Limited genetic diversity in Salmonella enterica Serovar Enteritidis PT13

<p>Abstract</p> <p>Background</p> <p><it>Salmonella enterica </it>serovar Enteritidis has emerged as a significant foodborne pathogen throughout the world and is commonly characterized by phage typing. In Canada phage types (PT) 4, 8 and 13 predominate and in 2005 a large foodborne PT13 outbreak occurred in the province of Ontario. The ability to link strains during this outbreak was difficult due to the apparent clonality of PT13 isolates in Canada, as there was a single dominant pulsed-field gel electrophoresis (PFGE) profile amongst epidemiologically linked human and food isolates as well as concurrent sporadic strains. The aim of this study was to perform comparative genomic hybridization (CGH), DNA sequence-based typing (SBT) genomic analyses, plasmid analyses, and automated repetitive sequence-based PCR (rep-PCR) to identify epidemiologically significant traits capable of subtyping <it>S</it>. Enteritidis PT13.</p> <p>Results</p> <p>CGH using an oligonucleotide array based upon chromosomal coding sequences of <it>S. enterica </it>serovar Typhimurium strain LT2 and the <it>Salmonella </it>genomic island 1 successfully determined major genetic differences between <it>S</it>. Typhimurium and <it>S</it>. Enteritidis PT13, but no significant strain-to-strain differences were observed between <it>S</it>. Enteritidis PT13 isolates. Individual loci (<it>safA </it>and <it>fliC</it>) that were identified as potentially divergent in the CGH data set were sequenced in a panel of <it>S</it>. Enteritidis strains, and no differences were detected between the PT13 strains. Additional sequence-based typing was performed at the <it>fimA</it>, <it>mdh</it>, <it>manB</it>, <it>cyaA</it>, <it>citT</it>, <it>caiC</it>, <it>dmsA</it>, <it>ratA </it>and STM0660 loci. Similarly, no diversity was observed amongst PT13 strains. Variation in plasmid content between PT13 strains was observed, but macrorestriction with B<it>gl</it>II did not identify further differences. Automated rep-PCR patterns were variable between serovars, but <it>S</it>. Enteritidis PT13 strains could not be differentiated.</p> <p>Conclusion</p> <p>None of the methods identified any significant variation between PT13 strains. Greater than 11,300 base pairs of sequence for each of seven <it>S</it>. Enteritidis PT13 strains were analyzed without detecting a single polymorphic site, although diversity between different phage types of <it>S</it>. Enteritidis was observed. These data suggest that Canadian <it>S</it>. Enteritidis PT13 strains are highly related genetically.</p

Equations to predict antimicrobial minimum inhibitory concentrations in Neisseria gonorrhoeae using molecular antimicrobial resistance determinants

The emergence of Neisseria gonorrhoeae strains that are resistant to azithromycin and extended-spectrum cephalosporins represents a public health threat, that of untreatable gonorrhea infections. Multivariate regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to the overall antimicrobial MICs for ceftriaxone, cefixime, azithromycin, tetracycline, ciprofloxacin, and penicillin. A training data set consisting of 1,280 N. gonorrhoeae strains was used to generate regression equations which were then applied to validation data sets of Canadian (n = 1,095) and international (n = 431) strains. The predicted MICs for extended-spectrum cephalosporins (ceftriaxone and cefixime) were fully explained by 5 amino acid substitutions in PenA, A311V, A501P/T/V, N513Y, A517G, and G543S; the presence of a disrupted mtrR promoter; and the PorB G120 and PonA L421P mutations. The correlation of predicted MICs within one doubling dilution to phenotypically determined MICs of the Canadian validation data set was 95.0% for ceftriaxone, 95.6% for cefixime, 91.4% for azithromycin, 98.2% for tetracycline, 90.4% for ciprofloxacin, and 92.3% for penicillin, with an overall sensitivity of 99.9% and specificity of 97.1%. The correlations of predicted MIC values to the phenotypically determined MICs were similar to those from phenotype MIC-only comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular data will facilitate the transition to whole-genome sequencing analysis from phenotypic testing and can fill the surveillance gap in an era of increased reliance on nucleic acid assay testing (NAAT) diagnostics to better monitor the dynamics of N. gonorrhoeae

Novel phages of healthy skin metaviromes from South Africa

Recent skin metagenomic studies have investigated the harbored viral diversity and its possible influence on healthy skin microbial populations, and tried to establish global patterns of skin-phage evolution. However, the detail associated with the phages that potentially play a role in skin health has not been investigated. While skin metagenome and -metavirome studies have indicated that the skin virome is highly site specific and shows marked interpersonal variation, they have not assessed the presence/absence of individual phages. Here, we took a semi-culture independent approach (metaviromic) to better understand the composition of phage communities on skin from South African study participants. Our data set adds over 130 new phage species of the skin to existing databases. We demonstrated that identical phages were present on different individuals and in different body sites, and we conducted a detailed analysis of the structural organization of these phages. We further found that a bacteriophage related to the Staphylococcus capitis phage Stb20 may be a common skin commensal virus potentially regulating its host and its activities on the ski

WGS to predict antibiotic MICs for Neisseria gonorrhoeae

Background: Tracking the spread of antimicrobial resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. Objectives: We investigate whether whole-genome sequencing, WGS, and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of minimum inhibitory concentrations, MICs, in N. gonorrhoeae. Methods: WGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin, and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross validation. Results: Overall 1785/3380(53%) MIC values were predicted to the nearest doubling dilution, and 3147(93%) within ±1 and 3314(98%) within ±2 doubling-dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error rate (VME, phenotypically resistant, WGS-prediction sensitive) was 21/1577(1.3%, 95%CI 0.8-2.0%), and the major error rate (ME, phenotypically sensitive, WGS-prediction resistant) was 20/1186(1.7%, 1.0-2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all 5 antimicrobials. Conclusions: We demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species

Analysis of multidrug resistance in the predominant Streptococcus pneumoniae serotypes in Canada:the SAVE study, 2011-15

Objectives: This study assessed MDR invasive isolates of Streptococcus pneumoniae, in relation to serotype evolution in Canada between 2011 and 2015 as part of the annual SAVE study. Methods: As part of a collaboration between the Canadian Antimicrobial Resistance Alliance and Public Health Agency of Canada-National Microbiology Laboratory, 6207 invasive isolates of S. pneumoniae were evaluated. All isolates were serotyped and had antimicrobial susceptibility testing performed, in accordance with CLSI guidelines (M07-A10, 2015). Complete susceptibility profiles were available for 6001 isolates. MDR was defined as resistance to three or more classes of antimicrobial agents (with penicillin MIC ≥2 mg/L defined as resistant). Results: The overall rate of MDR S. pneumoniae was 6.2% (372/6001) in SAVE, decreasing significantly from 8.5% in 2011 to 5.6% in 2015 (P = 0.0041). MDR was observed in 32 serotypes, with serotypes 15A and 19A predominating (26.6% and 41.7% of the MDR isolates, respectively). The overall proportion of serotypes 19A, 7F and 33A decreased significantly (P 5%) for 24F and 33F. Conclusions: In 2015, 56.3% of invasive MDR S. pneumoniae were serotypes included in the PCV-13 vaccine. PCV-13 includes the most commonly identified serotype, 19A; however, other increasingly important MDR serotypes, such as 15A, 24F and 33F, are notably not in the currently used vaccines

Analysis of meiotic recombination in 22q11.2, a region that frequently undergoes deletions and duplications

BACKGROUND: The 22q11.2 deletion syndrome is the most frequent genomic disorder with an estimated frequency of 1/4000 live births. The majority of patients (90%) have the same deletion of 3 Mb (Typically Deleted Region, TDR) that results from aberrant recombination at meiosis between region specific low-copy repeats (LCRs). METHODS: As a first step towards the characterization of recombination rates and breakpoints within the 22q11.2 region we have constructed a high resolution recombination breakpoint map based on pedigree analysis and a population-based historical recombination map based on LD analysis. RESULTS: Our pedigree map allows the location of recombination breakpoints with a high resolution (potential recombination hotspots), and this approach has led to the identification of 5 breakpoint segments of 50 kb or less (8.6 kb the smallest), that coincide with historical hotspots. It has been suggested that aberrant recombination leading to deletion (and duplication) is caused by low rates of Allelic Homologous Recombination (AHR) within the affected region. However, recombination rate estimates for 22q11.2 region show that neither average recombination rates in the 22q11.2 region or within LCR22-2 (the LCR implicated in most deletions and duplications), are significantly below chromosome 22 averages. Furthermore, LCR22-2, the repeat most frequently implicated in rearrangements, is also the LCR22 with the highest levels of AHR. In addition, we find recombination events in the 22q11.2 region to cluster within families. Within this context, the same chromosome recombines twice in one family; first by AHR and in the next generation by NAHR resulting in an individual affected with the del22q11.2 syndrome. CONCLUSION: We show in the context of a first high resolution pedigree map of the 22q11.2 region that NAHR within LCR22 leading to duplications and deletions cannot be explained exclusively under a hypothesis of low AHR rates. In addition, we find that AHR recombination events cluster within families. If normal and aberrant recombination are mechanistically related, the fact that LCR22s undergo frequent AHR and that we find familial differences in recombination rates within the 22q11.2 region would have obvious health-related implications

Neisseria gonorrhoeae sequence typing for antimicrobial resistance, a novel antimicrobial resistance multilocus typing scheme for tracking global dissemination of N. Gonorrhoeae strains

A curated Web-based user-friendly sequence typing tool based on antimicrobial resistance determinants in Neisseria gonorrhoeae was developed and is publicly accessible (https://ngstar.Canada.ca). The N. gonorrhoeae Sequence Typing for Antimicrobial Resistance (NG-STAR) molecular typing scheme uses the DNA sequences of 7 genes (penA, mtrR, porB, ponA, gyrA, parC, and 23S rRNA) associated with resistance to β-lactam antimicrobials, macrolides, or fluoroquinolones. NG-STAR uses the entire penA sequence, combining the historical nomenclature for penA types I to XXXVIII with novel nucleotide sequence designations; the full mtrR sequence and a portion of its promoter region; portions of ponA, porB, gyrA, and parC; and 23S rRNA sequences. NG-STAR grouped 768 isolates into 139 sequence types (STs) (n = 660) consisting of 29 clonal complexes (CCs) having a maximum of a single-locus variation, and 76 NG-STAR STs (n = 109) were identified as unrelated singletons. NG-STAR had a high Simpson's diversity index value of 96.5% (95% confidence interval [CI] = 0.959 to 0.969). The most common STs were NG-STAR ST-90 (n = 100; 13.0%), ST-42 and ST-91 (n = 45; 5.9%), ST-64 (n = 44; 5.72%), and ST-139 (n = 42; 5.5%). Decreased susceptibility to azithromycin was associated with NGSTAR ST-58, ST-61, ST-64, ST-79, ST-91, and ST-139 (n = 156; 92.3%); decreased susceptibility to cephalosporins was associated with NG-STAR ST-90, ST-91, and ST-97 (n = 162; 94.2%); and ciprofloxacin resistance was associated with NG-STAR ST-26, ST-90, ST-91, ST-97, ST-150, and ST-158 (n = 196; 98.0%). All isolates of NG-STAR ST- 42, ST-43, ST-63, ST-81, and ST-160 (n = 106) were susceptible to all four antimicrobials. The standardization of nomenclature associated with antimicrobial resistance determinants through an internationally available database will facilitate the monitoring of the global dissemination of antimicrobial-resistant N. gonorrhoeae strains

Prophage exotoxins enhance colonization fitness in epidemic scarlet fever-causing Streptococcus pyogenes

Abstract: The re-emergence of scarlet fever poses a new global public health threat. The capacity of North-East Asian serotype M12 (emm12) Streptococcus pyogenes (group A Streptococcus, GAS) to cause scarlet fever has been linked epidemiologically to the presence of novel prophages, including prophage ΦHKU.vir encoding the secreted superantigens SSA and SpeC and the DNase Spd1. Here, we report the molecular characterization of ΦHKU.vir-encoded exotoxins. We demonstrate that streptolysin O (SLO)-induced glutathione efflux from host cellular stores is a previously unappreciated GAS virulence mechanism that promotes SSA release and activity, representing the first description of a thiol-activated bacterial superantigen. Spd1 is required for resistance to neutrophil killing. Investigating single, double and triple isogenic knockout mutants of the ΦHKU.vir-encoded exotoxins, we find that SpeC and Spd1 act synergistically to facilitate nasopharyngeal colonization in a mouse model. These results offer insight into the pathogenesis of scarlet fever-causing GAS mediated by prophage ΦHKU.vir exotoxins

Trends in invasive bacterial diseases during the first 2 years of the COVID-19 pandemic: analyses of prospective surveillance data from 30 countries and territories in the IRIS Consortium.

BACKGROUND: The Invasive Respiratory Infection Surveillance (IRIS) Consortium was established to assess the impact of the COVID-19 pandemic on invasive diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, and Streptococcus agalactiae. We aimed to analyse the incidence and distribution of these diseases during the first 2 years of the COVID-19 pandemic compared to the 2 years preceding the pandemic. METHODS: For this prospective analysis, laboratories in 30 countries and territories representing five continents submitted surveillance data from Jan 1, 2018, to Jan 2, 2022, to private projects within databases in PubMLST. The impact of COVID-19 containment measures on the overall number of cases was analysed, and changes in disease distributions by patient age and serotype or group were examined. Interrupted time-series analyses were done to quantify the impact of pandemic response measures and their relaxation on disease rates, and autoregressive integrated moving average models were used to estimate effect sizes and forecast counterfactual trends by hemisphere. FINDINGS: Overall, 116 841 cases were analysed: 76 481 in 2018-19, before the pandemic, and 40 360 in 2020-21, during the pandemic. During the pandemic there was a significant reduction in the risk of disease caused by S pneumoniae (risk ratio 0·47; 95% CI 0·40-0·55), H influenzae (0·51; 0·40-0·66) and N meningitidis (0·26; 0·21-0·31), while no significant changes were observed for S agalactiae (1·02; 0·75-1·40), which is not transmitted via the respiratory route. No major changes in the distribution of cases were observed when stratified by patient age or serotype or group. An estimated 36 289 (95% prediction interval 17 145-55 434) cases of invasive bacterial disease were averted during the first 2 years of the pandemic among IRIS-participating countries and territories. INTERPRETATION: COVID-19 containment measures were associated with a sustained decrease in the incidence of invasive disease caused by S pneumoniae, H influenzae, and N meningitidis during the first 2 years of the pandemic, but cases began to increase in some countries towards the end of 2021 as pandemic restrictions were lifted. These IRIS data provide a better understanding of microbial transmission, will inform vaccine development and implementation, and can contribute to health-care service planning and provision of policies. FUNDING: Wellcome Trust, NIHR Oxford Biomedical Research Centre, Spanish Ministry of Science and Innovation, Korea Disease Control and Prevention Agency, Torsten Söderberg Foundation, Stockholm County Council, Swedish Research Council, German Federal Ministry of Health, Robert Koch Institute, Pfizer, Merck, and the Greek National Public Health Organization