The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

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.

PATRIC as a unique resource for studying antimicrobial resistance.

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.

Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling study.

OBJECTIVES: This research studies the role of slums in the spread and control of infectious diseases in the National Capital Territory of India, Delhi, using detailed social contact networks of its residents. METHODS: We use an agent-based model to study the spread of influenza in Delhi through person-to-person contact. Two different networks are used: one in which slum and non-slum regions are treated the same, and the other in which 298 slum zones are identified. In the second network, slum-specific demographics and activities are assigned to the individuals whose homes reside inside these zones. The main effects of integrating slums are that the network has more home-related contacts due to larger family sizes and more outside contacts due to more daily activities outside home. Various vaccination and social distancing interventions are applied to control the spread of influenza. RESULTS: Simulation-based results show that when slum attributes are ignored, the effectiveness of vaccination can be overestimated by 30%-55%, in terms of reducing the peak number of infections and the size of the epidemic, and in delaying the time to peak infection. The slum population sustains greater infection rates under all intervention scenarios in the network that treats slums differently. Vaccination strategy performs better than social distancing strategies in slums. CONCLUSIONS: Unique characteristics of slums play a significant role in the spread of infectious diseases. Modelling slums and estimating their impact on epidemics will help policy makers and regulators more accurately prioritise allocation of scarce medical resources and implement public health policies.

Isolation and molecular characterization of group B Streptococcus from laboratory Long-Evans rats (Rattus norvegicus) with and without invasive group B streptococcal disease.

Purpose. Group B Streptococcus (S. agalactiae, GBS) is a Gram-positive opportunistic pathogen that inhabits the respiratory, urogenital and gastrointestinal tracts of humans and animals. Maternal colonization of GBS is a risk factor for a spectrum of clinical diseases in humans and a principle cause of neonatal meningitis and septicaemia.Methodology. We describe polymicrobial sepsis including GBS in two gravid adult female Long-Evans rats experiencing acute mortality from a colony of long-term breeding pairs. Fluorescent in situ hybridization confirmed GBS association with pathological changes in affected tissues, including the heart and uterus.Results. Characterization of seven GBS strains obtained from clinically affected and non-affected animals indicated similar antibiotic resistance and susceptibility patterns to that of human strains of GBS. The rat strains have virulence factors known to contribute to pathogenicity, and shared serotypes with human invasive isolates. Phylogenetic analyses revealed that one rat-derived GBS strain was more closely related to human-derived strains than other rat-derived strains, strengthening the notion that interspecies transmission is possible.Conclusions. To our knowledge, this is the first investigation of genotypic and phenotypic features of rat-derived GBS strains and their comparison to human- and other animal-derived GBS strains. Since GBS commonly colonizes commercially available rats, its exclusion as a potential pathogen for immunocompromised or stressed animals is recommended.

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center.

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.

The Complete Genome Sequence of the Emerging Pathogen Mycobacterium haemophilum Explains Its Unique Culture Requirements.

UNLABELLED: Mycobacterium haemophilum is an emerging pathogen associated with a variety of clinical syndromes, most commonly skin infections in immunocompromised individuals. M. haemophilum exhibits a unique requirement for iron supplementation to support its growth in culture, but the basis for this property and how it may shape pathogenesis is unclear. Using a combination of Illumina, PacBio, and Sanger sequencing, the complete genome sequence of M. haemophilum was determined. Guided by this sequence, experiments were performed to define the basis for the unique growth requirements of M. haemophilum. We found that M. haemophilum, unlike many other mycobacteria, is unable to synthesize iron-binding siderophores known as mycobactins or to utilize ferri-mycobactins to support growth. These differences correlate with the absence of genes associated with mycobactin synthesis, secretion, and uptake. In agreement with the ability of heme to promote growth, we identified genes encoding heme uptake machinery. Consistent with its propensity to infect the skin, we show at the whole-genome level the genetic closeness of M. haemophilum with Mycobacterium leprae, an organism which cannot be cultivated in vitro, and we identify genes uniquely shared by these organisms. Finally, we identify means to express foreign genes in M. haemophilum. These data explain the unique culture requirements for this important pathogen, provide a foundation upon which the genome sequence can be exploited to improve diagnostics and therapeutics, and suggest use of M. haemophilum as a tool to elucidate functions of genes shared with M. leprae. IMPORTANCE: Mycobacterium haemophilum is an emerging pathogen with an unknown natural reservoir that exhibits unique requirements for iron supplementation to grow in vitro. Understanding the basis for this iron requirement is important because it is fundamental to isolation of the organism from clinical samples and environmental sources. Defining the molecular basis for M. haemophilium's growth requirements will also shed new light on mycobacterial strategies to acquire iron and can be exploited to define how differences in such strategies influence pathogenesis. Here, through a combination of sequencing and experimental approaches, we explain the basis for the iron requirement. We further demonstrate the genetic closeness of M. haemophilum and Mycobacterium leprae, the causative agent of leprosy which cannot be cultured in vitro, and we demonstrate methods to genetically manipulate M. haemophilum. These findings pave the way for the use of M. haemophilum as a model to elucidate functions of genes shared with M. leprae.

PATRIC, the bacterial bioinformatics database and analysis resource.

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.

Bacterial DNA sifted from the Trichoplax adhaerens (Animalia: Placozoa) genome project reveals a putative rickettsial endosymbiont.

Eukaryotic genome sequencing projects often yield bacterial DNA sequences, data typically considered as microbial contamination. However, these sequences may also indicate either symbiont genes or lateral gene transfer (LGT) to host genomes. These bacterial sequences can provide clues about eukaryote-microbe interactions. Here, we used the genome of the primitive animal Trichoplax adhaerens (Metazoa: Placozoa), which is known to harbor an uncharacterized Gram-negative endosymbiont, to search for the presence of bacterial DNA sequences. Bioinformatic and phylogenomic analyses of extracted data from the genome assembly (181 bacterial coding sequences [CDS]) and trace read archive (16S rDNA) revealed a dominant proteobacterial profile strongly skewed to Rickettsiales (Alphaproteobacteria) genomes. By way of phylogenetic analysis of 16S rDNA and 113 proteins conserved across proteobacterial genomes, as well as identification of 27 rickettsial signature genes, we propose a Rickettsiales endosymbiont of T. adhaerens (RETA). The majority (93%) of the identified bacterial CDS belongs to small scaffolds containing prokaryotic-like genes; however, 12 CDS were identified on large scaffolds comprised of eukaryotic-like genes, suggesting that T. adhaerens might have recently acquired bacterial genes. These putative LGTs may coincide with the placozoan's aquatic niche and symbiosis with RETA. This work underscores the rich, and relatively untapped, resource of eukaryotic genome projects for harboring data pertinent to host-microbial interactions. The nature of unknown (or poorly characterized) bacterial species may only emerge via analysis of host genome sequencing projects, particularly if these species are resistant to cell culturing, as are many obligate intracellular microbes. Our work provides methodological insight for such an approach.

PATRIC: the comprehensive bacterial bioinformatics resource with a focus on human pathogenic species.

Funded by the National Institute of Allergy and Infectious Diseases, the Pathosystems Resource Integration Center (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.

Phylogeny of gammaproteobacteria.

The phylogeny of the large bacterial class Gammaproteobacteria has been difficult to resolve. Here we apply a telescoping multiprotein approach to the problem for 104 diverse gammaproteobacterial genomes, based on a set of 356 protein families for the whole class and even larger sets for each of four cohesive subregions of the tree. Although the deepest divergences were resistant to full resolution, some surprising patterns were strongly supported. A representative of the Acidithiobacillales routinely appeared among the outgroup members, suggesting that in conflict with rRNA-based phylogenies this order does not belong to Gammaproteobacteria; instead, it (and, independently, "Mariprofundus") diverged after the establishment of the Alphaproteobacteria yet before the betaproteobacteria/gammaproteobacteria split. None of the orders Alteromonadales, Pseudomonadales, or Oceanospirillales were monophyletic; we obtained strong support for clades that contain some but exclude other members of all three orders. Extreme amino acid bias in the highly A+T-rich genome of Candidatus Carsonella prevented its reliable placement within Gammaproteobacteria, and high bias caused artifacts that limited the resolution of the relationships of other insect endosymbionts, which appear to have had multiple origins, although the unbiased genome of the endosymbiont Sodalis acted as an attractor for them. Instability was observed for the root of the Enterobacteriales, with nearly equal subsets of the protein families favoring one or the other of two alternative root positions; the nematode symbiont Photorhabdus was identified as a disruptor whose omission helped stabilize the Enterobacteriales root.

Rickettsia phylogenomics: unwinding the intricacies of obligate intracellular life.

BACKGROUND: Completed genome sequences are rapidly increasing for Rickettsia, obligate intracellular alpha-proteobacteria responsible for various human diseases, including epidemic typhus and Rocky Mountain spotted fever. In light of phylogeny, the establishment of orthologous groups (OGs) of open reading frames (ORFs) will distinguish the core rickettsial genes and other group specific genes (class 1 OGs or C1OGs) from those distributed indiscriminately throughout the rickettsial tree (class 2 OG or C2OGs). METHODOLOGY/PRINCIPAL FINDINGS: We present 1823 representative (no gene duplications) and 259 non-representative (at least one gene duplication) rickettsial OGs. While the highly reductive (approximately 1.2 MB) Rickettsia genomes range in predicted ORFs from 872 to 1512, a core of 752 OGs was identified, depicting the essential Rickettsia genes. Unsurprisingly, this core lacks many metabolic genes, reflecting the dependence on host resources for growth and survival. Additionally, we bolster our recent reclassification of Rickettsia by identifying OGs that define the AG (ancestral group), TG (typhus group), TRG (transitional group), and SFG (spotted fever group) rickettsiae. OGs for insect-associated species, tick-associated species and species that harbor plasmids were also predicted. Through superimposition of all OGs over robust phylogeny estimation, we discern between C1OGs and C2OGs, the latter depicting genes either decaying from the conserved C1OGs or acquired laterally. Finally, scrutiny of non-representative OGs revealed high levels of split genes versus gene duplications, with both phenomena confounding gene orthology assignment. Interestingly, non-representative OGs, as well as OGs comprised of several gene families typically involved in microbial pathogenicity and/or the acquisition of virulence factors, fall predominantly within C2OG distributions. CONCLUSION/SIGNIFICANCE: Collectively, we determined the relative conservation and distribution of 14354 predicted ORFs from 10 rickettsial genomes across robust phylogeny estimation. The data, available at PATRIC (PathoSystems Resource Integration Center), provide novel information for unwinding the intricacies associated with Rickettsia pathogenesis, expanding the range of potential diagnostic, vaccine and therapeutic targets.

Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis.

Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and the sudden oak death pathogen Phytophthora ramorum. Oömycetes such as these Phytophthora species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic ancestry for the stramenopiles. Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oömycete avirulence genes.

YODA: selecting signature oligonucleotides.

MOTIVATION: Selecting oligonucleotide probes for use in microarray design, and other applications requiring signature sequences, involves identifying sequences which will bind strongly to their intended target, while binding only weakly (or preferably, not at all) to non-target sequences which may be present in the hybridization reaction. While many tools to assist in selection of such sequences exist, all the ones we examined lack important oligo design and software features. RESULTS: YODA is an application for assisting biological researchers in selecting signature sequences. It incorporates a custom sequence similarity search to find potential cross-hybridizing non-target sequences. For this task, most oligo design tools rely on BLAST, which is ill suited for it due to an unacceptable risk of false negatives. YODA supports multiple probe design goals including single-genome, multiple-genome, pathogen-host and species/strain-identification. A graphical interface is provided as well as a command-line interface, both of which support many user-controlled parameters. YODA is easy to install and use and runs on Windows, Mac OS X and Linux platforms. AVAILABILITY: Freely available (LGLP) along with source code and additional documentation at http://pathport.vbi.vt.edu/YODA CONTACT: enordber@vbi.vt.edu.