list for obtaining the optimal feature subsets and building high-performance classification models. Furthermore, a series of classification rules were accessed by decision tree with the highest performance. Eventually, the rationality of the mined isoforms (features) and classification rules was verified by reviewing previous research. Features such as isoforms ENST00000464835 (expressed by LRRN3), ENST00000622663 (expressed by SASH1), and ENST00000284311 (expressed by GPR15), and pathways (cytotoxicity mediated by natural killer cell and cytokine–cytokine receptor interaction) revealed by the enrichment analysis, were highly relevant to smoking response, suggesting the robustness of our analysis pipeline

Web Resources for Microbial Data

There are multitudes of web resources that are quite useful for the microbial scientific research community. Here, we provide a brief introduction on some of the most notable microbial web resources and an evaluation of them based upon our own user experience