Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing

Abstract

The Gram-negative bacteria Klebsiella pneumoniae is a major cause of nosocomial infections, primarily among immunocompromised patients. The emergence of strains resistant to carbapenems has left few treatment options, making infection containment critical. In 2011, the U.S. National Institutes of Health Clinical Center experienced an outbreak of carbapenem-resistant K. pneumoniae that affected 18 patients, 11 of whom died. Whole-genome sequencing was performed on K. pneumoniae isolates to gain insight into why the outbreak progressed despite early implementation of infection control procedures. Integrated genomic and epidemiological analysis traced the outbreak to three independent transmissions from a single patient who was discharged 3 weeks before the next case became clinically apparent. Additional genomic comparisons provided evidence for unexpected transmission routes, with subsequent mining of epidemiological data pointing to possible explanations for these transmissions. Our analysis demonstrates that integration of genomic and epidemiological data can yield actionable insights and facilitate the control of nosocomial transmission.

Fig. 1

Patient location and overlap during the outbreak. (A) Timeline of first positive cultures of the outbreak strain for the 18 affected patients. (B) Patient traces for each of the 18 patients shown in (A). Black lines, first positive culture; blue lines, medical ICU; yellow lines, cohorted areas; other colors represent specific wards at the NIH Clinical Center. (C)Graph of possible transmission links among patients. Patient IDs are within the circles. An arrow is present from one patient to another if the two patients overlapped in the same unit before the potential recipient culturing positive. Red links, the transmission event is predicted by the analysis reported here (see Fig. 3).

Fig. 2

SNVs identified in K. pneumoniae genomes. (A) DNA sequence variation among isolates taken from patient 1 while at the NIH Clinical Center is shown as a heat map, with isolates in chronological order on the y axis and variants on the x axis. Gray, ancestral K. pneumoniae alleles present in the previously sequenced NTUH-K2044 strain; black, variants found in at least one of the isolates. (B) Variants among all outbreak genomes are shown in a clustered heat map, with patients shown on the y axis and variable positions in their respective genomes on the x axis. Blue and green, the two major patient clusters identified on the basis of shared variants.

Fig. 3

Putative map of K. pneumoniae transmission during outbreak. The transmission map was constructed with genetic and patient trace data, as detailed in Materials and Methods. Nodes represent patients, and arrows indicate a transmission event directly or indirectly from one patient to another. Blue, cluster I; green, cluster II (fromFig.2B). Red arrows, opportunity for a direct transmission event from patients overlapping in the same ward before the recipient culturing positive; black arrows, transmission events that cannot be explained by patient overlap (may result from a more complicated transmission route or an intermediate patient or environmental source); dashed lines, at least one other equally parsimonious transmission link exists leading to the given patient.

Fig. 4

Patient trace for patients 1 and 4 and all patients who could have acted as transmission intermediates between them. Patient traces for the 1115 patients present in the hospital during the outbreak were mined to identify those patients whose location in the hospital could have allowed them to act as an intermediary in a transmission event between patients 1 and 4. Patients who overlapped with patient 1 after her arrival to the hospital and overlapped with patient 4 before his first positive culture were selected. The patient traces for patients 1 and 4 and the five patients (patients A to E) fitting the criteria of potential transmission intermediate are shown. Locations of patients in different hospital wards are indicated by different colors.