BACKGROUND: Worldwide effort on sampling and characterization of molecular variation within a large number of human and animal pathogens has lead to the emergence of multi-locus sequence typing (MLST) databases as an important tool for studying the epidemiology and evolution of pathogens. Many of these databases are currently harboring several thousands of multi-locus DNA sequence types (STs) enriched with metadata over traits such as serotype, antibiotic resistance, host organism etc of the isolates. Curators of the databases have thus the possibility of dividing the pathogen populations into subsets representing different evolutionary lineages, geographically associated groups, or other subpopulations, which are defined in terms of molecular similarities and dissimilarities residing within a database. When combined with the existing metadata, such subsets may provide invaluable information for assessing the position of a new set of isolates in relation to the whole pathogen population. RESULTS: To enable users of MLST schemes to query the databases with sets of new bacterial isolates and to automatically analyze their relation to existing curated sequences, we introduce here a Bayesian model-based method for semi-supervised classification of MLST data. Our method can use an MLST database as a training set and assign simultaneously any set of query sequences into the earlier discovered lineages/populations, while also allowing some or all of these sequences to form previously undiscovered genetically distinct groups. This tool provides probabilistic quantification of the classification uncertainty and is highly efficient computationally, thus enabling rapid analyses of large databases and sets of query sequences. The latter feature is a necessary prerequisite for an automated access through the MLST web interface. We demonstrate the versatility of our approach by anayzing both real and synthesized data from MLST databases. The introduced method for semi-supervised classification of sets of query STs is freely available for Windows, Mac OS X and Linux operative systems in BAPS 5.4 software which is downloadable at http://web.abo.fi/fak/mnf/mate/jc/software/baps.html. The query functionality is also directly available for the Staphylococcus aureus database at http://www.mlst.net and shortly will be available for other species databases hosted at this web portal. CONCLUSIONS: We have introduced a model-based tool for automated semi-supervised classification of new pathogen samples that can be integrated into the web interface of the MLST databases. In particular, when combined with the existing metadata, the semi-supervised labeling may provide invaluable information for assessing the position of a new set of query strains in relation to the particular pathogen population represented by the curated database.Such information will be useful both for clinical and basic research purposes.

UNLABELLED: WebACT is an online resource which enables the rapid provision of simultaneous BLAST comparisons between up to five genomic sequences in a format amenable for visualization with the well-known Artemis Comparison Tool (ACT). Comparisons can be generated on-the-fly using sequences directly retrieved via EMBL database queries, or by entering or uploading user sequences. Furthermore, pre-computed comparisons are available between all publicly available, completed prokaryotic genomes and plasmids currently contained within the Genome Reviews database (372 sequences, representing 175 different species). The system is designed to minimize the volume of downloaded data and maximize performance. Genome sequences, annotation and pre-computed comparisons are stored in a relational database allowing flexible querying based on user-defined sequence regions, from whole genome to a defined region flanking a specified gene. Comparison and sequence files, whether computed online or retrieved from the database of pre-computed genome comparisons, can be viewed online using ACT and are available for download. AVAILABILITY: Freely accessible at http://www.webact.org. SUPPLEMENTARY INFORMATION: User guide and worked examples are available at http://www.webact.org/WebACT/docs.

Abstract Motivation: Multi Locus Sequence Typing (MLST) is a newly developed typing method for bacteria based on the sequence determination of internal fragments of seven house-keeping genes. It has proved useful in characterizing and monitoring disease-causing and antibiotic resistant lineages of bacteria. The strength of this approach is that unlike data obtained using most other typing methods, sequence data are unambiguous, can be held on a central database and be queried through a web server. Results: A database-driven software system (mlstdb) has been developed, which is used by public health laboratories and researchers globally to query their nucleotide sequence data against centrally held databases over the internet. The mlstdb system consists of a set of perl scripts for defining the database tables and generating the database management interface and dynamic web pages for querying the databases. Availability: http://www.mlst.net. Contact: [email protected] * To whom correspondence should be addressed. 2 Present address: Department of Paediatrics, The Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK. 3 Present address: Department of Infectious Disease Epidemiology, Imperial College School of Medicine, University of London, St Mary’s Campus, Norfolk Place, London W2 1PG, UK.