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Research Article | Clinical Science and Epidemiology

Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae

Rebekah M. Martin, Jie Cao, Sylvain Brisse, Virginie Passet, Weisheng Wu, Lili Zhao, Preeti N. Malani, Krishna Rao, Michael A. Bachman
Mariana Castanheira, Editor
Rebekah M. Martin
aDepartment of Pathology, University of Michigan Medical School, Ann Arbor, Michigan, USA
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Jie Cao
aDepartment of Pathology, University of Michigan Medical School, Ann Arbor, Michigan, USA
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Sylvain Brisse
bInstitut Pasteur, Microbial Evolutionary Genomics, Paris, France
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Virginie Passet
bInstitut Pasteur, Microbial Evolutionary Genomics, Paris, France
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Weisheng Wu
cBRCF Bioinformatics Core, University of Michigan, Ann Arbor, Michigan, USA
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Lili Zhao
dDepartment of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
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Preeti N. Malani
eDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
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Krishna Rao
eDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
fSection of Infectious Diseases, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan, USA
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Michael A. Bachman
aDepartment of Pathology, University of Michigan Medical School, Ann Arbor, Michigan, USA
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  • ORCID record for Michael A. Bachman
Mariana Castanheira
JMI Laboratories
Roles: Editor
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DOI: 10.1128/mSphere.00261-16
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Figures

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  • FIG 1
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    FIG 1

    Study population. Adult patients in the University of Michigan Health System’s ICU and adult hematology/oncology patients were screened for colonization and extraintestinal infection with K. pneumoniae between July and October 2014 (n = 1,765), divided into “infected” and “not infected” groups, and further divided into “colonized” and “not colonized.” The number of infections by body site are shown in boxes; one colonized patient met case definitions for both pneumonia and UTI.

  • FIG 2
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    FIG 2

    Receiver operator characteristic curve for a multivariable model of risk factors for clinical infection. Multiple logistic regression of K. pneumoniae infection was used to generate a predictive model using five patient variables (Table 4). Bars and shaded areas of ROC curves represent bootstrapped 95% confidence intervals (10,000 replicates) for specificity at each level of sensitivity (AUC, 0.78; 95% CI, 0.72 to 0.84).

  • FIG 3
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    FIG 3

    Phylogenetic tree for wzi sequence of patient rectal swab isolates. Unique patients (P) are numbered (P1 to P40). A rectal swab (S) isolate is indicated after the patient number and immediately before the isolate number (e.g., S463 is stool isolate number 463). The isolate wzi type is indicated, and novel alleles are designated unknown by UK. A total of 110 rectal swab isolates from 40 unique patients were tested for strain type using wzi gene sequencing. A total of 43 different wzi types of strains were identified. Rectal swab isolates for patients with K. pneumoniae colonization prior to infection were all included in the analysis (P1 to P16; colored font). The scale bar represents the amount of genetic change; 0.01 equals 1 change per 100 nucleotide sites. The numbers next to each node are the percentage of iterations that recovered the same node.

  • FIG 4
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    FIG 4

    Core genome similarity between infecting and colonizing strains within patients. Patients who had concordant colonizing and infecting isolates based on wzi sequencing were further analyzed by WGS and core genome MLST and are represented by a unweighted pair group method using average linkages dendrogram along with isolate number, MLST type (ST), wzi type, and body site of culture (source). Each color represents an individual patient. Isolates 463 and 1946 (patient 1) were discordant by wzi and were included as a control.

Tables

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  • TABLE 1

    Demographic characteristics of patients with and without infection

    VariableNo. (%) or mean ± SDP valuea
    Infected (n = 39)No infection (n = 1,726)
    Female19 (48.7)835 (48.3)>0.99
    White race31 (79.5)1,438 (83.3)0.488
    Hispanic0 (0)33 (1.9)0.984
    Prior admit (28 days)27 (69.2)947 (54.8)0.079
    Length of stay (days)14.9 ± 14.911.6 ± 18.90.01
    Neurologic disorderb6 (15.4)109 (6.3)0.029
    Fluid and electrolyte disorderb20 (51.3)569 (33)0.019
    Renal diseaseb5 (12.8)286 (16.6)0.533
    Liver diseaseb5 (12.8)112 (6.5)0.123
    Alcohol abuseb1 (2.6)94 (5.4)0.442
    Solid organ tumorb13 (33.3)403 (23.3)0.151
    Diabetes mellitus, uncomplicatedb8 (20.5)242 (14)0.218
    K. pneumoniae colonization21 (53.8)385 (22.3)<0.001
    Central line before colonization27 (69.2)963 (55.8)0.099
    Antibiotic exposurec5 (12.8)453 (26.2)0.067
        Aminoglycoside0 (0)178 (10.3)0.984
        Fluoroquinolone0 (0)0 (0)NA
        Macrolide2 (5.1)151 (8.7)0.433
        Cephalosporin1 (2.6)139 (8.1)0.237
        Carbapenem0 (0)0 (0)NA
        Clindamycin2 (5.1)97 (5.6)0.895
    Age (yrs)62.7 ± 12.858.2 ± 16.10.078
    Hemoglobin, baseline (g/dl)10.4 ± 2.411.1 ± 2.50.062
    Platelets, baseline (×103/µl)167.9 ± 90.9207.3 ± 115.50.012
    Albumin, baseline (g/dl)3.3 ± 0.63.5 ± 0.60.009
    Body mass index (kg/m2)27 ± 6.729.5 ± 9.50.128
    • ↵a P values were obtained using Student’s t test for continuous variables and the chi-square or Fisher's exact test for categorical variables.

    • ↵b As defined by the Elixhauser index (35).

    • ↵c All classes combined, with receipt before colonization; selected individual classes are also listed.

  • TABLE 2

    Prior colonization with K. pneumoniae versus subsequent infection

    Infection statusNo. (%)
    colonized
    No. (%)
    not colonized
    TotalOR (95% CI)
    for infection
    P valuea
    Infection21 (5.2)18 (1.3)394.06 (2.14–7.7)<0.001
    No infection385 (94.8)1,341 (98.7)1,726
    Total406 (23)1,359 (77)1,765
    • ↵a Determined using the Fisher's exact test.

  • TABLE 3

    Association with prior colonization for each site of infection

    Site of infectionColonization frequency (%)OR (95% CI)P valuea
    InfectedNot infected
    Blood7/11 (64)399/1,754 (23)5.94 (1.73–20.41)0.005
    Respiratory8/15 (53)398/1,750 (23)3.88 (1.40–10.77)0.01
    Urine7/14 (50)399/1,751 (23)3.39 (1.18–9.72)0.024
    • ↵a P values were obtained using Fisher’s exact test.

  • TABLE 4

    Multiple logistic regression model of risk factors for infection

    VariableOR95% CIP value
    Colonized4.012.08–7.73<0.001
    Fluid and electrolyte disordera2.371.22–4.590.011
    Neurologic disordera3.311.28–8.540.013
    Prior admit (28 days)2.161.04–4.480.038
    Baseline platelet count/100 units (×103/µl)b0.730.53–1.010.058
    • ↵a As defined by the Elixhauser index (35).

    • ↵b For every 100-unit increase in baseline platelet count, the odds of infection was 0.73-fold lower.

Supplemental Material

  • Figures
  • Tables
  • Figure S1

    The wzi sequencing method has similar discriminatory power as MLST. Phylogenetic trees based on MLST results (a) and wzi sequencing results (b) are shown, each distinguishing 16 sequence types among 20 K. pneumoniae isolates. The scale bar represents the amount of genetic change. The numbers next to each node are the percentages of iterations that recovered the same node. Download Figure S1, TIF file, 0.2 MB.

    Copyright © 2016 Martin et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .

  • Figure S2

    Phylogenetic trees of rectal swab and infecting isolates based on wzi gene sequencing. Phylogenetic trees, built using the neighbor-joining method, for infecting and colonizing isolates from patients with BSI (a), pneumonia (PNA) (b), and UTI (c) are shown along with the fraction of patients with a concordant colonizing-infecting isolate pair. Unique patients are indicated by different colors and labeled as follows: patient number_ isolate number_wzi allele (unless a novel allele), _K-type (if known), where the isolate number prefixes indicate rectal swab (S), blood (B), respiratory (R), or urine (U). The scale bar represents the amount of genetic change. The numbers next to each node are the percentages of iterations that recovered the same node. Download Figure S2, PDF file, 1.1 MB.

    Copyright © 2016 Martin et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .

  • Figure S3

    Concordant colonizing-infecting isolate pairs show high core genome allelic similarity. The minimum-spanning tree based on the core genome MLST profiles, onto which the number of allelic differences between isolates, is indicated along the links. Note that the numbers are not additive, and that the tree should not be interpreted as depicting phylogenetic relationships. Isolate names are shown in bold. Each color represents an individual patient. Isolates 463 and 1946 (patient 1) were discordant by wzi and included as a control. cgMLST profiles of isolates within a single circle were totally identical. Download Figure S3, PDF file, 0.6 MB.

    Copyright © 2016 Martin et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .

  • Table S1

    Categorical agreement of colonizing-infecting isolate pairs in case patients. Download Table S1, DOCX file, 0.02 MB.

    Copyright © 2016 Martin et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .

  • Text S1

    wzi alleles used to construct phylogenetic trees. Download Text S1, DOC file, 0.1 MB.

    Copyright © 2016 Martin et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .

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Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae
Rebekah M. Martin, Jie Cao, Sylvain Brisse, Virginie Passet, Weisheng Wu, Lili Zhao, Preeti N. Malani, Krishna Rao, Michael A. Bachman
mSphere Oct 2016, 1 (5) e00261-16; DOI: 10.1128/mSphere.00261-16

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Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae
Rebekah M. Martin, Jie Cao, Sylvain Brisse, Virginie Passet, Weisheng Wu, Lili Zhao, Preeti N. Malani, Krishna Rao, Michael A. Bachman
mSphere Oct 2016, 1 (5) e00261-16; DOI: 10.1128/mSphere.00261-16
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    • ABSTRACT
    • INTRODUCTION
    • RESULTS
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KEYWORDS

Klebsiella
MLST
cgMLST
colonization
infection
pneumonia
whole-genome sequencing
wzi

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