Core Genome Multilocus Sequence Typing: a Standardized Approach for Molecular Typing of Mycoplasma gallisepticum.
ABSTRACT: Mycoplasma gallisepticum is the most virulent and economically important Mycoplasma species for poultry worldwide. Currently, M. gallisepticum strain differentiation based on sequence analysis of 5 loci remains insufficient for accurate outbreak investigation. Recently, whole-genome sequences (WGS) of many human and animal pathogens have been successfully used for microbial outbreak investigations. However, the massive sequence data and the diverse properties of different genes within bacterial genomes results in a lack of standard reproducible methods for comparisons among M. gallisepticum whole genomes. Here, we proposed the development of a core genome multilocus sequence typing (cgMLST) scheme for M. gallisepticum strains and field isolates. For development of this scheme, a diverse collection of 37 M. gallisepticum genomes was used to identify cgMLST targets. A total of 425 M. gallisepticum conserved genes (49.85% of M. gallisepticum genome) were selected as core genome targets. A total of 81 M. gallisepticum genomes from 5 countries on 4 continents were typed using M. gallisepticum cgMLST. Analyses of phylogenetic trees generated by cgMLST displayed a high degree of agreement with geographical and temporal information. Moreover, the high discriminatory power of cgMLST allowed differentiation between M. gallisepticum strains of the same outbreak. M. gallisepticum cgMLST represents a standardized, accurate, highly discriminatory, and reproducible method for differentiation among M. gallisepticum isolates. cgMLST provides stable and expandable nomenclature, allowing for comparison and sharing of typing results among laboratories worldwide. cgMLST offers an opportunity to harness the tremendous power of next-generation sequencing technology in applied avian mycoplasma epidemiology at both local and global levels.
Project description:Clostridium difficile, recently renamed Clostridioides difficile, is the most common cause of antibiotic-associated nosocomial gastrointestinal infections worldwide. To differentiate endogenous infections and transmission events, highly discriminatory subtyping is necessary. Today, methods based on whole-genome sequencing data are increasingly used to subtype bacterial pathogens; however, frequently a standardized methodology and typing nomenclature are missing. Here we report a core genome multilocus sequence typing (cgMLST) approach developed for C. difficile Initially, we determined the breadth of the C. difficile population based on all available MLST sequence types with Bayesian inference (BAPS). The resulting BAPS partitions were used in combination with C. difficile clade information to select representative isolates that were subsequently used to define cgMLST target genes. Finally, we evaluated the novel cgMLST scheme with genomes from 3,025 isolates. BAPS grouping (n = 6 groups) together with the clade information led to a total of 11 representative isolates that were included for cgMLST definition and resulted in 2,270 cgMLST genes that were present in all isolates. Overall, 2,184 to 2,268 cgMLST targets were detected in the genome sequences of 70 outbreak-associated and reference strains, and on average 99.3% cgMLST targets (1,116 to 2,270 targets) were present in 2,954 genomes downloaded from the NCBI database, underlining the representativeness of the cgMLST scheme. Moreover, reanalyzing different cluster scenarios with cgMLST were concordant to published single nucleotide variant analyses. In conclusion, the novel cgMLST is representative for the whole C. difficile population, is highly discriminatory in outbreak situations, and provides a unique nomenclature facilitating interlaboratory exchange.
Project description:We have employed whole genome sequencing to define and evaluate a core genome multilocus sequence typing (cgMLST) scheme for Acinetobacter baumannii. To define a core genome we downloaded a total of 1,573 putative A. baumannii genomes from NCBI as well as representative isolates belonging to the eight previously described international A. baumannii clonal lineages. The core genome was then employed against a total of fifty-three carbapenem-resistant A. baumannii isolates that were previously typed by PFGE and linked to hospital outbreaks in eight German cities. We defined a core genome of 2,390 genes of which an average 98.4% were called successfully from 1,339 A. baumannii genomes, while Acinetobacter nosocomialis, Acinetobacter pittii, and Acinetobacter calcoaceticus resulted in 71.2%, 33.3%, and 23.2% good targets, respectively. When tested against the previously identified outbreak strains, we found good correlation between PFGE and cgMLST clustering, with 0-8 allelic differences within a pulsotype, and 40-2,166 differences between pulsotypes. The highest number of allelic differences was between the isolates representing the international clones. This typing scheme was highly discriminatory and identified separate A. baumannii outbreaks. Moreover, because a standardised cgMLST nomenclature is used, the system will allow inter-laboratory exchange of data.
Project description: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.
Project description:Vibrio parahaemolyticus is an important human foodborne pathogen whose transmission is associated with the consumption of contaminated seafood, with a growing number of infections reported over recent years worldwide. A multilocus sequence typing (MLST) database for V. parahaemolyticus was created in 2008, and a large number of clones have been identified, causing severe outbreaks worldwide (sequence type 3 [ST3]), recurrent outbreaks in certain regions (e.g., ST36), or spreading to other regions where they are nonendemic (e.g., ST88 or ST189). The current MLST scheme uses sequences of 7 genes to generate an ST, which results in a powerful tool for inferring the population structure of this pathogen, although with limited resolution, especially compared to pulsed-field gel electrophoresis (PFGE). The application of whole-genome sequencing (WGS) has become routine for trace back investigations, with core genome MLST (cgMLST) analysis as one of the most straightforward ways to explore complex genomic data in an epidemiological context. Therefore, there is a need to generate a new, portable, standardized, and more advanced system that provides higher resolution and discriminatory power among V. parahaemolyticus strains using WGS data. We sequenced 92 V. parahaemolyticus genomes and used the genome of strain RIMD 2210633 as a reference (with a total of 4,832 genes) to determine which genes were suitable for establishing a V. parahaemolyticus cgMLST scheme. This analysis resulted in the identification of 2,254 suitable core genes for use in the cgMLST scheme. To evaluate the performance of this scheme, we performed a cgMLST analysis of 92 newly sequenced genomes, plus an additional 142 strains with genomes available at NCBI. cgMLST analysis was able to distinguish related and unrelated strains, including those with the same ST, clearly showing its enhanced resolution over conventional MLST analysis. It also distinguished outbreak-related from non-outbreak-related strains within the same ST. The sequences obtained from this work were deposited and are available in the public database (http://pubmlst.org/vparahaemolyticus). The application of this cgMLST scheme to the characterization of V. parahaemolyticus strains provided by different laboratories from around the world will reveal the global picture of the epidemiology, spread, and evolution of this pathogen and will become a powerful tool for outbreak investigations, allowing for the unambiguous comparison of strains with global coverage.
Project description:Among enterococci, Enterococcus faecalis occurs ubiquitously, with the highest incidence of human and animal infections. The high genetic plasticity of E. faecalis complicates both molecular investigations and phylogenetic analyses. Whole-genome sequencing (WGS) enables unraveling of epidemiological linkages and putative transmission events between humans, animals, and food. Core genome multilocus sequence typing (cgMLST) aims to combine the discriminatory power of classical multilocus sequence typing (MLST) with the extensive genetic data obtained by WGS. By sequencing a representative collection of 146 E. faecalis strains isolated from hospital outbreaks, food, animals, and colonization of healthy human individuals, we established a novel cgMLST scheme with 1,972 gene targets within the Ridom SeqSphere+ software. To test the E. faecalis cgMLST scheme and assess the typing performance, different collections comprising environmental and bacteremia isolates, as well as all publicly available genome sequences from the NCBI and SRA databases, were analyzed. In more than 98.6% of the tested genomes, >95% good cgMLST target genes were detected (mean, 99.2% target genes). Our genotyping results not only corroborate the known epidemiological background of the isolates but exceed previous typing resolution. In conclusion, we have created a powerful typing scheme, hence providing an international standardized nomenclature that is suitable for surveillance approaches in various sectors, linking public health, veterinary public health, and food safety in a true One Health fashion.
Project description:Many listeriosis outbreaks are caused by a few globally distributed clonal groups, designated clonal complexes or epidemic clones, of Listeria monocytogenes, several of which have been defined by classic multilocus sequence typing (MLST) schemes targeting 6 to 8 housekeeping or virulence genes. We have developed and evaluated core genome MLST (cgMLST) schemes and applied them to isolates from multiple clonal groups, including those associated with 39 listeriosis outbreaks. The cgMLST clusters were congruent with MLST-defined clonal groups, which had various degrees of diversity at the whole-genome level. Notably, cgMLST could distinguish among outbreak strains and epidemiologically unrelated strains of the same clonal group, which could not be achieved using classic MLST schemes. The precise selection of cgMLST gene targets may not be critical for the general identification of clonal groups and outbreak strains. cgMLST analyses further identified outbreak strains, including those associated with recent outbreaks linked to contaminated French-style cheese, Hispanic-style cheese, stone fruit, caramel apple, ice cream, and packaged leafy green salad, as belonging to major clonal groups. We further developed lineage-specific cgMLST schemes, which can include accessory genes when core genomes do not possess sufficient diversity, and this provided additional resolution over species-specific cgMLST. Analyses of isolates from different common-source listeriosis outbreaks revealed various degrees of diversity, indicating that the numbers of allelic differences should always be combined with cgMLST clustering and epidemiological evidence to define a listeriosis outbreak.Classic multilocus sequence typing (MLST) schemes targeting internal fragments of 6 to 8 genes that define clonal complexes or epidemic clones have been widely employed to study L. monocytogenes biodiversity and its relation to pathogenicity potential and epidemiology. We demonstrated that core genome MLST schemes can be used for the simultaneous identification of clonal groups and the differentiation of individual outbreak strains and epidemiologically unrelated strains of the same clonal group. We further developed lineage-specific cgMLST schemes that targeted more genomic regions than the species-specific cgMLST schemes. Our data revealed the genome-level diversity of clonal groups defined by classic MLST schemes. Our identification of U.S. and international outbreaks caused by major clonal groups can contribute to further understanding of the global epidemiology of L. monocytogenes.
Project description:Pseudomonas aeruginosa is a ubiquitous microorganism and an important opportunistic pathogen responsible for a broad spectrum of infections mainly in immunosuppressed and critically ill patients. Molecular investigations traditionally rely on pulsed field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). In this work we propose a core genome multilocus sequence typing (cgMLST) scheme for P. aeruginosa, a methodology that combines traditional MLST principles with whole genome sequencing data. All publicly available complete P. aeruginosa genomes, representing the diversity of this species, were used to establish a cgMLST scheme targeting 2,653 genes. The scheme was then tested using genomes available at contig, chromosome and scaffold levels. The proposed cgMLST scheme for P. aeruginosa typed over 99% (2,314/2,325) of the genomes available for this study considering at least 95% of the cgMLST target genes present. The absence of a certain number gene targets at the threshold considered for both the creation and validation steps due to low genome sequence quality is possibly the main reason for this result. The cgMLST scheme was compared with previously published whole genome single nucleotide polymorphism analysis for the characterization of the population structure of the epidemic clone ST235 and results were highly similar. In order to evaluate the typing resolution of the proposed scheme, collections of isolates belonging to two important STs associated with cystic fibrosis, ST146 and ST274, were typed using this scheme, and ST235 isolates associated with an outbreak were evaluated. Besides confirming the relatedness of all the isolates, earlier determined by MLST, the higher resolution of cgMLST denotes that it may be suitable for surveillance programs, overcoming possible shortcomings of classical MLST. The proposed scheme is publicly available at: https://github.com/BioinformaticsHIAEMolecularMicrobiology/cgMLST-Pseudomonas-aeruginosa.
Project description:Enterococcus faecium, a common inhabitant of the human gut, has emerged in the last 2 decades as an important multidrug-resistant nosocomial pathogen. Since the start of the 21st century, multilocus sequence typing (MLST) has been used to study the molecular epidemiology of E. faecium. However, due to the use of a small number of genes, the resolution of MLST is limited. Whole-genome sequencing (WGS) now allows for high-resolution tracing of outbreaks, but current WGS-based approaches lack standardization, rendering them less suitable for interlaboratory prospective surveillance. To overcome this limitation, we developed a core genome MLST (cgMLST) scheme for E. faecium. cgMLST transfers genome-wide single nucleotide polymorphism(SNP) diversity into a standardized and portable allele numbering system that is far less computationally intensive than SNP-based analysis of WGS data. The E. faecium cgMLST scheme was built using 40 genome sequences that represented the diversity of the species. The scheme consists of 1,423 cgMLST target genes. To test the performance of the scheme, we performed WGS analysis of 103 outbreak isolates from five different hospitals in the Netherlands, Denmark, and Germany. The cgMLST scheme performed well in distinguishing between epidemiologically related and unrelated isolates, even between those that had the same sequence type (ST), which denotes the higher discriminatory power of this cgMLST scheme over that of conventional MLST. We also show that in terms of resolution, the performance of the E. faecium cgMLST scheme is equivalent to that of an SNP-based approach. In conclusion, the cgMLST scheme developed in this study facilitates rapid, standardized, and high-resolution tracing of E. faecium outbreaks.
Project description:Pathogen whole-genome sequencing has huge potential as a tool to better understand infection transmission. However, rapidly identifying closely related genomes among a background of thousands of other genomes is challenging. Here, we describe a refinement to core genome multilocus sequence typing (cgMLST) in which alleles at each gene are reproducibly converted to a unique hash, or short string of letters (hash-cgMLST). This avoids the resource-intensive need for a single centralized database of sequentially numbered alleles. We test the reproducibility and discriminatory power of cgMLST/hash-cgMLST compared to those of mapping-based approaches in Clostridium difficile, using repeated sequencing of the same isolates (replicates) and data from consecutive infection isolates from six English hospitals. Hash-cgMLST provided the same results as standard cgMLST, with minimal performance penalty. Comparing 272 replicate sequence pairs using reference-based mapping, there were 0, 1, or 2 single-nucleotide polymorphisms (SNPs) between 262 (96%), 5 (2%), and 1 (<1%) of the pairs, respectively. Using hash-cgMLST, 218 (80%) of replicate pairs assembled with SPAdes had zero gene differences, and 31 (11%), 5 (2%), and 18 (7%) pairs had 1, 2, and >2 differences, respectively. False gene differences were clustered in specific genes and associated with fragmented assemblies, but were reduced using the SKESA assembler. Considering 412 pairs of infections with ?2 SNPS, i.e., consistent with recent transmission, 376 (91%) had ?2 gene differences and 16 (4%) had ?4. Comparing a genome to 100,000 others took <1 min using hash-cgMLST. Hash-cgMLST is an effective surveillance tool for rapidly identifying clusters of related genomes. However, cgMLST/hash-cgMLST generate more false variants than mapping-based approaches. Follow-up mapping-based analyses are likely required to precisely define close genetic relationships.
Project description:Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions.