The Dominant Australian Community-Acquired Methicillin-Resistant Staphylococcus aureus Clone ST93-IV [2B] Is Highly Virulent and Genetically Distinct

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) USA300 has spread rapidly across North America, and CA-MRSA is also increasing in Australia. However, the dominant Australian CA-MRSA strain, ST93-IV [2B] appears distantly related to USA300 despite strikingly similar clinical and epidemiological profiles. Here, we compared the virulence of a recent Australian ST93 isolate (JKD6159) to other MRSA, including USA300, and found that JKD6159 was the most virulent in a mouse skin infection model. We fully sequenced the genome of JKD6159 and confirmed that JKD6159 is a distinct clone with 7616 single nucleotide polymorphisms (SNPs) distinguishing this strain from all other S. aureus genomes. Despite its high virulence there were surprisingly few virulence determinants. However, genes encoding α-hemolysin, Panton-Valentine leukocidin (PVL) and α-type phenol soluble modulins were present. Genome comparisons revealed 32 additional CDS in JKD6159 but none appeared to encode new virulence factors, suggesting that this clone's enhanced pathogenicity could lie within subtler genome changes, such as SNPs within regulatory genes. To investigate the role of accessory genome elements in CA-MRSA epidemiology, we next sequenced three additional Australian non-ST93 CA-MRSA strains and compared them with JKD6159, 19 completed S. aureus genomes and 59 additional S. aureus genomes for which unassembled genome sequence data was publicly available (82 genomes in total). These comparisons showed that despite its distinctive genotype, JKD6159 and other CA-MRSA clones (including USA300) share a conserved repertoire of three notable accessory elements (SSCmecIV, PVL prophage, and pMW2). This study demonstrates that the genetically distinct ST93 CA-MRSA from Australia is highly virulent. Our comparisons of geographically and genetically diverse CA-MRSA genomes suggest that apparent convergent evolution in CA-MRSA may be better explained by the rapid dissemination of a highly conserved accessory genome from a common source

Evolution of Multidrug Resistance during Staphylococcus aureus Infection Involves Mutation of the Essential Two Component Regulator WalKR

Antimicrobial resistance in Staphylococcus aureus is a major public health threat, compounded by emergence of strains with resistance to vancomycin and daptomycin, both last line antimicrobials. Here we have performed high throughput DNA sequencing and comparative genomics for five clinical pairs of vancomycin-susceptible (VSSA) and vancomycin-intermediate ST239 S. aureus (VISA); each pair isolated before and after vancomycin treatment failure. These comparisons revealed a frequent pattern of mutation among the VISA strains within the essential walKR two-component regulatory locus involved in control of cell wall metabolism. We then conducted bi-directional allelic exchange experiments in our clinical VSSA and VISA strains and showed that single nucleotide substitutions within either walK or walR lead to co-resistance to vancomycin and daptomycin, and caused the typical cell wall thickening observed in resistant clinical isolates. Ion Torrent genome sequencing confirmed no additional regulatory mutations had been introduced into either the walR or walK VISA mutants during the allelic exchange process. However, two potential compensatory mutations were detected within putative transport genes for the walK mutant. The minimal genetic changes in either walK or walR also attenuated virulence, reduced biofilm formation, and led to consistent transcriptional changes that suggest an important role for this regulator in control of central metabolism. This study highlights the dramatic impacts of single mutations that arise during persistent S. aureus infections and demonstrates the role played by walKR to increase drug resistance, control metabolism and alter the virulence potential of this pathogen

Individual and community predictors of urinary ceftriaxone-resistant Escherichia coli isolates, Victoria, Australia

Abstract Background Ceftriaxone-resistant Enterobacteriaceae are priority pathogens of critical importance. Escherichia coli is the most commonly isolated Enterobacteriaceae. There are few data regarding non-invasive ceftriaxone-resistant E. coli (CR-EC) isolates in the Australian community. We aimed to describe the prevalence, phenotype, geographic variation, and sociodemographic predictors of ceftriaxone-resistance among E. coli isolates recovered from urine specimens. Methods In August 2017, we prospectively analysed E. coli isolates recovered from urine specimens submitted to Dorevitch Pathology (Victoria, Australia), a laboratory that services patients in the community and hospitals. In addition to patient-level predictors of ceftriaxone resistance, we mapped patient postcodes to community-level indicators including Index of Relative Socioeconomic Deprivation, remoteness, and proportion of residents born overseas. We used Poisson regression with log link and robust standard errors to quantify the association between ceftriaxone resistance and patient- and community-level factors. Results We included 6732 non-duplicate E. coli isolates. Most (89.2%, 6008/6732) were obtained from female patients. Median age was 56 years (IQR, 32–74). Most patients (90.5%, 5789/6732) were neither referred from a hospital nor residing in a residential aged care facility (RACF). Among the 6732 isolates, 5.7% (382) were CR-EC, ranging from 3.5% (44/1268) in inner regional areas to 6.3% (330/5267) in major cities. Extended spectrum ß–lactamase (ESBL) -production was the most common mechanism for ceftriaxone resistance (89%, 341/382). Nitrofurantoin was the most active oral agent against CR-EC. Eight CR-EC isolates (2.4%) were susceptible only to amikacin, meropenem and nitrofurantoin. None were resistant to meropenem. On multivariable analysis, ceftriaxone resistance was associated with age, residence in a RACF (adjusted relative risk [aRR] 2.94, 95% confidence interval [CI] 2.10–4.13), specimen referral from hospital (aRR 2.05, 95% CI 1.45–2.9), and the proportion of residents born in North Africa and the Middle East (aRR 1.30 for each 5% absolute increase, 95% CI 1.09–1.54), South-East Asia (aRR 1.14, 95% CI 1.02–1.27), and Southern and Central Asia (aRR 1.16, 95% CI 1.04–1.28). Conclusions These results provide insights into sociodemographic variation in CR-EC in the community. A better understanding of this variation may inform empiric treatment guidelines and strategies to reduce community dissemination of CR-EC

What assay is optimal for the diagnosis of measles virus infection? An evaluation of the performance of a measles virus real-time reverse transcriptase PCR using the Cepheid SmartCycler? and antigen detection by immunofluorescence

Background: Despite the World Health Organization (WHO)-reported elimination of measles in Australia, importation of cases especially in travellers from Asia continues in Sydney, Australia’s largest city. Laboratory confirmation supports clinico-epidemiological evidence of measles virus infection, and is needed to establish elimination. Objectives: To evaluate the performance of a random access real-time reverse transcriptase polymerase chain reaction (RT-PCR) assay using the moderate complexity SmartCycler® platform, and measles antigen detection by immunofluorescence (IFA), for the detection of measles virus in patient samples. Study design: One hundred samples comprising nose and throat swabs, nasopharyngeal aspirates and urine, collected from patients with suspected measles were tested in parallel using IFA and nucleic acid testing using the SmartCycler® and LightCycler® RT-PCR platforms. The LightCycler® RT-PCR was used as the reference assay against which the SmartCycler® RT-PCR and IFA were compared. Results: Using the LightCycler® RT-PCR, measles virus was detected in 35 clinical samples. There was 100% concordance between the results of the SmartCycler® and the LightCycler®-based RT-PCR. Measles genotypes detected included B3, D8, and D9. Testing urine in addition to NTS did not improve diagnostic yield. In contrast, the sensitivity and specificity of IFA compared to the reference LightCycler® RT-PCR was 34.3% and 96.7%, respectively. Conclusion: The performance of the SmartCycler® is comparable to the LightCycler® for the detection of measles virus. However, IFA had poor sensitivity and should not be used to confirm measles virus infection where nucleic acid testing is available

A Supervised Statistical Learning Approach for Accurate Legionella pneumophila Source Attribution during Outbreaks

Public health agencies are increasingly relying on genomics during Legionnaires' disease investigations. However, the causative bacterium (Legionella pneumophila) has an unusual population structure, with extreme temporal and spatial genome sequence conservation. Furthermore, Legionnaires' disease outbreaks can be caused by multiple L. pneumophila genotypes in a single source. These factors can confound cluster identification using standard phylogenomic methods. Here, we show that a statistical learning approach based on L. pneumophila core genome single nucleotide polymorphism (SNP) comparisons eliminates ambiguity for defining outbreak clusters and accurately predicts exposure sources for clinical cases. We illustrate the performance of our method by genome comparisons of 234 L. pneumophila isolates obtained from patients and cooling towers in Melbourne, Australia, between 1994 and 2014. This collection included one of the largest reported Legionnaires' disease outbreaks, which involved 125 cases at an aquarium. Using only sequence data from L. pneumophila cooling tower isolates and including all core genome variation, we built a multivariate model using discriminant analysis of principal components (DAPC) to find cooling tower-specific genomic signatures and then used it to predict the origin of clinical isolates. Model assignments were 93% congruent with epidemiological data, including the aquarium Legionnaires' disease outbreak and three other unrelated outbreak investigations. We applied the same approach to a recently described investigation of Legionnaires' disease within a UK hospital and observed a model predictive ability of 86%. We have developed a promising means to breach L. pneumophila genetic diversity extremes and provide objective source attribution data for outbreak investigations

Hyperexpression of alpha-hemolysin explains enhanced virulence of sequence type 93 community-associated methicillin-resistant Staphylococcus aureus

BACKGROUND: The community-associated methicillin-resistant S. aureus (CA-MRSA) ST93 clone is becoming dominant in Australia and is clinically highly virulent. In addition, sepsis and skin infection models demonstrate that ST93 CA-MRSA is the most virulent global clone of S. aureus tested to date. While the determinants of virulence have been studied in other clones of CA-MRSA, the basis for hypervirulence in ST93 CA-MRSA has not been defined. RESULTS: Here, using a geographically and temporally dispersed collection of ST93 isolates we demonstrate that the ST93 population hyperexpresses key CA-MRSA exotoxins, in particular α-hemolysin, in comparison to other global clones. Gene deletion and complementation studies, and virulence comparisons in a murine skin infection model, showed unequivocally that increased expression of α-hemolysin is the key staphylococcal virulence determinant for this clone. Genome sequencing and comparative genomics of strains with divergent exotoxin profiles demonstrated that, like other S. aureus clones, the quorum sensing agr system is the master regulator of toxin expression and virulence in ST93 CA-MRSA. However, we also identified a previously uncharacterized AraC/XylS family regulator (AryK) that potentiates toxin expression and virulence in S. aureus. CONCLUSIONS: These data demonstrate that hyperexpression of α-hemolysin mediates enhanced virulence in ST93 CA-MRSA, and additional control of exotoxin production, in particular α-hemolysin, mediated by regulatory systems other than agr have the potential to fine-tune virulence in CA-MRSA

Minimum spanning tree (MST) of the six ST93 <i>dru</i> types.

<p>Cluster analysis was performed using the Polymorphic VNTR plug-in tool of the BioNumerics program. <i>dru</i> types separated by an MST distance of ≤1 (i.e., if they were ≥98% similar) were considered closely related and assigned to the same cluster. Pulsed-field gel electrophoresis (PFGE) pulsotypes and <i>spa</i> types are recorded for each <i>dru</i> type.</p

Minimum spanning tree (MST) of the seven ST93 <i>spa</i> types.

<p>Cluster analysis was performed using the spa typing plug-in tool of the BioNumerics program. <i>spa</i> types separated by an MST distance of ≤1 (i.e., if they were ≥98% similar) were considered closely related and assigned to the same cluster. MSSA and MRSA <i>spa</i> types are designated in red and green print respectively. Pulsed-field gel electrophoresis (PFGE) pulsotypes and <i>dru</i> types (dt) are recorded for each <i>spa</i> type.</p

Relative LukF-PV expression in ST93 isolates.

<p>All isolates were tested for LukF-PV expression using western blot and LukF-PV specific antibody. Results are expressed as optical density of test strain relative to a 50 µg control of rLukF-PV that was run on every gel. All experiments were performed with multiple replicates and mean and range is shown. Positive control, rLUKF-PV; negative control, RN4220.</p

Characterisation of ST93 isolates.

<p>Regions: ACT, Australian Capital Territory; NSW, New South Wales; NT, Northern Territory, Qld, Queensland; SA, South Australia; Vic, Victoria; WA, Western Australia.</p><p>Antibiogram: Ox, oxacillin; Em, erythromycin; Te, tetracycline.</p><p>Resistance Genotype: <i>mecA</i>, alternate penicillin binding protein 2 gene; <i>blaZ</i>, beta lactamase gene; <i>blaI</i>, beta-lactamase repressor (inhibitor) gene; <i>blaR</i> beta-lactamase regulatory protein gene, <i>ermC</i>, erythromycin/clindamycin resistance gene; <i>msr(A)</i>, macrolide resistance gene; <i>tetK</i>, tetracycline resistance gene; <i>dfrA</i>, trimethoprim resistance gene; qacC quaternary ammonium compound resistance gene protein C.</p><p>PFGE, pulsed field gel electrophoresis; MLST, multilocus sequence type; SCCmec, staphylococcal cassette chromosome mec; <i>spa, Staphylococcus aureus</i> protein gene A; <i>dru</i>, the direct-repeat unit (<i>dru</i>) variable-number tandem repeat region adjacent to IS431 in SCC<i>mec.</i></p><p><i>lukF</i>/<i>lukS</i> PV, Panton Valentine leucocidin F and S component genes.</p