Harmonized Genome Wide Typing of Tubercle Bacilli Using a Web-Based Gene-By-Gene Nomenclature System.

BACKGROUND: Global tuberculosis (TB) control is challenged by uncontrolled transmission of Mycobacterium tuberculosis complex (Mtbc) strains, esp. of multidrug (MDR) or extensively resistant (XDR) variants. Precise analysis of transmission networks is the basis to trace outbreak M/XDR clones and improve TB control. However, classical genotyping tools lack discriminatory power due to the high similarity of strains of particular successful lineages, e.g. Beijing or outbreak strains. This can be overcome by whole genome sequencing (WGS) approaches, but these are not yet standardized to facilitate larger investigations encompassing different laboratories or outbreak tracing across borders. METHODS: We established and improved a whole genome gene-by-gene multi locus sequence typing approach encompassing a stable set of core genome genes (cgMLST) and linked it to a web-based nomenclature server (cgMLST.org) facilitating assignment and storage of allele numbers. FINDINGS: We evaluated and refined a previously suggested cgMLST schema by using a reference strain set (n = 251) reflecting the global diversity of the Mtbc. A set of 2891 genes showed excellent performance with at least 97% of the genes reliably identified in strains of all Mtbc lineages and in discriminating outbreak strains. cgMLST allele numbers were automatically retrieved from and stored at cgMLST.org. INTERPRETATION: The refined cgMLST schema provides high resolution genome-based typing of clinical strains of all Mtbc lineages. Combined with a web-based nomenclature server, it facilitates rapid, high-resolution, and harmonized tracing of clinical Mtbc strains needed for prospective local and global surveillance.

Whole-genome-based Mycobacterium tuberculosis surveillance: a standardized, portable, and expandable approach.

Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system.

Identification of intermediate in evolutionary model of enterohemorrhagic Escherichia coli O157.

Highly pathogenic enterohemorrhagic Escherichia coli (EHEC) O157 cause a spectrum of clinical signs that include diarrhea, bloody diarrhea, and hemolytic uremic syndrome. The current evolutionary model of EHEC O157:H7/H(-) consists of a stepwise evolution scenario proceeding from O55:H7 to a node (hypothetical intermediate) that then branches into sorbitol-fermenting (SF) O157:H(-) and non-SF (NSF) O157:H7. To identify this hypothetical intermediate, we performed single nucleotide polymorphism analysis by sequencing of 92 randomly distributed backbone genomic regions of 40 O157:H7/H(-) isolates. Overall, 111 single nucleotide polymorphisms were identified in 75/92 partial open reading frames after sequencing 51,041 nt/strain. The EHEC O157:H7 strain LSU-61 from deer occupied an intermediate position between O55:H7 and both O157 branches (SF and NSF O157), complementing the stepwise evolutionary model of EHEC O157:H7/H(-). The animal origin of this intermediate emphasizes the value of nonhuman reservoirs in the clarification of the evolution of human pathogens.

Phylogenetic analysis of enterohemorrhagic Escherichia coli O157, Germany, 1987-2008.

Multilocus variable number tandem repeat analysis (MLVA) is a subtyping technique for characterizing human pathogenic bacteria such as enterohemorrhagic Escherichia coli (EHEC) O157. We determined the phylogeny of 202 epidemiologically unrelated EHEC O157:H7/H- clinical isolates through 8 MLVA loci obtained in Germany during 1987-2008. Biodiversity in the loci ranged from 0.66 to 0.90. Four of 8 loci showed null alleles and a frequency < or =44.1%. These loci were distributed among 48.5% of all strains. Overall, 141 MLVA profiles were identified. Phylogenetic analysis assigned 67.3% of the strains to 19 MLVA clusters. Specific MLVA profiles with an evolutionary persistence were identified, particularly within sorbitol-fermenting EHEC O157:H-.These pathogens belonged to the same MLVA cluster. Our findings indicate successful persistence of this clone.

Based Upon Repeat Pattern (BURP): an algorithm to characterize the long-term evolution of Staphylococcus aureus populations based on spa polymorphisms.

BACKGROUND: For typing of Staphylococcus aureus, DNA sequencing of the repeat region of the protein A (spa) gene is a well established discriminatory method for outbreak investigations. Recently, it was hypothesized that this region also reflects long-term epidemiology. However, no automated and objective algorithm existed to cluster different repeat regions. In this study, the Based Upon Repeat Pattern (BURP) implementation that is a heuristic variant of the newly described EDSI algorithm was investigated to infer the clonal relatedness of different spa types. For calibration of BURP parameters, 400 representative S. aureus strains with different spa types were characterized by MLST and clustered using eBURST as "gold standard" for their phylogeny. Typing concordance analysis between eBURST and BURP clustering (spa-CC) were performed using all possible BURP parameters to determine their optimal combination. BURP was subsequently evaluated with a strain collection reflecting the breadth of diversity of S. aureus (JCM 2002; 40:4544). RESULTS: In total, the 400 strains exhibited 122 different MLST types. eBURST grouped them into 23 clonal complexes (CC; 354 isolates) and 33 singletons (46 isolates). BURP clustering of spa types using all possible parameter combinations and subsequent comparison with eBURST CCs resulted in concordances ranging from 8.2 to 96.2%. However, 96.2% concordance was reached only if spa types shorter than 8 repeats were excluded, which resulted in 37% excluded spa types. Therefore, the optimal combination of the BURP parameters was "exclude spa types shorter than 5 repeats" and "cluster spa types into spa-CC if cost distances are less than 4" exhibiting 95.3% concordance to eBURST. This algorithm identified 24 spa-CCs, 40 singletons, and excluded only 7.8% spa types. Analyzing the natural population with these parameters, the comparison of whole-genome micro-array groupings (at the level of 0.31 Pearson correlation index) and spa-CCs gave a concordance of 87.1%; BURP spa-CCs vs. manually grouped spa types resulted in 95.7% concordance. CONCLUSION: BURP is the first automated and objective tool to infer clonal relatedness from spa repeat regions. It is able to extract an evolutionary signal rather congruent to MLST and micro-array data.

Automated DNA sequence-based early warning system for the detection of methicillin-resistant Staphylococcus aureus outbreaks.

BACKGROUND: The detection of methicillin-resistant Staphylococcus aureus (MRSA) usually requires the implementation of often rigorous infection-control measures. Prompt identification of an MRSA epidemic is crucial for the control of an outbreak. In this study we evaluated various early warning algorithms for the detection of an MRSA cluster. METHODS AND FINDINGS: Between 1998 and 2003, 557 non-replicate MRSA strains were collected from staff and patients admitted to a German tertiary-care university hospital. The repeat region of the S. aureus protein A (spa) gene in each of these strains was sequenced. Using epidemiological and typing information for the period 1998-2002 as reference data, clusters in 2003 were determined by temporal-scan test statistics. Various early warning algorithms (frequency, clonal, and infection control professionals [ICP] alerts) were tested in a prospective analysis for the year 2003. In addition, a newly implemented automated clonal alert system of the Ridom StaphType software was evaluated. A total of 549 of 557 MRSA were typeable using spa sequencing. When analyzed using scan test statistics, 42 out of 175 MRSA in 2003 formed 13 significant clusters (p < 0.05). These clusters were used as the "gold standard" to evaluate the various algorithms. Clonal alerts (spa typing and epidemiological data) were 100% sensitive and 95.2% specific. Frequency (epidemiological data only) and ICP alerts were 100% and 62.1% sensitive and 47.2% and 97.3% specific, respectively. The difference in specificity between clonal and ICP alerts was not significant. Both methods exhibited a positive predictive value above 80%. CONCLUSIONS: Rapid MRSA outbreak detection, based on epidemiological and spa typing data, is a suitable alternative for classical approaches and can assist in the identification of potential sources of infection.

Ridom TraceEdit: a DNA trace editor and viewer.

Ridom TraceEdit is a cross-platform graphical DNA trace viewer and editor. TraceEdit displays the chromatogram files from Applied Biosystems automated sequencers and files in the Staden SCF format. Incorrect base calls can be edited and saved.

Typing of methicillin-resistant Staphylococcus aureus in a university hospital setting by using novel software for spa repeat determination and database management.

The spa gene of Staphylococcus aureus encodes protein A and is used for typing of methicillin-resistant Staphylococcus aureus (MRSA). We used sequence typing of the spa gene repeat region to study the epidemiology of MRSA at a German university hospital. One hundred seven and 84 strains were studied during two periods of 10 and 4 months, respectively. Repeats and spa types were determined by Ridom StaphType, a novel software tool allowing rapid repeat determination, data management and retrieval, and Internet-based assignment of new spa types following automatic quality control of DNA sequence chromatograms. Isolates representative of the most abundant spa types were subjected to multilocus sequence typing and pulsed-field gel electrophoresis. One of two predominant spa types was replaced by a clonally related variant in the second study period. Ten unique spa types, which were equally distributed in both study periods, were recovered. The data show a rapid dynamics of clone circulation in a university hospital setting. spa typing was valuable for tracking of epidemic isolates. The data show that disproval of epidemiologically suggested transmissions of MRSA is one of the main objectives of spa typing in departments with a high incidence of MRSA.

RIDOM: comprehensive and public sequence database for identification of Mycobacterium species.

BACKGROUND: Molecular identification of Mycobacterium species has two primary advantages when compared to phenotypic identification: rapid turn-around time and improved accuracy. The information content of the 5' end of the 16S ribosomal RNA gene (16S rDNA) is sufficient for identification of most bacterial species. However, reliable sequence-based identification is hampered by many faulty and some missing sequence entries in publicly accessible databases. METHODS: In order to establish an improved 16S rDNA sequence database for the identification of clinical and environmental isolates, we sequenced both strands of the 5' end of 16S rDNA (Escherichia coli positions 54 to 510) from 199 mycobacterial culture collection isolates. All validly described species (n = 89; up to March 21, 2000) and nearly all published sequevar variants were included. If the 16S rDNA sequences were not discriminatory, the internal transcribed spacer (ITS) region sequences (n = 84) were also determined. RESULTS: Using 5'-16S rDNA sequencing a total of 64 different mycobacterial species (71.9%) could be identified. With the additional input of the ITS sequence, a further 16 species or subspecies could be differentiated. Only Mycobacterium tuberculosis complex species, M. marinum/M. ulcerans and the M. avium subspecies could not be differentiated using 5'-16S rDNA or ITS sequencing. A total of 77 culture collection strain sequences, exhibiting an overlap of at least 80% and identical by strain number to the isolates used in this study, were found in the GenBank. Comparing these with our sequences revealed that an average of 4.31 nucleotide differences (SD +/- 0.57) were present. CONCLUSIONS: The data from this analysis show that it is possible to differentiate most mycobacterial species by sequence analysis of partial 16S rDNA. The high-quality sequences reported here, together with ancillary information (e.g., taxonomic, medical), are available in a public database, which is currently being expanded in the RIDOM project http://www.ridom-rdna.de), for similarity searches.

RIDOM: Ribosomal Differentiation of Medical Micro-organisms Database.

The ribosomal differentiation of medical micro-organisms (RIDOM) web server, first described by Harmsen et al. [Harmsden,D., Rothganger,J., Singer,C., Albert,J. and Frosch,M. (1999) Lancet, 353, 291], is an evolving electronic resource designed to provide micro-organism differentiation services for medical identification needs. The diagnostic procedure begins with a specimen partial small subunit ribosomal DNA (16S rDNA) sequence. Resulting from a similarity search, a species or genus name for the specimen in question will be returned. Where the first results are ambiguous or do not define to species level, hints for further molecular, i.e. internal transcribed spacer, and conventional phenotypic differentiation will be offered ('sequential and polyphasic approach'). Additionally, each entry in RIDOM contains detailed medical and taxonomic information linked, context-sensitive, to external World Wide Web services. Nearly all sequences are newly determined and the sequence chromatograms are available for intersubjective quality control. Similarity searches are now also possible by direct submission of trace files (ABI or SCF format). Based on the PHRED/PHRAP software, error probability measures are attached to each predicted nucleotide base and visualised with a new 'Trace Editor'. The RIDOM web site is directly accessible on the World Wide Web at http://www.ridom.de/. The email address for questions and comments is webmaster@ridom.de.