Tracking Down the Cause of Necrotizing Fasciitis in a Patient with Negative Cultures

In a patient suspected of lower abdominal necrotizing fasciitis cultures remained negative, possibly because broad spectrum antibiotics had already been given before tissue for culture was obtained. 16S-23S rDNANext Generation Sequencing showed that 99.7% of bacterial DNA was of Streptococcus pyogenes. 16S-23S rDNA can replace culture for identification of bacteria, also in polymicrobial infection

Molecular characterization and phylogeny of Shiga toxin–producing Escherichia coli isolates obtained from two Dutch regions using whole genome sequencing

AbstractShiga toxin–producing Escherichia coli (STEC) is one of the major causes of human gastrointestinal disease and has been implicated in sporadic cases and outbreaks of diarrhoea, haemorrhagic colitis and haemolytic uremic syndrome worldwide. In this study, we determined the molecular characteristics and phylogenetic relationship of STEC isolates, and their genetic diversity was compared to that of other E. coli populations. Whole genome sequencing was performed on 132 clinical STEC isolates obtained from the faeces of 129 Dutch patients with gastrointestinal complaints. STEC isolates of this study belonged to 44 different sequence types (STs), 42 serogenotypes and 14 stx subtype combinations. Antibiotic resistance genes were more frequently present in stx1-positive isolates compared to stx2 and stx1 + stx2–positive isolates. The iha, mchB, mchC, mchF, subA, ireA, senB, saa and sigA genes were significantly more frequently present in eae-negative than in eae-positive STEC isolates. Presence of virulence genes encoding type III secretion proteins and adhesins was associated with isolates obtained from patients with bloody diarrhoea. Core genome phylogenetic analysis showed that isolates clustered according to their ST or serogenotypes irrespective of stx subtypes. Isolates obtained from patients with bloody diarrhoea were from diverse phylogenetic backgrounds. Some STEC isolates shared common ancestors with non-STEC isolates. Whole genome sequencing is a powerful tool for clinical microbiology, allowing high-resolution molecular typing, population structure analysis and detailed molecular characterization of strains. STEC isolates of a substantial genetic diversity and of distinct phylogenetic groups were observed in this study

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

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

Inguinal microbiome in patients undergoing an endovascular aneurysm repair:Application of next-generation sequencing of the 16S-23S rRNA regions

Background: Surgical site infection (SSI) remains a hazardous complication after vascular surgery. In this pilot study we investigated the inguinal microbiome in skin biopsies using histology and 16S-23S rDNA Next Generation Sequencing (NGS). Our hypothesis was that causative microorganisms of SSI are present in the inguinal microbiome. Methods: Data on surgical site infections and skin samples from the Percutaneous in Endovascular Repair versus Open (PiERO) trail were evaluated. Two patients with SSI were matched for age and comorbidity to eight matching patients of the PiERO trial. All patients were treated for an abdominal aortic aneurysm with endovascular repair. Nasal and perineal cultures were taken preoperatively to detect Staphylococcus aureus carriage. After disinfection with chlorhexidine, groin biopsies were taken to identify bacteria in deeper skin layers. All samples were subjected to histological analysis and culture-free 16S-23S rDNA NGS. Results: Staphylococcus aureus species were cultured in 5 out of 20 preoperative nasal and perineal swaps. Histology detected only a few bacteria, NGS of the 16S-23S rRNA regions identified DNA of bacterial species in all biopsies (20/20). Most identified genera and species proved to be known skin flora bacteria. No relation was found between SSIs and the preoperative microbiome. Conclusion: In this pilot study, an innovative analysis of the preoperative microbiome using 16S-23S rDNA NGS did not show a relation with the occurrence of a surgical site infection. No pathogenic bacterial species were present in the inguinal skin after disinfection with chiorhexidine

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

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

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

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