1
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Scholz HC, Heckers KO, Appelt S, Geier-Dömling D, Schlegel P, Wattam AR. Isolation of Brucella inopinata from a White's tree frog ( Litoria caerulea): pose exotic frogs a potential risk to human health? Front Microbiol 2023; 14:1173252. [PMID: 37362939 PMCID: PMC10285381 DOI: 10.3389/fmicb.2023.1173252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 05/02/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction Cold-blooded hosts, particularly exotic frogs, have become a newly recognized reservoir for atypical Brucella species and strains worldwide, but their pathogenicity to humans remains largely unknown. Here we report the isolation and molecular characterization of a B. inopinata strain (FO700662) cultured from clinical samples taken from a captive diseased White's Tree Frog (Litoria caerulea) in Switzerland. The isolation of B. inopinata from a frog along with other reports of human infection by atypical Brucella raises the question of whether atypical Brucella could pose a risk to human health and deserves further attention. Methods The investigations included histopathological analysis of the frog, bacterial culture and in-depth molecular characterization of strain FO700662 based on genome sequencing data. Results and Discussion Originally identified as Ochrobactrum based on its rapid growth and biochemical profile, strain FO700622 was positive for the Brucella- specific markers bcsp31 and IS711. It showed the specific banding pattern of B. inopinata in conventional Bruce-ladder multiplex PCR and also had identical 16S rRNA and recA gene sequences as B. inopinata. Subsequent genome sequencing followed by core genome-based MLST (cgMLST) analysis using 2704 targets (74% of the total chromosome) revealed only 173 allelic differences compared to the type strain of B. inopinata BO1T, while previously considered the closest related strain BO2 differed in 2046 alleles. The overall average nucleotide identity (ANI) between the type strain BO1T and FO700622 was 99,89%, confirming that both strains were almost identical. In silico MLST-21 and MLVA-16 also identified strain FO700662 as B. inopinata. The nucleotide and amino acid-based phylogenetic reconstruction and comparative genome analysis again placed the isolate together with B. inopinata with 100% support. In conclusion, our data unequivocally classified strain FO700622, isolated from an exotic frog, as belonging to B. inopinata.
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Affiliation(s)
- Holger C. Scholz
- Department of Bacteriology and Toxinology, Bundeswehr Institute of Microbiology, Munich, Germany
| | - Kim O. Heckers
- LABOklin GmbH and Co KG, Labor für klinische Diagnostik, Bad Kissingen, Germany
| | - Sandra Appelt
- Department of Bacteriology and Toxinology, Bundeswehr Institute of Microbiology, Munich, Germany
| | | | - Patrick Schlegel
- Kleintierpraxis Dr. med vet. Patrick Schlegel, Sargans, Switzerland
| | - Alice R. Wattam
- Biocomplexity Institute, University of Virginia, Charlottesville, VA, United States
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2
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Huang C, Guo F, Wang H, Olivares J, Dalton Iii J, Belyanina O, Wattam AR, Cucinell CA, Dickerman AW, Qin QM, Han A, de Figueiredo P. An automated system for interrogating the evolution of microbial endosymbiosis. Lab Chip 2023; 23:671-683. [PMID: 36227118 DOI: 10.1039/d2lc00602b] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Inter-kingdom endosymbiotic interactions between bacteria and eukaryotic cells are critical to human health and disease. However, the molecular mechanisms that drive the emergence of endosymbiosis remain obscure. Here, we describe the development of a microfluidic system, named SEER (S̲ystem for the E̲volution of E̲ndosymbiotic R̲elationships), that automates the evolutionary selection of bacteria with enhanced intracellular survival and persistence within host cells, hallmarks of endosymbiosis. Using this system, we show that a laboratory strain of Escherichia coli that initially possessed limited abilities to survive within host cells, when subjected to SEER selection, rapidly evolved to display a 55-fold enhancement in intracellular survival. Notably, molecular dissection of the evolved strains revealed that a single-point mutation in a flexible loop of CpxR, a gene regulator that controls bacterial stress responses, substantially contributed to this intracellular survival. Taken together, these results establish SEER as the first microfluidic system for investigating the evolution of endosymbiosis, show the importance of CpxR in endosymbiosis, and set the stage for evolving bespoke inter-kingdom endosymbiotic systems with novel or emergent properties.
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Affiliation(s)
- Can Huang
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Fengguang Guo
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
| | - Han Wang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, 100084, Beijing, China
| | - Jasmine Olivares
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
| | - James Dalton Iii
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
| | - Olga Belyanina
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
| | - Alice R Wattam
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Clark A Cucinell
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Allan W Dickerman
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Qing-Ming Qin
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
| | - Arum Han
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Paul de Figueiredo
- Department of Microbial Pathogenesis and Immunology, Texas A&M Health Science Center, Bryan, TX 77843, USA.
- Department of Veterinary Pathobiology, Texas A&M University, College Station, TX 77843, USA
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3
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VanOeffelen M, Nguyen M, Aytan-Aktug D, Brettin T, Dietrich EM, Kenyon RW, Machi D, Mao C, Olson R, Pusch GD, Shukla M, Stevens R, Vonstein V, Warren AS, Wattam AR, Yoo H, Davis JJ. A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes. Brief Bioinform 2021; 22:bbab313. [PMID: 34379107 PMCID: PMC8575023 DOI: 10.1093/bib/bbab313] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/18/2021] [Accepted: 07/20/2021] [Indexed: 11/14/2022] Open
Abstract
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.
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Affiliation(s)
| | - Marcus Nguyen
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - Derya Aytan-Aktug
- National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Thomas Brettin
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL, USA
| | - Emily M Dietrich
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL, USA
| | - Ronald W Kenyon
- Biocomplexity Institute and Initiative, University of Virginia, Virginia, USA
| | - Dustin Machi
- Biocomplexity Institute and Initiative, University of Virginia, Virginia, USA
| | - Chunhong Mao
- Biocomplexity Institute and Initiative, University of Virginia, Virginia, USA
| | - Robert Olson
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - Gordon D Pusch
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA
| | - Maulik Shukla
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - Rick Stevens
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL, USA
- Department of Computer Science, University of Chicago, Chicago, IL, USA
| | | | - Andrew S Warren
- Biocomplexity Institute and Initiative, University of Virginia, Virginia, USA
| | - Alice R Wattam
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
- Biocomplexity Institute and Initiative, University of Virginia, Virginia, USA
| | - Hyunseung Yoo
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - James J Davis
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
- Northwestern Argonne Institute for Science and Engineering, Evanston, IL, USA
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4
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Antonopoulos DA, Assaf R, Aziz RK, Brettin T, Bun C, Conrad N, Davis JJ, Dietrich EM, Disz T, Gerdes S, Kenyon RW, Machi D, Mao C, Murphy-Olson DE, Nordberg EK, Olsen GJ, Olson R, Overbeek R, Parrello B, Pusch GD, Santerre J, Shukla M, Stevens RL, VanOeffelen M, Vonstein V, Warren AS, Wattam AR, Xia F, Yoo H. PATRIC as a unique resource for studying antimicrobial resistance. Brief Bioinform 2020; 20:1094-1102. [PMID: 28968762 PMCID: PMC6781570 DOI: 10.1093/bib/bbx083] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 06/13/2017] [Indexed: 02/07/2023] Open
Abstract
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.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Alice R Wattam
- Corresponding author: Alice R. Wattam, Biocomplexity Institute of Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061 USA. Tel.: 540-231-1263; Fax: 540-231-2606; E-mail:
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5
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Saranathan R, Levi MH, Wattam AR, Malek A, Asare E, Behin DS, Pan DH, Jacobs WR, Szymczak WA. Helicobacter pylori Infections in the Bronx, New York: Surveying Antibiotic Susceptibility and Strain Lineage by Whole-Genome Sequencing. J Clin Microbiol 2020; 58:e01591-19. [PMID: 31801839 PMCID: PMC7041580 DOI: 10.1128/jcm.01591-19] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 11/27/2019] [Indexed: 12/16/2022] Open
Abstract
The emergence of drug resistance in Helicobacter pylori has resulted in a greater need for susceptibility-guided treatment. While the alleles associated with resistance to clarithromycin and levofloxacin have been defined, there are limited data regarding the molecular mechanisms underlying resistance to other antimicrobials. Using H. pylori isolates from 42 clinical specimens, we compared phenotypic and whole-genome sequencing (WGS)-based detection of resistance. Phenotypic resistance correlated with the presence of alleles of 23S rRNA (A2142G/A2143G) for clarithromycin (kappa coefficient, 0.84; 95% confidence interval [CI], 0.67 to 1.0) and gyrA (N87I/N87K/D91Y/D91N/D91G/D99N) for levofloxacin (kappa coefficient, 0.90; 95% CI, 0.77 to 1.0). Phenotypic resistance to amoxicillin in three isolates correlated with mutations in pbp1, pbp2, and/or pbp3 within coding regions near known amoxicillin binding motifs. All isolates were phenotypically susceptible to tetracycline, although four bore a mutation in 16S rRNA (A926G). For metronidazole, nonsense mutations and R16H substitutions in rdxA correlated with phenotypic resistance (kappa coefficient, 0.76; 95% CI, 0.56 to 0.96). Previously identified mutations in the rpoB rifampin resistance-determining region (RRDR) were not present, but 14 novel mutations outside the RRDR were found in rifampin-resistant isolates. WGS also allowed for strain lineage determination, which may be important for future studies in associating precise MICs with specific resistance alleles. In summary, WGS allows for broad analyses of H. pylori isolates, and our findings support the use of WGS for the detection of clarithromycin and levofloxacin resistance. Additional studies are warranted to better define mutations conferring resistance to amoxicillin, tetracycline, and rifampin, but combinatorial analyses for rdxA gene truncations and R16H mutations have utility for determining metronidazole resistance.
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Affiliation(s)
- Rajagopalan Saranathan
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Michael H Levi
- Department of Pathology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA
| | - Alice R Wattam
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, Virginia, USA
| | - Adel Malek
- Provincial Public Health Laboratory, Eastern Health Microbiology Services, St. John's, New Foundland and Labrador, Canada
| | - Emmanuel Asare
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York, USA
- Department of Pathology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA
| | - Daniel S Behin
- Department of Medicine, Division of Gastroenterology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA
| | - Debra H Pan
- Department of Pediatrics, Division of Gastroenterology and Nutrition, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA
| | - William R Jacobs
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Wendy A Szymczak
- Department of Pathology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, New York, USA
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6
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Gagetti P, Errecalde L, Wattam AR, De Belder D, Ojeda Saavedra M, Corso A, Rosato AE. Characterization of the First mecA-Positive Multidrug-Resistant Staphylococcus pseudintermedius Isolated from an Argentinian Patient. Microb Drug Resist 2020; 26:717-721. [PMID: 32031908 DOI: 10.1089/mdr.2019.0308] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Staphylococcus pseudintermedius is commonly associated with colonization or infection in dogs, and was identified as a novel species within the genus Staphylococcus in 2006. Methicillin resistance emerged in S. pseudintermedius during the last decade. We describe here a genomic characterization of the first methicillin-resistant S. pseudintermedius (MRSP) recovered from a human patient in Argentina. The strain was phenotypically identified as MRSP 8510 by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and antimicrobial susceptibility testing. We assessed genetic characterization by mecA PCR, SCCmec (staphylococcal chromosomal cassette) typing, and whole-genome sequencing. MRSP 8510 was phenotypically resistant to six classes of antimicrobial agents, consistent with the genes found in its genome. We concluded that MRSP 8510 was a multidrug-resistant ST1412 isolate. This study highlights the importance of the detection and characterization of pathogens with potential risks of zoonotic transmission to humans, as they may constitute a reservoir of genes associated with antimicrobial resistance.
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Affiliation(s)
- Paula Gagetti
- Servicio Antimicrobianos, INEI-ANLIS- "Dr. Carlos G. Malbrán," Buenos Aires, Argentina
| | - Laura Errecalde
- Departamento de Microbiologia, Hospital J. A. Fernandez, Buenos Aires, Argentina
| | - Alice R Wattam
- Biocomplexity Institute, University of Virginia, Charlottesville, Virginia, USA
| | - Denise De Belder
- Servicio Antimicrobianos, INEI-ANLIS- "Dr. Carlos G. Malbrán," Buenos Aires, Argentina
| | - Matthew Ojeda Saavedra
- Department of Pathology and Genomic Medicine, Center for Molecular and Translational Human Infectious Diseases Research, Houston Methodist Research Institute, Houston, Texas, USA
| | - Alejandra Corso
- Servicio Antimicrobianos, INEI-ANLIS- "Dr. Carlos G. Malbrán," Buenos Aires, Argentina
| | - Adriana E Rosato
- Department of Pathology and Genomic Medicine, Center for Molecular and Translational Human Infectious Diseases Research, Houston Methodist Research Institute, Houston, Texas, USA
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7
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Davis JJ, Wattam AR, Aziz RK, Brettin T, Butler R, Butler RM, Chlenski P, Conrad N, Dickerman A, Dietrich EM, Gabbard JL, Gerdes S, Guard A, Kenyon RW, Machi D, Mao C, Murphy-Olson D, Nguyen M, Nordberg EK, Olsen GJ, Olson RD, Overbeek JC, Overbeek R, Parrello B, Pusch GD, Shukla M, Thomas C, VanOeffelen M, Vonstein V, Warren AS, Xia F, Xie D, Yoo H, Stevens R. The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities. Nucleic Acids Res 2020; 48:D606-D612. [PMID: 31667520 PMCID: PMC7145515 DOI: 10.1093/nar/gkz943] [Citation(s) in RCA: 401] [Impact Index Per Article: 100.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 10/07/2019] [Accepted: 10/11/2019] [Indexed: 12/24/2022] Open
Abstract
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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Affiliation(s)
- James J Davis
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Alice R Wattam
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Ramy K Aziz
- Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, 11562 Cairo, Egypt
- Center for Genome and Microbiome Research, Cairo University, 11562 Cairo, Egypt
| | - Thomas Brettin
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Ralph Butler
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
- Middle Tennessee State University, Murfreesboro, TN 37132, USA
| | - Rory M Butler
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | | | - Neal Conrad
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Allan Dickerman
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Emily M Dietrich
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | | | - Svetlana Gerdes
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Andrew Guard
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
| | - Ronald W Kenyon
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Dustin Machi
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Chunhong Mao
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Dan Murphy-Olson
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Marcus Nguyen
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Eric K Nordberg
- Transportation Institute, Virginia Tech University, Blacksburg, VA 24061, USA
| | - Gary J Olsen
- Department of Microbiology, University of Illinois, Urbana, IL 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana, IL 61801, USA
| | - Robert D Olson
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Jamie C Overbeek
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Ross Overbeek
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
| | - Bruce Parrello
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Gordon D Pusch
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Maulik Shukla
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Chris Thomas
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
| | | | | | - Andrew S Warren
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Fangfang Xia
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Dawen Xie
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Hyunseung Yoo
- University of Chicago Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL 60637, USA
- Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Rick Stevens
- Computing Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
- University of Chicago, Department of Computer Science, Chicago, IL 60637, USA
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8
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Gagetti P, Wattam AR, Giacoboni G, De Paulis A, Bertona E, Corso A, Rosato AE. Identification and molecular epidemiology of methicillin resistant Staphylococcus pseudintermedius strains isolated from canine clinical samples in Argentina. BMC Vet Res 2019; 15:264. [PMID: 31351494 PMCID: PMC6660709 DOI: 10.1186/s12917-019-1990-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 07/02/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Staphylococcus pseudintermedius is the leading cause of pyoderma in dogs and the frequent use of antimicrobial treatment is associated to the development of resistance to nearly all classes of antibiotics. Despite S. pseudintermedius significance, our understanding of the molecular mechanism of β-lactam resistance and its genetic diversity remains limited. We aimed to: i) determine the phenotypic resistance profile of methicillin resistant Staphylococcus pseudintermedius (MRSP) isolated from infected dogs in three different veterinary hospitals in Buenos Aires, Argentina; ii) identify the SCCmec elements and resistance genes; and iii) analyze the clonal relationship between isolates and in regard of dominant lineages found in the world. RESULTS In addition to the differential levels of β-lactam resistance, MRSP isolates (n = 10) showed resistance to 5-6 families of antibiotics, and were therefore categorized as multidrug-resistant. All the isolates were variant of SCCmec V homologous to S. aureus; additional SCCmecFinder analysis classified five of the genomes as SCCmec type V (5C2&5) with mecA (encodes for PBP2a), mecRI and mecI and all the genes closely related to the reference SCCmec type V S. aureus TSGH17 strain. In the remaining five strains, mecA was present, although other genes associated with SCCmec V including mecR1 and mecI were missing. PBP2a was inducible in low level resistance strains (MRSP 8151), and constitutively expressed in MRSP 8150, suggesting different mecA regulatory mechanisms. MRSP isolates showed significant genetic diversity: eight PFGE clonal types and six multilocus-sequence typing (MLST) sequence types (STs) (339, 649, 919, 920, 921 and 922), including four new STs genetically distinct from STs reported in other geographic areas. Comparative genomics and phylogenetic analyses of the MRSP showed a correlation between the genetic content and the phenotypes, and established the genetic relationship between the isolates. CONCLUSIONS MRSP could be a threat to animal health due to it concerning level of antimicrobial resistance. Our study highlights genetic and epidemiological aspects of multidrug-resistant MRSP strains from Argentina showing high degree of correlation between the resistance genes and the phenotype of the isolates and, furthermore, they appeared evolutionary closer to major worldwide reported ST68 and ST71.
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Affiliation(s)
- Paula Gagetti
- Servicio Antimicrobianos INEI-ANLIS "Dr. Carlos G. Malbran" , CABA, Argentina.,Department of Pathology and Genomic Medicine, Houston Methodist Research Institute, Houston, TX, USA
| | - Alice R Wattam
- Biocomplexity Institute, University of Virginia, Virginia, USA
| | - Gabriela Giacoboni
- Departamento de Microbiologia, Facultad de Ciencias Veterinarias-UNLP, La Plata, Argentina
| | - Adriana De Paulis
- Departamento Microbiología, Instituto de Investigaciones Médicas Alfredo Lanari-UBA, CABA, Argentina
| | - Eugenia Bertona
- Departamento Microbiología, Instituto de Investigaciones Médicas Alfredo Lanari-UBA, CABA, Argentina
| | - Alejandra Corso
- Servicio Antimicrobianos INEI-ANLIS "Dr. Carlos G. Malbran" , CABA, Argentina
| | - Adriana E Rosato
- Department of Pathology and Genomic Medicine, Houston Methodist Research Institute, Houston, TX, USA.
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9
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Imchen M, Kumavath R, Barh D, Azevedo V, Ghosh P, Viana M, Wattam AR. Author Correction: Searching for signatures across microbial communities: Metagenomic analysis of soil samples from mangrove and other ecosystems. Sci Rep 2018; 8:165. [PMID: 29302053 PMCID: PMC5754361 DOI: 10.1038/s41598-017-18550-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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10
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Imchen M, Kumavath R, Barh D, Vaz A, Góes-Neto A, Tiwari S, Ghosh P, Wattam AR, Azevedo V. Comparative mangrove metagenome reveals global prevalence of heavy metals and antibiotic resistome across different ecosystems. Sci Rep 2018; 8:11187. [PMID: 30046123 PMCID: PMC6060162 DOI: 10.1038/s41598-018-29521-4] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 07/13/2018] [Indexed: 12/17/2022] Open
Abstract
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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Affiliation(s)
- Madangchanok Imchen
- Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Tejaswini Hills, Periya P.O, Kasaragod, Kerala, 671316, India
| | - Ranjith Kumavath
- Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Tejaswini Hills, Periya P.O, Kasaragod, Kerala, 671316, India.
| | - Debmalya Barh
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, West Bengal, India.,Division of Bioinformatics and Computational Genomics, NITTE University Center for Science Education and Research (NUCSER), NITTE (Deemed to be University), Deralakatte, Mangaluru, Karnataka, India.,Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Aline Vaz
- Molecular and Computational Biology of Fungi Laboratory, Department of Microbiology, Institute of Biological Sciences (ICB), Federal University of Minas Gerais (UFMG), Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Aristóteles Góes-Neto
- Molecular and Computational Biology of Fungi Laboratory, Department of Microbiology, Institute of Biological Sciences (ICB), Federal University of Minas Gerais (UFMG), Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Sandeep Tiwari
- Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Preetam Ghosh
- Department of Computer Science Virginia Commonwealth University, Virginia, 23284, USA
| | - Alice R Wattam
- Biocomplexity Institute, Virginia Tech University, Blacksburg, Virginia, 24061, USA
| | - Vasco Azevedo
- Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
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11
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Oliveira AF, Folador EL, Gomide ACP, Goes-Neto A, Azevedo VAC, Wattam AR. Cell Division in genus Corynebacterium: protein-protein interaction and molecular docking of SepF and FtsZ in the understanding of cytokinesis in pathogenic species. AN ACAD BRAS CIENC 2018; 90:2179-2188. [PMID: 29451601 DOI: 10.1590/0001-3765201820170385] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 08/23/2017] [Indexed: 11/22/2022] Open
Abstract
The genus Corynebacterium includes species of great importance in medical, veterinary and biotechnological fields. The genus-specific families (PLfams) from PATRIC have been used to observe conserved proteins associated to all species. Our results showed a large number of conserved proteins that are associated with the cellular division process. Was not observe in our results other proteins like FtsA and ZapA that interact with FtsZ. Our findings point that SepF overlaps the function of this proteins explored by molecular docking, protein-protein interaction and sequence analysis. Transcriptomic analysis showed that these two (Sepf and FtsZ) proteins can be expressed in different conditions together. The work presents novelties on molecules participating in the cell division event, from the interaction of FtsZ and SepF, as new therapeutic targets.
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Affiliation(s)
- Alberto F Oliveira
- Departamento de Biologia Geral, Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901 Belo Horizonte, MG, Brazil
| | - Edson L Folador
- Centro de Biotecnologia/CBiotec, Universidade Federal da Paraíba/UFPB, s/n, Castelo Branco III, 58051-085 João Pessoa, PB, Brazil
| | - Anne C P Gomide
- Departamento de Biologia Geral, Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901 Belo Horizonte, MG, Brazil
| | - Aristóteles Goes-Neto
- Departamento de Microbiologia, Laboratório de Biologia Molecular e Computacional de Fungos, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901 Belo Horizonte, MG, Brazil
| | - Vasco A C Azevedo
- Departamento de Biologia Geral, Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901 Belo Horizonte, MG, Brazil
| | - Alice R Wattam
- Biocomplexity Institute of Virginia Tech, 1015 Life Science Circle, Virginia Tech, 24060, Blacksburg, VA, U.S.A
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12
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Abstract
Bacteria and archaea, collectively known as prokaryotes, have in general genomes that are much smaller than those of eukaryotes. As a result, thousands of these genomes have been sequenced. In prokaryotes, gene architecture lacks the intron-exon structure of eukaryotic genes (with an occasional exception). These two facts mean that there is an abundance of data for prokaryotic genomes, and that they are easier to study than the more complex eukaryotic genomes. In this chapter, we provide an overview of genome comparison tools that have been developed primarily (sometimes exclusively) for prokaryotic genomes. We cover methods that use only the DNA sequences, methods that use only the gene content, and methods that use both data types.
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Affiliation(s)
- João C Setubal
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, Av. Prof. Lineu Prestes 748, São Paulo, SP, 05508-000, Brazil.
| | - Nalvo F Almeida
- School of Computing, Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil
| | - Alice R Wattam
- Biocomplexity Institute, Virginia Tech, Blacksburg, VA, USA
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13
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Oliveira A, Oliveira LC, Aburjaile F, Benevides L, Tiwari S, Jamal SB, Silva A, Figueiredo HCP, Ghosh P, Portela RW, De Carvalho Azevedo VA, Wattam AR. Insight of Genus Corynebacterium: Ascertaining the Role of Pathogenic and Non-pathogenic Species. Front Microbiol 2017; 8:1937. [PMID: 29075239 PMCID: PMC5643470 DOI: 10.3389/fmicb.2017.01937] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 09/21/2017] [Indexed: 11/22/2022] Open
Abstract
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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Affiliation(s)
- Alberto Oliveira
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Leticia C Oliveira
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Flavia Aburjaile
- Center of Genomics and System Biology, Federal University of Pará, Belém, Brazil
| | - Leandro Benevides
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Sandeep Tiwari
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Syed B Jamal
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Arthur Silva
- Center of Genomics and System Biology, Federal University of Pará, Belém, Brazil
| | - Henrique C P Figueiredo
- Aquacen, National Reference Laboratory for Aquatic Animal Diseases, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Preetam Ghosh
- Department of Computational Science, Virginia Commonwealth University, Richmond, VA, United States
| | - Ricardo W Portela
- Laboratory of Immunology and Molecular Bióloga, Health Sciences Institute, Federal University of Bahiaa, Salvador, Brazil
| | - Vasco A De Carvalho Azevedo
- Molecular and Cellular Laboratory, General Biology Department, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Alice R Wattam
- Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg, VA, United States
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14
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Imchen M, Kumavath R, Barh D, Azevedo V, Ghosh P, Viana M, Wattam AR. Searching for signatures across microbial communities: Metagenomic analysis of soil samples from mangrove and other ecosystems. Sci Rep 2017; 7:8859. [PMID: 28821820 PMCID: PMC5562921 DOI: 10.1038/s41598-017-09254-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 07/26/2017] [Indexed: 02/06/2023] Open
Abstract
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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Affiliation(s)
- Madangchanok Imchen
- Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Periye, Padanakkad P.O, Kasaragod, Kerala, 671314, India
| | - Ranjith Kumavath
- Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Periye, Padanakkad P.O, Kasaragod, Kerala, 671314, India.
| | - Debmalya Barh
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology, Nonakuri, Purba Medinipur, West Bengal, 721172, India.,Xcode Life Sciences, 3D Eldorado, 112 Nungambakkam High Road, Nungambakkam, Chennai, Tamil Nadu, 600034, India.,Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Vasco Azevedo
- Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Preetam Ghosh
- Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, 23284, USA
| | - Marcus Viana
- Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Instituto de Ciências Biológicas (ICB), Universidade Federal de Minas Gerais, Pampulha, Belo Horizonte, Minas Gerais, Brazil
| | - Alice R Wattam
- Biocomplexity Institute, Virginia Tech University, Blacksburg, Virginia, 24061, USA.
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15
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Viana MVC, Figueiredo H, Ramos R, Guimarães LC, Pereira FL, Dorella FA, Selim SAK, Salaheldean M, Silva A, Wattam AR, Azevedo V. Comparative genomic analysis between Corynebacterium pseudotuberculosis strains isolated from buffalo. PLoS One 2017; 12:e0176347. [PMID: 28445543 PMCID: PMC5406005 DOI: 10.1371/journal.pone.0176347] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 04/10/2017] [Indexed: 12/15/2022] Open
Abstract
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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Affiliation(s)
- Marcus Vinicius Canário Viana
- Departament of General Biology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Henrique Figueiredo
- AQUACEN, National Reference Laboratory for Aquatic Animal Diseases, Ministry of Fisheries and Aquaculture, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Rommel Ramos
- Center of Genomic and System Biology, Federal University of Pará, Belém, Pará, Brazil
| | - Luis Carlos Guimarães
- Center of Genomic and System Biology, Federal University of Pará, Belém, Pará, Brazil
| | - Felipe Luiz Pereira
- AQUACEN, National Reference Laboratory for Aquatic Animal Diseases, Ministry of Fisheries and Aquaculture, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Fernanda Alves Dorella
- AQUACEN, National Reference Laboratory for Aquatic Animal Diseases, Ministry of Fisheries and Aquaculture, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Mohammad Salaheldean
- Department of Microbiology, Faculty of Veterinary Medicine, Cairo University, Giza, Egypt
| | - Artur Silva
- Center of Genomic and System Biology, Federal University of Pará, Belém, Pará, Brazil
| | - Alice R. Wattam
- Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Vasco Azevedo
- Departament of General Biology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- * E-mail:
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16
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Al Dahouk S, Köhler S, Occhialini A, Jiménez de Bagüés MP, Hammerl JA, Eisenberg T, Vergnaud G, Cloeckaert A, Zygmunt MS, Whatmore AM, Melzer F, Drees KP, Foster JT, Wattam AR, Scholz HC. Brucella spp. of amphibians comprise genomically diverse motile strains competent for replication in macrophages and survival in mammalian hosts. Sci Rep 2017; 7:44420. [PMID: 28300153 PMCID: PMC5353553 DOI: 10.1038/srep44420] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 02/07/2017] [Indexed: 12/31/2022] Open
Abstract
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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Affiliation(s)
- Sascha Al Dahouk
- German Federal Institute for Risk Assessment (BfR), Department of Biological Safety, Berlin, Germany.,RWTH Aachen University, Department of Internal Medicine III, Aachen, Germany
| | - Stephan Köhler
- Université Montpellier, Centre d'études d'agents Pathogènes et Biotechnologies pour la Santé (CPBS), Montpellier, France.,CNRS, FRE3689, CPBS, Montpellier, France
| | - Alessandra Occhialini
- Université Montpellier, Centre d'études d'agents Pathogènes et Biotechnologies pour la Santé (CPBS), Montpellier, France.,CNRS, FRE3689, CPBS, Montpellier, France
| | - María Pilar Jiménez de Bagüés
- Unidad de Producción y Sanidad Animal, Centro de Investigación y Tecnología Agroalimentaria, Instituto Agroalimentario de Aragón - IA2 (CITA-Universidad de Zaragoza), Zaragoza, Spain
| | - Jens Andre Hammerl
- German Federal Institute for Risk Assessment (BfR), Department of Biological Safety, Berlin, Germany
| | | | - Gilles Vergnaud
- I2BC, CNRS, CEA, Univ. Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Axel Cloeckaert
- ISP, INRA, Université François Rabelais de Tours, UMR1282, Nouzilly, France
| | - Michel S Zygmunt
- ISP, INRA, Université François Rabelais de Tours, UMR1282, Nouzilly, France
| | | | - Falk Melzer
- Friedrich-Loeffler-Institut, German National Reference Laboratory for Animal Brucellosis, Jena, Germany
| | - Kevin P Drees
- University of New Hampshire, Department of Molecular, Cellular, and Biomedical Sciences, Durham, NH, USA
| | - Jeffrey T Foster
- University of New Hampshire, Department of Molecular, Cellular, and Biomedical Sciences, Durham, NH, USA
| | - Alice R Wattam
- Biocomplexity Institute, Virginia Tech, Blacksburg, VA, USA
| | - Holger C Scholz
- Bundeswehr Institute of Microbiology and German Center for Infection Research (DZIF), Munich, Germany
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17
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Wattam AR, Davis JJ, Assaf R, Boisvert S, Brettin T, Bun C, Conrad N, Dietrich EM, Disz T, Gabbard JL, Gerdes S, Henry CS, Kenyon RW, Machi D, Mao C, Nordberg EK, Olsen GJ, Murphy-Olson DE, Olson R, Overbeek R, Parrello B, Pusch GD, Shukla M, Vonstein V, Warren A, Xia F, Yoo H, Stevens RL. Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. Nucleic Acids Res 2016; 45:D535-D542. [PMID: 27899627 PMCID: PMC5210524 DOI: 10.1093/nar/gkw1017] [Citation(s) in RCA: 1036] [Impact Index Per Article: 129.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 10/14/2016] [Accepted: 11/09/2016] [Indexed: 12/14/2022] Open
Abstract
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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Affiliation(s)
- Alice R Wattam
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - James J Davis
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Rida Assaf
- Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | | | - Thomas Brettin
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Christopher Bun
- Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Neal Conrad
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Emily M Dietrich
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Terry Disz
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Joseph L Gabbard
- Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USA
| | - Svetlana Gerdes
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Christopher S Henry
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Ronald W Kenyon
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - Dustin Machi
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - Chunhong Mao
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - Eric K Nordberg
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - Gary J Olsen
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Daniel E Murphy-Olson
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Robert Olson
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Ross Overbeek
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA.,Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Bruce Parrello
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA.,Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Gordon D Pusch
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA
| | - Maulik Shukla
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | | | - Andrew Warren
- Biocomplexity Institute, Virginia Tech University, Blacksburg, VA 24060, USA
| | - Fangfang Xia
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Hyunseung Yoo
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Rick L Stevens
- Computation Institute, University of Chicago, Chicago, IL 60637, USA.,Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA.,Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
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18
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Davis JJ, Gerdes S, Olsen GJ, Olson R, Pusch GD, Shukla M, Vonstein V, Wattam AR, Yoo H. PATtyFams: Protein Families for the Microbial Genomes in the PATRIC Database. Front Microbiol 2016; 7:118. [PMID: 26903996 PMCID: PMC4744870 DOI: 10.3389/fmicb.2016.00118] [Citation(s) in RCA: 110] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 01/22/2016] [Indexed: 01/12/2023] Open
Abstract
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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Affiliation(s)
- James J Davis
- Computation Institute, University of ChicagoChicago, IL, USA; Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA
| | - Svetlana Gerdes
- Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA; Fellowship for Interpretation of GenomesBurr Ridge, IL, USA
| | - Gary J Olsen
- Department of Microbiology and Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign Urbana, IL, USA
| | - Robert Olson
- Computation Institute, University of ChicagoChicago, IL, USA; Mathematics and Computer Science Division, Argonne National LaboratoryArgonne, IL, USA
| | - Gordon D Pusch
- Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA; Fellowship for Interpretation of GenomesBurr Ridge, IL, USA
| | - Maulik Shukla
- Computation Institute, University of ChicagoChicago, IL, USA; Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA
| | - Veronika Vonstein
- Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA; Fellowship for Interpretation of GenomesBurr Ridge, IL, USA
| | - Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech University Blacksburg, VA, USA
| | - Hyunseung Yoo
- Computation Institute, University of ChicagoChicago, IL, USA; Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne IL, USA
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19
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Warren AS, Aurrecoechea C, Brunk B, Desai P, Emrich S, Giraldo-Calderón GI, Harb O, Hix D, Lawson D, Machi D, Mao C, McClelland M, Nordberg E, Shukla M, Vosshall LB, Wattam AR, Will R, Yoo HS, Sobral B. RNA-Rocket: an RNA-Seq analysis resource for infectious disease research. Bioinformatics 2015; 31:1496-8. [PMID: 25573919 PMCID: PMC4410666 DOI: 10.1093/bioinformatics/btv002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2014] [Revised: 12/10/2014] [Accepted: 12/31/2014] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. RESULTS RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. AVAILABILITY AND IMPLEMENTATION RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. CONTACT anwarren@vt.edu SUPPLEMENTARY INFORMATION Supplementary materials are available at Bioinformatics online.
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Affiliation(s)
- Andrew S Warren
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Cristina Aurrecoechea
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Brian Brunk
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Prerak Desai
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Scott Emrich
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Gloria I Giraldo-Calderón
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Omar Harb
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Deborah Hix
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Daniel Lawson
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Dustin Machi
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Chunhong Mao
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Michael McClelland
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Eric Nordberg
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Maulik Shukla
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Leslie B Vosshall
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Rebecca Will
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Hyun Seung Yoo
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
| | - Bruno Sobral
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA
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20
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Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, Olson R, Overbeek R, Parrello B, Pusch GD, Shukla M, Thomason JA, Stevens R, Vonstein V, Wattam AR, Xia F. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep 2015; 5:8365. [PMID: 25666585 PMCID: PMC4322359 DOI: 10.1038/srep08365] [Citation(s) in RCA: 1645] [Impact Index Per Article: 182.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 01/02/2015] [Indexed: 12/31/2022] Open
Abstract
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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Affiliation(s)
- Thomas Brettin
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Computation Institute, University of Chicago, Chicago, Illinois, 60637, USA
| | - James J. Davis
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Computation Institute, University of Chicago, Chicago, Illinois, 60637, USA
| | - Terry Disz
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Robert A. Edwards
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA
- Department of Computer Science, San Diego State University, San Diego, California, 92182, USA
| | - Svetlana Gerdes
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Gary J. Olsen
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Robert Olson
- Computation Institute, University of Chicago, Chicago, Illinois, 60637, USA
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA
| | - Ross Overbeek
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Bruce Parrello
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Gordon D. Pusch
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Maulik Shukla
- Virginia Bioinformatics Institute, Virginia Tech University, Blacksburg, VA, 24060, USA
| | - James A. Thomason
- USDA-ARS Laboratory at Cold Spring Harbor Laboratory, Cold Spring Harbor NY, 11724, USA
| | - Rick Stevens
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Computation Institute, University of Chicago, Chicago, Illinois, 60637, USA
- Department of Computer Science, University of Chicago, Chicago, Illinois, 60637, USA
| | - Veronika Vonstein
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne IL, 60439, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, 60527, USA
| | - Alice R. Wattam
- Virginia Bioinformatics Institute, Virginia Tech University, Blacksburg, VA, 24060, USA
| | - Fangfang Xia
- Computation Institute, University of Chicago, Chicago, Illinois, 60637, USA
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA
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Faria JP, Edirisinghe JN, Davis JJ, Disz T, Hausmann A, Henry CS, Olson R, Overbeek RA, Pusch GD, Shukla M, Vonstein V, Wattam AR. Enabling comparative modeling of closely related genomes: example genus Brucella. 3 Biotech 2015; 5:101-105. [PMID: 28324362 PMCID: PMC4327756 DOI: 10.1007/s13205-014-0202-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 02/17/2014] [Indexed: 12/22/2022] Open
Abstract
For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this short report, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as well as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.
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Affiliation(s)
- José P Faria
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
- IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
| | - Janaka N Edirisinghe
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
- Computation Institute, University of Chicago, Chicago, IL, USA
| | - James J Davis
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA.
- Computation Institute, University of Chicago, Chicago, IL, USA.
| | - Terrence Disz
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Anna Hausmann
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA
| | - Christopher S Henry
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
- Computation Institute, University of Chicago, Chicago, IL, USA
| | - Robert Olson
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Ross A Overbeek
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA
| | - Gordon D Pusch
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA
| | - Maulik Shukla
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA
| | - Veronika Vonstein
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
- Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA
| | - Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA
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22
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Mao C, Abraham D, Wattam AR, Wilson MJC, Shukla M, Yoo HS, Sobral BW. Curation, integration and visualization of bacterial virulence factors in PATRIC. ACTA ACUST UNITED AC 2014; 31:252-8. [PMID: 25273106 PMCID: PMC4287947 DOI: 10.1093/bioinformatics/btu631] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Motivation: We’ve developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity. Results: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A–C bacterial pathogen genera, Mycobacterium, Salmonella, Escherichia, Shigella, Listeria and Bartonella, using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein–protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC. Availability and implementation: All tools and data are freely available at PATRIC (http://patricbrc.org). Contact:cmao@vbi.vt.edu. Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Chunhong Mao
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | - David Abraham
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | - Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | | | - Maulik Shukla
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | - Hyun Seung Yoo
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | - Bruno W Sobral
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
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23
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Wattam AR, Foster JT, Mane SP, Beckstrom-Sternberg SM, Beckstrom-Sternberg JM, Dickerman AW, Keim P, Pearson T, Shukla M, Ward DV, Williams KP, Sobral BW, Tsolis RM, Whatmore AM, O'Callaghan D. Comparative phylogenomics and evolution of the Brucellae reveal a path to virulence. J Bacteriol 2014; 196:920-30. [PMID: 24336939 PMCID: PMC3957692 DOI: 10.1128/jb.01091-13] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Accepted: 12/04/2013] [Indexed: 11/20/2022] Open
Abstract
Brucella species include important zoonotic pathogens that have a substantial impact on both agriculture and human health throughout the world. Brucellae are thought of as "stealth pathogens" that escape recognition by the host innate immune response, modulate the acquired immune response, and evade intracellular destruction. We analyzed the genome sequences of members of the family Brucellaceae to assess its evolutionary history from likely free-living soil-based progenitors into highly successful intracellular pathogens. Phylogenetic analysis split the genus into two groups: recently identified and early-dividing "atypical" strains and a highly conserved "classical" core clade containing the major pathogenic species. Lateral gene transfer events brought unique genomic regions into Brucella that differentiated them from Ochrobactrum and allowed the stepwise acquisition of virulence factors that include a type IV secretion system, a perosamine-based O antigen, and systems for sequestering metal ions that are absent in progenitors. Subsequent radiation within the core Brucella resulted in lineages that appear to have evolved within their preferred mammalian hosts, restricting their virulence to become stealth pathogens capable of causing long-term chronic infections.
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Affiliation(s)
- Alice R. Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
| | - Jeffrey T. Foster
- Center for Microbial Genetics & Genomics, Northern Arizona University, Flagstaff, Arizona, USA
| | | | - Stephen M. Beckstrom-Sternberg
- Center for Microbial Genetics & Genomics, Northern Arizona University, Flagstaff, Arizona, USA
- Translational Genomics Research Institute, Pathogen Genomics Division, Phoenix, Arizona, USA
| | - James M. Beckstrom-Sternberg
- Center for Microbial Genetics & Genomics, Northern Arizona University, Flagstaff, Arizona, USA
- Translational Genomics Research Institute, Pathogen Genomics Division, Phoenix, Arizona, USA
| | - Allan W. Dickerman
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
| | - Paul Keim
- Center for Microbial Genetics & Genomics, Northern Arizona University, Flagstaff, Arizona, USA
- Translational Genomics Research Institute, Pathogen Genomics Division, Phoenix, Arizona, USA
| | - Talima Pearson
- Center for Microbial Genetics & Genomics, Northern Arizona University, Flagstaff, Arizona, USA
| | - Maulik Shukla
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
| | - Doyle V. Ward
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Kelly P. Williams
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
| | - Bruno W. Sobral
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
| | - Renee M. Tsolis
- Department of Medical Microbiology and Immunology, School of Medicine, University of California, Davis, California, USA
| | - Adrian M. Whatmore
- Department of Bacteriology, Animal Health & Veterinary Laboratories Agency, Addlestone, United Kingdom
| | - David O'Callaghan
- INSERM U1047, UFR Médecine, Nîmes, France
- Université Montpellier 1, UFR Médecine, Nîmes, France
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24
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Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, Edwards RA, Gerdes S, Parrello B, Shukla M, Vonstein V, Wattam AR, Xia F, Stevens R. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 2014; 42:D206-14. [PMID: 24293654 PMCID: PMC3965101 DOI: 10.1093/nar/gkt1226] [Citation(s) in RCA: 3096] [Impact Index Per Article: 309.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Revised: 11/04/2013] [Accepted: 11/05/2013] [Indexed: 01/12/2023] Open
Abstract
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.
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Affiliation(s)
- Ross Overbeek
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Robert Olson
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Gordon D. Pusch
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Gary J. Olsen
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - James J. Davis
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Terry Disz
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Robert A. Edwards
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Svetlana Gerdes
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Bruce Parrello
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Maulik Shukla
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Veronika Vonstein
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Alice R. Wattam
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Fangfang Xia
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
| | - Rick Stevens
- Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Department of Computer Science, San Diego State University, San Diego, CA 92182, USA, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL 60439, USA and Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
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25
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Abstract
The Pathosystems Resource Integration Center (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious-disease research. This method paper provides detailed instructions on using this resource to finding data specific to genomes, saving it in a personalized workspace and using a variety of interactive tools to analyze that data. While PATRIC contains many diverse tools and functionalities to explore both genome-scale and gene expression data, the main focus of this chapter is on comparative analysis of bacterial genomes.
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Affiliation(s)
- Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA, 24061, USA,
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26
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Wattam AR, Abraham D, Dalay O, Disz TL, Driscoll T, Gabbard JL, Gillespie JJ, Gough R, Hix D, Kenyon R, Machi D, Mao C, Nordberg EK, Olson R, Overbeek R, Pusch GD, Shukla M, Schulman J, Stevens RL, Sullivan DE, Vonstein V, Warren A, Will R, Wilson MJC, Yoo HS, Zhang C, Zhang Y, Sobral BW. PATRIC, the bacterial bioinformatics database and analysis resource. Nucleic Acids Res 2013; 42:D581-91. [PMID: 24225323 PMCID: PMC3965095 DOI: 10.1093/nar/gkt1099] [Citation(s) in RCA: 873] [Impact Index Per Article: 79.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
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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Affiliation(s)
- Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60637, USA, Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60637, USA and Nestlé Institute of Health Sciences SA, Campus EPFL, Quartier de L'innovation, Lausanne, Switzerland
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27
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Abstract
MOTIVATION A vast amount of information about human, animal and plant pathogens has been acquired, stored and displayed in varied formats through different resources, both electronically and otherwise. However, there is no community standard format for organizing this information or agreement on machine-readable format(s) for data exchange, thereby hampering interoperation efforts across information systems harboring such infectious disease data. RESULTS The Pathogen Information Markup Language (PIML) is a free, open, XML-based format for representing pathogen information. XSLT-based visual presentations of valid PIML documents were developed and can be accessed through the PathInfo website or as part of the interoperable web services federation known as ToolBus/PathPort. Currently, detailed PIML documents are available for 21 pathogens deemed of high priority with regard to public health and national biological defense. A dynamic query system allows simple queries as well as comparisons among these pathogens. Continuing efforts are being taken to include other groups' supporting PIML and to develop more PIML documents. AVAILABILITY All the PIML-related information is accessible from http://www.vbi.vt.edu/pathport/pathinfo/
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Affiliation(s)
- Yongqun He
- Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA.
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28
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Affiliation(s)
- M G Kidwell
- Department of Ecology and Evolutionary Biology and The Center for Insect Science, The University of Arizona, Tucson, AZ 85721, USA.
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29
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Wattam AR, Christensen BM. Further evidence that the genes controlling susceptibility of Aedes aegypti to filarial parasites function independently. J Parasitol 1992; 78:1092-5. [PMID: 1491306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Comparisons were made of in vivo labeled polypeptides from Aedes aegypti strains refractory to either Brugia malayi or Dirofilaria immitis. There does not seem to be a generalized "anti-parasite" polypeptide response that mosquitoes refractory to filarial worm infection produce following bloodfeeding. Instead, it seems that any response produced by these mosquitoes is localized to the tissue in which the filarial parasite develops.
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Affiliation(s)
- A R Wattam
- Department of Animal Health and Biomedical Sciences, University of Wisconsin, Madison 53706
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30
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Wattam AR, Christensen BM. Further Evidence That the Genes Controlling Susceptibility of Aedes aegypti to Filarial Parasites Function Independently. J Parasitol 1992. [DOI: 10.2307/3283238] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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31
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Abstract
Translation products were used to monitor changes in gene expression between different strains and developmental stages of Aedes aegypti. Total RNA was isolated from fourth stadium larvae, male and female pupae, and male and female adults collected at fixed time intervals following pupation and ecdysis. Differences in RNA populations were assessed by in vitro translation followed by one- and two-dimensional polyacrylamide gel electrophoresis and fluorography. Variations in gene expression between sexes and during development were examined in Liverpool (LVP) and Rockefeller (RKF) Ae. aegypti strains. Sex-related differences consisted primarily of differing lengths of expression for certain polypeptides, although two-dimensional electrophoresis revealed changes in intensity of a 44-kD polypeptide with a pI of 7.9 between males and females. Fourth stadium larvae, pupae, and adults expressed different translation products, which probably correlated with developmental differences. Strain-related differences were observed between LVP and RKF.
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Affiliation(s)
- A R Wattam
- Department of Animal Health and Biomedical Sciences, University of Wisconsin, Madison
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32
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Abstract
Brugia malayi and Wuchereria bancrofti are mosquito-borne parasitic nematodes responsible for lymphatic filariasis in approximately 90 million people. The genetic control of the susceptibility of Aedes aegypti mosquitoes to B. malayi was well defined 30 years ago, but no data have since been provided regarding the gene products responsible for susceptibility or refractoriness or both. We addressed this problem by assessing polypeptide synthesis in thoracic tissue, the developmental site of this parasite, in susceptible and refractory strains of A. aegypti. Polyacrylamide gel electrophoresis of radiolabeled polypeptides synthesized in vivo were compared between (i) established susceptible and refractory strains and (ii) a refractory strain newly isolated from the established susceptible strain. Six polypeptide differences recognized by SDS/PAGE and two-dimensional gel electrophoresis were seen only in the refractory strains after they took a blood meal. A seventh polypeptide was present in those refractory mosquitoes that had ingested sucrose but increased in intensity after blood-feeding. The presence of parasites in the blood meal was not necessary to stimulate the synthesis of these polypeptides. These refractory strain-associated molecules may mediate genetically determined variation in susceptibility.
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Affiliation(s)
- A R Wattam
- Department of Animal Health and Biomedical Sciences, University of Wisconsin, Madison 53706
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33
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Abstract
Moles from England were examined for coccidian oocysts and all 64 Talpa europaea were infected; of 64 infected hosts, 56 (88%) had multiple infections representing two to six coccidian species when examined. Oocysts in 31 of the 64 samples remainedunsporulated. Three eimerians and one isosporan were studied from the 33 fecal samples that had sporulated oocysts and these are described as new species; Cyclospora talpae Pellérdy & Tanyi, 1968, and Isospora sofiae (Golemansky, 1978) Levine & Ivens, 1979, are redescribed; and Cyclospora sp., similar to C. talpae, is discussed. Sporulated oocysts of C. talpae are ellipsoidal, 14.3 X 9.6 (12-19 X 6-13) microns with sporocysts ovoid, 9.4 X 5.7 (6-13 X 4-8) microns; it was found in 21 of the 33 (63.6%) sporulated samples. Sporulated oocysts of Cyclospora sp. are subspheroidal to ellipsoidal, 12.5 X 8.9 (10-14 X 6-12) microns with sporocysts ovoid, 8.6 X 5.3 (6-10 X 4-6) microns; it was found in 21 of the 33 (63.6%) sporulated samples. Sporulated oocysts of Eimeria avonensis n. sp. are elongate-ellipsoidal, 15.0 X 9.6 (13-20 X 7-12) microns with sporocysts ovoid, 6.6 X 3.6 (5-9 X 3-7) microns; it was found in 15 of the 33 (45.5%) sporulated samples. Sporulated oocysts of Eimeria berea n. sp. are subspheroidal, 12.1 X 10.5 (10-15 X 8-14) microns with sporocysts ovoid, 6.3 X 3.9 (5-10 X 2-5) microns; it was found in 8 of the 33 (24.2%) sporulated samples.(ABSTRACT TRUNCATED AT 250 WORDS)
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Affiliation(s)
- D W Duszynski
- Department of Biology, University of New Mexico, Albuquerque 87131
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Duszynski DW, Wattam AR. Coccidian parasites (Apicomplexa: Eimeriidae) from insectivores. V. Ten forms from the moles of Japan (Euroscaptor, Mogera spp.). J Protozool 1988; 35:55-7. [PMID: 3367320 DOI: 10.1111/j.1550-7408.1988.tb04076.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Moles from Japan were examined for coccidian oocysts, and 67 of 77 (87%) hosts were infected including 8 of 11 (73%) Euroscaptor mizura, 31 of 36 (86%) Mogera kobeae, 17 of 17 M. tokudae, and 11 of 13 (85%) M. wogura. Of 67 infected hosts, 57 (85%) had multiple infections representing 2-5 coccidian species when examined. All oocysts in the infected fecal samples remained unsporulated and the absence of sporulation may be the result of storing feces from Japanese moles in 2% aqueous H2SO4. Five structurally distinct forms of unsporulated oocysts were found in E. mizura, and five distinct forms of unsporulated oocysts were also seen in Mogera spp. Two of the forms from E. mizura were similar to forms from Mogera spp., and the five forms from Mogera were shared freely between the three Mogera species. This is the first systematic survey of Japanese moles for coccidia.
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Affiliation(s)
- D W Duszynski
- Department of Biology, University of New Mexico, Albuquerque 87131
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