Browsing by Author "Wattam, Alice R."

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    Antimicrobial Resistance Prediction in PATRIC and RAST
    Davis, James J.; Boisvert, Sebastien; Brettin, Thomas; Kenyon, Ronald W.; Mao, Chunhong; Olson, Robert D.; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R.; Will, Rebecca; Xia, Fangfang; Stevens, Rick L. (Springer Nature, 2016-06-14)
    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.
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    Brucella spp. of amphibians comprise genomically diverse motile strains competent for replication in macrophages and survival in mammalian hosts
    Al Dahouk, Sascha; Koehler, Stephan; Occhialini, Alessandra; Jimenez de Bagues, Maria Pilar; Hammerl, Jens Andre; Eisenberg, Tobias; Vergnaud, Gilles; Cloeckaert, Axel; Zygmunt, Michel S.; Whatmore, Adrian M.; Melzer, Falk; Drees, Kevin P.; Foster, Jeffrey T.; Wattam, Alice R.; Scholz, Holger C. (Springer Nature, 2017-03-16)
    Twenty-one small Gram-negative motile coccobacilli were isolated from 15 systemically diseased African bullfrogs (Pyxicephalus edulis), and were initially identified as Ochrobactrum anthropi by standard microbiological identification systems. Phylogenetic reconstructions using combined molecular analyses and comparative whole genome analysis of the most diverse of the bullfrog strains verified affiliation with the genus Brucella and placed the isolates in a cluster containing B. inopinata and the other non-classical Brucella species but also revealed significant genetic differences within the group. Four representative but molecularly and phenotypically diverse strains were used for in vitro and in vivo infection experiments. All readily multiplied in macrophage-like murine J774-cells, and their overall intramacrophagic growth rate was comparable to that of B. inopinata BO1 and slightly higher than that of B. microti CCM 4915. In the BALB/c murine model of infection these strains replicated in both spleen and liver, but were less efficient than B. suis 1330. Some strains survived in the mammalian host for up to 12 weeks. The heterogeneity of these novel strains hampers a single species description but their phenotypic and genetic features suggest that they represent an evolutionary link between a soil-associated ancestor and the mammalian host-adapted pathogenic Brucella species.
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    Comparative genomic analysis between Corynebacterium pseudotuberculosis strains isolated from buffalo
    Canario Viana, Marcus Vinicius; Figueiredo, Henrique; Ramos, Rommel; Guimaraes, Luis Carlos; Pereira, Felipe Luiz; Dorella, Fernanda Alves; Selim, Salah Abdel Karim; Salaheldean, Mohammad; Silva, Artur; Wattam, Alice R.; Azevedo, Vasco (PLOS, 2017-04-26)
    Corynebacterium pseudotuberculosis is a Gram-positive, pleomorphic, facultative intracellular pathogen that causes Oedematous Skin Disease (OSD) in buffalo. To better understand the pathogenic mechanisms of OSD, we performed a comparative genomic analysis of 11 strains of C. pseudotuberculosis isolated from different buffalo found to be infected in Egypt during an outbreak that occurred in 2008. Sixteen previously described pathogenicity islands (PiCp) were present in all of the new buffalo strains, but one of them, PiCp12, had an insertion that contained both a corynephage and a diphtheria toxin gene, both of which may play a role in the adaptation of C. pseudotuberculosis to this new host. Synteny analysis showed variations in the site of insertion of the corynephage during the same outbreak. A gene functional comparison showed the presence of a nitrate reductase operon that included genes involved in molybdenum cofactor biosynthesis, which is necessary for a positive nitrate reductase phenotype and is a possible adaptation for intracellular survival. Genomes from the buffalo strains also had fusions in minor pilin genes in the spaA and spaD gene cluster (spaCX and spaYEF), which could suggest either an adaptation to this particular host, or mutation events in the immediate ancestor before this particular epidemic. A phylogenomic analysis confirmed a clear separation between the Ovis and Equi biovars, but also showed what appears to be a clustering by host species within the Equi strains.
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    Comparative Genomics of Early-Diverging Brucella Strains Reveals a Novel Lipopolysaccharide Biosynthesis Pathway
    Wattam, Alice R.; Inzana, Thomas J.; Williams, Kelly P.; Mane, Shrinivasrao P.; Shukla, Maulik; Almeida, Nalvo F.; Dickerman, Allan W.; Mason, Steven; Moriyon, Ignacio; O'Callaghan, David; Whatmore, Adrian M.; Sobral, Bruno; Tiller, Rebekah V.; Hoffmaster, Alex R.; Frace, Michael A.; De Castro, Cristina; Molinaro, Antonio; Boyle, Stephen M.; De, Barun K.; Setubal, Joao C. (American Society for Microbiology, 2012-11)
    Brucella species are Gram-negative bacteria that infect mammals. Recently, two unusual strains (Brucella inopinata BO1T and B. inopinata-like BO2) have been isolated from human patients, and their similarity to some atypical brucellae isolated from Australian native rodent species was noted. Here we present a phylogenomic analysis of the draft genome sequences of BO1T and BO2 and of the Australian rodent strains 83-13 and NF2653 that shows that they form two groups well separated from the other sequenced Brucella spp. Several important differences were noted. Both BO1T and BO2 did not agglutinate significantly when live or inactivated cells were exposed to monospecific A and M antisera against O-side chain sugars composed of N-formyl-perosamine. While BO1T maintained the genes required to synthesize a typical Brucella O-antigen, BO2 lacked many of these genes but still produced a smooth LPS (lipopolysaccharide). Most missing genes were found in the wbk region involved in O-antigen synthesis in classic smooth Brucella spp. In their place, BO2 carries four genes that other bacteria use for making a rhamnose-based O-antigen. Electrophoretic, immunoblot, and chemical analyses showed that BO2 carries an antigenically different O-antigen made of repeating hexose-rich oligosaccharide units that made the LPS water-soluble, which contrasts with the homopolymeric O-antigen of other smooth brucellae that have a phenol-soluble LPS. The results demonstrate the existence of a group of early-diverging brucellae with traits that depart significantly from those of the Brucella species described thus far. IMPORTANCE This report examines differences between genomes from four new Brucella strains and those from the classic Brucella spp. Our results show that the four new strains are outliers with respect to the previously known Brucella strains and yet are part of the genus, forming two new clades. The analysis revealed important information about the evolution and survival mechanisms of Brucella species, helping reshape our knowledge of this important zoonotic pathogen. One discovery of special importance is that one of the strains, BO2, produces an O-antigen distinct from any that has been seen in any other Brucella isolates to date.
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    Comparative mangrove metagenome reveals global prevalence of heavy metals and antibiotic resistome across different ecosystems
    Imchen, Madangchanok; Kumavath, Ranjith; Barh, Debmalya; Vaz, Aline; Goes-Neto, Aristoteles; Tiwari, Sandeep; Ghosh, Preetam; Wattam, Alice R.; Azevedo, Vasco (Springer Nature, 2018-07-25)
    The mangrove ecosystem harbors a complex microbial community that plays crucial role in biogeochemical cycles. In this study, we analyzed mangrove sediments from India using de novo whole metagenome next generation sequencing (NGS) and compared their taxonomic and functional community structures to mangrove metagenomics samples from Brazil and Saudi Arabia. The most abundant phyla in the mangroves of all three countries was Proteobacteria, followed by Firmicutes and Bacteroidetes. A total of 1,942 genes were found to be common across all the mangrove sediments from each of the three countries. The mangrove resistome consistently showed high resistance to fluoroquinolone and acriflavine. A comparative study of the mangrove resistome with other ecosystems shows a higher frequency of heavy metal resistance in mangrove and terrestrial samples. Ocean samples had a higher abundance of drug resistance genes with fluoroquinolone and methicillin resistance genes being as high as 28.178% +/- 3.619 and 10.776% +/- 1.823. Genes involved in cobalt-zinc-cadmium resistance were higher in the mangrove (23.495% +/- 4.701) and terrestrial (27.479% +/- 4.605) ecosystems. Our comparative analysis of samples collected from a variety of habitats shows that genes involved in resistance to both heavy metals and antibiotics are ubiquitous, irrespective of the ecosystem examined.
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    The Complete Genome Sequence of the Emerging Pathogen Mycobacterium haemophilum Explains Its Unique Culture Requirements
    Tufariello, JoAnn M.; Kerantzas, Christopher A.; Vilcheze, Catherine; Calder, R. Brent; Nordberg, Eric K.; Fischer, Jack A.; Hartman, Travis E.; Yang, Eva; Driscoll, Timothy; Cole, Laura E.; Sebra, Robert; Maqbool, Shahina B.; Wattam, Alice R.; Jacobs, William R. Jr. (American Society for Microbiology, 2015-11)
    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.
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    Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center
    Wattam, Alice R.; Davis, James J.; Assaf, Rida; Boisvert, Sebastien; Brettin, Thomas; Bun, Christopher; Conrad, Neal; Dietrich, Emily M.; Disz, Terry L.; Gabbard, Joseph L.; Gerdes, Svetlana; Henry, Christopher S.; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olsen, Gary J.; Murphy-Olson, Daniel E.; Olson, Robert D.; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Vonstein, Veronika; Warren, Andrew S.; Xia, Fangfang; Yoo, Hyunseung; Stevens, Rick L. (2017-01-04)
    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.
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    Insight of Genus Corynebacterium: Ascertaining the Role of Pathogenic and Non-pathogenic Species
    Oliveira, Alberto; Oliveira, Leticia C.; Aburjaile, Flavia; Benevides, Leandro; Tiwari, Sandeep; Jamal, Syed B.; Silva, Arthur; Figueiredo, Henrique C. P.; Ghosh, Preetam; Portela, Ricardo W.; De Carvalho Azevedo, Vasco A.; Wattam, Alice R. (Frontiers, 2017-10-12)
    This review gathers recent information about genomic and transcriptomic studies in the Corynebacterium genus, exploring, for example, prediction of pathogenicity islands and stress response in different pathogenic and non-pathogenic species. In addition, is described several phylogeny studies to Corynebacterium, exploring since the identification of species until biological speciation in one species belonging to the genus Corynebacterium. Important concepts associated with virulence highlighting the role of Pld protein and Tox gene. The adhesion, characteristic of virulence factor, was described using the sortase mechanism that is associated to anchorage to the cell wall. In addition, survival inside the host cell and some diseases, were too addressed for pathogenic corynebacteria, while important biochemical pathways and biotechnological applications retain the focus of this review for non-pathogenic corynebacteria. Concluding, this review broadly explores characteristics in genus Corynebacterium showing to have strong relevance inside the medical, veterinary, and biotechnology field.
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    The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities
    Davis, James J.; Wattam, Alice R.; Aziz, Ramy K.; Brettin, Thomas; Butler, Ralph; Butler, Rory M.; Chlenski, Philippe; Conrad, Neal; Dickerman, Allan W.; Dietrich, Emily M.; Gabbard, Joseph L.; Gerdes, Svetlana; Guard, Andrew; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Murphy-Olson, Daniel E.; Nguyen, Marcus; Nordberg, Eric K.; Olsen, Gary J.; Olson, Robert D.; Overbeek, Jamie C.; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomas, Chris; VanOeffelen, Margo; Vonstein, Veronika; Warren, Andrew S.; Xia, Fangfang; Xie, Dawen; Yoo, Hyunseung; Stevens, Rick L. (2020-01-08)
    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.
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    PATRIC, the bacterial bioinformatics database and analysis resource
    Wattam, Alice R.; Abraham, David; Dalay, Oral; Disz, Terry L.; Driscoll, Timothy; Gabbard, Joseph L.; Gillespie, Joseph J.; Gough, Roger; Hix, Deborah; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olson, Robert; Overbeek, Ross; Pusch, Gordon D.; Shukla, Maulik; Schulman, Julie; Stevens, Rick L.; Sullivan, Daniel E.; Vonstein, Veronika; Warren, Andrew S.; Will, Rebecca; Wilson, Meredith J. C.; Yoo, Hyunseung; Zhang, Chengdong; Zhang, Yan; Sobral, Bruno (2014-01)
    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.
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    PATtyFams: Protein Families for the Microbial Genomes in the PATRIC Database
    Davis, James J.; Gerdes, Svetlana; Olsen, Gary J.; Olson, Robert; Pusch, Gordon D.; Shukla, Maulik; Vonstein, Veronika; Wattam, Alice R.; Yoo, Hyunseung (Frontiers, 2016-02-08)
    The ability to build accurate protein families is a fundamental operation in bioinformatics that influences comparative analyses, genome annotation, and metabolic modeling. For several years we have been maintaining protein families for all microbial genomes in the PATRIC database (Pathosystems Resource Integration Center, patricbrc.org) in order to drive many of the comparative analysis tools that are available through the PATRIC website. However, due to the burgeoning number of genomes, traditional approaches for generating protein families are becoming prohibitive. In this report, we describe a new approach for generating protein families, which we call PATtyFams. This method uses the k-mer-based function assignments available through RAST (Rapid Annotation using Subsystem Technology) to rapidly guide family formation, and then differentiates the function-based groups into families using a Markov Cluster algorithm (MCL). This new approach for generating protein families is rapid, scalable and has properties that are consistent with alignment-based methods.
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    RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes
    Brettin, Thomas; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomason, James A., III; Stevens, Rick L.; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang (Springer Nature, 2015-02-10)
    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.
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    Searching for signatures across microbial communities: Metagenomic analysis of soil samples from mangrove and other ecosystems
    Imchen, Madangchanok; Kumavath, Ranjith; Barh, Debmalya; Avezedo, Vasco; Ghosh, Preetam; Viana, Marcus; Wattam, Alice R. (Springer Nature, 2017-08-18)
    In this study, we categorize the microbial community in mangrove sediment samples from four different locations within a vast mangrove system in Kerala, India. We compared this data to other samples taken from the other known mangrove data, a tropical rainforest, and ocean sediment. An examination of the microbial communities from a large mangrove forest that stretches across southwestern India showed strong similarities across the higher taxonomic levels. When ocean sediment and a single isolate from a tropical rain forest were included in the analysis, a strong pattern emerged with Bacteria from the phylum Proteobacteria being the prominent taxon among the forest samples. The ocean samples were predominantly Archaea, with Euryarchaeota as the dominant phylum. Principal component and functional analyses grouped the samples isolated from forests, including those from disparate mangrove forests and the tropical rain forest, from the ocean. Our findings show similar patterns in samples were isolated from forests, and these were distinct from the ocean sediment isolates. The taxonomic structure was maintained to the level of class, and functional analysis of the genes present also displayed these similarities. Our report for the first time shows the richness of microbial diversity in the Kerala coast and its differences with tropical rain forest and ocean microbiome.
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    The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST)
    Overbeek, Ross; Olson, Robert; Pusch, Gordon D.; Olsen, Gary J.; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Parrello, Bruce; Shukla, Maulik; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang; Stevens, Rick L. (2014-01)
    In 2004, the SEED (http://pubseed.theseed.org/) was created to provide consistent and accurate genome annotations across thousands of genomes and as a platform for discovering and developing de novo annotations. The SEED is a constantly updated integration of genomic data with a genome database, web front end, API and server scripts. It is used by many scientists for predicting gene functions and discovering new pathways. In addition to being a powerful database for bioinformatics research, the SEED also houses subsystems (collections of functionally related protein families) and their derived FIGfams (protein families), which represent the core of the RAST annotation engine (http://rast.nmpdr.org/). When a new genome is submitted to RAST, genes are called and their annotations are made by comparison to the FIGfam collection. If the genome is made public, it is then housed within the SEED and its proteins populate the FIGfam collection. This annotation cycle has proven to be a robust and scalable solution to the problem of annotating the exponentially increasing number of genomes. To date, >12 000 users worldwide have annotated >60 000 distinct genomes using RAST. Here we describe the interconnectedness of the SEED database and RAST, the RAST annotation pipeline and updates to both resources.