PATRIC as a unique resource for studying antimicrobial resistance

Briefings in Bioinformatics

Volumn 20, Issue 4, 2018, Pages 1094-1102

  Antonopoulos, Dionysios A ^a   Assaf, Rida ^a   Aziz, Ramy Karam ^b   Brettin, Thomas ^c   Bun, Christopher ^a   Conrad, Neal ^c   Davis, James J ^c   Dietrich, Emily M ^c   Disz, Terry ^d   Gerdes, Svetlana ^d   Kenyon, Ronald W ^e   Machi, Dustin ^e   Mao, Chunhong ^e   Murphy Olson, Daniel E ^c   Nordberg, Eric K ^e   Olsen, Gary J ^f   Olson, Robert ^c   Overbeek, Ross ^a   Parrello, Bruce ^c   Pusch, Gordon D ^g   Santerre, John ^a   Shukla, Maulik ^c   Stevens, Rick L ^c,g   Vanoeffelen, Margo ^d   Vonstein, Veronika ^d   Warren, Andrew S ^e   Wattam, Alice R ^e   Xia, Fangfang ^g   Yoo, Hyunseung ^c   more..

^a UNIVERSITY OF CHICAGO   (United States)

^b CAIRO UNIVERSITY   (Egypt)

^c ARGONNE NATIONAL LABORATORY   (United States)

^d Fellowship for Interpretation of Genomes in Illinois   (United States)

^e VIRGINIA BIOINFORMATICS INSTITUTE   (United States)

^f UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^g SEED and RAST   (United States)

Author keywords

antibiotic; antimicrobial resistance (AMR); genome annotation; minimum inhibitory concentration; RAST; the SEED

Indexed keywords

ANTIBIOTIC RESISTANCE; BIOLOGY; GENETIC DATABASE; GENETICS; HUMAN; INTERNET; MICROBIAL GENOME; MOLECULAR GENETICS; PROCEDURES; SYSTEM ANALYSIS;

COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; DRUG RESISTANCE, MICROBIAL; GENOME, MICROBIAL; HUMANS; INTERNET; MOLECULAR SEQUENCE ANNOTATION; SYSTEMS INTEGRATION;

EID: 85072949833     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbx083     Document Type: Article

References (57)

1. Wattam AR, Davis JJ, Assaf R, et al. Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. Nucleic Acids Res 2017;45:D535-42.
2. Greene JM, Collins F, Lefkowitz EJ, et al. National Institute of Allergy and Infectious Diseases bioinformatics resource centers: new assets for pathogen informatics. Infect Immun 2007; 75:3212-9.
3. Aziz RK, Bartels D, Best AA, et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics 2008; 9:1.
4. Brettin T, Davis JJ, Disz T, et al. 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.
5. Davis JJ, Gerdes S, Olsen GJ, et al. PATtyFams: protein families for the microbial genomes in the PATRIC database. Front Microbiol 2016;7:118.
6. Clark K, Karsch-Mizrachi I, Lipman DJ, et al. GenBank. Nucleic Acids Res 2016;44:D67-72.
7. Benson DA, Cavanaugh M, Clark K, et al. GenBank. Nucleic Acids Res 2017;45:D37.
8. O'Leary NA, Wright MW, Brister JR, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 2016; 44:D733-45.
9. World Health Organization. Antimicrobial Resistance. Draft Global Action Plan on Antimicrobial Resistance. Geneva:WHO, 2015.
10. Eurosurveillance Editorial Team. WHO member states adopt global action plan on antimicrobial resistance. Euro Surveill 2015;20.
11. Fauci AS, Collins FS. New strategies in battle against antibiotic resistance. https://directorsblog.nih.gov/2014/09/18/new-strategies-in-battle-against-antibiotic-resistance/.
12. Roca I, Akova M, Baquero F, et al. The global threat of antimicrobial resistance: science for intervention. New Microbes New Infect 2015;6:22-9.
13. Chen L. Notes from the field: pan-resistant New Delhi metallo-beta-lactamase-producing Klebsiella pneumoniae-Washoe County, Nevada, 2016. MMWR Morb Mortal Wkly Rep 2017;66:33.
14. Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States, 2013. Centres for Disease Control and Prevention, US Department of Health and Human Services, 2013.
15. Barrett T, Clark K, Gevorgyan R, et al. BioProject and BioSample databases at NCBI: facilitating capture and organization of metadata. Nucleic Acids Res 2012;40:D57-63.
16. Davis JJ, Boisvert S, Brettin T, et al. Antimicrobial resistance prediction in PATRIC and RAST. Sci Rep 2016;6:27930.
17. Kodama Y, Shumway M, Leinonen R. The Sequence Read Archive: explosive growth of sequencing data. Nucleic Acids Res 2012;40:D54-6.
18. Leinonen R, Akhtar R, Birney E, et al. The European Nucleotide Archive. Nucleic Acids Res 2010;gkq967.
19. Bankevich A, Nurk S, Antipov D, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012;19:455-77.
20. European Committee on Antimicrobial Susceptibility Testing. EUCAST guidelines for detection of resistance mechanisms and specific resistances of clinical and/or epidemiological importance. EUCAST, Basel, Switzerland, 2013. http://www/eucast.org/clinical-breakpoints.
21. Patel J, Cockerill F, Alder J, et al. Performance standards for antimicrobial susceptibility testing; twenty-fourth informational supplement. In: CLSI Standards for Antimicrobial Susceptibility Testing. Clinical and Laboratory Standards Institute, Wayne, PA, vol. 34, 2014, 1-226.
22. Bradley P, Gordon NC, Walker TM, et al. Rapid antibioticresistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat Commun 2015;6:10063.
23. Drouin A, Giguère S, Sagatovich V, et al. Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine. arXiv, preprint arXiv:1412.1074 [q-bio.GN], 2014.
24. Santerre JW, Davis JJ, Xia F, et al. Machine learning for antimicrobial resistance. arXiv:1607.01224 [stat.ML], 2016.
25. Freund Y, Schapire RE, A decision-theoretic generalization of on-line learning and an application to boosting. In: European Conference on Computational Learning Theory. Springer, 1995, 23-37.
26. Freund Y, Schapire R, Abe N. A short introduction to boosting. J Jpn Soc Artif Intell 1999;14:1612.
27. Long SW, Olsen RJ, Eager TN, et al. Population genomic analysis of 1, 777 extended-spectrum beta-lactamase producing Klebsiella pneumoniae, Houston, Texas: unexpected abundance of clonal group 307. mBio, vol. 8, 2017.
28. Overbeek R, Olson R, Pusch GD, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 2014;42:D206-14.
29. Levy SB, McMurry LM, Barbosa TM, et al. Nomenclature for new tetracycline resistance determinants. Antimicrob Agents Chemother 1999;43:1523-4.
30. Chopra I, Roberts M. Tetracycline antibiotics: mode of action, applications, molecular biology, and epidemiology of bacterial resistance. Microbiol Mol Biol Rev 2001;65:232-60. second page, table of contents.
31. Bush K, Pazkill T, Jacoby J. β-lactamase classification and amino acid sequences for TEM, SHV and OXA extended-spectrumand inhibitor resistant enzymes. http://www.lahey.org/Studies/.
32. Thai QK, Bös F, Pleiss J. The lactamase engineering database: a critical survey of TEM sequences in public databases. BMC Genomics 2009;10:390.
33. FischerM, Thai QK, GriebM, et al. DWARF-a data warehouse system for analyzing protein families. BMC Bioinformatics 2006;7:495.
34. Pasteur I. Klebsiella sequence typing. http://bigsdb.pasteur.fr/klebsiella/klebsiella.html.
35. McArthur AG, Waglechner N, Nizam F, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 2013;57:3348-57.
36. NCBI. Bacterial antimicrobial resistance reference gene database, 2017. https://www.ncbi.nlm.nih.gov/bioproject/?term1/231 30472017.
37. Zankari E, Hasman H, Cosentino S, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012;67:2640-4.
38. Boratyn GM, Camacho C, Cooper PS, et al. BLAST: a more efficient report with usability improvements. Nucleic Acids Res 2013;41:W29-33.
39. Madden T. The BLAST sequence analysis tool. In: The NCBI Handbook [Internet], 2nd ed., National Center for Biotechnology Information, Bethesda, MD, 2013.
40. Haft DH, Selengut JD, Richter RA, et al. TIGRFAMs and genome properties in 2013. Nucleic Acids Res 2013;41:D387-95.
41. Sun J, Deng Z, Yan A. Bacterial multidrug efflux pumps: mechanisms, physiology and pharmacological exploitations. Biochem Biophys Res Commun 2014;453:254-67.
42. Roberts MC, Sutcliffe J, Courvalin P, et al. Nomenclature for macrolide and macrolide-lincosamide-streptogramin B resistance determinants. Antimicrob Agents Chemother 1999; 43:2823-30.
43. Furnham N, Garavelli JS, Apweiler R, et al. Missing in action: enzyme functional annotations in biological databases. Nat Chem Biol 2009;5:521-5.
44. Schnoes AM, Brown SD, Dodevski I, et al. Annotation error in public databases: misannotation of molecular function in enzyme superfamilies. PLoS Comput Biol 2009;5:e1000605.
45. Ramirez MS, Tolmasky ME. Aminoglycoside modifying enzymes. Drug Resist Updat 2010;13:151-71.
46. Shaw KJ, Rather PN, Hare RS, et al. Molecular genetics of aminoglycoside resistance genes and familial relationships of the aminoglycoside-modifying enzymes. Microbiol Rev 1993; 57:138-63.
47. van Hoek AH, Mevius D, Guerra B, et al. Acquired antibiotic resistance genes: an overview. Front Microbiol 2011;2:203.
48. Roberts MC. Update on macrolide-lincosamide-streptogramin, ketolide, and oxazolidinone resistance genes. FEMS Microbiol Lett 2008;282:147-59.
49. Roberts MC. Nomenclature for tetracycline genes/nomenclature center for MLS genes, 2017. http://faculty.washington.edu/marilynr/2017.
50. Kim S, Thiessen PA, Bolton EE, et al. PubChem substance and compound databases. Nucleic Acids Res 2015;4:44.
51. Federhen S. Type material in the NCBI taxonomy database. Nucleic Acids Res 2015;43:D1086-98.
52. Maness MJ, Sparling PF. Multiple antibiotic resistance due to a single mutation in Neisseria gonorrhoeae. J Infect Dis 1973;128: 321-30.
53. Mac Aogain M, Kilkenny S, Walsh C, et al. Identification of a novel mutation at the primary dimer interface of GyrA conferring fluoroquinolone resistance in Clostridium difficile. J Glob Antimicrob Resist 2015;3:295-9.
54. Santos-Lopez A, Bernabe-Balas C, Ares-Arroyo M, et al. A naturally occurring single nucleotide polymorphism in a multicopy plasmid produces a reversible increase in antibiotic resistance. Antimicrob Agents Chemother 2017;61: e01735-16.
55. Martinez J, Baquero F. Mutation frequencies and antibiotic resistance. Antimicrob Agents Chemother 2000;44:1771-7.
56. Suzuki S, Horinouchi T, Furusawa C. Prediction of antibiotic resistance by gene expression profiles. Nat Commun 2014;5.
57. Buels R, Yao E, Diesh CM, et al. JBrowse: a dynamic web platformfor genome visualization and analysis. Genome Biol 2016; 17:66.