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BACKGROUND Few methicillin-resistant Staphylococcus aureus (MRSA) from the early years of its global emergence have been sequenced. Knowledge about evolutionary factors promoting the success of specific MRSA multi-locus sequence types (MLSTs) remains scarce. We aimed to characterize a legacy MRSA collection isolated from 1965 to 1987 and compare it against publicly available international and local genomes. METHODS We accessed 451 historic (1965-1987) MRSA isolates stored in the Culture Collection of Switzerland, mostly collected from the Zurich region. We determined phenotypic antimicrobial resistance (AMR) and performed whole genome sequencing (WGS) using Illumina short-read sequencing on all isolates and long-read sequencing on a selection with Oxford Nanopore Technology. For context, we included 103 publicly available international assemblies from 1960 to 1992 and sequenced 1207 modern Swiss MRSA isolates from 2007 to 2022. We analyzed the core genome (cg)MLST and predicted SCCmec cassette types, AMR, and virulence genes. RESULTS Among the 451 historic Swiss MRSA isolates, we found 17 sequence types (STs) of which 11 have been previously described. Two STs were novel combinations of known loci and six isolates carried previously unsubmitted MLST alleles, representing five new STs (ST7843, ST7844, ST7837, ST7839, and ST7842). Most isolates (83% 376/451) represented ST247-MRSA-I isolated in the 1960s, followed by ST7844 (6% 25/451), a novel single locus variant (SLV) of ST239. Analysis by cgMLST indicated that isolates belonging to ST7844-MRSA-III cluster within the diversity of ST239-MRSA-III. Early MRSA were predominantly from clonal complex (CC)8. From 1980 to the end of the twentieth century, we observed that CC22 and CC5 as well as CC8 were present, both locally and internationally. CONCLUSIONS The combined analysis of 1761 historic and contemporary MRSA isolates across more than 50 years uncovered novel STs and allowed us a glimpse into the lineage flux betw

PURPOSE: Panel PCR tests provide rapid pathogen identification. However, their diagnostic performance is unclear. We assessed the performance of the Biofire$^{©}$ FilmArray pneumonia (PN)-panel against standard culture in broncho-alveolar lavage (BAL) samples. METHODS: Setting: University Hospital Basel (February 2019 to July 2020), including hospitalized patients with a BAL (± pneumonia). We determined sensitivity and specificity of the PN-panel against standard culture. Using univariate logistic regression, we calculated odds ratios (OR) for pneumonia according to PN-panel and culture status, stratifying by chronic pulmonary disease. We calculated ORs for pneumonia for different pathogens to estimate the clinical relevance. RESULTS: We included 840 adult patients, 60% were males, median age was 68 years, 35% had chronic pulmonary disease, 21% had pneumonia, and 36% had recent antibiotic use. In 1078 BAL samples, bacterial pathogens were detected in 36% and 16% with PN-panel and culture, respectively. The overall sensitivity and specificity of the PN-panel was high, whereas the positive predictive value was low. The OR of pneumonia was 1.1 (95% CI 0.7-1.6) for PN-panel-positive only; 2.6 (95% CI 1.3-5.3) for culture-positive only, and 1.6 (95% CI 1.0-2.4) for PN-panel and culture-positive. The detection rate of Haemophilus influenzae, Staphylococcus aureus, and Moraxella catarrhalis in the PN-panel was high but not associated with pneumonia. CONCLUSION: While sensitivity and specificity of PN-panel are high compared to culture, pathogen detection did not correlate well with a pneumonia diagnosis. Patients with culture-positive BAL had the highest OR for pneumonia-thus the impact of the PN-panel on clinical management needs further evaluation in randomized controlled trials.

BACKGROUND Urinary tract infections (UTIs) are among the most common bacterial infections worldwide, often caused by uropathogenic Escherichia coli. Multiple bacterial virulence factors or patient characteristics have been linked separately to progressive, more invasive infections. In this study, we aim to identify pathogen- and patient-specific factors that drive the progression to urosepsis by jointly analysing bacterial and host characteristics. METHODS We analysed 1076 E. coli strains isolated from 825 clinical cases with UTI and/or bacteraemia by whole-genome sequencing (Illumina). Sequence types (STs) were determined via srst2 and capsule loci via fastKaptive. We compared the isolates from urine and blood to confirm clonality. Furthermore, we performed a bacterial genome-wide association study (bGWAS) (pyseer) using bacteraemia as the primary clinical outcome. Clinical data were collected by an electronic patient chart review. We concurrently analysed the association of the most significant bGWAS hit and important patient characteristics with the clinical endpoint bacteraemia using a generalised linear model (GLM). Finally, we designed qPCR primers and probes to detect papGII-positive E. coli strains and prospectively screened E. coli from urine samples (n = 1657) at two healthcare centres. RESULTS Our patient cohort had a median age of 75.3 years (range: 18.00-103.1) and was predominantly female (574/825, 69.6%). The bacterial phylogroups B2 (60.6%; 500/825) and D (16.6%; 137/825), which are associated with extraintestinal infections, represent the majority of the strains in our collection, many of which encode a polysaccharide capsule (63.4%; 525/825). The most frequently observed STs were ST131 (12.7%; 105/825), ST69 (11.0%; 91/825), and ST73 (10.2%; 84/825). Of interest, in 12.3% (13/106) of cases, the E. coli pairs in urine and blood were only distantly related. In line with previous bGWAS studies, we identified the gene papGII (p-value < 0.001), which en

BACKGROUND: Blood cultures (BC) are critical for the diagnosis of bloodstream infections, pathogen identification, and resistance testing. Guidelines recommend a blood volume of 8-10 mL per bottle as lower volumes result in decreased sensitivity. We aimed to evaluate factors for non-adherence to recommended volumes and assess the effects on diagnostic performance. METHODS: From February to April 2020, we measured collected blood volumes by weighing all BC containers from inpatient samples at the University Hospital Basel. Information on BC volumes was merged with clinical and microbiological data, as well as nursing staff schedules. We analyzed factors associated with (i) BC sampling volume, (ii) reaching recommended volumes (≥8 mL), (iii) BC positivity, and (iv) time to positivity using linear and generalized linear mixed effect models. RESULTS: We evaluated a total of 4'118 BC bottles collected from 686 patients. A total of 1'495 (36.3%) of all bottles contained the recommended filling volume of ≥8 mL. Using a central venous and arterial catheter for drawing blood resulted in an increase of filling volume by 0.26 mL (95% CI 0.10, 0.41) and 0.50 mL (95% CI 0.31, 0.69) compared to peripheral venipuncture, respectively. Each additional nursing staff working at the time of blood drawing was associated with 6% higher odds of achieving the recommended filling volume. We found no significant correlation between the filling volume and the positivity rate. CONCLUSION: Our results indicate critical pre-analytical quality markers linked to BC collection procedures to reach recommended collection volumes. No significant impact on the positivity rate was found.

Infections with carbapenemase-producing Gram-negative bacteria are related to increased morbidity and mortality, yet little is known regarding infections caused by non-beta-lactamase mediated carbapenem-resistant bacteria. Our objective was to identify risk factors for, and the clinical impact of infections caused by carbapenem-resistant carbapenemase-negative Enterobacterales and Pseudomonas aeruginosa. This retrospective matched case-control study was performed at the University Hospital of Basel, Switzerland, in 2016. We focused on other resistance mechanisms by excluding laboratory-confirmed carbapenemase-positive cases. Carbapenem resistance was set as the primary endpoint, and important risk factors were investigated by conditional logistic regression. The clinical impact of carbapenem resistance was estimated using regression models containing the resistance indicator as explanatory factor and adjusting for potential confounders. Seventy-five cases of infections with carbapenem-resistant, carbapenemase-negative bacteria were identified and matched with 75 controls with carbapenem-susceptible infections. The matched data set was well-balanced regarding age, gender, and comorbidity. Duration of prior carbapenem treatment (OR 1.15, [1.01, 1.31]) correlated with resistance to carbapenems. Our study showed that patients with carbapenem-resistant bacteria stayed 1.59 times (CI [0.81, 3.14]) longer in an ICU. The analyzed dataset did not provide evidence for strong clinical implications of resistance to carbapenems or increased mortality. The duration of prior carbapenem treatment seems to be a strong risk factor for the development of carbapenem resistance. The higher risk for a longer ICU stay could be a consequence of a carbapenem resistance. In contrast to carbapenemase-producers, the clinical impact of carbapenamase-negative, carbapenem-resistant strains may be limited. Trial registration: The study design was prospectively approved by the local Ethics Commissi

The increasing integration of genomics into routine clinical diagnostics requires reliable computational tools to identify determinants of antimicrobial resistance (AMR) from whole-genome sequencing data. Here, we developed PorinPredict, a bioinformatic tool that predicts defects of the Pseudomonas aeruginosa outer membrane porin OprD, which are strongly associated with reduced carbapenem susceptibility. PorinPredict relies on a database of intact OprD variants and reports inactivating mutations in the coding or promoter region. PorinPredict was validated against 987 carbapenemase-negative P. aeruginosa genomes, of which OprD loss was predicted for 454 out of 522 (87.0%) meropenem-nonsusceptible and 46 out of 465 (9.9%) meropenem-susceptible isolates. OprD loss was also found to be common among carbapenemase-producing isolates, resulting in even further increased MICs. Chromosomal mutations in quinolone resistance-determining regions and OprD loss commonly co-occurred, likely reflecting the restricted use of carbapenems for multidrug-resistant infections as recommended in antimicrobial stewardship programs. In combination with available AMR gene detection tools, PorinPredict provides a robust and standardized approach to link P. aeruginosa phenotypes to genotypes. IMPORTANCE Pseudomonas aeruginosa is a major cause of multidrug-resistant nosocomial infections. The emergence and spread of clones exhibiting resistance to carbapenems, a class of critical last-line antibiotics, is therefore closely monitored. Carbapenem resistance is frequently mediated by chromosomal mutations that lead to a defective outer membrane porin OprD. Here, we determined the genetic diversity of OprD variants across the P. aeruginosa population and developed PorinPredict, a bioinformatic tool that enables the prediction of OprD loss from whole-genome sequencing data. We show a high correlation between predicted OprD loss and meropenem nonsusceptibility irrespective of the presence of carbapene