Detecting, mapping, and suppressing the spread of a decade-long Pseudomonas aeruginosa nosocomial outbreak with genomics
- Multidrug-Resistant Organism Repository and Surveillance Network (MRSN), Walter Reed Army Institute of Research, United States
- Department of Pathology, Brooke Army Medical Center, Joint Base San Antonio-Fort Sam Houston, United States
- Infection Prevention & Control, Brooke Army Medical Center, Joint Base San Antonio-Fort Sam Houston, United States
- Infectious Disease Service, Department of Medicine, Brooke Army Medical Center, Joint Base San Antonio Fort Sam Houston, United States
- Bacterial Disease Branch, Walter Reed Army Institute of Research, United States
Figures
Figure 1
Minimum spanning trees of P. aeruginosa core genome multilocus sequence typing (cgMLST).
Isolates are color-coded by facility, showing the 10 most prominent. (A) Includes all 5129 P. aeruginosa in the Multidrug-Resistant Organism Repository and Surveillance Network (MRSN’s) collection from 2011 to 2020. Clusters of isolates belonging to ST-235, -244, and -621 are indicated. (B) Includes all ST-621 isolates from 2011 to 2020. Genetic distances higher than 23 allelic differences are indicated.
Figure 2 with 2 supplements
Phylogenetic and spatiotemporal analysis of 253 clinical ST-621 P. aeruginosa isolates.
(A) Single nucleotide polymorphism (SNP)-based, core genome phylogeny. Outbreak subclones are colored with red (SC1) or blue (SC2) branches. From inner- to outermost, datasets show the year, the floor, the building, and the source of isolation. Patients with prolonged carriage (>1 year) are indicated. (B) Timeline of isolate collection. Each line indicates a single patient. Isolates are shown as dots colored by the floor the patient was on. Patients with prolonged carriage are highlighted. (C) Simplified floor plan of the Main (light blue) and Tower (dark blue) Buildings of Facility A. Wards and floors are numbered. For each floor, a pie chart indicates the proportion of isolates collected from urine, respiratory, or other cultures. Within each ward, isolates are colored by year of collection with a red outline indicating primary (first) isolates. Symbols indicate the presumed origin of infection. (D) Bar charts showing for each year the number of all P. aeruginosa primary clinical isolates collected at Facility A (bottom), the subset of genome-sequenced primary isolates (middle), and the subset of identified ST-621 isolates (top). Bars are color-coded by the isolation source. (E) Distribution of SNP distances for all inter-patient isolates or subsets collected in the same month, the same ward, or both. SNP distances within patient isolates are also indicated. Dotted lines indicate the local maxima.
Figure 2—figure supplement 1
Bar chart showing the distribution of single nucleotide polymorphism (SNP) distances for all inter-patient isolates.
For a given SNP distance (x-axis), the number of observed isolate pairs is plotted (y-axis). Raw data is available in Supplementary file 2.
Figure 2—figure supplement 2
Bar charts showing the percentage of sequenced P. aeruginosa isolates compared to the total collected by Hospital A stratified by year (2011–2020) and isolate types (respiratory, urine, or other).
Figure 3
Dated phylogeny of 253 ST-621 outbreak isolates.
Time-stamped phylogeny. Error bars for annotated nodes are shown as gray boxes. Years are indicated on the left, along with the opening of the Main Building (T1) and the Tower Building extension (T2). The most recent common ancestor (MRCA) of SC1 and SC2 is indicated in black text above the node. The MRCA of isolates from patients with prolonged carriage is shown in red, indicated by their patient ID. The predicted emergence of select variants is shown in blue. Data showing the floor and source isolates were collected from is shown, as in Figure 1. Select datasets are shown, including the antibiotic susceptibility testing results for cefepime (cephalosporin) and imipenem (carbapenem).
Figure 4
Identification of environmental reservoirs of the ST-621 outbreak clone in sink drains.
(A) Photos depict a swab from a sink drain in a patient room and the typical sink design (shallow basins and gooseneck faucets) in Facility A. (B) Minimum spanning tree of 326 Facility A ST-621 P. aeruginosa isolates, including contemporary isolates collected in 2021 and 2022 from clinical (n=56) and environmental (n=17) sources. Isolates from wards #1, 6, and 20 where environmental contamination was identified are colored. Environmental isolates are indicated with the letter E.
Figure 5
Antibiotic resistance and poly-variant sites of 253 outbreak isolates.
(A) Bar charts showing the proportion of clinical isolates resistant to tobramycin, cefepime, imipenem, and ciprofloxacin each year from 2011 to 2020. (B) Chart of mutations (excluding synonymous) in resistance-associated genes. Each block indicates one distinct mutation observed within the corresponding gene. Blocks are colored by the number of isolates sharing this exact mutation. Blocks are outlined to indicate whether the mutation is found within SC1, SC2, or isolates from both subclones. Mutations causing a predicted loss-of-function (LOF) are indicated with a star. (C) Pruned single nucleotide polymorphism (SNP)-based phylogeny showing the acquisition of colistin resistance in Patient 2. Patient ID, day of collection (since the first outbreak isolate), and available colistin MIC are shown on the right. The most recent common ancestor (MRCA) of the PhoQ E77fs mutation is indicated with a triangle.
Figure 6
Identification of pathoadaptive mutations.
(A) Distribution of COG functional categories for all genes (Ref) compared to the subset of genes (Sel) with two or more distinct mutated sites (excluding synonymous) in outbreak isolates. Significant enrichment in cell wall biogenesis and signal transduction categories is indicated. A positional chart of mutations across the entire chromosome of a closed reference genome for isolate 4605 is provided. The number of unique mutation sites within each gene is indicated (top), as well as the number of outbreak isolates which carried each mutation (bottom). Genes with three or more distinct mutated sites are labeled and genes involved in cell wall biogenesis and signal transduction genes are color-coded. (B) Accumulation of mutations (excluding synonymous) in genes and pathways associated with P. aeruginosa pathogenesis. Each block indicates one distinct mutation observed within a gene part of the indicated functional group (data available in Supplementary file 8). Blocks are colored by the number of isolates sharing this exact mutation. Blocks are outlined to indicate whether the mutation is found within SC1, SC2, or isolates from both subclones. Mutations causing a predicted loss-of-function (LOF) are indicated with a star.
Additional files
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Supplementary file 1
Isolate metadata.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp1-v1.xlsx
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Supplementary file 2
All-vs-all SNP comparison.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp2-v1.xlsx
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Supplementary file 3
Environmental isolates.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp3-v1.xlsx
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Supplementary file 4
Antibiotic susceptibility testing.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp4-v1.xlsx
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Supplementary file 5
Prediction of variants in outbreak isolates.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp5-v1.xlsx
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Supplementary file 6
Resistome reference intrinsic alleles.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp6-v1.xlsx
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Supplementary file 7
Mutations in intrinsic genes associated with antibiotic resistance.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp7-v1.xlsx
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Supplementary file 8
Mutations in functional groups or pathways.
- https://cdn.elifesciences.org/articles/93181/elife-93181-supp8-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/93181/elife-93181-mdarchecklist1-v1.docx
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Detecting, mapping, and suppressing the spread of a decade-long Pseudomonas aeruginosa nosocomial outbreak with genomics
eLife 13:RP93181.
https://doi.org/10.7554/eLife.93181.3
