Global microbial identifier

The genomic epidemiological database for global identification of microorganisms or global microbial identifier (GMI) [1] is a platform for storing whole genome sequencing (WGS) data of microorganisms, for the identification of relevant genes and for the comparison of genomes to detect and track-and-trace infectious disease outbreaks and emerging pathogens.[2] The database holds two types of information: 1) genomic information of microorganisms, linked to, 2) metadata of those microorganism such as epidemiological details. The database includes all genera of microorganisms: bacteria, viruses, parasites and fungi.

Technology

For genotyping of microorganisms for medical diagnosis, or other purposes, scientists may use a wide variety of DNA profiling techniques, such as PCR, PFGE and MLST. A complication of this broad variety of pre-WGS techniques is the difficulty to standardize between techniques, laboratories and microorganisms, which may be overcome using the complete DNA code of the genome generated by WGS techniques.[3] For straight forward diagnostic identification the WGS information of a microbiological sample is fed into a global genomic database and compared using BLAST procedures to the genomes already present in the database.[4] In addition, WGS data may be used to back calculate to the different pre-WGS genotyping methods, so previous collected valuable information is not lost.[5][6] For the global microbial identifier the genomic information is coupled to a wide spectrum of metadata about the specific microbial clone and includes important clinical and epidemiological information such as the global finding place(s), treatment options and antimicrobial resistance, making it a general microbiological identification tool.This makes personalized treatment of microbial disease possible as well as real-time tracing systems for global surveillance of infectious diseases for food safety and serving human health.

The initiative

The initiative for building the database arose in 2011 and when several preconditions were met : 1) WGS has become mature and serious alternative for other genotyping techniques,[7][8] 2) the price of WGS has started falling dramatically and in some cases below the price of traditional identifications, 3) vast amounts of IT resources and a fast Internet have become available, and 4) there is the idea that via a cross sectoral and One Health approach infectious diseases may be better controlled.[9][10]

Starting the second millennium, many microbiological laboratories, as well as national health institutes, started genome sequencing projects for sequencing the infectious agents collections they had in their biobanks.[11][12] Thereby generating private databases and sending model genomes to global nucleotide databases such as GenBank of the NCBI[13] or the nucleotide database of the EMBL.[14] This created a wealth of genomic information and independent databases for eukaryotic as well as prokaryotic genomes.[15][16][17] The need to further integrate these databases and to harmonize data collection, and to link the genomic data to metadata for optimal prevention of infectious diseases, was generally recognized by the scientific community.[18] In 2011, several infectious disease control centers and other organizations took the initiative of a series of international scientific- and policy-meetings, to develop a common platform and to better understand the potentials of an interactive microbiological genomic database. The first meeting was in Brussels, September 2011,[19][20] followed by meetings in Washington (March 2012) and Copenhagen[21] (February 2013). In addition to experts from around the globe, Intergovernmental Organizations have been included in the action, notably the World Health Organization (WHO) and the World Organization for Animal Health (OIE).

Development plan

A detailed roadmap[22] for the development of the database was set up with the following general timeline:

2010 - 2012: Development of pilot systems.[4]
2011 - 2013: International structural start-up, with the formation of an international core group, analysis of the present and future landscape to build the database, and diplomacy efforts to bring the relevant groups together.
2012 - 2016: Development of a robust IT-backbone for the database, and development of novel genome analysis algorithms and software.
2017 - 2020: Construction of a global solution, including the creation of networks and regional hubs.

Steering committee

Current members:

Former members:

Secretariat

  • Research manager, Frank Møller Aarestrup, Technical University of Denmark.
  • Administrative coordinator, Vibeke Dybdahl Hammer, Technical University of Denmark.

See also

References

  1. GMI. "Global Microbial Identifier".
  2. Schlundt, J (2011). "The time is right for a global genomic database for microorganisms" (PDF). Health Diplomacy Monitor. 3 (2): 2–3.
  3. Shendure, J (2008). "Next-generation DNA sequencing". Nat. Biotechnol. 26 (10): 1135–1145. doi:10.1038/nbt1486. PMID 18846087.
  4. 1 2 "genomic epidemiolgy database".
  5. Inouye, M; et al. (2012). "Short read sequence typing (SRST):multi-locus sequence types from short reads". BMC Genomics. 13: 388. doi:10.1186/1471-2164-13-338. PMC 3460743. PMID 22827703.
  6. Larsen, MV; et al. (2012). "Multilocus sequence typing of total-genome-sequenced bacteria". J Clin Microbiol. 50 (4): 1355–1366. doi:10.1128/JCM.06094-11. PMC 3318499. PMID 22238442.
  7. Zankari, E; et al. (2013). "Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing". J Antimicrob Chemother. 68 (4): 771–7. doi:10.1093/jac/dks496. PMID 23233485.
  8. Dunne, WM; et al. (2012). "Next-generation and whole-genome sequencing in the diagnostic clinical microbiology laboratory". Eur J Clin Microbiol Infect. Dis. 31 (8): 1719–17126. doi:10.1007/s10096-012-1641-7. PMID 22678348.
  9. Current Topics in Microbiology and Immunology, Vol 366 (2013). Mackenzie, J.S.; Jeggo, M.; Daszak, P.; Richt, J, eds. One Health: The Human-Animal-Environment Interfaces in Emerging Infectious Diseases. Springer. p. 280. ISBN 978-3-540-70961-9.
  10. Wielinga, PR; Schlundt, J (2013). "Food Safety: At the Center of a One Health Approach for Combating Zoonoses". Curr Top Microbiol Immunol: 3–17. doi:10.1007/82_2012_238. PMID 22763857.
  11. A summary of genomic databases. "Bacterial genome databases".
  12. WGS projects info by EBI. "WGS projects".
  13. Genome Browser NCBI. "Genome information by organism".
  14. Genome Browser EMBL. "Access to Completed Genomes".
  15. Microbial Genomes Database. "MBGD".
  16. "Other genomic databases via EBI".
  17. DOE's Joint Genome Institute Integrated Microbial Genomes (IMG). "IMG DOEs JGI".
  18. Aarestrup, F; et al. (2012). "Integrating Genome-based Informatics to Modernize Global Disease Monitoring, Information Sharing, and Response". Emerg Infect Dis. 18 (11): e1. doi:10.3201/eid/1811.120453. PMC 3559169. PMID 23092707.
  19. Kupferschmidt, K (2011). "Epidemiology. Outbreak detectives embrace the genome era". Science. 333 (6051): 1818–1819. doi:10.1126/science.333.6051.1818. PMID 21960605.
  20. "Consensus report of an expert meeting 1-2 September 2011, Brussels, Belgium" (PDF).
  21. GMI. "GMI news and events".
  22. GMI. "GMI development plan".
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