28 research outputs found

    Virulence, Antimicrobial Resistance Properties and Phylogenetic Background of Non-H7 Enteropathogenic Escherichia coli O157

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    Escherichia coli (E.coli) O157 that do not produce Shiga toxin and do not possess flagellar antigen H7 are of diverse H serotypes. In this study, the antibiotic resistance properties, genotype of a set of virulence associated genes and the phylogenetic background of E. coli O157:non-H7 groups were compared. Whole genome sequencing was performed on fourteen O157:non-H7 isolates collected in the STEC-ID-net study. The genomes were compared with E. coli O157 genomes and a typical Enteropathogenic E. coli (tEPEC) genome downloaded from NCBI. Twenty-six (86%) of the analyzed genomes had the intimin encoding gene eae but of different types mostly correlating with their H types, e.g., H16, H26, H39, and H45 carried intimin type epsilon, beta, kappa, and alpha, respectively. They belonged to several E. coli phylogenetic groups, i.e., to phylogenetic group A, B1, B2, and D. Seven (50%) of our collected O157:non-H7 isolates were resistant to two or more antibiotics. Several mobile genetic elements, such as plasmids, insertion elements, and pathogenicity islands, carrying a set of virulence and resistance genes were found in the E. coli O157:non-H7 isolates. Core genome phylogenetic analysis showed that O157:non-H7 isolates probably evolved from different phylogenetic lineages and were distantly related to the E. coli O157:H7 lineage. We hypothesize that independent acquisition of mobile genetic elements by isolates of different lineages have contributed to the different molecular features of the O157:non-H7 strains. Although distantly related to the STEC O157, E. coli O157:non-H7 isolates from multiple genetic background could be considered as pathogen of concern for their diverse virulence and antibiotic resistance properties

    A Comparison of Three Different Bioinformatics Analyses of the 16S–23S rRNA Encoding Region for Bacterial Identification

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    Rapid and reliable identification of bacterial pathogens directly from patient samples is required for optimizing antimicrobial therapy. Although Sanger sequencing of the 16S ribosomal RNA (rRNA) gene is used as a molecular method, species identification and discrimination is not always achievable for bacteria as their 16S rRNA genes have sometimes high sequence homology. Recently, next generation sequencing (NGS) of the 16S–23S rRNA encoding region has been proposed for reliable identification of pathogens directly from patient samples. However, data analysis is laborious and time-consuming and a database for the complete 16S–23S rRNA encoding region is not available. Therefore, a better, faster, and stronger approach is needed for NGS data analysis of the 16S–23S rRNA encoding region. We compared speed and diagnostic accuracy of different data analysis approaches: de novo assembly followed by Basic Local Alignment Search Tool (BLAST), operational taxonomic unit (OTU) clustering, or mapping using an in-house developed 16S–23S rRNA encoding region database for the identification of bacterial species. De novo assembly followed by BLAST using the in-house database was superior to the other methods, resulting in the shortest turnaround time (2 h and 5 min), approximately 2 h less than OTU clustering and 4.5 h less than mapping, and a sensitivity of 80%. Mapping was the slowest and most laborious data analysis approach with a sensitivity of 60%, whereas OTU clustering was the least laborious approach with 70% sensitivity. Although the in-house database requires more sequence entries to improve the sensitivity, the combination of de novo assembly and BLAST currently appears to be the optimal approach for data analysis

    MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli

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    Shigella spp. and E. coli are closely related and cannot be distinguished using matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp., E. coli, and its pathotype EIEC were explored and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp./E. coli complex, but other tests should be used for distinction

    Development and validation of a reference data set for assigning Staphylococcus species based on next-generation sequencing of the 16S-23S rRNA region

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    Many members of the Staphylococcus genus are clinically relevant opportunistic pathogens that warrant accurate and rapid identification for targeted therapy. The aim of this study was to develop a careful assignment scheme for staphylococcal species based on next-generation sequencing (NGS) of the 16S-23S rRNA region. All reference staphylococcal strains were identified at the species level using Sanger sequencing of the 16S rRNA, sodA, tuf, and rpoB genes and NGS of the 16S-23S rRNA region. To broaden the database, an additional 100 staphylococcal strains, including 29 species, were identified by routine diagnostic methods, 16S rRNA Sanger sequencing and NGS of the 16S-23S rRNA region. The results enabled development of reference sequences encompassing the 16S-23S rRNA region for 50 species (including one newly proposed species) and 6 subspecies of the Staphylococcus genus. This study showed sodA and rpoB targets were the most discriminative but NGS of the 16S-23S rRNA region was more discriminative than tuf gene sequencing and much more discriminative than 16S rRNA gene sequencing. Almost all Staphylococcus species could be distinguished when the max score was 99.0% or higher and the sequence similarity between the best and second best species was equal to or >0.2% (min. 9 nucleotides). This study allowed development of reference sequences for 21 staphylococcal species and enrichment for 29 species for which sequences were publicly available. We confirmed the usefulness of NGS of the 16S-23S rRNA region by identifying the whole species content in 45 clinical samples and comparing the results to those obtained using routine diagnostic methods. Based on the developed reference database, all staphylococcal species can be reliably detected based on the 16S-23S rRNA sequences in samples composed of both single species and more complex polymicrobial communities. This study will be useful for introduction of a novel diagnostic tool, which undoubtedly is an improvement for reliable species identification in polymicrobial samples. The introduction of this new method is hindered by a lack of reference sequences for the 16S-23S rRNA region for many bacterial species. The results will allow identification of all Staphylococcus species, which are clinically relevant pathogens

    High Detection Rates of Enteropathogens in Asymptomatic Children Attending Day Care

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    BACKGROUND: Gastroenteritis morbidity is high among children under the age of four, especially amongst those who attend day care. OBJECTIVE: To determine the prevalence of a range of enteropathogens in the intestinal flora of children attending day care and to relate their occurrence with characteristics of the sampled child and the sampling season. METHODS: We performed three years of enteropathogen surveillance in a network of 29 child day care centers in the Netherlands. The centers were instructed to take one fecal sample from ten randomly chosen children each month, regardless of gastrointestinal symptoms at time of sampling. All samples were analyzed for the molecular detection of 16 enteropathogenic bacteria, parasites and viruses by real-time multiplex PCR. RESULTS: Enteropathogens were detected in 78.0% of the 5197 fecal samples. Of the total, 95.4% of samples were obtained from children who had no gastroenteritis symptoms at time of sampling. Bacterial enteropathogens were detected most often (most prevalent EPEC, 19.9%), followed by parasitic enteropathogens (most prevalent: D. fragilis, 22.1%) and viral enteropathogens (most prevalent: norovirus, 9.5%). 4.6% of samples related to children that experienced symptoms of gastroenteritis at time of sampling. Only rotavirus and norovirus were significantly associated with gastroenteritis among day care attendees. CONCLUSIONS: Our study indicates that asymptomatic infections with enteropathogens in day care attendees are not a rare event and that gastroenteritis caused by infections with these enteropathogens is only one expression of their presence

    Development of a reference data set for assigning Streptococcus and Enterococcus species based on next generation sequencing of the 16S-23S rRNA region

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    Background: Many members of Streptococcus and Enterococcus genera are clinically relevant opportunistic pathogens warranting accurate and rapid identification for targeted therapy. Currently, the developed method based on next generation sequencing (NGS) of the 16S-23S rRNA region proved to be a rapid, reliable and precise approach for species identification directly from polymicrobial and challenging clinical samples. The introduction of this new method to routine diagnostics is hindered by a lack of the reference sequences for the 16S-23S rRNA region for many bacterial species. The aim of this study was to develop a careful assignment for streptococcal and enterococcal species based on NGS of the 16S-23S rRNA region. Methods: Thirty two strains recovered from clinical samples and 19 reference strains representing 42 streptococcal species and nine enterococcal species were subjected to bacterial identification by four Sanger-based sequencing methods targeting the genes encoding (i) 16S rRNA, (ii) sodA, (iii) tuf and (iv) rpoB; and NGS of the 16S-23S rRNA region. Results: This study allowed obtainment and deposition of reference sequences of the 16S-23S rRNA region for 15 streptococcal and 3 enterococcal species followed by enrichment for 27 and 6 species, respectively, for which reference sequences were available in the databases. For Streptococcus, NGS of the 16S-23S rRNA region was as discriminative as Sanger sequencing of the tuf and rpoB genes allowing for an unambiguous identification of 93% of analyzed species. For Enterococcus, sodA, tuf and rpoB genes sequencing allowed for identification of all species, while the NGS-based method did not allow for identification of only one enterococcal species. For both genera, the sequence analysis of the 16S rRNA gene was endowed with a low identification potential and was inferior to that of other tested identification methods. Moreover, in case of phylogenetically related species the sequence analysis of only the intergenic spacer region was not sufficient enough to precisely identify Streptococcus strains at the species level. Conclusions: Based on the developed reference dataset, clinically relevant streptococcal and enterococcal species can now be reliably identified by 16S-23S rRNA sequences in samples. This study will be useful for introduction of a novel diagnostic tool, NGS of the 16S-23S rRNA region, which undoubtedly is an improvement for reliable culture-independent species identification directly from polymicrobially constituted clinical samples

    Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

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    BACKGROUND: We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control. RESULTS: The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and > 3,000,000 k-mers, indicating adequate performance of the algorithms used. CONCLUSIONS: To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC

    Targeted next-generation sequencing of the 16S-23S rRNA region for culture-independent bacterial identification - increased discrimination of closely related species

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    The aim of this study was to develop an easy-to-use culture-free diagnostic method based on next generation sequencing (NGS) of PCR amplification products encompassing whole 16S-23S rRNA region to improve the resolution of bacterial species identification. To determine the resolution of the new method 67 isolates were subjected to four identification methods: Sanger sequencing of the 16S rRNA gene; NGS of the 16S-23S rRNA region using MiSeq (Illumina) sequencer; Microflex MS (Bruker) and VITEK MS (bioMerieux). To evaluate the performance of this new method when applied directly on clinical samples, we conducted a proof of principle study with 60 urine samples from patients suspected of urinary tract infections (UTIs), 23 BacT/ALERT (bioMerieux) positive blood culture bottles and 21 clinical orthopedic samples. The resolution power of NGS of the 16S-23S rRNA region was superior to other tested identification methods. Furthermore, the new method correctly identified pathogens established as the cause of UTIs and blood stream infections with conventional culture. NGS of the 16S-23S rRNA region also showed increased detection of bacterial microorganisms in clinical samples from orthopedic patients. Therefore, we conclude that our method has the potential to increase diagnostic yield for detection of bacterial pathogenic species compared to current methods

    A Multifactorial Approach for Surveillance of Shigella spp. and Entero-Invasive Escherichia coli Is Important for Detecting (Inter)national Clusters

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    Shigella spp. and entero-invasive Escherichia coli (EIEC) can cause mild diarrhea to dysentery. In Netherlands, although shigellosis is a notifiable disease, there is no laboratory surveillance for Shigella spp. and EIEC in place. Consequently, the population structure for circulating Shigella spp. and EIEC isolates is not known. This study describes the phenotypic and serological characteristics, the phenotypic and genetic antimicrobial resistance (AMR) profiles, the virulence gene profiles, the classic multi-locus sequence types (MLST) and core genome (cg)MLST types, and the epidemiology of 414 Shigella spp. and EIEC isolates collected during a cross-sectional study in Netherlands in 2016 and 2017. S. sonnei (56%), S. flexneri (25%), and EIEC (15%) were detected predominantly in Netherlands, of which the EIEC isolates were most diverse according to their phenotypical profile, O-types, MLST types, and cgMLST clades. Virulence gene profiling showed that none of the isolates harbored Shiga toxin genes. Most S. flexneri and EIEC isolates possessed nearly all virulence genes examined, while these genes were only detected in approximately half of the S. sonnei isolates, probably due to loss of the large invasion plasmid upon subculturing. Phenotypical resistance correlated well with the resistant genotype, except for the genes involved in resistance to aminoglycosides. A substantial part of the characterized isolates was resistant to antimicrobials advised for treatment, i.e., 73% was phenotypically resistant to co-trimoxazole and 19% to ciprofloxacin. AMR was particularly observed in isolates from male patients who had sex with men (MSM) or from patients that had traveled to Asia. Furthermore, isolates related to international clusters were also circulating in Netherlands. Travel-related isolates formed clusters with isolates from patients without travel history, indicating their emergence into the Dutch population. In conclusion, laboratory surveillance using whole genome sequencing as high-resolution typing technique and for genetic characterization of isolates complements the current epidemiological surveillance, as the latter is not sufficient to detect all (inter)national clusters, emphasizing the importance of multifactorial public health approaches

    The role of nasal carriage in Staphylococcus aureus burn wound colonization

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    Thermal injury destroys the physical skin barrier that normally prevents invasion of microorganisms. This and concomitant depression of local and systemic host cellular and humoral immune responses are important factors that contribute to colonization and infection of the burn wound. One of the most common burn wound pathogens is Staphylococcus aureus. Staphylococcus aureus is both a human commensal and a frequent cause of infections leading to mild to life-threatening diseases. Despite a variety of infection control measures, for example patient cohorting and contact precaution at burn centres, S. aureus is still frequently encountered in burn wounds. Colonization with S. aureus has been associated with delayed wound healing, increased need for surgical interventions, and prolonged length of stay at burn centres. In this minireview, we focus on S. aureus nasal carriage in relation to S. aureus burn wound colonization and subsequent infection, and its impact on strategies for infection control. © 2009 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd
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