Frequent Undetected Ward-Based Methicillin-Resistant Staphylococcus aureus Transmission Linked to Patient Sharing Between Hospitals.

Background: Recent evidence suggests that hospital transmission of methicillin-resistant Staphylococcus aureus (MRSA) is uncommon in UK centers that have implemented sustained infection control programs. We investigated whether a healthcare-network analysis could shed light on transmission paths currently sustaining MRSA levels in UK hospitals. Methods: A cross-sectional observational study was performed in 2 National Health Service hospital groups and a general district hospital in Southeast London. All MRSA patients identified at inpatient, outpatient, and community settings between 1 November 2011 and 29 February 2012 were included. We identified genetically defined MRSA transmission clusters in individual hospitals and across the healthcare network, and examined genetic differentiation of sequence type (ST) 22 MRSA isolates within and between hospitals and inpatient or outpatient and community settings, as informed by average and median pairwise single-nucleotide polymorphisms (SNPs) and SNP-based proportions of nearly identical isolates. Results: Two hundred forty-eight of 610 (40.7%) MRSA patients were linked in 90 transmission clusters, of which 27 spanned multiple hospitals. Analysis of a large 32 patient ST22-MRSA cluster showed that 26 of 32 patients (81.3%) had multiple contacts with one another during ward stays at any hospital. No residential, outpatient, or significant community healthcare contacts were identified. Genetic differentiation between ST22 MRSA inpatient isolates from different hospitals was less than between inpatient isolates from the same hospitals (P ≤ .01). Conclusions: There is evidence of frequent ward-based transmission of MRSA brought about by frequent patient admissions to multiple hospitals. Limiting in-ward transmission requires sharing of MRSA status data between hospitals

Deep Sequencing of B Cell Receptor Repertoires From COVID-19 Patients Reveals Strong Convergent Immune Signatures.

Deep sequencing of B cell receptor (BCR) heavy chains from a cohort of 31 COVID-19 patients from the UK reveals a stereotypical naive immune response to SARS-CoV-2 which is consistent across patients. Clonal expansion of the B cell population is also observed and may be the result of memory bystander effects. There was a strong convergent sequence signature across patients, and we identified 1,254 clonotypes convergent between at least four of the COVID-19 patients, but not present in healthy controls or individuals following seasonal influenza vaccination. A subset of the convergent clonotypes were homologous to known SARS and SARS-CoV-2 spike protein neutralizing antibodies. Convergence was also demonstrated across wide geographies by comparison of data sets between patients from UK, USA, and China, further validating the disease association and consistency of the stereotypical immune response even at the sequence level. These convergent clonotypes provide a resource to identify potential therapeutic and prophylactic antibodies and demonstrate the potential of BCR profiling as a tool to help understand patient responses

Methodology for Whole-Genome Sequencing of Methicillin-Resistant <i>Staphylococcus aureus</i> Isolates in a Routine Hospital Microbiology Laboratory

There is growing evidence for the value of bacterial whole-genome sequencing in hospital outbreak investigations. Our aim was to develop methods that support efficient and accurate low-throughput clinical sequencing of methicillin-resistant Staphylococcus aureus (MRSA) isolates. </jats:p

Evidence for Community Transmission of Community-Associated but Not Health-Care-Associated Methicillin-Resistant Staphylococcus Aureus Strains Linked to Social and Material Deprivation: Spatial Analysis of Cross-sectional Data

Supporting information for a paper titled "Evidence for Community Transmission of Community-Associated but Not Health-Care-Associated Methicillin-Resistant Staphylococcus Aureus Strains Linked to Social and Material Deprivation: Spatial Analysis of Cross-sectional Data". This includes: an MS Word document that describes the modelling approach (S1 Methods), Summary statistics for area-level variables in 513 LSOAs within catchment areas of the hospital cohort (S1 Table), data from the 2011 England and Wales census that outlines population structure of 513 LSOAs within catchment areas of the hospital cohort. (S2 Table), Individual patient-level metadata (S1 Text), and LSOA-level aggregated metadata (S2 Text

Methodology for Whole-Genome Sequencing of Methicillin-Resistant Staphylococcus aureus Isolates in a Routine Hospital Microbiology Laboratory.

There is growing evidence for the value of bacterial whole-genome sequencing in hospital outbreak investigations. Our aim was to develop methods that support efficient and accurate low-throughput clinical sequencing of methicillin-resistant Staphylococcus aureus (MRSA) isolates. Using a test panel of 25 MRSA isolates previously associated with outbreak investigations, we devised modifications to library preparation that reduced the processing time by 1 hour. We determined the maximum number of isolates that could be sequenced per run using an Illumina MiniSeq platform and a 13-hour (overnight) run time, which equated to 21 MRSA isolates and 3 controls (no template, positive, and negative). Repeatability and reproducibility assays based on this sequencing methodology demonstrated 100% accuracy in assigning species and sequence type (ST) and in detecting mecA Established genetic relatedness between isolates was recapitulated. Quality control (QC) metrics were evaluated over nine sequencing runs. Of the test panel MRSA genomes, 168/173 (97%) passed QC metrics based on the correct species assigned, detection of mecA and ST, and depth/coverage metrics. An evaluation of contamination in these 9 runs showed that positive and negative controls and test MRSA sequence files contained <0.14% and <0.48% of fragments that matched another species, respectively. Deliberate contamination experiments confirmed that this was insufficient to impact data interpretation. These methods support reliable and reproducible clinical MRSA sequencing with a turnaround time (from DNA extraction to availability of data files) of 24 hours

A culture-independent sequence-based metagenomics approach to the investigation of an outbreak of Shiga-Toxigenic Escherichia coli O104:H4

Identification of the bacterium responsible for an outbreak can aid in disease management. However, traditional culture-based diagnosis can be difficult, particularly if no specific diagnostic test is available for an outbreak strain. To explore the potential of metagenomics, which is the direct sequencing of DNA extracted from microbiologically complex samples, as an open-ended clinical discovery platform capable of identifying and characterizing bacterial strains from an outbreak without laboratory culture. In a retrospective investigation, 45 samples were selected from fecal specimens obtained from patients with diarrhea during the 2011 outbreak of Shiga-toxigenic Escherichia coli (STEC) O104:H4 in Germany. Samples were subjected to high-throughput sequencing (August-September 2012), followed by a 3-phase analysis (November 2012-February 2013). In phase 1, a de novo assembly approach was developed to obtain a draft genome of the outbreak strain. In phase 2, the depth of coverage of the outbreak strain genome was determined in each sample. In phase 3, sequences from each sample were compared with sequences from known bacteria to identify pathogens other than the outbreak strain. The recovery of genome sequence data for the purposes of identification and characterization of the outbreak strain and other pathogens from fecal samples. During phase 1, a draft genome of the STEC outbreak strain was obtained. During phase 2, the outbreak strain genome was recovered from 10 samples at greater than 10-fold coverage and from 26 samples at greater than 1-fold coverage. Sequences from the Shiga-toxin genes were detected in 27 of 40 STEC-positive samples (67%). In phase 3, sequences from Clostridium difficile, Campylobacter jejuni, Campylobacter concisus, and Salmonella enterica were recovered. These results suggest the potential of metagenomics as a culture-independent approach for the identification of bacterial pathogens during an outbreak of diarrheal disease. Challenges include improving diagnostic sensitivity, speeding up and simplifying workflows, and reducing costs

Clonal variation in high- and low-level phenotypic and genotypic mupirocin resistance of MRSA isolates in south-east London

OBJECTIVES: Both low-level mupirocin resistance (LMR) and high-level mupirocin resistance (HMR) have been identified. The aim of this study was to determine the epidemiology of LMR and HMR in MRSA isolates at five hospitals that have used mupirocin for targeted decolonization as part of successful institutional control programmes. METHODS: All MRSA identified in three microbiology laboratories serving five central and south-east London hospitals and surrounding communities between November 2011 and February 2012 were included. HMR and LMR were determined by disc diffusion testing. WGS was used to derive multilocus sequence types (MLSTs) and the presence of HMR and LMR resistance determinants. RESULTS: Prevalence of either HMR or LMR amongst first healthcare episode isolates from 795 identified patients was 9.69% (95% CI 7.72-11.96); LMR was 6.29% (95% CI 4.70-8.21) and HMR was 3.40% (95% CI 2.25-4.90). Mupirocin resistance was not significantly different in isolates identified from inpatients at each microbiology laboratory, but was more common in genotypically defined 'hospital' rather than 'community' isolates (OR 3.17, 95% CI 1.36-9.30, P = 0.002). LMR was associated with inpatient stay, previous history of MRSA and age ≥65 years; HMR was associated with age ≥65 years and residential postcode outside London. LMR and HMR varied by clone, with both being low in the dominant UK MRSA clone ST22 compared with ST8, ST36 and ST239/241 for LMR and with ST8 and ST36 for HMR. V588F mutation and mupA carriage had high specificity (>97%) and area under the curve (>83%) to discriminate phenotypic mupirocin resistance, but uncertainty around the sensitivity point estimate was large (95% CI 52.50%-94.44%). Mutations in or near the mupA gene were found in eight isolates that carried mupA but were not HMR. CONCLUSIONS: Mupirocin resistance was identified in <10% of patients and varied significantly by clone, implying that changes in clonal epidemiology may have an important role in determining the prevalence of resistance in conjunction with selection due to mupirocin use

Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms.

DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons