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.Staphylococcus aureus is a major human pathogen causing skin and tissue infections, pneumonia, septicemia, and deviceassociated infections. The emergence of strains resistant to methicillin and other antibacterial agents has become a major concern especially in the hospital environment, because of the higher mortality due to systemic methicillin-resistant Staphylococcus aureus (MRSA) infections (2). Typing of MRSA is used to support infection control measures. While pulsed-field gel electrophoresis (PFGE) is a "gold standard" for strain typing of MRSA (20), DNA sequence-based approaches are becoming more frequently used because sequence data can easily be transferred between laboratories via the Internet. Multilocus sequence typing (MLST), which was developed by using Neisseria meningitidis as the model species (9, 18), has been successfully adapted to S. aureus (7,8). However, MLST is not suitable for routine surveillance of MRSA because of the high cost and the necessity of access to a high-throughput DNA sequencing facility.Although there is evidence for recombination in S. aureus (10), it has been shown that point mutations by far exceed recombination events, in contrast to N. meningitidis or Streptococcus pneumoniae (11). Furthermore, there is only a small number of clonal groupings of MRSA circulating worldwide (7). Therefore, single-locus DNA sequencing of repeat regions of the coa (coagulase) gene and the spa gene (protein A), respectively, could be used for reliable and accurate typing of MRSA (12,13,(26)(27)(28)(29). spa typing is especially interesting for rapid typing of MRSA in a hospital setting since it offers higher resolution than coa typing (27). The repeat region of the spa gene is subject to spontaneous mutations, as well as loss and gain of repeats. ...
An ongoing outbreak of exceptionally virulent Shiga toxin (Stx)-producing Escherichia coli O104:H4 centered in Germany, has caused over 830 cases of hemolytic uremic syndrome (HUS) and 46 deaths since May 2011. Serotype O104:H4, which has not been detected in animals, has rarely been associated with HUS in the past. To prospectively elucidate the unique characteristics of this strain in the early stages of this outbreak, we applied whole genome sequencing on the Life Technologies Ion Torrent PGM™ sequencer and Optical Mapping to characterize one outbreak isolate (LB226692) and a historic O104:H4 HUS isolate from 2001 (01-09591). Reference guided draft assemblies of both strains were completed with the newly introduced PGM™ within 62 hours. The HUS-associated strains both carried genes typically found in two types of pathogenic E. coli, enteroaggregative E. coli (EAEC) and enterohemorrhagic E. coli (EHEC). Phylogenetic analyses of 1,144 core E. coli genes indicate that the HUS-causing O104:H4 strains and the previously published sequence of the EAEC strain 55989 show a close relationship but are only distantly related to common EHEC serotypes. Though closely related, the outbreak strain differs from the 2001 strain in plasmid content and fimbrial genes. We propose a model in which EAEC 55989 and EHEC O104:H4 strains evolved from a common EHEC O104:H4 progenitor, and suggest that by stepwise gain and loss of chromosomal and plasmid-encoded virulence factors, a highly pathogenic hybrid of EAEC and EHEC emerged as the current outbreak clone. In conclusion, rapid next-generation technologies facilitated prospective whole genome characterization in the early stages of an outbreak.
Hajo Grundmann and colleagues describe the development of a new interactive mapping tool for analyzing the spatial distribution of invasive Staphylococcus aureus clones.
Because of its portable data, discriminatory power, and recently proposed standardization, mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing has become a major method for the epidemiological tracking of Mycobacterium tuberculosis complex (MTBC) clones. However, no public MIRU-VNTR database based on well-characterized reference strains has been available hitherto for easy strain identification. Therefore, a collection of 186 reference strains representing the primary MTBC lineages was used to build a database, which is freely accessible at http://www.MIRU-VNTRplus.org. The geographical origin and the drug susceptibility profile of each strain were stored together with comprehensive genetic lineage information, including the 24-locus MIRU-VNTR profile, the spoligotyping pattern, the singlenucleotide-and large-sequence-polymorphism profiles, and the IS6110 restriction fragment length polymorphism fingerprint. Thanks to flexible import functions, a single or multiple user strains can be analyzed, e.g., for lineage identification with or without the use of reference strains, by best-match or tree-based analyses with single or combined marker data sets. The results can easily be exported. In the present study, we evaluated the database consistency and various analysis parameters both by testing the reference collection against itself and by using an external population-based data set comprising 629 different strains. Under the optimal conditions found, lineage predictions based on typing by 24-locus MIRU-VNTR analysis optionally combined with spoligotyping were verified in >99% of the cases. On the basis of this evaluation, a user strategy was defined, which consisted of best-match analysis followed, if necessary, by tree-based analysis. The MIRU-VNTRplus database is a powerful tool for high-resolution clonal identification and has little equivalent in terms of functionalities among the bacterial genotyping databases available so far.Mycobacterium tuberculosis is among the most successful human pathogens worldwide and is responsible for extensive morbidity and mortality, with approximately 2 million deaths each year (51). The importance of tuberculosis (TB) as a major public health problem has been dramatically reinforced due to the human immunodeficiency virus coepidemic and the emergence of (multi)drug-resistant M. tuberculosis strains.Methods for genotyping of clinical M. tuberculosis complex (MTBC) strains have proven to be valuable tools for TB control. At the individual clinical management level, the application of genotyping enables the detection (1) or exclusion (25) of laboratory errors and the follow-up of relapse cases to identify treatment failures, reactivations of latent disease, and exogenous reinfections (46). At the public health level, genotyping enables the detection of unsuspected outbreaks and the identification of transmission chains and secondary cases of infection (4, 46).
Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterize Listeria monocytogenes outbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a new L. monocytogenes typing scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of the L. monocytogenes population based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67 L. monocytogenes isolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated five L. monocytogenes groups. Using all available NCBI RefSeq genomes (n = 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.
Nonfermenting bacteria are ubiquitous environmental opportunists that cause infections in humans, especially compromised patients. Due to their limited biochemical reactivity and different morphotypes, misidentification by classical phenotypic means occurs frequently. Therefore, we evaluated the use of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for species identification. By using 248 nonfermenting culture collection strains composed of 37 genera most relevant to human infections, a reference database was established for MALDI-TOF MS-based species identification according to the manufacturer's recommendations for microflex measurement and MALDI BioTyper software (Bruker Daltonik GmbH, Leipzig, Germany), i.e., by using a mass range of 2,000 to 20,000 Da and a new pattern-matching algorithm. To evaluate the database, 80 blind-coded clinical nonfermenting bacterial strains were analyzed. As a reference method for species designation, partial 16S rRNA gene sequencing was applied. By 16S rRNA gene sequencing, 57 of the 80 isolates produced a unique species identification (>99% sequence similarity); 11 further isolates gave ambiguous results at this threshold and were rated as identified to the genus level only. Ten isolates were identified to the genus level (>97% similarity); and two isolates had similarity values below this threshold, were counted as not identified, and were excluded from further analysis. MALDI-TOF MS identified 67 of the 78 isolates (85.9%) included, in agreement with the results of the reference method; 9 were misidentified and 2 were unidentified. The identities of 10 randomly selected strains were 100% correct when three different mass spectrometers and four different cultivation media were used. Thus, MALDI-TOF MS-based species identification of nonfermenting bacteria provided accurate and reproducible results within 10 min without any substantial costs for consumables.
Multilocus sequence typing of 169 non-O157 enterohemorrhagic Escherichia coli (EHEC) isolated from patients with hemolytic uremic syndrome (HUS) demonstrated 29 different sequence types (STs); 78.1% of these strains clustered in 5 STs. From all STs and serotypes identified, we established a reference panel of EHEC associated with HUS (HUSEC collection).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.