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.

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.

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The increasing prevalence of multidrug-resistant (MDR) bacteria is a serious global challenge. Here, we studied prospectively whether bacterial whole-genome sequencing (WGS) for real-time MDR surveillance is technical feasible, returns actionable results, and is cost-beneficial. WGS was applied to all MDR isolates of four species (methicillin-resistant Staphylococcus aureus [MRSA], vancomycin-resistant Enterococcus faecium, MDR Escherichia coli, and MDR Pseudomonas aeruginosa) at the University Hospital Muenster, Muenster, Germany, a tertiary care hospital with 1,450 beds, during two 6-month intervals. Turnaround times (TAT) were measured, and total costs for sequencing per isolate were calculated. After cancelling prior policies of preemptive isolation of patients harboring certain Gram-negative MDR bacteria in risk areas, the second interval was conducted. During interval I, 645 bacterial isolates were sequenced. From culture, TATs ranged from 4.4 to 5.3 days, and costs were €202.49 per isolate. During interval II, 550 bacterial isolates were sequenced. Hospital-wide transmission rates of the two most common species (MRSA and MDR E. coli) were low during interval I (5.8% and 2.3%, respectively) and interval II (4.3% and 5.0%, respectively). Cancellation of isolation of patients infected with non-pan-resistant MDR E. coli in risk wards did not increase transmission. Comparing sequencing costs with avoided costs mostly due to fewer blocked beds during interval II, we saved in excess of €200,000. Real-time microbial WGS in our institution was feasible, produced precise actionable results, helped us to monitor transmission rates that remained low following a modification in isolation procedures, and ultimately saved costs.

Periodontitis, one of the most common diseases in the world, is caused by a mixture of pathogenic bacteria and inflammatory host responses and often treated by antimicrobials as an adjunct to scaling and root planing (SRP). Our study aims to elucidate explorative and descriptive temporal shifts in bacterial communities between patients treated by SRP alone versus SRP plus antibiotics. This is the first metagenomic study using an Ion Torrent Personal Genome Machine (PGM). Eight subgingival plaque samples from four patients with chronic periodontitis, taken before and two months after intervention were analyzed. Amplicons from the V6 hypervariable region of the 16S rRNA gene were generated and sequenced each on a 314 chip. Sequencing reads were clustered into operational taxonomic units (OTUs, 3% distance), described by community metrics, and taxonomically classified. Reads ranging from 599,933 to 650,416 per sample were clustered into 1,648 to 2,659 non-singleton OTUs, respectively. Increased diversity (Shannon and Simpson) in all samples after therapy was observed regardless of the treatment type whereas richness (ACE) showed no correlation. Taxonomic analysis revealed different microbial shifts between both therapy approaches at all taxonomic levels. Most remarkably, the genera Porphyromonas, Tannerella, Treponema, and Filifactor all harboring periodontal pathogenic species were removed almost only in the group treated with SPR and antibiotics. For the species T. forsythia and P. gingivalis results were corroborated by real-time PCR analysis. In the future, hypothesis free metagenomic analysis could be the key in understanding polymicrobial diseases and be used for therapy monitoring. Therefore, as read length continues to increase and cost to decrease, rapid benchtop sequencers like the PGM might finally be used in routine diagnostic.

Empiric antibiotics are often used in combination with mechanical debridement to treat patients suffering from periodontitis and to eliminate disease-associated pathogens. Until now, only a few next generation sequencing 16S rDNA amplicon based publications with rather small sample sizes studied the effect of those interventions on the subgingival microbiome. Therefore, we studied subgingival samples of 89 patients with chronic periodontitis (solely non-smokers) before and two months after therapy. Forty-seven patients received mechanical periodontal therapy only, whereas 42 patients additionally received oral administered amoxicillin plus metronidazole (500 and 400 mg, respectively; 3x/day for 7 days). Samples were sequenced with Illumina MiSeq 300 base pairs paired end technology (V3 and V4 hypervariable regions of the 16S rDNA). Inter-group differences before and after therapy of clinical variables (percentage of sites with pocket depth ≥ 5mm, percentage of sites with bleeding on probing) and microbiome variables (diversity, richness, evenness, and dissimilarity) were calculated, a principal coordinate analysis (PCoA) was conducted, and differential abundance of agglomerated ribosomal sequence variants (aRSVs) classified on genus level was calculated using a negative binomial regression model. We found statistically noticeable decreased richness, and increased dissimilarity in the antibiotic, but not in the placebo group after therapy. The PCoA revealed a clear compositional separation of microbiomes after therapy in the antibiotic group, which could not be seen in the group receiving mechanical therapy only. This difference was even more pronounced on aRSV level. Here, adjunctive antibiotics were able to induce a microbiome shift by statistically noticeably reducing aRSVs belonging to genera containing disease-associated species, e.g., Porphyromonas, Tannerella, Treponema, and Aggregatibacter, and by noticeably increasing genera containing health-associated species. Mechanical therapy alone did not statistically noticeably affect any disease-associated taxa. Despite the difference in microbiome modulation both therapies improved the tested clinical parameters after two months. These results cast doubt on the relevance of the elimination and/or reduction of disease-associated taxa as a main goal of periodontal therapy.

The aim of the present study was to determine the prevalence of Porphyromonas gingivalis fimA genotypes in Caucasian patients with periodontitis. A total of 102 patients harboring P. gingivalis subgingivally were enrolled into the study. Pooled subgingival plaque samples of the six most severely affected sites were taken and analysed by fimA-specific polymerase chain reaction (PCR) and restriction analysis. Moreover, 26 P. gingivalis isolates were analysed by sequence analysis of the fimA gene. Sequence analysis revealed five major fimA genotypes (fimA types I-V) and allowed further subtyping of fimA genotypes II and IV into two subgroups each. The overall prevalences of fimA genotypes as assessed by PCR and restriction analysis among the P. gingivalis-positive patients with periodontitis were: type I, 25.5%; type II, 38.2%; type III, 4.9%; type IV, 18.6%; type V, 3.9%; and non-typable, 6.9%. Two patients were colonized by both type II and type IV, or type III and type IV fimA genotypes, respectively. Patients harboring different fimA genotypes showed no significant difference in severity of periodontal disease, as assessed by pocket probing depth and bleeding on probing following adjustment for smoking habit and age. The results indicate that predominant fimA genotypes in Caucasian periodontitis patients are types I, II, and IV. However, there was no difference in the association of the various fimA genotypes with disease severity.

Sequence-based typing (SBT) for Legionella pneumophila (Lp) has dramatically improved Legionnaires' disease (LD) cluster investigation. Microbial whole genome sequencing (WGS) is a promising modality for investigation but sequence analysis methods are neither standardised, nor agreed. We sought to develop a WGS-based typing scheme for Lp using de novo assembly and a genome-wide gene-by-gene approach (core genome multilocus sequence typing, cgMLST). We analysed 17 publicly available Lp genomes covering the whole species variation to define a core genome (1,521 gene targets) which was validated using 21 additional published genomes. The genomes of 12 Lp strains implicated in three independent cases of paediatric humidifier-associated LD were subject to cgMLST together with three 'outgroup' strains. cgMLST was able to resolve clustered strains and clearly identify related and unrelated strains. Thus, a cgMLST scheme was readily achievable and provided highresolution analysis of Lp strains. cgMLST appears to have satisfactory discriminatory power for LD cluster analysis and is advantageous over mapping followed by single nucleotide polymorphism (SNP) calling as it is portable and easier to standardise. cgMLST thus has the potential for becoming a gold standard tool for LD investigation. Humidifiers pose an ongoing risk as vehicles for LD and should be considered in cluster investigation and control efforts.