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. 2016 Dec;54(12):2874-2881.
doi: 10.1128/JCM.00790-16. Epub 2016 Aug 24.

Real-Time Genome Sequencing of Resistant Bacteria Provides Precision Infection Control in an Institutional Setting

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Real-Time Genome Sequencing of Resistant Bacteria Provides Precision Infection Control in an Institutional Setting

Alexander Mellmann et al. J Clin Microbiol. 2016 Dec.

Abstract

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.

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Figures

FIG 1
FIG 1
Prospective real-time WGS-based typing of all MRSA isolates exhibiting 71 different spa types. (A) Epidemic curve over interval I for all MRSA isolates detected. Each box represents a single isolate; the 10 most common spa types (≥4 isolates per spa type) are color coded. (B) Clonal relationship of all 66 livestock-associated (LA) MRSA indistinguishable by MLST (all ST398) and spa typing (spa type t011) in a minimum-spanning tree based on whole-genome sequencing. Each circle represents a single genotype, i.e., an allelic profile based on up to 1,861 target genes present in the isolates with the “pairwise ignoring missing values” option turned on in the SeqSphere+ software during comparison. The circles are named with the isolate identifiers (IDs) and colored according to ward, and the sizes are proportional to the number of isolates with identical genotypes. The number on connecting lines represents the number of alleles that differ between the connected genotypes.
FIG 2
FIG 2
Minimum-spanning tree of all MDR E. coli isolates of ST131. The figure illustrates the clonal relationship of all 39 MDR E. coli isolates of MLST ST131 of interval I in a minimum-spanning tree based on whole-genome sequencing. Each circle represents a single genotype, i.e., an allelic profile based on up to 2,325 target genes present in the isolates with the “pairwise ignoring missing values” option turned on in the SeqSphere+ software during comparisons. The circles are named with the isolate IDs and colored according to the ward, and the sizes are proportional to the number of isolates with identical genotypes. The number on connecting lines represents the number of alleles that differ between the connected genotypes.

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