Dataset Information

Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data.

ABSTRACT: The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacterial meningitis worldwide. Neisseria meningitidis strains are characterized with MLST as specific sequence types (ST) and clonal complexes (CC) based on the DNA sequences at defined loci. These data are vital to molecular epidemiology studies of N. meningitidis, including outbreak investigations and population biology. MGIP analyzes DNA sequence trace files, returns individual allele calls and characterizes the STs and CCs. MGIP represents a substantial advance over existing software in several respects: (i) ease of use-MGIP is user friendly, intuitive and thoroughly documented; (ii) flexibility--because MGIP is a website, it is compatible with any computer with an internet connection, can be used from any geographic location, and there is no installation; (iii) speed--MGIP takes just over one minute to process a set of 96 trace files; and (iv) expandability--MGIP has the potential to expand to more loci than those used in MLST and even to other bacterial species.

SUBMITTER: Katz LS

PROVIDER: S-EPMC2703879 | biostudies-other | 2009 Jul

REPOSITORIES: biostudies-other

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Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data.

Katz Lee S LS Bolen Chris R CR Harcourt Brian H BH Schmink Susanna S Wang Xin X Kislyuk Andrey A Taylor Robert T RT Mayer Leonard W LW Jordan I King IK

Nucleic acids research 20090525 Web Server issue

The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacterial meningitis worldwide. Neisseria meningitidis strains are characterized with MLST as specific sequence types (ST) and clonal complexes (CC) based on the DNA sequences at defined loci. These data are ...[more]

PMID: 19468047

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Project description:Streptococcus mutans is one of the primary pathogens responsible for the development of dental caries. Recent whole-genome sequencing (WGS)-based core genome multilocus sequence typing (cgMLST) approaches have been employed in epidemiological studies of specific human pathogens. However, this approach has not been reported in studies of S. mutans Here, we therefore developed a cgMLST scheme for S. mutans We surveyed 199 available S. mutans genomes as a means of identifying cgMLST targets, developing a scheme that incorporated 594 targets from the S. mutans UA159 reference genome. Sixty-eight sequence types (STs) were identified in this cgMLST scheme (cgSTs) in 80 S. mutans isolates from 40 children that were sequenced in this study, compared to 35 STs identified by multilocus sequence typing (MLST). Fifty-six cgSTs (82.35%) were associated with a single isolate based on our cgMLST scheme, which is significantly higher than in the MLST scheme (11.43%). In addition, 58.06% of all MLST profiles with??2 isolates were further differentiated by our cgMLST scheme. Topological analyses of the maximum likelihood phylogenetic trees revealed that our cgMLST scheme was more reliable than the MLST scheme. A minimum spanning tree of 145 S. mutans isolates from 10 countries developed based upon the cgMLST scheme highlighted the diverse population structure of S. mutans This cgMLST scheme thus offers a new molecular typing method suitable for evaluating the epidemiological distribution of this pathogen and has the potential to serve as a benchmark for future global studies of the epidemiological nature of dental caries.IMPORTANCE Streptococcus mutans is regarded as a major pathogen responsible for the onset of dental caries. S. mutans can transmit among people, especially within families. In this study, we established a new epidemiological approach to S. mutans classification. This approach can effectively differentiate among closely related isolates and offers superior reliability relative to that of the traditional MLST molecular typing method. As such, it has the potential to better support effective public health strategies centered around this bacterium that are aimed at preventing and treating dental caries.

Dataset Information

Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data.

Publications

Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data.

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