PathBank 2.0-the pathway database for model organism metabolomics.

PathBank (https://pathbank.org) and its predecessor database, the Small Molecule Pathway Database (SMPDB), have been providing comprehensive metabolite pathway information for the metabolomics community since 2010. Over the past 14 years, these pathway databases have grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in computing technology. This year's update, PathBank 2.0, brings a number of important improvements and upgrades that should make the database more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of primary or canonical pathways (from 1720 to 6951); (ii) a massive increase in the total number of pathways (from 110 234 to 605 359); (iii) significant improvements to the quality of pathway diagrams and pathway descriptions; (iv) a strong emphasis on drug metabolism and drug mechanism pathways; (v) making most pathway images more slide-compatible and manuscript-compatible; (vi) adding tools to support better pathway filtering and selecting through a more complete pathway taxonomy; (vii) adding pathway analysis tools for visualizing and calculating pathway enrichment. Many other minor improvements and updates to the content, the interface and general performance of the PathBank website have also been made. Overall, we believe these upgrades and updates should greatly enhance PathBank's ease of use and its potential applications for interpreting metabolomics data.

PathBank: a comprehensive pathway database for model organisms.

PathBank (www.pathbank.org) is a new, comprehensive, visually rich pathway database containing more than 110 000 machine-readable pathways found in 10 model organisms (Homo sapiens, Bos taurus, Rattus norvegicus, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, Escherichia coli and Pseudomonas aeruginosa). PathBank aims to provide a pathway for every protein and a map for every metabolite. This resource is designed specifically to support pathway elucidation and pathway discovery in transcriptomics, proteomics, metabolomics and systems biology. It provides detailed, fully searchable, hyperlinked diagrams of metabolic, metabolite signaling, protein signaling, disease, drug and physiological pathways. All PathBank pathways include information on the relevant organs, organelles, subcellular compartments, cofactors, molecular locations, chemical structures and protein quaternary structures. Each small molecule is hyperlinked to the rich data contained in public chemical databases such as HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. All PathBank pathways are accompanied with references and detailed descriptions which provide an overview of the pathway, condition or processes depicted in each diagram. Every PathBank pathway is downloadable in several machine-readable and image formats including BioPAX, SBML, PWML, SBGN, RXN, PNG and SVG. PathBank also supports community annotations and submissions through the web-based PathWhiz pathway illustrator. The vast majority of PathBank's pathways (>95%) are not found in any other public pathway database.

A Web Tool for Generating High Quality Machine-readable Biological Pathways.

PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to generate over 2,000 pathway diagrams, which are now found in many online databases including HMDB, DrugBank, SMPDB, and ECMDB.

Random shearing as an alternative to digestion for mitochondrial DNA processing in droplet digital PCR.

Droplet digital PCR (ddPCR) is a quantitative assay that requires DNA fragmentation to maximize reaction efficiency. Here, we measured the proportion of mitochondrial DNA (mtDNA) carrying the "common deletion," a rare event, to compare quantification sensitivities between alternative DNA fragmentation methods (sonication and QIAshredder spin columns) against enzymatic digestion (traditionally used). QIAshredder showed the highest sensitivity when compared to sonication, followed by digestion. Also, both sonication and QIAshredder fragmentation had shorter processing times than enzymatic digestion; therefore, QIAshredder fragmentation and sonication are alternative DNA processing methods that maximize ddPCR quantification for the detection of rare events.

Bacteremia and Skin Infections in Four Patients Caused by Helicobacter-Like Organisms.

BACKGROUND: Enterohepatic Helicobacter-like organisms (HLO) have been recognized as causes of human infection since 1984, primarily as a cause of bacteremia and cellulitis in immunocompromised individuals, but the spectrum of illness due to HLO has expanded based on numerous reports from Japan. METHODS: We report 4 epidemiologically unrelated immunocompetent patients with HLO bacteremia diagnosed within a 2-year period. Three patients had cellulitis and 1 patient had unexplained fever. 16S ribosomal deoxyribonucleic acid (rDNA) sequence analysis of 2 isolates suggested that they were Helicobacter cinaedi, and whole-genome sequencing showed that they differed only slightly from reference strains. CONCLUSIONS: We believe that this syndrome is more common than reported, but it is easily overlooked because the skin lesions resemble streptococcal cellulitis and respond very rapidly to ß-lactam antibiotics, and the organism is difficult to isolate from the blood. All HLO in our series were isolated from blood using the ESP system and were not detected in 2 other widely used commercial blood culture systems.

YMDB 2.0: a significantly expanded version of the yeast metabolome database.

YMDB or the Yeast Metabolome Database (http://www.ymdb.ca/) is a comprehensive database containing extensive information on the genome and metabolome of Saccharomyces cerevisiae Initially released in 2012, the YMDB has gone through a significant expansion and a number of improvements over the past 4 years. This manuscript describes the most recent version of YMDB (YMDB 2.0). More specifically, it provides an updated description of the database that was previously described in the 2012 NAR Database Issue and it details many of the additions and improvements made to the YMDB over that time. Some of the most important changes include a 7-fold increase in the number of compounds in the database (from 2007 to 16 042), a 430-fold increase in the number of metabolic and signaling pathway diagrams (from 66 to 28 734), a 16-fold increase in the number of compounds linked to pathways (from 742 to 12 733), a 17-fold increase in the numbers of compounds with nuclear magnetic resonance or MS spectra (from 783 to 13 173) and an increase in both the number of data fields and the number of links to external databases. In addition to these database expansions, a number of improvements to YMDB's web interface and its data visualization tools have been made. These additions and improvements should greatly improve the ease, the speed and the quantity of data that can be extracted, searched or viewed within YMDB. Overall, we believe these improvements should not only improve the understanding of the metabolism of S. cerevisiae, but also allow more in-depth exploration of its extensive metabolic networks, signaling pathways and biochemistry.

Cancer Metabolomics and the Human Metabolome Database.

The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world's largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer.

Cell-free mitochondrial DNA in CSF is associated with early viral rebound, inflammation, and severity of neurocognitive deficits in HIV infection.

Cell-free mitochondiral DNA (mtDNA) is an immunogenic molecule associated with many inflammatory conditions. We evaluated the relationship between cell-free mtDNA in cerebrospinal fluid (CSF) and neurocognitive performance and inflammation during HIV infection. In a cross-sectional analysis, we evaluated the association of mtDNA levels with clinical assessments, inflammatory markers, and neurocognitive performance in 28 HIV-infected individuals. In CSF, we measured mtDNA levels by droplet digital PCR, and soluble CD14 and CD163, neurofilament light, and neopterin by ELISA. In blood and CSF, we measured soluble IP-10, MCP-1, TNF-α, and IL-6 by ELISA, and intracellular expression of IL-2, IFN-γ, and TNF-α in CD4(+) and CD8(+) T cells by flow cytometry. We also evaluated the relationship between CSF pleocytosis and mtDNA longitudinally in another set of five individuals participating in an antiretroviral treatment (ART) interruption study. Cell-free CSF mtDNA levels strongly correlated with neurocognitive performance among individuals with neurocognitive impairment (NCI) (r = 0.77, p = 0.001). CSF mtDNA also correlated with levels of IP-10 in CSF (r = 0.70, p = 0.007) and MCP-1 in blood plasma (r = 0.66, p = 0.01) in individuals with NCI. There were no significant associations between inflammatory markers and mtDNA in subjects without NCI, and levels of mtDNA did not differ between subjects with and without NCI. MtDNA levels preceded pleocytosis and HIV RNA following ART interruption. Cell-free mtDNA in CSF was strongly associated with the severity of neurocognitive dysfunction and inflammation only in individuals with NCI. Our findings suggest that within a subset of subjects cell-free CSF mtDNA is associated with inflammation and degree of NCI.