Molecular Epidemiology of Colonizing and Infecting Isolates of Klebsiella pneumoniae.

Klebsiella pneumoniae is among the most common causes of hospital-acquired infections and has emerged as an urgent threat to public health due to carbapenem antimicrobial resistance. K. pneumoniae commonly colonizes hospitalized patients and causes extraintestinal infections such as urinary tract infection, bloodstream infection (septicemia), and pneumonia. If colonization is an intermediate step before infection, then detection and characterization of colonizing isolates could enable strategies to prevent or empirically treat K. pneumoniae infections in hospitalized patients. However, the strength of the association between colonization and infection is unclear. To test the hypothesis that hospitalized patients become infected with their colonizing strain, 1,765 patients were screened for rectal colonization with K. pneumoniae, and extraintestinal isolates from these same patients were collected over a 3-month period in a cohort study design. The overall colonization prevalence was 23.0%. After adjustment for other patient factors, colonization was significantly associated with subsequent infection: 21 of 406 (5.2%) colonized patients later had extraintestinal infection, compared to 18 of 1,359 (1.3%) noncolonized patients (adjusted odds ratio [OR], 4.01; 95% confidence interval, 2.08 to 7.73; P < 0.001). Despite a high diversity of colonizing isolates, 7/7 respiratory, 4/4 urinary, and 2/5 bloodstream isolates from colonized patients matched the patient corresponding rectal swab isolates, based on wzi capsular typing, multilocus sequence typing (MLST), and whole-genome sequence analysis. These results suggest that K. pneumoniae colonization is directly associated with progression to extraintestinal infection. IMPORTANCE K. pneumoniae commonly infects hospitalized patients, and these infections are increasingly resistant to carbapenems, the antibiotics of last resort for life-threatening bacterial infections. To prevent and treat these infections, we must better understand how K. pneumoniae causes disease and discover new ways to predict and detect infections. This study demonstrates that colonization with K. pneumoniae in the intestinal tract is strongly linked to subsequent infection. This finding helps to identify a potential time frame and possible approach for intervention: the colonizing strain from a patient could be isolated as part of a risk assessment, and antibiotic susceptibility testing could guide empirical therapy if the patient becomes acutely ill.

INTRODUCTION

Klebsiella pneumoniae is a Gram-negative bacillus and a member of the Enterobacteriaceae family. Klebsiella spp. are among the most common causes of hospital-acquired infections (HAIs) in the United States and are responsible for about 10% of all infections (1). K. pneumoniae commonly infects the urinary tract, respiratory tract, surgical sites, and the bloodstream and can cause severe diseases such as pneumonia and sepsis (2). Complicating treatment of K. pneumoniae infections is the recent emergence of strains encoding extended-spectrum β-lactamases (ESBLs) (3) and K. pneumoniae carbapenemases (KPCs) (4). Because of their high associated mortality and potential for rapid spread, the Centers for Disease Control and Prevention (CDC) has declared carbapenem-resistant Enterobacteriaceae (CRE) an urgent threat to public health (5). A 2012-2013 epidemiological study found the annual incidence of CRE in seven U.S. states was 2.93 per 100,000 people, with most cases found in individuals with underlying comorbidities or previous exposure to health care (6).

The major sources of K. pneumoniae that cause HAIs remain unclear. Intestinal colonization (7), the presence of K. pneumoniae in the environment, contaminated instruments (8), and healthcare workers’ hands (8, 9) have all been implicated in transmission. K. pneumoniae gastrointestinal colonization rates in hospitalized patients are estimated to be 20 to 38%, based largely on studies conducted before 1980 (2, 7, 10, 11), and a more recent study identified a 21.1% fecal carriage rate in healthy adults in Korea (12) with a high proportion of sequence type 23 (ST23) isolates that were associated with pyogenic liver abscess. Prior treatment with antimicrobials has been reported as a risk factor for colonization (7, 13, 14), but this factor may be specific for antimicrobial-resistant Klebsiella. Earlier work identified gastrointestinal colonization with K. pneumoniae as a reservoir for infection with K. pneumoniae (7), but such colonization may reflect the virulence potential of two predominant serotypes in the cohort. Regardless of transmission route, K. pneumoniae appears to be transmitted efficiently, as evidenced by reported outbreaks (15).

New techniques in molecular strain typing offer the opportunity to measure concordance among colonizing and infecting isolates of K. pneumoniae in patients. Repetitive sequence-based PCR (rep-PCR) has been widely used to characterize isolates of antibiotic-resistant K. pneumoniae (16–18). Multilocus sequence typing (MLST) has been used to characterize K. pneumoniae based on polymorphisms of seven conserved genes (rpoB, gapA, mdh, pgi, phoE, infB, and tonB) (19), and it is widely used as a common language for K. pneumoniae strain typing. Sequencing of the wzi gene is a rapid and inexpensive approach to differentiate K. pneumoniae capsular types (20). Recent studies reported that wzi sequencing has a similar discriminatory power to MLST (21–23), suggesting that wzi could be used as a rapid and inexpensive method to screen for genetic differences among strains. As probably the most discriminatory method, whole-genome sequencing (WGS) is even able to distinguish isolates from the same lineage evolving in a single patient (15). For K. pneumoniae, a core genome MLST scheme, based on WGS and 634 conserved genes, has been validated as a way to characterize strains in a systematic and reproducible manner. These new tools provide methods to both screen for strain differences and confirm strain concordance with the power of WGS (24).

The objective of this study was to test the hypothesis that intestinal colonization leads to subsequent infection with K. pneumoniae in hospitalized patients. To test this hypothesis, we determined the association and strain concordance between intestinal K. pneumoniae colonization and subsequent extraintestinal infections in a large cohort. The rationale for this study was that, if colonizing isolates are highly likely to cause disease, they can provide a focus for pathogenesis research and a potential window for infection prevention interventions.

RESULTS

Patient demographics.

During a 3-month period, 1,800 patients were screened for K. pneumoniae colonization by rectal swab culture; extraintestinal infection with K. pneumoniae among this group was assessed based on positive clinical cultures. After excluding 35 patients whose first rectal swabs were collected after their first positive K. pneumoniae isolate at an extraintestinal site, a total of 1,765 patients were included in subsequent analysis (Fig. 1). Of 77 patients with a positive blood, respiratory, or urine culture, 39 patients met case definitions of infection (11 cases of bloodstream infection [BSI], 15 pneumonia cases, and 14 with urinary tract infection [UTI]; 1 patient met case definitions for both pneumonia and a UTI). The demographic characteristics of patients with and without clinical infections are shown in Table 1. There were no significant differences in age, sex, or self-reported race/Hispanic ethnicity. Antibiotic exposure was numerically higher in the uninfected group (26.2% versus 12.8% of infected patients), but the difference did not reach statistical significance (P = 0.067). Neurologic disorders and fluid and electrolyte disorders were significantly more frequent in infected patients than in noninfected patients. Baseline albumin levels were significantly lower in the infected group (P = 0.009), and length of stay was significantly longer in the infected group (14.9 versus 11.6 days for uninfected; P = 0.01).

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.

TABLE 1 

Demographic characteristics of patients with and without infection

Variable	No. (%) or mean ± SD		P valuea
	Infected (n = 39)	No infection (n = 1,726)
Female	19 (48.7)	835 (48.3)	>0.99
White race	31 (79.5)	1,438 (83.3)	0.488
Hispanic	0 (0)	33 (1.9)	0.984
Prior admit (28 days)	27 (69.2)	947 (54.8)	0.079
Length of stay (days)	14.9 ± 14.9	11.6 ± 18.9	0.01
Neurologic disorderb	6 (15.4)	109 (6.3)	0.029
Fluid and electrolyte disorderb	20 (51.3)	569 (33)	0.019
Renal diseaseb	5 (12.8)	286 (16.6)	0.533
Liver diseaseb	5 (12.8)	112 (6.5)	0.123
Alcohol abuseb	1 (2.6)	94 (5.4)	0.442
Solid organ tumorb	13 (33.3)	403 (23.3)	0.151
Diabetes mellitus, uncomplicatedb	8 (20.5)	242 (14)	0.218
K. pneumoniae colonization	21 (53.8)	385 (22.3)	<0.001
Central line before colonization	27 (69.2)	963 (55.8)	0.099
Antibiotic exposurec	5 (12.8)	453 (26.2)	0.067
Aminoglycoside	0 (0)	178 (10.3)	0.984
Fluoroquinolone	0 (0)	0 (0)	NA
Macrolide	2 (5.1)	151 (8.7)	0.433
Cephalosporin	1 (2.6)	139 (8.1)	0.237
Carbapenem	0 (0)	0 (0)	NA
Clindamycin	2 (5.1)	97 (5.6)	0.895
Age (yrs)	62.7 ± 12.8	58.2 ± 16.1	0.078
Hemoglobin, baseline (g/dl)	10.4 ± 2.4	11.1 ± 2.5	0.062
Platelets, baseline (×103/µl)	167.9 ± 90.9	207.3 ± 115.5	0.012
Albumin, baseline (g/dl)	3.3 ± 0.6	3.5 ± 0.6	0.009
Body mass index (kg/m2)	27 ± 6.7	29.5 ± 9.5	0.128

P values were obtained using Student’s t test for continuous variables and the chi-square or Fisher's exact test for categorical variables.

As defined by the Elixhauser index (35).

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

Association of colonization with K. pneumoniae and infection.

Of the 1,765 patients analyzed, 406 (23%) were identified as colonized (Table 2). Of those colonized, 5.2% (n = 21) later developed infection with K. pneumoniae at an extraintestinal site, compared to only 1.3% (n = 18) of noncolonized patients (unadjusted odds ratio [OR], 4.06; 95% confidence interval [CI], 2.14 to 7.7; P < 0.0001). In terms of specific sites, colonization was significantly associated with BSI (OR, 5.94; 95% CI, 1.73 to 20.41; P = 0.005), pneumonia (OR, 3.88; 95% CI, 1.40 to 10.77; P =. 01), and UTI (OR, 3.39; 95% CI, 1.18 to 9.72; P = 0.024) (Table 3). For 20 of 21 colonized patients who became infected, colonization was detected on their initial rectal swab; 1 patient became positive on their second rectal swab 6 days later.

TABLE 2 

Prior colonization with K. pneumoniae versus subsequent infection

Infection status	No. (%)colonized	No. (%)not colonized	Total	OR (95% CI)for infection	P valuea
Infection	21 (5.2)	18 (1.3)	39	4.06 (2.14–7.7)	<0.001
No infection	385 (94.8)	1,341 (98.7)	1,726
Total	406 (23)	1,359 (77)	1,765

Determined using the Fisher's exact test.

TABLE 3 

Association with prior colonization for each site of infection

Site of infection	Colonization frequency (%)		OR (95% CI)	P valuea
	Infected	Not infected
Blood	7/11 (64)	399/1,754 (23)	5.94 (1.73–20.41)	0.005
Respiratory	8/15 (53)	398/1,750 (23)	3.88 (1.40–10.77)	0.01
Urine	7/14 (50)	399/1,751 (23)	3.39 (1.18–9.72)	0.024

P values were obtained using Fisher’s exact test.

In the final multivariable model, colonization with K. pneumoniae had the highest association with infection (all sites) after adjustment for other potential confounders (OR, 4.01; 95% CI, 2.08 to 7.73; P < 0.001) (Table 4). In addition, fluid and electrolyte disorder, neurologic disorder, and previous hospital admissions within the past 28 days were independently associated with infection. Low baseline platelet levels approached but did not reach significance (P = 0.058); however, this variable was retained, as it significantly improved the performance of the model (P = 0.046 for the likelihood ratio test) without significantly altering the other variables’ estimates. The area under the receiver-operator characteristic (AUROC) demonstrated acceptable performance of the model (0.78; 95% CI, 0.718 to 0.842) (Fig. 2), and the Hosmer-Lemeshow test did not indicate poor model fit (P = 0.135).

TABLE 4 

Multiple logistic regression model of risk factors for infection

Variable	OR	95% CI	P value
Colonized	4.01	2.08–7.73	<0.001
Fluid and electrolyte disordera	2.37	1.22–4.59	0.011
Neurologic disordera	3.31	1.28–8.54	0.013
Prior admit (28 days)	2.16	1.04–4.48	0.038
Baseline platelet count/100 units (×103/µl)b	0.73	0.53–1.01	0.058

As defined by the Elixhauser index (35).

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

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).

Concordance of colonizing and infecting isolate pairs based on molecular strain typing.

To determine if patients become infected with strains with which they were previously colonized, we first screened for genetic differences using wzi gene sequencing. Preliminary results from 17 patients indicated that wzi sequencing had a similar discriminatory power to MLST, with both distinguishing 16 sequence types among 20 isolates (see Fig. S1 in the supplemental material). In order to assess the diversity of strains with which patients were colonized, we determined the wzi types of colonizing isolates from 40 patients. Sixteen of these colonized patients had subsequent positive clinical cultures and met case definitions for BSI, pneumonia, or UTI; 24 patients did not. A total of 110 rectal swab isolates were tested; up to three isolates were obtained from each patient. From these 40 patients, only 8 patients had two wzi types detected, and no patients had three types within a sample. Despite the homogeneity within individual patients, 43 different wzi types were identified among these 40 patients, suggesting high genetic diversity of colonizing K. pneumoniae in this patient population (Fig. 3).

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.

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.

Of 21 colonized patients who developed infection, 16 sets of colonizing and infecting isolates were available for analysis. Two out of five patients with BSI (40%) had concordant pairs based on wzi sequencing of blood and rectal swab isolates. Respiratory and rectal swab isolates from patients with pneumonia (n = 7) demonstrated perfect concordance (7/7) (see Fig. S2 in the supplemental material). Although two patients with pneumonia were each colonized with 2 different wzi types, one was concordant with each patient’s respiratory isolate (stool isolate 1043 matched respiratory isolates 733 and 734, and stool isolate 1967 matched respiratory isolate 2005) (see Fig. S2). Analysis of urine and rectal swab isolates from patients with UTI (n = 4) also demonstrated perfect concordance (4/4).

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.

Despite high concordance of colonizing and infecting isolate pairs by wzi sequencing, using a single gene typing method may not be sufficient to determine true isolate concordance. To confirm that isolate pairs were the same strain, we performed WGS and determined isolate ST by both 7-gene MLST and 634-gene core genome multilocus sequence typing (cgMLST). We analyzed 13 preliminarily concordant pairs and one unmatched pair as a discordant control (pair 463/1946). MLST analysis showed perfect agreement with wzi sequence typing results in identifying 13 concordant pairs (Fig. 4). Two novel STs were identified, ST2359 and ST2360. For patients in whom one of two colonizing isolates matched the infecting isolate, MLST distinguished between the colonizing isolates and indicated that only one was concordant with the infecting isolate.

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.

The cgMLST method provides a more discriminatory approach to defining concordance, since it is based on allelic similarities of 634 K. pneumoniae genes (24). All concordant pairs, based on wzi and MLST analyses, also clustered together based on cgMLST (Fig. 4). The only pairs that did not group together were our discordant control, and the discordant colonizing isolates (numbers 1045 and 1968) from patients with another colonizing strain that matched the pneumonia isolates. These isolates were also discordant by wzi and MLST analyses. To measure the strength of cgMLST concordance of colonizing-infecting pairs within patients compared to between patients, a minimum spanning tree (see Fig. S3 in the supplemental material) was also generated based on the cgMLST data. For example, there were two allelic differences between stool isolate 1223 and pneumonia isolate 1317 in the same patient, while there were 189 allelic differences between these isolates and their closest neighbors from a different patient (pair 1319/868). Overall, there was an average of 2 allelic mismatches between concordant pairs (range, 0 to 7) and 449 allelic mismatches between patients (range, 189 to 629). Taken together, the wzi, MLST, and cgMLST data indicate that 100% of urinary and pneumonia isolates tested corresponded to the previously colonizing strain of K. pneumoniae.

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.

Categorical agreement of antimicrobial susceptibility of colonizing and infecting isolate pairs.

To measure antibiotic susceptibility agreement between concordant and discordant colonizing-infecting isolate pairs, we tested 17 antimicrobials active against Gram-negative bacteria and measured categorical agreement (CA) for susceptible (S), intermediate (I), or resistant (R) isolates based on MIC breakpoints (see Table S1 in the supplemental material) (25). CA was greater than 90% for all antimicrobials tested. However, this isolate collection had a low prevalence of antibiotic resistance. In 12 of 16 patients, both isolates were susceptible to all antimicrobials tested, including the 3 patients with discordant pairs based on sequence type. Two patients with concordant strain types had initially discordant susceptibility results. Only one discrepancy was reproducible by broth microdilution (trimethoprim-sulfamethoxazole in pair 1967/2005). The remaining 11 patients with concordant isolate pairs by sequence type had identical susceptibility patterns, including one ESBL K. pneumoniae isolate (pair 767/664).

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

DISCUSSION

The objective of this study was to examine the association between K. pneumoniae rectal colonization and subsequent extraintestinal K. pneumoniae infection. Based on data from 1,765 intensive care and hematology/oncology patients, we found that approximately 1 in 4 patients were rectal carriers of K. pneumoniae. We also observed a significant association between rectal K. pneumoniae colonization and subsequent infection, even after adjusting for patient variables. Furthermore, there was high concordance among colonizing isolates and subsequent infecting isolates, particularly for pneumonia and UTI, as measured by wzi, MLST, and cgMLST analyses. Taken together, these results implicate colonization as a critical step in the pathogenesis of hospital-acquired infections. These results also identify a possible window for intervention to decolonize patients or characterize their colonizing strain in order to predict risk of disease and inform empirical therapy if infection develops.

Our study has several strengths. First, whereas previous studies focused on drug-resistant K. pneumoniae or strains involved in outbreaks (26–28), we tested all isolates during a 3-month collection period across multiple wards and units in the hospital. This approach provided comprehensive information on K. pneumoniae colonization in the hospital setting and minimized potential selection bias. The large sample size (n = 1,765) provided sufficient power to examine the relationship between colonization and patients that met strict case definitions of infection. Second, we used wzi gene sequencing to rapidly screen for genetic differences between K. pneumoniae isolates (20). We then confirmed concordant pairs by using WGS-based MLST and cgMLST. In a hospital laboratory setting, wzi could be used to screen for a potential outbreak strain as a triage step before more costly WGS (20). Lastly, molecular strain typing indicated high K. pneumoniae strain diversity in our study population. Molecular epidemiology studies show clonal spread of carbapenem-resistant K. pneumoniae in the United States (28, 29). If a dominant clone existed in our population, it would obscure the true association between colonization and subsequent infection. In our diverse setting, the high concordance between colonizing and infecting strains suggests a robust pathogenic mechanism in which patients become infected by their colonizing strain.

This study also has some limitations. First, 35 patients with a positive clinical culture had unknown colonization status prior to the culture date and, thus, were excluded. By excluding this subset of data, we potentially lost cases of infection, and we cannot predict in which direction this would bias the results. Although we collected three rectal swab isolates per patient, most extraintestinal K. pneumoniae isolates provided by the clinical lab represented one isolate per site. It is possible that multiple strains may be present at an extraintestinal site but only one isolate was sampled. For wzi sequencing, rectal swab isolates from fewer than 10% of colonized patients were tested. Given 40 unique patients with 43 unique strains, almost every patient was colonized with a different strain. This high level of diversity is unlikely to be maintained in the larger sample set. A limitation of the susceptibility data was that the majority of isolates had no detectable acquired resistance. With a low diversity of resistance phenotypes, we were unable to rigorously test the agreement of susceptibility testing between colonizing isolates and subsequent infecting isolates in the same patient. Future studies should determine if high categorical agreement holds in a larger, more resistant colonized-infected patient population.

We conclude, based on three distinct methods, that there is high concordance between colonizing and infecting isolates, particularly for pneumonia and UTI. The discordance in bloodstream infections could be due to exogenous sources of K. pneumoniae, such as insertion of an intravenous catheter or a healthcare worker’s hands. The perfect concordance for UTI is consistent with the paradigm for Escherichia coli UTI, where fecal colonizing strains contaminate the urogenital tract (30). However, the perfect concordance between rectal isolates and pneumonia isolates was striking. This may indicate simultaneous colonization of the respiratory tract at the time of intestinal acquisition of the strain. This strong concordance suggests that infection prevention approaches or guidance of empirical therapies based on detection and characterization of colonizing K. pneumoniae isolates is feasible.

In addition to prior colonization, prior admission, low baseline platelets, and comorbidities of neurologic and fluid and electrolyte disorders were highly predictive of K. pneumoniae infection in a multivariable model. The association between healthcare exposure and subsequent infection is plausible, even after adjustment for colonization, since it likely indicates overall poor health status, itself a risk factor for infection. This is likely also true of the other comorbidities included in the final model. The components of this model include information readily available at admission as part of routine testing and chart review. If validated in an independent cohort, rectal screening paired with these variables could rapidly predict risk of K. pneumoniae infection.

The finding that patients often become infected with their colonizing strain has strong implications for both infection control and patient care interventions. A recent study in a long-term acute care hospital (LTACH) determined that interventions based on screening for KPC decreased both the colonization rate of patients as well as the rate of clinical infections (31). Moreover, characterization of colonizing strains could inform treatment decisions. Understanding the pathogenic mechanisms of progression from K. pneumoniae colonization to disease could enable novel diagnostics and therapeutics to prevent and rapidly treat these common nosocomial infections.

MATERIALS AND METHODS

Patient population and setting.

The study was conducted at the University of Michigan Health System (UMHS), a tertiary care hospital with more than 1,000 beds, in Ann Arbor, MI. Approval for this study was granted by the Institutional Review Board of the University of Michigan Medical School. During a 3-month period from 30 July to 31 October 2014, rectal swabs from 1,800 adult (≥18 years old) patients from the intensive care unit (ICU) or hematology/oncology wards were screened for K. pneumoniae. Concurrently, extraintestinal K. pneumoniae isolates were obtained from the clinical microbiology lab. A total of 1,765 patients had either a rectal swab performed prior to a positive clinical culture or a rectal swab and no positive clinical culture, and these patients were included for analysis of the association between colonization and subsequent infection. Patient demographic characteristics and clinical information was obtained through the electronic medical record (EMR).

Bacterial identification and growth conditions.

Rectal swabs were collected during the course of clinical care (upon unit admission, weekly, and at discharge) and were transported and stored in an ESwab transport system (BD, Franklin Lakes, NJ) at room temperature. Within 24 h of receipt, 1 µl of inoculated ESwab media was plated onto MacConkey agar (Remel, Lenexa, KS), streaked for quantification, and incubated for 18 to 24 h at 35°C. To ensure collection of the dominant clone in each sample, three mucoid lactose-fermenting (MLF) colonies were isolated as potential K. pneumoniae and subcultured onto blood agar plates (BAP; Remel, Lenexa, KS) (32). If fewer than three MLF colonies were present in a particular sample, all were subcultured. Bacterial identification was performed using matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) analysis. Isolates were stored at −80°C in Luria-Bertani (LB) broth containing 20% glycerol and were grown on either BAP or LB plates at 30°C overnight unless otherwise indicated.

Definitions.

In patients without K. pneumoniae infection, K. pneumoniae colonization was defined as a positive rectal swab culture for K. pneumoniae at any point during the hospital admission. For patients with K. pneumoniae infection, colonization was only considered positive if detected prior to the date of the documented infection. If a patient was identified as colonized on more than one date of collection, we used the first positive sample before infection for wzi sequencing, MLST, cgMLST, and antimicrobial susceptibility testing. Patient EMRs were reviewed for any positive culture for K. pneumoniae within 90 days of rectal swab culture. Bloodstream infection was defined as any positive blood culture for K. pneumoniae. Pneumonia was defined based on a positive K. pneumoniae respiratory culture and other Infectious Diseases Society of America (IDSA) diagnostic criteria (33). Patients with positive urine cultures were identified as cases based on the CDC National Healthcare Safety Network (NHSN) UTI case definitions (34). Patients not meeting a case definition of infection within 90 days of a rectal swab culture were considered uninfected. Comorbid disease definitions were extracted from the EMR based on ICD-9 and DRG codes as specified in the Elixhauser index (35). To ensure that we were capturing antibiotic exposure as a risk factor and not an outcome, this variable was constructed to ensure that exposure was present prior to colonization/infection. Exposure to an antibiotic was defined as true for patients without K. pneumoniae infection or colonization if administered at any point during the admission. For those patients with colonization, the antibiotic exposure variable was true if antibiotics were started at least 48 hours prior to the detected colonization. For those patients with infection but no preceding colonization, antibiotic exposure was positive if started at least 48 hours prior to documented infection.

wzi gene sequencing.

DNA preparation and PCR amplification were performed as described by Brisse et al. (20) with the following modifications: PCR products were diluted 1:20 in sterile water, and sequencing primers (wzi_for2 and wzi_rev) were diluted to 1 pM/µl prior to submission for Sanger sequencing. Forward and reverse chromatograms were assembled using Lasergene SeqMan (DNASTAR, Madison, WI). Complete alignment was done using ClustalX 2.1 (36). Initial phylogenetic trees were constructed using MEGA 6 (37) based on the neighbor-joining method (500 bootstrap replicates) and Jukes-Cantor distance. The wzi library obtained from Brisse et al. (20) was used as a reference in the current analysis.

Whole-genome sequencing and assembly.

Bacterial genomic DNA (gDNA) was purified using the UltraClean microbial DNA isolation kit (MoBio Laboratories, Inc., Carlsbad, CA). Purified gDNA was sent to the University of Michigan DNA Sequencing Core, where it was sheared (320 bp) and prepared as a multiplex library with unique bar codes for each sample. Whole-genome sequencing was performed using the HiSeq 4000 sequencing system (Illumina, San Diego, CA). Reads were preprocessed for each sample by trimming bases at both ends if the quality score was below 10, using Trimmomatic (v0.32) (38), removing read duplicates using FastUniq (39), and performing error correction using SOAPec (v2.01) (40). Preprocessed reads were assembled using VelvetOptimiser (v2.2.5). In this process, the reads were assembled by using Velvet (41) and a stepwise Kmer size at a step of 2, from 51 to 149 (for paired-end samples), or from 25 to 51 (for shared-end samples). The assembly with the largest N50 value was used for subsequent analysis.

MLST and cgMLST.

The gene sequences corresponding to the international MLST scheme of Institut Pasteur (19) were extracted from the genomic assemblies by using the BIGSdb platform (42) and the BLASTN algorithm, and the corresponding allelic number was defined by comparison with the reference nomenclature database (http://bigsdb.pasteur.fr/klebsiella). cgMLST was performed in the same way using the strict core genome MLST scheme defined by Bialek-Davenet et al. (24). Novel alleles and MLST profiles were submitted to the nomenclature database. MLST profiles were compared using the categorical mismatch method within BioNumerics version 6.6 (Applied-Maths, Sint-Martens Latem, Belgium). Uncalled alleles were not considered mismatches in pairwise profile comparisons.

Antimicrobial susceptibility testing.

Antimicrobial susceptibility testing was performed on the Vitek 2 automated system (bioMérieux, Marcy-l’Étoile, France), using AST-GN82 cards loaded per the manufacturer’s instructions. Isolates were grown on BAP at 37°C overnight. Colonizing and infecting isolates from the same patient were tested in the same batch. Susceptibility testing was performed on one rectal isolate for each patient. ESBL phenotypes were determined with the use of the Vitek 2 Advanced Expert System (AES). Pairs with discrepant results for any antibiotic were tested by Sensititre broth microdilution (Trek Diagnostics Systems, Oakwood Village, OH).

Statistical analyses.

Initial tests included examination of variables for out-of-range values, measures of central tendency/spread for continuous variables, and frequencies for categorical variables. These initial analyses assisted in constructing variables, including transformations (for example, length of stay was log transformed prior to analysis, given the nonnormal distribution). Initial bivariable analyses were conducted with Student’s t test for continuous variables and the chi-square or Fisher’s exact test for categorical variables. Based on these initial analyses, variables with a P value of <0.2 on bivariable tests were eligible for inclusion in the final multiple logistic regression model. This final model of K. pneumoniae infection was constructed via backwards elimination using a likelihood ratio test for variable retention, with a cutoff α of 0.05. Interactions between variables in the final model were tested and included if significant. Additional model regression assessments included the Hosmer-Lemeshow test for goodness of fit and calculation of the AUROC curve. For interpretation of the results, a P value of 0.05 was considered statistically significant for all analyses. The analyses were performed using SAS 9.3 (SAS Institute, Cary, NC) and R 3.2.2 (R Foundation for Statistical Computing, Vienna, Austria).

Accession number(s).

Whole-genome sequencing files have been deposited in the NCBI Sequence Read Archive (PRJNA341404) under accession numbers SAMN05722982, SAMN05722983, SAMN05722984, SAMN05722985, SAMN05722986, SAMN05722987, SAMN05722988, SAMN05722989, SAMN05722990, SAMN05722991, SAMN05722992, SAMN05722993, SAMN05722994, SAMN05722995, SAMN05722996, SAMN05722997, SAMN05722998, SAMN05722999, SAMN05723000, SAMN05723001, SAMN05723002, SAMN05723003, SAMN05723004, SAMN05723005, SAMN05723006, SAMN05723007, SAMN05723008, SAMN05723009, SAMN05723010, SAMN05723011, and SAMN05723012.

Sequences of wzi alleles used for strain comparison are included in Text S1 in the supplemental material. All other data are available upon request.

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