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Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. We demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low. This AMR metadata collection is freely available and maintained on the Bacterial and Viral Bioinformatics Center (BV-BRC) FTP site ftp://ftp.bvbrc.org/RELEASE_NOTES/PATRIC_genomes_AMR.txt.

The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other ‘omic’ data analyses. In response to mounting concern over antimicrobial resistance (AMR), the PATRIC team has been developing new tools that help researchers understand AMR and its genetic determinants. To support comparative analyses, we have added AMR phenotype data to over 15 000 genomes in the PATRIC database, often assembling genomes from reads in public archives and collecting their associated AMR panel data from the literature to augment the collection. We have also been using this collection of AMR metadata to build machine learning-based classifiers that can predict the AMR phenotypes and the genomic regions associated with resistance for genomes being submitted to the annotation service. Likewise, we have undertaken a large AMR protein annotation effort by manually curating data from the literature and public repositories. This collection of 7370 AMR reference proteins, which contains many protein annotations (functional roles) that are unique to PATRIC and RAST, has been manually curated so that it projects stably across genomes. The collection currently projects to 1 610 744 proteins in the PATRIC database. Finally, the PATRIC Web site has been expanded to enable AMR-based custom page views so that researchers can easily explore AMR data and design experiments based on whole genomes or individual genes.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data. National Institute of Allergy and Infectious Diseases (NIAID)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Allergy & Infectious Diseases (NIAID) [HHSN272201400027C]; NIAIDUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Allergy & Infectious Diseases (NIAID) National Institute of Allergy and Infectious Diseases (NIAID) [HHSN272201400027C to R.S.]. Funding for open access charge: NIAID.

In the "big data" era, research biologists are faced with analyzing new types that usually require some level of computational expertise. A number of programs and pipelines exist, but acquiring the expertise to run them, and then understanding the output can be a challenge.The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org ) has created an end-to-end analysis platform that allows researchers to take their raw reads, assemble a genome, annotate it, and then use a suite of user-friendly tools to compare it to any public data that is available in the repository. With close to 113,000 bacterial and more than 1000 archaeal genomes, PATRIC creates a unique research experience with "virtual integration" of private and public data. PATRIC contains many diverse tools and functionalities to explore both genome-scale and gene expression data, but the main focus of this chapter is on assembly, annotation, and the downstream comparative analysis functionality that is freely available in the resource.

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user- created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics. National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services [HHSN272201400027C] PATRIC has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services [HHSN272201400027C]. Funding for open access charge: Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services [HHSN272201400027C].

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services. United States National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [HHSN272201400027C] This work was supported by the United States National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [Contract No. HHSN272201400027C]. We thank Emily Dietrich for her careful editing.

The facultative intracellular bacterial pathogen Brucella infects a wide range of warm-blooded land and marine vertebrates and causes brucellosis. Currently, there are nine recognized Brucella species based on host preferences and phenotypic differences. The availability of 10 different genomes consisting of two chromosomes and representing six of the species allowed for a detailed comparison among themselves and relatives in the order Rhizobiales . Phylogenomic analysis of ortholog families shows limited divergence but distinct radiations, producing four clades as follows: Brucella abortus-Brucella melitensis, Brucella suis-Brucella canis, Brucella ovis , and Brucella ceti . In addition, Brucella phylogeny does not appear to reflect the phylogeny of Brucella species' preferred hosts. About 4.6% of protein-coding genes seem to be pseudogenes, which is a relatively large fraction. Only B. suis 1330 appears to have an intact β-ketoadipate pathway, responsible for utilization of plant-derived compounds. In contrast, this pathway in the other species is highly pseudogenized and consistent with the “domino theory” of gene death. There are distinct shared anomalous regions (SARs) found in both chromosomes as the result of horizontal gene transfer unique to Brucella and not shared with its closest relative Ochrobactrum , a soil bacterium, suggesting their acquisition occurred in spite of a predominantly intracellular lifestyle. In particular, SAR 2-5 appears to have been acquired by Brucella after it became intracellular. The SARs contain many genes, including those involved in O-polysaccharide synthesis and type IV secretion, which if mutated or absent significantly affect the ability of Brucella to survive intracellularly in the infected host.

The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host–pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/.

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e. g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue. National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [HHSN272200900040C] Funding for open access charge: National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [Contract No. HHSN272200900040C].

Funded by the National Institute of Allergy and Infectious Diseases, the Pat hosystems R esource I ntegration C enter (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious-disease research. Specifically, PATRIC provides scientists with (i) a comprehensive bacterial genomics database, (ii) a plethora of associated data relevant to genomic analysis, and (iii) an extensive suite of computational tools and platforms for bioinformatics analysis. While the primary aim of PATRIC is to advance the knowledge underlying the biology of human pathogens, all publicly available genome-scale data for bacteria are compiled and continually updated, thereby enabling comparative analyses to reveal the basis for differences between infectious free-living and commensal species. Herein we summarize the major features available at PATRIC, dividing the resources into two major categories: (i) organisms, genomes, and comparative genomics and (ii) recurrent integration of community-derived associated data. Additionally, we present two experimental designs typical of bacterial genomics research and report on the execution of both projects using only PATRIC data and tools. These applications encompass a broad range of the data and analysis tools available, illustrating practical uses of PATRIC for the biologist. Finally, a summary of PATRIC's outreach activities, collaborative endeavors, and future research directions is provided.

A synthesis of the grevillin group of pyrandione pigments e.g.3, 23 and 24 present in fungi is described. The synthesis, which is based on a biogenetic model, uses bis-benzylacyloins 9 and their corresponding oxalate derivatives as key intermediates (Scheme 3). Treatment of the grevillins 25–c with sodium ethoxide in ethanol effects their quantitative isomerisation into the corresponding terphenylquinone pigments 4a–c. Perkin-type condensations between the terphenylquinones 4 and arylacetic acids in the presence of sodium acetate–acetic anhydride then produces the xylerythrin pigments 29a–e, whereas rearrangements of 4 in the presence of dimethyl sulphoxide leads to pulvinic acid derivatives, e.g.31, 32 and 5. These synthetic studies interrelate the biosynthetic origins of the pigment types 3, 4, 5 and 8 together with the related pulvinone 6 and furanone 7 fungal pigments.

The PathoSystems Resource Integration Center (PATRIC) is one of eight Bioinformatics Resource Centers (BRCs) funded by the National Institute of Allergy and Infection Diseases (NIAID) to create a data and analysis resource for selected NIAID priority pathogens, specifically proteobacteria of the genera Brucella, Rickettsia and Coxiella, and corona-, calici- and lyssaviruses and viruses associated with hepatitis A and E. The goal of the project is to provide a comprehensive bioinformatics resource for these pathogens, including consistently annotated genome, proteome and metabolic pathway data to facilitate research into counter-measures, including drugs, vaccines and diagnostics. The project's curation strategy has three prongs: 'breadth first' beginning with whole-genome and proteome curation using standardized protocols, a 'targeted' approach addressing the specific needs of researchers and an integrative strategy to leverage high-throughput experimental data (e.g. microarrays, proteomics) and literature. The PATRIC infrastructure consists of a relational database, analytical pipelines and a website which supports browsing, querying, data visualization and the ability to download raw and curated data in standard formats. At present, the site warehouses complete sequences for 17 bacterial and 332 viral genomes. The PATRIC website (https://patric.vbi.vt.edu) will continually grow with the addition of data, analysis and functionality over the course of the project. PHS HHS [HHSN266200400035C]

A synthesis of the grevillin group of pyrandione pigments e.g.3, 23 and 24 present in fungi is described. The synthesis, which is based on a biogenetic model, uses bis-benzylacyloins 9 and their corresponding oxalate derivatives as key intermediates (Scheme 3). Treatment of the grevillins 25–c with sodium ethoxide in ethanol effects their quantitative isomerisation into the corresponding terphenylquinone pigments 4a–c. Perkin-type condensations between the terphenylquinones 4 and arylacetic acids in the presence of sodium acetate–acetic anhydride then produces the xylerythrin pigments 29a–e, whereas rearrangements of 4 in the presence of dimethyl sulphoxide leads to pulvinic acid derivatives, e.g.31, 32 and 5. These synthetic studies interrelate the biosynthetic origins of the pigment types 3, 4, 5 and 8 together with the related pulvinone 6 and furanone 7 fungal pigments.

A synthesis of the grevillin group [e.g.(2),(16)], of pigments present in fungi, using benzylacyloins, viz (9), as key intermediates is described, and the biogenetic interrelationships between them and the terphenylquinone, xylerythrin and pulvinic acid families of natural colouring matter, are exemplified with the in vitro conversions (16)→(17), (17)→(20) and (17)→(22).