Skip to main content
Applied and Environmental Microbiology logoLink to Applied and Environmental Microbiology
. 2020 Mar 18;86(7):e02711-19. doi: 10.1128/AEM.02711-19

The ZKIR Assay, a Real-Time PCR Method for the Detection of Klebsiella pneumoniae and Closely Related Species in Environmental Samples

Elodie Barbier a,, Carla Rodrigues b, Geraldine Depret a, Virginie Passet b, Laurent Gal a, Pascal Piveteau a, Sylvain Brisse b,
Editor: Edward G Dudleyc
PMCID: PMC7082575  PMID: 32005732

The Klebsiella pneumoniae species complex Kp includes human and animal pathogens, some of which are emerging as hypervirulent and/or antibiotic-resistant strains. These pathogens are diverse and classified into seven phylogroups, which may differ in their reservoirs and epidemiology. Proper management of this public health hazard requires a better understanding of Kp ecology and routes of transmission to humans. So far, detection of these microorganisms in complex matrices such as food or the environment has been difficult due to a lack of accurate and sensitive methods. Here, we describe a novel method based on real-time PCR which enables detection of all Kp phylogroups with high sensitivity and specificity. We used this method to detect Kp isolates from environmental samples, and we show based on genomic sequencing that they differ in antimicrobial resistance and virulence gene content from human clinical Kp isolates. The ZKIR PCR assay will enable rapid screening of multiple samples for Kp presence and will thereby facilitate tracking the dispersal patterns of these pathogenic strains across environmental, food, animal and human sources.

KEYWORDS: Klebsiella, phylogroup, soil, detection, screening, ZKIR qPCR, culture method, environment

ABSTRACT

Klebsiella pneumoniae is of growing public health concern due to the emergence of strains that are multidrug resistant, virulent, or both. Taxonomically, the K. pneumoniae complex (“Kp”) includes seven phylogroups, with Kp1 (K. pneumoniae sensu stricto) being medically prominent. Kp can be present in environmental sources such as soils and vegetation, which could act as reservoirs of animal and human infections. However, the current lack of screening methods to detect Kp in complex matrices limits research on Kp ecology. Here, we analyzed 1,001 genome sequences and found that existing molecular detection targets lack specificity for Kp. A novel real-time PCR method, the ZKIR (zur-khe intergenic region) assay, was developed and used to detect Kp in 96 environmental samples. The results were compared to a culture-based method using Simmons citrate agar with 1% inositol medium coupled to matrix-assisted laser desorption ionization–time of flight mass spectrometry identification. Whole-genome sequencing of environmental Kp was performed. The ZKIR assay was positive for the 48 tested Kp reference strains, whereas 88 non-Kp strains were negative. The limit of detection of Kp in spiked soil microcosms was 1.5 × 10−1 CFU g−1 after enrichment for 24 h in lysogeny broth supplemented with ampicillin, and it was 1.5 × 103 to 1.5 × 104 CFU g−1 directly after soil DNA extraction. The ZKIR assay was more sensitive than the culture method. Kp was detected in 43% of environmental samples. Genomic analysis of the isolates revealed a predominance of phylogroups Kp1 (65%) and Kp3 (32%), a high genetic diversity (23 multilocus sequence types), a quasi-absence of antibiotic resistance or virulence genes, and a high frequency (50%) of O-antigen type 3. This study shows that the ZKIR assay is an accurate, specific, and sensitive novel method to detect the presence of Kp in complex matrices and indicates that Kp isolates from environmental samples differ from clinical isolates.

IMPORTANCE The Klebsiella pneumoniae species complex Kp includes human and animal pathogens, some of which are emerging as hypervirulent and/or antibiotic-resistant strains. These pathogens are diverse and classified into seven phylogroups, which may differ in their reservoirs and epidemiology. Proper management of this public health hazard requires a better understanding of Kp ecology and routes of transmission to humans. So far, detection of these microorganisms in complex matrices such as food or the environment has been difficult due to a lack of accurate and sensitive methods. Here, we describe a novel method based on real-time PCR which enables detection of all Kp phylogroups with high sensitivity and specificity. We used this method to detect Kp isolates from environmental samples, and we show based on genomic sequencing that they differ in antimicrobial resistance and virulence gene content from human clinical Kp isolates. The ZKIR PCR assay will enable rapid screening of multiple samples for Kp presence and will thereby facilitate tracking the dispersal patterns of these pathogenic strains across environmental, food, animal and human sources.

INTRODUCTION

Klebsiella pneumoniae is one of the leading causes of multidrug-resistant (MDR) health care-acquired infections, with increasing rates of resistance to carbapenems and other last resort antibiotics being reported (1, 2). Furthermore, is also an important agent of severe community-acquired infections (so-called “hypervirulent” strains) in healthy persons (3), with recent worrisome reports of convergence between hypervirulent and MDR phenotypes (1, 4). K. pneumoniae is recognized as a colonizer of the throat and the intestinal tract in humans and animals (57).

The main sources of human exposure to K. pneumoniae are not well defined. Previous studies highlighted the large distribution of K. pneumoniae in outdoor environments, including water, sewage, soil, and plants (813). Animal and human food, particularly retail meat or salad, may also be contaminated (6, 14, 15). Many studies suggest that food, water, and/or environmental exposure may be associated with virulent and/or antibiotic-resistant K. pneumoniae in humans (13, 14, 16, 17). However, little is known of the relative contributions of these different sources of transmission. Although such information is a prerequisite to control efficiently transmission routes and reduce exposure, the ecology of K. pneumoniae is currently poorly understood.

The systematics of K. pneumoniae has been refined through recent taxonomic updates, which highlighted the existence of seven phylogroups (phylogroup 1 [Kp1] to Kp7), corresponding to distinct taxa, within Klebsiella pneumoniae sensu lato. The K. pneumoniae species complex includes five different species: K. pneumoniae sensu stricto (Kp1), K. quasipneumoniae subsp. quasipneumoniae (Kp2) and subsp. similipneumoniae (Kp4), K. variicola subsp. variicola (Kp3) and subsp. tropica (Kp5), “K. quasivariicola” (Kp6), and K. africana (Kp7) (8, 1820). Most of these taxa are still often misidentified as “K. pneumoniae” or “K. variicola” due to the unsuitability of traditional clinical microbiology methods to distinguish among members of the Kp complex (21). Henceforth, we use the “Kp” abbreviation to refer collectively to the seven phylogroups of the K. pneumoniae species complex and will reserve “K. pneumoniae” for K. pneumoniae sensu stricto (i.e., phylogroup Kp1). Since all Kp organisms are potentially pathogenic for humans and animals and can share acquired resistance and virulence genes, it is important that the seven taxa be considered together when investigating the routes of transmission and ecology of Kp.

Detection of Kp is not well integrated in food or environmental microbiological surveillance programs, and there is a general lack of tools and procedures for its detection and quantification. Culture-based laboratory methods used for the detection of microorganisms in complex matrices are time-consuming and have a low throughput. Moreover, Kp culture methods have not been validated so far for food safety screening. Some molecular methods (without need of sequencing) have been proposed over the years for the rapid detection of Kp (2226). These organisms target the 16S-23S rRNA internal transcribed spacer sequence (ITS) (22), coding sequences of tyrB (26), khe (25, 27), chromosomal beta-lactamase (bla) genes (28, 29), or other molecular targets (23). Some of these targets are described as able to detect the Kp complex (22), whereas others were designed for specific members of the Kp complex, such as Kp1 and Kp3 (23, 24).

Real-time PCR is a powerful approach for the rapid detection and quantification of microorganisms in complex matrices (30). This approach presents multiple advantages, including easy standardization and high throughput. The aims of this work were (i) to define the phylogenetic distribution of previously proposed molecular targets for Kp detection, in light of recent taxonomic updates, and (ii) to develop a real-time PCR method for the rapid, specific and sensitive detection of all Kp members. (iii) In addition, we used a novel qPCR method to detect Kp in environmental samples and explored the genomic features (including antibiotic resistance and virulence genes) of the recovered Kp isolates.

RESULTS

Revisiting the phylogenetic distribution of proposed molecular targets for Kp detection.

Fourteen molecular targets were found in the literature (Fig. 1; Table 1 ) (2228, 31). Four of them were proposed to detect the Kp complex, while others were designed for specific members of this complex (K. pneumoniae, K. variicola, or K. quasipneumoniae; Table 1). Mapping of the presence or absence of the sequence region expected to be amplified by the primers was performed across Klebsiella phylogenetic diversity (Fig. 1). Regarding the targets proposed for the entire Kp complex, this in silico analysis revealed that only khe and tyrB (25, 26) presented both high sensitivity and high specificity. We further analyzed in silico the primers target sites for these two genes using primer blast. The results showed that khe primers would be expected to amplify the same region in Raoultella spp. (77 bp, with a sequence identity of the homologous region of <80%, and thus not visible on Fig. 1), as well as an additional region (348 bp) in these organisms. Furthermore, tyrB primers also appear to be able to amplify the target region in K. aerogenes and Raoultella spp., consistent with the distribution of the target region (Fig. 1). Regarding the targets that were proposed to be specific for Kp1, target KpI50233a (24) proved to be the most specific and sensitive one (although with ability to also amplify K. aerogenes isolates), whereas the ones proposed for Kp3 (23) appeared unspecific or to lack sensitivity in our in silico analysis (Fig. 1). Regarding the targeted chromosomal class A beta-lactamase genes blaSHV, blaOKP, and blaLEN (28), there appeared to be a lack of specificity (Fig. 1), which is explained by the high degree of sequence identity between these bla genes, even though they represent distinct targets. To clarify their distribution, we mapped the expected amplicon sequences of blaSHV, blaOKP, and blaLEN using a higher threshold (92%, defined based on observed sequence similarity within and between the three gene families) (see Fig. S1 in the supplemental material). Using this threshold, we observed a high degree of specificity of the three families for their respective phylogroup/species, as expected (32). However, it was evident that horizontal gene transfer events implicating the beta-lactamase genes have occurred. In particular, the blaSHV gene was often observed in non-Kp1 phylogroups (particularly Kp2 and Kp4) and even in species outside the Kp complex, such as E. coli or Salmonella spp. This can be attributed to the presence of blaSHV on plasmids and was previously described (21). The gene blaLEN was also observed in a few Kp1 genomes. These observations clearly render the use of the chromosomal beta-lactamase gene targets unreliable as phylogroup/species identification markers (Fig. S1).

FIG 1.

FIG 1

Phylogenetic distribution of the molecular targets for K. pneumoniae detection described in the literature. The ZKIR target sequence corresponds to target 15; other targets are given in Table 1. The inner circle colored sectors correspond to K. pneumoniae phylogroups or other Klebsiella species (see color key). Molecular targets were detected in the corresponding genomes using BLASTN with 80% nucleotide identity and 80% length coverage.

TABLE 1.

Molecular target sequences previously proposed for K. pneumoniae identificationa

Target Annotation Amplicon (bp) Targeted group Reference (PubMed ID)
16S-23S rRNA ITS tDNA-Ala 130 Kp complex 18579248
16S-23S rRNA ITS tDNA-Ala/23S rDNA 260 Kp complex 18579248
khe Hemolysin 77 Kp complex 19644019
tyrB Tyrosine aminotransferase 931 Kp complex 23357944
KpI50233a Putative acyltransferase 484 Kp1 25261063
KP878 Transferase 878 Kp1 25886267
KP888 Phosphohydrolase 888 Kp1 25886267
blaSHV Chromosomal SHV 995 Kp1 28139276
celB Cellobiose-specific PTS family enzyme IIC component 180 Kp1 31456171
KV770 Phosphoglycerate mutase 449 Kp3/5 25886267
KV1000 Thiopurine S-methyltransferase 499 Kp3/5 25886267
KV1615 N-Acetyltransferase 438 Kp3/5 25886267
blaLEN Chromosomal LEN 485 Kp3/5 28139276
blaOKP Chromosomal OKP 348 Kp2/4 28139276
ZKIR zur-khe intergenic region 78 Kp complex This study
a

ITS, internal transcribed spacer; PTS, phosphotransferase system; bla, beta-lactamase.

ZKIR primer design, PCR assay development, and optimization.

The tyrB and khe genes were previously proposed as targets for the specific detection of Kp (25, 26). As shown above, tyrB and khe targets were not totally specific for the Kp complex. We therefore attempted to define primers within the coding sequence of these genes but external to the previously proposed target fragments. However, a high identity was observed with non-Kp complex species when blasting the entire coding sequence (data not shown). Consequently, Kp complex-specific primers could not be designed within the coding sequence of these two genes.

Interestingly, investigation of sequences upstream of khe did reveal a sequence that was highly conserved within the Kp complex. This region located in the intergenic region (IR) upstream of khe is partly deleted in other species such as K. oxytoca and Raoultella spp. Since this 249-bp noncoding IR is located between zur (zinc uptake regulator) and khe (annotated as a putative hemolysin) genes (Fig. 2), it was named ZKIR for the zur-khe intergenic region.

FIG 2.

FIG 2

Genetic context of the ZKIR region on the genome of strain K. pneumoniae ATCC 13883T (GenBank accession number GCA_000742135.1) and detailed location of ZKIR primers and amplicon within the 249-bp region that is specific for the K. pneumoniae species complex (boxed area).

A pair of primers (ZKIR_F and ZKIR_R, Fig. 2) targeting the ZKIR region was designed and tested in silico. When implemented in the SYBR green PCR assay using reference strain ATCC 700603 (known as K. pneumoniae, but belonging in fact to K. quasipneumoniae subsp. similipneumoniae), these primers successfully amplified a 78-bp sequence, with a melting temperature of 80.3°C. Sequencing of PCR products confirmed amplification of the target sequence.

The sensitivity and specificity of the primers were experimentally tested on 2 ng of purified DNA of representatives of Kp phylogroups Kp1 to Kp7 (Table 2) and non-Kp strains. The ZKIR_F and ZKIR_R primers amplified the target sequence in all tested isolates of the Kp complex, with a threshold cycle (CT) value ranging from 13 to 26 and melting temperatures of 80.1 to 80.7°C. In contrast, when the ZKIR PCR was performed on 88 non-Kp isolates, no amplification was observed, showing that the PCR did not yield false positives. Late, nonspecific amplification was recorded with a few isolates in the last cycles of the reaction (i.e., after cycle 35), and the melting temperatures were clearly lower or higher than 80°C, indicating a nonspecific amplification. All assays performed on non-Kp samples can therefore be considered negative.

TABLE 2.

Bacterial strains tested to develop the ZKIR PCR assaya

Organism name (phylogroup) Strain Strain bank ID Country Isolation yr
K. pneumoniae (Kp1) SB4-2 SB1067 Netherlands 2002
ATCC 13883T SB132 NA NA
MGH 78578 SB107 NA 1994
None SB1139 Netherlands 2002
5-2 SB617 Netherlands 2000
04A025 SB20 France 1997
2-3 SB612 Netherlands 2000
BJ1-GA SB4496 France 2011
NA MIAE07651 France 2015
K. quasipneumoniae subsp. quasipneumoniae (Kp2) 01A030T SB11 Austria 1997
None SB1124 Netherlands 2002
U41 SB2110 Germany 1990
10A442 SB224 Italy 1998
99-1002 SB2478 Netherlands 1999
18A451 SB255 Spain 1998
11128 SB3445 NA NA
18A069 SB59 Spain 1997
Kleb Ali 0320584 SB98 NA NA
K. variicola subsp. variicola (Kp3) 01A065 SB1 Austria 1997
07A058 SB31 Germany 1997
IPEUC-1516 SB3278 France 1988
CIP 53.24 SB3295 NA NA
Ørskov 1756/51 SB3301 NA NA
F2R9T SB48 Mexico NA
6115 SB489 NA NA
Ørskov 4425/51 SB497 NA NA
Kp342 SB579 USA NA
K. quasipneumoniae subsp. similipneumoniae (Kp4) 09A323 SB164 Greece 1997
12A476 SB203 Netherlands 1998
07A044T SB30 Germany 1997
325 SB3233 France 1975
Ørskov 1303/50 SB3297 Turkey NA
Ørskov 4463/52 SB500 NA NA
CIP 110288 SB4697 China 2010
1-1 SB610 Netherlands 2000
K. variicola subsp. tropica (Kp5) Gal12 SB824 Mexico NA
CDC 4241-71 SB94 NA NA
885 SB5439 Madagascar 2016
1266T SB5531 Madagascar 2016
1283 SB5544 Madagascar 2016
1375 SB5610 Madagascar 2016
814 SB5387 Madagascar 2015
K. quasivariicola” (Kp6) 08A119 SB33 Germany 1997
10982 SB6071 USA 2005
01-467-2ECBU SB6094 Madagascar 2015
01-310A SB6095 Madagascar 2013
KPN1705T SB6096 USA 2014
K. africana (Kp7) 200023T SB5857 Senegal 2016
K. michiganensis (Ko1) CIP 110787T SB4934 USA 2010
05A071 SB71 France 1997
09A029 SB78 Greece 1997
K. grimontii (Ko6) 07A479 SB324 Germany 1998
06D090 SB352 France 1998
06D021T SB73 France 1997
K. oxytoca (Ko2) ATCC 13182T SB175 NA NA
02A067 SB131 Belgium 1997
NCTC 49131 SB136 NA NA
K. aerogenes None MIAE07652 France NA
CIP 60.86T SB3629 France NA
01A089 SB538 Austria 1997
02A002 SB539 Belgium 1997
R. terrigena ATCC 33257T SB170 NA NA
17C143 SB313 Spain 1998
V9813596 SB2796 Netherlands 1998
R. planticola 01A041 SB7 Austria 1997
ATCC 33531T SB174 NA NA
12C169 SB303 Netherlands 1998
R. ornithinolytica ATCC 31898 SB171 NA NA
A. calcoaceticus ATCC 14987 None USA NA
A. lwoffii None MIAE07654 France 1998
A. johnsonii ATCC 17909T None NA NA
A. pittii None MIAE07655 France 1998
A. caviae None MIAE07656 France NA
A. hydrophila None MIAE07657 France NA
A. tumefaciens C.58 MIAE07675 France 1996
A. faecalis None MIAE07658 France NA
B. cereus ATCC 53522 None USA NA
None MIAE07659 France NA
B. circulans None MIAE07660 France NA
B. megaterium None MIAE07661 France NA
B. subtilis None MIAE07662 France NA
E. hoshinae DSM 13771T None France NA
E. tarda DSM 30052T None USA NA
E. hafnia None MIAE07653 France NA
E. casseliflavus DSM 20680T None NA 1984
E. faecalis DSM 12956 None USA NA
DSM 20376 None NA NA
E. faecium DSM 25389 None Netherlands NA
DSM 6177 None NA NA
DSM 25644 None Georgia NA
DSM 25697 None South Korea NA
DSM 13590 None Germany NA
DSM 20477T None NA NA
E. gallinarum DSM 20628 None NA NA
E. hirae DSM 20160T None NA NA
E. raffinosus DSM 5633T None USA 1979
E. coli DSM 499 None NA NA
None MIAE02388 France 2015
None MIAE02376 France 2015
None MIAE02510 France 2015
None MIAE02381 France 2015
None MIAE02198 France 2015
H. alvei DSM 30163T None NA NA
L. monocytogenes ATCC BAA-679 (EGDe) None NA NA
DSM 15675 None NA NA
DSM 19094 None United Kingdom NA
L. innocua None MIAE07668 France 2018
M. morganii None MIAE07669 France NA
P. agglomerans DSM 3493T None Zimbabwe 1956
P. mirabilis None MIAE07670 France NA
P. vulgaris None MIAE07671 France NA
P. rettgeri None MIAE07672 France NA
P. stuartii None MIAE07673 France NA
P. brassicacearum DSM 13227T None France NA
P. fluorescens DSM 50106 None NA NA
P. gessardii CIP 105469T None France NA
P. jessenii CFBP4842 None France 1995
P. kilonensis DSM 13647T None Germany NA
P. libanenis DSM 17149T None Lebanon 1995
P. lini DSM 16768T None France NA
P. monteilii DSM 14164T None France 1990
P. putida ATCC 12633T None NA NA
P. rhodesiae DSM 14020T None France NA
P. thivervalensis CFBP5754 None France 2000
S. bongori DSM 13772T None NA NA
S. enterica DSM 554 None NA NA
S. enteritidis None Miae07674 France 2007
S. subterranea DSM 16208T None USA NA
S. fonticola DSM 4576T None NA NA
S. liquefaciens DSM 4487T None Ireland 1997
S. boydii DSM 7532T None India NA
S. aureus DSM 2569 None South Korea NA
S. capitis DSM 20326T None NA NA
S. epidermidis DSM 20044T None NA NA
S. maltophilia DSM 50170T None USA 1961
V. chagasii DSM 17138T None Norway NA
a

NA, information not available. A superscript “T” indicates a type strain. “SB” is an internal strain collection number of the Biodiversity and Epidemiology of Bacterial Pathogens unit, Institut Pasteur; MIAE, internal strain collection number of the UMR Agroecologie, INRA.

Analytical sensitivity of the ZKIR PCR.

PCRs were performed with quantities of genomic DNA of K. pneumoniae ATCC 13883T ranging from 7.5 ng (2.5 × 106 genomes) to 15 fg (5 genomes) (Fig. 3A and B). The linearity of the assay was evaluated by plotting the CT values against the log10 calculated genome number (calculated genome size is about 3.0 fg of DNA per cell, based on a 5.54 Mb K. pneumoniae genome). CT values were closely proportional to the logarithm of the genome number (R2 = 0.99) (Fig. 4). The sensitivity of the assay was determined as 15 genomes (45 fg) per reaction mix. No amplification was observed at the lower DNA concentration of 15 fg corresponding to five genomes.

FIG 3.

FIG 3

Amplification curves (A) and melting curve peaks (B) established using real-time PCR targeting the ZKIR region with serial dilutions of K. pneumoniae ATCC 13883T DNA. Triplicate values with DNA concentrations of 7.5 ng, 750 pg, 75 pg, 7.5 pg, and 750 fg are presented, but results with lower dilutions are not.

FIG 4.

FIG 4

Standard curve established using real-time ZKIR PCR with serial dilutions of K. pneumoniae ATCC 13883T DNA from 7.5 ng to 45 fg.

Analytical sensitivity of the ZKIR assay on soil samples.

In order to assess the performance of the ZKIR assay for detection of Kp directly from soil samples, two soils (A and V) were spiked with bacterial concentrations ranging from 1.5 × 10−1 CFU/g to 1.5 × 104 CFU/g. When soil samples were enriched in LB for 24 h and processed as described above, Kp was detected in all spiked microcosms except in two out of the three microcosms of soil A inoculated with the lowest Kp concentration. When the soil/LB suspension was tested prior to incubation, Kp was not detected in any of the spiked microcosms of soil V, whereas in soil A Kp could only be detected at the highest concentration (1.5 × 104 CFU/g). Finally, when the ZKIR assay was performed using purified metagenomic DNA from soil, positive results were only observed in microcosms spiked with 1.5 × 104 and 1.5 × 103 CFU/g in both soils, whereas no positive signal was observed at lower concentrations. The enrichment step thus appeared critical to reach high sensitivity.

Comparison of the ZKIR real-time PCR and culture-based methods for the detection of Kp in environmental samples.

After enrichment and ZKIR real-time PCR, Kp was detected in 41 of 96 (42.7%) assayed environmental samples, when the 1:10 dilution was used as template DNA (Table 3). When the 1:100 dilution was used, Kp was detected in a lower number of positive samples (38/96). The CT values were in the range 18.4 to 36.2. The 96 samples were processed in parallel with the culture-based method. Kp was not detected in any of the ZKIR-negative samples: when presumptive colonies were detected, they were always identified by matrix-assisted laser desorption ionization–time of flight mass spectroscopy (MALDI-TOF MS) as non-Kp and belonged to closely related species such as K. oxytoca, Raoultella spp., and Serratia spp. In contrast, Kp was isolated in 37 of the 41 ZKIR positive samples. These isolates were all identified as either K. pneumoniae or K. variicola by MALDI-TOF MS.

TABLE 3.

Comparison between ZKIR qPCR and culture results obtained using samples collected in Auxonne, France, between July and September 2018

Source Total no. of samples No. (%) of samples
qPCR positive Culture positive
Bulk soil 32 13 (40.6) 13 (40.6)
Roots 31 19 (61.3) 16 (51.6)
Leaves 29 8 (27.6) 7 (24.1)
Water 4 1 (25.0) 1 (25.0)
Total 96 41 (42.7) 37 (38.5)

Genomic characterization of 31 of these isolates (1 was contaminated, and 5 were not yet available) revealed a dominance of Kp1 (n = 20, 65%), followed by Kp3 (n = 10, 32%) and Kp4 (n = 1, 3%; see Table S1 in the supplemental material). Population diversity analysis based on multilocus sequence typing (MLST) (33) and core genome MLST (cgMLST) (24) revealed a high genotypic diversity, with 23 STs and 25 cgMLST types. In five cases, the strain detected in the soil was the same as the one present in the leaves and/or roots (e.g., SB6439 and SB6440; Table S1), showing colonization of several plant sites by the same strain. Only two isolates belonging to STs commonly found in the clinical settings were detected (ST37 and ST76). Interestingly, from the predicted O types, the O3 type represented 50% of Kp population, which contrasts with the nosocomial situation, where types O1 and O2 are dominant (2, 34), but not with human carriage, where the O3 type is also dominant (O3, 31%; O1, 19%; and O2, 17% [our unpublished results]). Also contrasting with the clinical epidemiology of Kp, a low level of antibiotic resistance and virulence genes was observed, with 93.5% of the strains presenting an ancestral “wild-type” susceptibility genotype (Table S1). The number of strains harboring plasmids detected in these environmental samples was also low (n = 9, 29%), as well as the number of plasmid-encoded heavy metal tolerance genes (mainly the silver and copper tolerance clusters). These results contrast with clinical and animal isolates, where plasmids and metal tolerance clusters are common (34; C. Rodrigues, unpublished results). As expected (1, 35), all Kp3 isolates harbored the nif cluster responsible for nitrogen fixation. Interestingly, the nif cluster was also present in one Kp1 isolate from soil (SB6181). The phylogenetic analysis (Fig. S2) of the nif cluster from our environmental isolates compared to a panel of reference strains (35) revealed that strain SB6181 (Kp1) branched within K. variicola strains (Kp3), showing that the nif cluster in this Kp1 strain was acquired via horizontal gene transfer from a K. variicola donor. Kp3 was also the inferred donor of the nif gene cluster for Kp5 and Kp6 nif-positive strains (Fig. S2).

DISCUSSION

Routes of transmission of ecologically generalist human pathogens are usually complex and poorly understood. Proper risk management requires a holistic approach which has been theorized as the “One Health concept” (36). Despite the fact that the number of human infections caused by members of the Kp complex are on the rise and are increasingly resistant to antimicrobial treatment (1, 37), the ecology of Kp remains poorly understood. Identification of the various habitats in which Kp strives and the routes of transmission to humans, for example, through specific types of food, is critical in order to limit exposure. Large-scale sampling is needed to define the sources of Kp contamination, and such surveys will require sensitive, reliable, and cost-efficient detection methods.

Several molecular assays for the detection and/or identification of Klebsiella from clinical or food and environmental samples have been previously proposed. These methods allow detecting mainly K. pneumoniae (sensu stricto) and K. variicola (Fig. 1). However, the Kp complex currently encompasses seven taxa. Our in silico analyses showed that some previously described PCR assays could be useful for the identification of phylogenetic subsets of the Kp complex (Kp150233a for Kp1, blaOKP for Kp2/Kp4, and blaLEN for Kp3/Kp5).

Given that all members of the Kp complex can cause infections in humans or animals, developing a novel method with the ability to detect the Kp complex by targeting exhaustively all currently known Kp phylogroups would be an important advance. Although several previous targets were designed for the entire Kp complex, they predate recent taxonomic advances and have therefore not been validated on the entire phylogenetic breadth of this bacterial group. Here, we found by in silico approaches that khe and tyrB assays lack specificity, which may negatively affect Kp detection efforts especially when testing microbiologically complex samples from the environment, such as soil.

We therefore aimed to develop a novel real-time PCR assay and used an intergenic region located adjacent to the previously proposed target gene khe. Using well-defined reference strains representative of current taxonomy (20, 38, 39), we show that the novel ZKIR PCR real-time assay allows the accurate detection of all members of the Kp complex. We found complete specificity and sensitivity (i.e., phylogenetic coverage) of this assay based on our reference strains panel. To improve analytical sensitivity, a 24-h enrichment culture followed by an easy, fast, and cost-effective sample processing was implemented prior to molecular detection using the ZKIR assay. This was necessary for complex matrices such as soil or sewage, where microbial diversity and abundance are high, in which case direct detection of one particular group of organisms, which might be present only at low abundance, is challenging. This procedure turned out to be sensitive enough to detect a single Kp bacterium in 5 g of soil. The ZKIR assay also appeared slightly more sensitive than the SCAI (Simmons citrate agar with 1% inositol) culture-based method, which is based on the ability of Klebsiella strains to utilize citrate and inositol, itself previously shown to be highly sensitive and to recover most Kp members (40, 41). Therefore, this fast and easy novel molecular method represents a powerful approach for screening large numbers of samples. This will spare the time-consuming handling of numerous presumptive colonies necessary for confirmation of their identification, given that K. oxytoca, Raoultella, Serratia, and Enterobacter are able to form colonies on SCAI agar, with morphological characteristics similar to Kp (40, 42). As such, the ZKIR protocol was significantly faster than culture, since results were available on average 26 h after sampling (24-h enrichment, sample treatment, and PCR), while up to 96 h were necessary when using the culture-based method (24-h enrichment, plate incubation, colony purification, and MALDI-TOF identification).

Interestingly, the implementation of the ZKIR PCR real-time assay evidenced a high (43%) detection rate of Kp from environmental samples, which represent niches that are still underexplored for Kp presence and biological characteristics. The high detection rate was largely confirmed by culture, suggesting a low rate of false positive qPCR results. This novel and original sampling strategy allowed us to explore the genomic features of environmental Kp populations. A strong contrast with Kp isolates typically recovered in the clinical setting was observed. First, a high genetic diversity was observed, with no predominant sublineage. This situation contrasts with MDR or hypervirulent Kp populations, from which frequent sublineages (so-called high-risk clones) are recovered. Second, environmental Kp isolates were almost devoid of antibiotic resistance and virulence genes, in conspicuous contrast with clinical samples (43). Finally, the genomic characteristics of environmental Kp isolates revealed interesting biological features, such as a frequent O3 O-antigen type and the horizontal transfer of nitrogen fixation gene cluster into Kp1, the main phylogroup associated with human infections. These data call for further studies into the biology of soil Kp isolates, which may reveal interesting novel adaptive strategies of this important generalist pathogen. Finally, our findings suggest that environmental Kp populations differ from clinical Kp populations, which implies indirect and possibly complex epidemiological links between environmental and clinical Kp. The ZKIR PCR real-time assay developed here is expected to enable future large-scale studies into this important question.

In conclusion, the ZKIR assay is a new tool for Kp detection that is highly specific, sensitive, reliable, and cost effective. To accelerate uptake of this method, the corresponding protocol was released publicly on protocols.io (https://doi.org/10.17504/protocols.io.7n6hmhe). This simple method can easily be implemented in laboratories equipped with real-time PCR thermocyclers (MedVetKlebs consortium, unpublished results). Using the ZKIR method after a short culture enrichment step greatly enhances sensitivity. As this rapid screen of samples allows one to focus only on ZKIR-positive samples for more labor-intensive downstream microbiological isolation and characterization, it is our hope that it will contribute to advance knowledge on the biology of environmental Kp and on the reservoirs and transmission routes of this increasingly important group of pathogens.

MATERIALS AND METHODS

Bacterial strains and culture conditions.

A panel of 136 strains from the collections of the Institut Pasteur (Paris, France) and INRA (Dijon, France) was used (Table 2). It included the K. pneumoniae type strain ATCC 13883T and 47 other strains of the Kp complex (the Kp1 to Kp7 phylogroups, including type strains) isolated from patients, animals and outdoor environments from multiple geographic locations. A total of 88 non-Kp bacterial strains from other species of the genus Klebsiella, closely related genera (Raoultella and Enterobacter), and other species that have similar environmental niches were included for comparison. All strains were regenerated by streaking on tryptone soy agar (TSA; Conda, Spain). After 24 h at 37°C, single colonies were transferred to 10 ml of tryptone soy broth (TSB; Conda). Bacterial suspensions were collected after 24 h of incubation at 37°C for further experiments.

Bacterial DNA extraction.

The bacterial DNA was extracted according to a homemade protocol. One milliliter of the 24-h bacterial culture was centrifuged (7,000 × g, 10 min, 4°C), and the pellet washed with sterile water and suspended in 800 μl of Tris (50 mM, pH 8) in which 10 μl of EDTA (500 mM, pH 8), 115 μl of lysozyme (10 mg/ml, incubation at 37°C for 30 min), 57 μl of 20% sodium dodecyl sulfate (incubation at 65°C for 15 min), 5 μl of RNase (10 mg/ml, incubation at 37°C for 30 min), and 23 μl of proteinase K (6 mg/ml, incubation at 37°C for 1 h and 30 min) were added. Finally, a 1:1 volume of phenol-chloroform-isoamyl alcohol (25/24/1) was added. The suspension was shaken 3 min at 15 rpm and then centrifuged 3 min at 20,000 × g. The supernatant was transferred in a new tube, and a 1:1 volume of chloroform/isoamyl alcohol (24/1) was added. After shaking (3 min, 25 rpm) and centrifugation (3 min, 20,000 × g), this step was repeated once. After transfer of the supernatant in a new tube, a 1:10 volume of NaCl (5 M) was added (shaking for 1 min at 15 rpm). Finally, a 1:1 volume of isopropanol (shaking for 3 min at 15 rpm) was added. Precipitated DNA filaments were collected with a glass Pasteur pipette and transferred in 400 μl frozen ethanol (70%). After shaking for 3 min at 15 rpm, DNA filaments were collected, dried at room temperature, and finally dissolved in 100 μl of TE (pH 8). The DNA concentration was estimated using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific) and adjusted at 20 ng/μl. Purified DNA was stored at –20°C.

A simpler protocol was implemented for the PCR specificity assay and validation study. Bacteria grown in TSB or enrichment medium were centrifuged 5 min at 13,000 × g. Pellets were suspended in 200 μl of Tris-HCl (5 mM, pH 8.2) supplemented with 13 μl of proteinase K (1 mg/ml). After 2 h of incubation at 55°C, proteinase K was inactivated during 10 min of boiling. The cell debris were discarded by centrifugation (5 min at 13,000 × g), and the supernatant was stored at – 20°C before use for real-time PCR.

Soil DNA extraction.

Soil metagenomic DNA was extracted from 2-g aliquots of soil using the modified ISO standard 11063 method (44). Crude soil DNA extracts were first purified onto PVPP (polyvinylpolypyrrolidone) minicolumns (Bio-Rad, France) and then with the GeneClean Turbo kit (MP Biomedicals, France) according to the manufacturer’s protocol (44). Purified DNA concentrations were determined using a NanoDrop 2000 spectrophotometer.

In silico identification of the target DNA region.

The phylogenetic distribution of molecular targets that were previously described in the literature for Kp detection, was investigated in silico. All available Kp genomes were downloaded from the NCBI database (n = 3,552, February 2018) and combined with the ones of Institut Pasteur’s internal reference collection (n = 670) (20, 38, 39), representing a total of 4,222 genomes, which included Klebsiella species and closely related Raoultella species. The average nucleotide identity (ANI) metric was used to classify the Kp genomes in each of the phylogroups. To avoid redundancy in the data set and due to the difficulty of analyzing phylogenetically 4,222 genomes, in the case of the genomes belonging to the Kp complex (which represented the majority of the data set), we selected unique representatives of each MLST sequence type (ST), as defined using the mlst software tool (https://github.com/tseemann/mlst). This resulted in a final collection of 1,001 genomes that were tested for the presence of targets from the literature. Nucleotide BLAST (BLASTN) was used to detect the presence of the target sequences in the 1,001 genomes, with 80% nucleotide identity (also with 92% in the case of blaSHV, blaOKP, and blaLEN targets) and 80% length coverage as cutoffs. Primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/) was used (with default parameters) to check the distribution of primer target sites in the genomic sequences. Specificity was defined as the proportion of target organisms among those expected to be amplified by the target assay. Sensitivity was defined as the proportion of target organisms expected to be amplified by the target assay. A phylogenetic tree was constructed (45), and the output was visualized using iTOL (https://itol.embl.de/; Fig. 1; see also Fig. S1 in the supplemental material).

Design of primers.

The Kp tyrB and khe gene sequences (accession numbers: AF074934.1 and AF293352.1) were aligned against the genome sequences of K. pneumoniae (CP012744.1, CP012743.1, and CP028787.1), K. variicola (CP008700.1, CP013985.1, and CP017289.1), K. quasipneumoniae (CP014071.1, CP023478.1, and CP029432.1), and K. quasivariicola (CP022823.1) using BLASTN to identify conserved genomic regions within the Kp complex. Sequences of closely related bacterial species K. oxytoca (CP027426.1), Raoultella ornithinolytica (CP010557.1), R. planticola (CP026047.1), and K. aerogenes (CP014029.2) were added in the alignments to confirm the specificity of these regions for the Kp complex.

Primer sets were designed using Primer3Plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi). The specificity of the predicted primer sets and amplicons was checked by applying BLASTN on the GenBank nucleotide collection (nr/nt) from the NCBI database, and Multiple Primer Analyzer (Thermo Fisher) was run to check for dimer formation. The best candidate primer sets defined by this in silico approach were ordered for synthesis at Eurogentec; among these was the primer pair ZKIR_F (5′-CTA-AAA-CCG-CCA-TGT-CCG-ATT-TAA-3′) and ZKIR_R (5′-TTC-CGA-AAA-TGA-GAC-ACT-TCA-GA–3′).

Real-time PCR.

All real-time PCR assays were performed on an ABI StepOne real-time thermocycler (Fisher Scientific, France) with the following temperature program: 95°C for 3 min and 40 cycles at 95°C 10 s and 60°C for 1 min. Melting curves were generated with temperature increments of 0.3°C per cycle from 60 to 95°C. DNA was amplified in a 20-μl PCR mix containing 10 μl of Takyon Low Rox SYBR MasterMix dTTP Blue (Eurogentec, Belgium), 2 μl of each primer (final concentrations, 300 nM), 2.5 μl of template DNA, and 3.5 μl of PCR-grade water. For the detection of Kp from environmental samples, 0.5 μl of T4 gene 32 protein (Sigma-Aldrich) was added to the PCR mix. The specificity and cross-reactivity of the ZKIR assay was evaluated with 2 ng of purified DNA of 48 Kp complex strains and 88 non-Kp isolates (Table 2).

Two universal primers targeting a 174-bp region of the 16S rRNA gene of Eubacteria, 341f (5′-CCT-ACG-GGA-GGC-AGC-AG-3′) and 515r (5′-ATT-CCG-CGG-CTG-GCA-3′), were used for positive-control PCRs, as described in a previous report (46).

Standard curve development and sensitivity assessment.

Aliquots (2.5 μl) adjusted to 7.5 ng, 750 pg, 75 pg, 7.5 pg, 750 fg, 375 fg, 45 fg, and 15 fg of genomic DNA of K. pneumoniae ATCC 13883T were prepared in triplicate and amplified using the optimized PCR conditions described above. The results were analyzed with the StepOne data analysis software, and the PCR efficiency was determined. The genome number expressed as a logarithm was plotted against CT values, and the correlation coefficient (R2) of the standard curve was calculated.

Comparison of the ZKIR PCR and culture methods for the detection of Kp in environmental samples.

Ninety-six environmental samples collected between July and September 2018 (23 in July, 39 in August, and 34 in September) in Auxonne (Burgundy, France) were analyzed for Kp presence using the ZKIR assay and culture methods in parallel. Samples corresponded to bulk soils (n = 32), roots (n = 44), leaves (n = 29), and irrigation water (n = 4) and were processed in the lab within 24 h after sampling. Then, 10-g samples of soil were weighed in 180-ml pots (Dutscher, France). Plant leaves and roots were properly cut, cleaned with sterile water, and transferred in 180-ml pots. Processed samples were suspended in 90 ml of lysogeny broth (LB; 5 g of NaCl, 5 g of yeast extract, and 10 g of tryptone for a 1-liter final volume) supplemented with ampicillin (10 mg/liter, ampicillin sodium salt; Sigma-Aldrich). Water samples (500 ml) were filtered through a 0.25-μm-pore-size membrane (Millipore, France). The membrane was incubated in 20 ml of LB supplemented with ampicillin as described above. After 24 h of incubation at 30°C, enrichments were vortexed, and 500-μl aliquots were centrifuged (5 min at 5,800 × g) and washed with sterile water. The pellet was suspended in 500 μl of sterile water and boiled for 10 min. Boiled enrichments were 10-fold diluted (1:10 and 1:100), and the dilutions were used as templates for real-time PCR.

In parallel, enrichments were serially diluted (1:10 to 1:10,000) in sterile water before plating on Simmons citrate agar enriched with 1% inositol (SCAI medium) (40). Plates were incubated 48 h at 37°C. Each plate was screened for presumptive colonies of Klebsiella (large, yellow, dome-shaped colonies), and ten candidate colonies were purified on SCAI medium and identified using MALDI-TOF MS (MALDI Biotyper; Bruker) according to the MALDI Biotyper Compass database, version 4.1.80 (Bruker Daltonics, Germany). In addition, whole-genome sequencing was performed for environmental Kp isolates (n = 31) using the NextSeq-500 sequencing platform (Nextera XT library; 2 × 150 nucleotides). Genomic assemblies were obtained using SPAdes v3.9. MLST and cgMLST were performed using the BIGSdb-Kp Web tool (https://bigsdb.pasteur.fr/klebsiella/klebsiella.html). This resource coupled with Kleborate (https://github.com/katholt/Kleborate) was used to search for antibiotic resistance, virulence, and heavy metal tolerance genes and to predict capsular types. PlasmidFinder was used to look for plasmid replicons (https://cge.cbs.dtu.dk/services/PlasmidFinder/). To construct the tree based on nif cluster genes (see Fig. S2 in the supplemental material), the DNA region between the nifQ and nifJ genes was extracted from the nif carrying strains and from a set of reference strains carrying this cluster (35). Sequences were aligned with MUSCLE, and IQ-TREE (http://iqtree.cibiv.univie.ac.at) was used to reconstruct the maximum likelihood phylogeny using the HKY+I+F+G4 model.

Determination of the limit of detection of the ZKIR assay in artificially spiked soils.

Two soils with contrasting edaphic characteristics (sandy soil A and clay soil V) and free of indigenous Kp, according to the procedure described above, were used. A bacterial suspension of K. pneumoniae ATCC 13883T was serially diluted in sterile water and dilutions were enumerated on TSA plates. Then, 5-g aliquots of each soil were spiked with these decreasing Kp dilutions, resulting in final concentrations from 1.5 × 104 to 1.5 × 10−1 CFU/g. Soil samples were prepared in triplicate with three independently grown inoculums at four dilutions (36 spiked microcosms for each soil). Negative controls were prepared by adding the same volume of sterile water (three microcosms for each soil). All 78 spiked and control soil microcosms were enriched for 24 h at 30°C in 45 ml of LB supplemented with ampicillin (10 mg/liter; Sigma-Aldrich). Next, 500-μl aliquots of enrichment broth were sampled before and after the 24-h enrichment step, centrifuged 5 min at 5,800 × g, and washed with sterile water. The pellet was suspended in 500 μl of sterile water and boiled for 10 min. Boiled enrichments were serially 10-fold diluted (1:10 to 1:100,000), and the diluted suspensions were used for real-time PCR. Moreover, metagenomic DNA was extracted from spiked soils as described above under “Soil DNA extraction.”

Data availability.

The detailed ZKIR qPCR operating procedure was made publicly accessible to the scientific community through the protocols.io platform (https://doi.org/10.17504/protocols.io.7n6hmhe). Genomic sequences generated in this study were submitted to the European Nucleotide Archive and are accessible under the BioProject number PRJEB34643.

Supplementary Material

Supplemental file 1
AEM.02711-19-s0001.pdf (3.5MB, pdf)
Supplemental file 2
AEM.02711-19-sd002.xlsx (21.3KB, xlsx)

ACKNOWLEDGMENTS

We thank Alexis Criscuolo for access to an early version of the JolyTree software tool, Julien Guglielmini for providing us access to in-house scripts for mapping the target genes, and Juan Sebastian Lopez Fernandes for assistance with genomic analyses.

This study is part of the MedVetKlebs project, a component of the One Health European Joint Program, and has thereby received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 773830.

Footnotes

Supplemental material is available online only.

REFERENCES

  • 1.Holt KE, Wertheim H, Zadoks RN, Baker S, Whitehouse CA, Dance D, Jenney A, Connor TR, Hsu LY, Severin J, Brisse S, Cao H, Wilksch J, Gorrie C, Schultz MB, Edwards DJ, Nguyen KV, Nguyen TV, Dao TT, Mensink M, Minh VL, Nhu NTK, Schultsz C, Kuntaman K, Newton PN, Moore CE, Strugnell RA, Thomson NR. 2015. Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health. Proc Natl Acad Sci U S A 112:E3574–E3581. doi: 10.1073/pnas.1501049112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.David S, Reuter S, Harris SR, Glasner C, Feltwell T, Argimon S, Abudahab K, Goater R, Giani T, Errico G, Aspbury M, Sjunnebo S, Koraqi A, Lacej D, Apfalter P, Hartl R, Glupczynski Y, Huang T-D, Strateva T, Marteva-Proevska Y, Andrasevic AT, Butic I, Pieridou-Bagatzouni D, Maikanti-Charalampous P, Hrabak J, Zemlickova H, Hammerum A, Jakobsen L, Ivanova M, Pavelkovich A, Jalava J, Österblad M, Dortet L, Vaux S, Kaase M, Gatermann SG, Vatopoulos A, Tryfinopoulou K, Tóth Á, Jánvári L, Boo TW, McGrath E, Carmeli Y, Adler A, Pantosti A, Monaco M, Raka L, Kurti A, Balode A, Saule M, Miciuleviciene J, Mierauskaite A, Perrin-Weniger M, Reichert P, Nestorova N, Debattista S, Mijovic G, Lopicic M, Samuelsen Ø, Haldorsen B, Zabicka D, Literacka E, Caniça M, Manageiro V, Kaftandzieva A, Trajkovska-Dokic E, Damian M, Lixandru B, Jelesic Z, Trudic A, Niks M, Schreterova E, Pirs M, Cerar T, Oteo J, Aracil B, Giske C, Sjöström K, Gür D, Cakar A, Woodford N, Hopkins K, Wiuff C, Brown DJ, Feil EJ, Rossolini GM, Aanensen DM, Grundmann H, The EuSCAPE Working Group, the ESGEM Study Group . 2019. Epidemic of carbapenem-resistant Klebsiella pneumoniae in Europe is driven by nosocomial spread. Nat Microbiol 4:1919–1929. doi: 10.1038/s41564-019-0492-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Ko W-C, Paterson DL, Sagnimeni AJ, Hansen DS, Von Gottberg A, Mohapatra S, Casellas JM, Goossens H, Mulazimoglu L, Trenholme G, Klugman KP, McCormack JG, Yu VL. 2002. Community-acquired Klebsiella pneumoniae bacteremia: global differences in clinical patterns. Emerg Infect Dis 8:160–166. doi: 10.3201/eid0802.010025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Zhang Y, Zeng J, Liu W, Zhao F, Hu Z, Zhao C, Wang Q, Wang X, Chen H, Li H, Zhang F, Li S, Cao B, Wang H. 2015. Emergence of a hypervirulent carbapenem-resistant Klebsiella pneumoniae isolate from clinical infections in China. J Infect 71:553–560. doi: 10.1016/j.jinf.2015.07.010. [DOI] [PubMed] [Google Scholar]
  • 5.Gorrie CL, Mirčeta M, Wick RR, Edwards DJ, Thomson NR, Strugnell RA, Pratt NF, Garlick JS, Watson KM, Pilcher DV, McGloughlin SA, Spelman DW, Jenney AWJ, Holt KE. 2017. Gastrointestinal carriage is a major reservoir of Klebsiella pneumoniae infection in intensive care patients. Clin Infect Dis 65:208–215. doi: 10.1093/cid/cix270. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Brisse S, Grimont F, Grimont P. 2006. The genus Klebsiella, p 159–196. In Dworkin M, Falkow S, Rosenberg E, Schleifer K-H, Stackebrandt E (ed), The prokaryotes. Springer, New York, NY. [Google Scholar]
  • 7.Munoz MA, Ahlström C, Rauch BJ, Zadoks RN. 2006. Fecal shedding of Klebsiella pneumoniae by dairy cows. J Dairy Sci 89:3425–3430. doi: 10.3168/jds.S0022-0302(06)72379-7. [DOI] [PubMed] [Google Scholar]
  • 8.Rosenblueth M, Martínez L, Silva J, Martínez-Romero E. 2004. Klebsiella variicola, a novel species with clinical and plant-associated isolates. Syst Appl Microbiol 27:27–35. doi: 10.1078/0723-2020-00261. [DOI] [PubMed] [Google Scholar]
  • 9.Lee D-Y, Shannon K, Beaudette LA. 2006. Detection of bacterial pathogens in municipal wastewater using an oligonucleotide microarray and real-time quantitative PCR. J Microbiol Methods 65:453–467. doi: 10.1016/j.mimet.2005.09.008. [DOI] [PubMed] [Google Scholar]
  • 10.Benami M, Gross A, Herzberg M, Orlofsky E, Vonshak A, Gillor O. 2013. Assessment of pathogenic bacteria in treated graywater and irrigated soils. Sci Total Environ 458-460:298–302. doi: 10.1016/j.scitotenv.2013.04.023. [DOI] [PubMed] [Google Scholar]
  • 11.Barati A, Ghaderpour A, Chew L, Bong C, Thong K, Chong V, Chai L. 2016. Isolation and characterization of aquatic-borne Klebsiella pneumoniae from tropical estuaries in Malaysia. Int J Environ Res Public Health 13:426. doi: 10.3390/ijerph13040426. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Falomir MP, Gozalbo D, Rico H. 2010. Coliform bacteria in fresh vegetables: from cultivated lands to consumers, p 1175–1181. In Mendez-Vilas A. (ed), Current research, technology, and education: topics in applied microbiology and microbial biotechnology, vol 2 Formatex Research Center, Badajoz, Spain. [Google Scholar]
  • 13.Podschun R, Pietsch S, Holler C, Ullmann U. 2001. Incidence of Klebsiella species in surface waters and their expression of virulence factors. Appl Environ Microbiol 67:3325–3327. doi: 10.1128/AEM.67.7.3325-3327.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Davis GS, Waits K, Nordstrom L, Weaver B, Aziz M, Gauld L, Grande H, Bigler R, Horwinski J, Porter S, Stegger M, Johnson JR, Liu CM, Price LB. 2015. Intermingled Klebsiella pneumoniae populations between retail meats and human urinary tract infections. Clin Infect Dis 61:892–899. doi: 10.1093/cid/civ428. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zadoks RN, Griffiths HM, Munoz MA, Ahlstrom C, Bennett GJ, Thomas E, Schukken YH. 2011. Sources of Klebsiella and Raoultella species on dairy farms: be careful where you walk. J Dairy Sci 94:1045–1051. doi: 10.3168/jds.2010-3603. [DOI] [PubMed] [Google Scholar]
  • 16.Runcharoen C, Moradigaravand D, Blane B, Paksanont S, Thammachote J, Anun S, Parkhill J, Chantratita N, Peacock SJ. 2017. Whole-genome sequencing reveals high-resolution epidemiological links between clinical and environmental Klebsiella pneumoniae. Genome Med 9:6. doi: 10.1186/s13073-017-0397-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Davis GS, Price LB. 2016. Recent research examining links among Klebsiella pneumoniae from food, food animals, and human extraintestinal infections. Curr Environ Health Rep 3:128–135. doi: 10.1007/s40572-016-0089-9. [DOI] [PubMed] [Google Scholar]
  • 18.Brisse S, Passet V, Grimont P. 2014. Description of Klebsiella quasipneumoniae sp. nov., isolated from human infections, with two subspecies, Klebsiella quasipneumoniae subsp. quasipneumoniae subsp. nov. and Klebsiella quasipneumoniae subsp. similipneumoniae subsp. nov., and demonstration that Klebsiella singaporensis is a junior heterotypic synonym of Klebsiella variicola. Int J Syst Evol Microbiol 64:3146–3152. doi: 10.1099/ijs.0.062737-0. [DOI] [PubMed] [Google Scholar]
  • 19.Long SW, Linson SE, Ojeda Saavedra M, Cantu C, Davis JJ, Brettin T, Olsen RJ. 2017. Whole-genome sequencing of a human clinical isolate of the novel species Klebsiella quasivariicola sp. nov. Genome Announc 5:e01057-17. doi: 10.1128/genomeA.01057-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Rodrigues C, Passet V, Rakotondrasoa A, Diallo TA, Criscuolo A, Brisse S. 2019. Description of Klebsiella africanensis sp. nov., Klebsiella variicola subsp. tropicalensis subsp. nov. and Klebsiella variicola subsp. variicola subsp. nov. Res Microbiol 170:165–170. doi: 10.1016/j.resmic.2019.02.003. [DOI] [PubMed] [Google Scholar]
  • 21.Long SW, Linson SE, Ojeda Saavedra M, Cantu C, Davis JJ, Brettin T, Olsen RJ. 2017. Whole-genome sequencing of human clinical Klebsiella pneumoniae isolates reveals misidentification and misunderstandings of Klebsiella pneumoniae, Klebsiella variicola, and Klebsiella quasipneumoniae. mSphere 2:e00290-17. doi: 10.1128/mSphereDirect.00290-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Liu Y, Liu C, Zheng W, Zhang X, Yu J, Gao Q, Hou Y, Huang X. 2008. PCR detection of Klebsiella pneumoniae in infant formula based on 16S–23S internal transcribed spacer. Int J Food Microbiol 125:230–235. doi: 10.1016/j.ijfoodmicro.2008.03.005. [DOI] [PubMed] [Google Scholar]
  • 23.Garza-Ramos U, Silva-Sánchez J, Martínez-Romero E, Tinoco P, Pina-Gonzales M, Barrios H, Martínez-Barnetche J, Gómez-Barreto RE, Tellez-Sosa J. 2015. Development of a multiplex-PCR probe system for the proper identification of Klebsiella variicola. BMC Microbiol 15:64. doi: 10.1186/s12866-015-0396-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Bialek-Davenet S, Criscuolo A, Ailloud F, Passet V, Nicolas-Chanoine M-H, Decré D, Brisse S. 2014. Development of a multiplex PCR assay for identification of Klebsiella pneumoniae hypervirulent clones of capsular serotype K2. J Med Microbiol 63:1608–1614. doi: 10.1099/jmm.0.081448-0. [DOI] [PubMed] [Google Scholar]
  • 25.Yin-Ching C, Jer-Horng S, Ching-Nan L, Ming-Chung C. 2002. Cloning of a gene encoding a unique haemolysin from Klebsiella pneumoniae and its potential use as a species-specific gene probe. Microb Pathog 33:1–6. doi: 10.1006/mpat.2002.0499. [DOI] [PubMed] [Google Scholar]
  • 26.Jeong E-S, Lee K-S, Heo S-H, Seo J-H, Choi Y-K. 2013. Rapid identification of Klebsiella pneumoniae, Corynebacterium kutscheri, and Streptococcus pneumoniae using triplex polymerase chain reaction in rodents. Exp Anim 62:35–40. doi: 10.1538/expanim.62.35. [DOI] [PubMed] [Google Scholar]
  • 27.Hartman LJ, Selby EB, Whitehouse CA, Coyne SR, Jaissle JG, Twenhafel NA, Burke RL, Kulesh DA. 2009. Rapid real-time PCR assays for detection of Klebsiella pneumoniae with the rmpA or magA genes associated with the hypermucoviscosity phenotype. J Mol Diagn 11:464–471. doi: 10.2353/jmoldx.2009.080136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Fonseca EL, Ramos NDV, Andrade BGN, Morais L, Marin MFA, Vicente A. 2017. A one-step multiplex PCR to identify Klebsiella pneumoniae, Klebsiella variicola, and Klebsiella quasipneumoniae in the clinical routine. Diagn Microbiol Infect Dis 87:315–317. doi: 10.1016/j.diagmicrobio.2017.01.005. [DOI] [PubMed] [Google Scholar]
  • 29.Singh K, Mangold KA, Wyant K, Schora DM, Voss B, Kaul KL, Hayden MK, Chundi V, Peterson LR. 2012. Rectal screening for Klebsiella pneumoniae carbapenemases: comparison of real-time PCR and culture using two selective screening agar plates. J Clin Microbiol 50:2596–2600. doi: 10.1128/JCM.00654-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Bilodeau G. 2011. Quantitative polymerase chain reaction for the detection of organisms in soil. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour 6:014. [Google Scholar]
  • 31.Tian Y, Wang L, Zhang J, Han Q, Xia X, Song Y, Yang G. 2019. CelB is a suitable marker for rapid and specific identification of Klebsiella pneumoniae by the loop-mediated isothermal amplification (LAMP) assay. Braz J Microbiol 50:961–967. doi: 10.1007/s42770-019-00144-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Haeggman S, Lofdahl S, Paauw A, Verhoef J, Brisse S. 2004. Diversity and evolution of the class a chromosomal beta-lactamase gene in Klebsiella pneumoniae. Antimicrob Agents Chemother 48:2400–2408. doi: 10.1128/AAC.48.7.2400-2408.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Diancourt L, Passet V, Verhoef J, Grimont PAD, Brisse S. 2005. Multilocus sequence typing of Klebsiella pneumoniae nosocomial isolates. J Clin Microbiol 43:4178–4182. doi: 10.1128/JCM.43.8.4178-4182.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Follador R, Heinz E, Wyres KL, Ellington MJ, Kowarik M, Holt KE, Thomson NR. 2016. The diversity of Klebsiella pneumoniae surface polysaccharides. Microb Genom 2:e000073. doi: 10.1099/mgen.0.000073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Blin C, Passet V, Touchon M, Rocha EPC, Brisse S. 2017. Metabolic diversity of the emerging pathogenic lineages of Klebsiella pneumoniae: metabolic diversity of Klebsiella pneumoniae. Environ Microbiol 19:1881–1898. doi: 10.1111/1462-2920.13689. [DOI] [PubMed] [Google Scholar]
  • 36.King LJ, Anderson LR, Blackmore CG, Blackwell MJ, Lautner EA, Marcus LC, Meyer TE, Monath TP, Nave JE, Ohle J, Pappaioanou M, Sobota J, Stokes WS, Davis RM, Glasser JH, Mahr RK. 2008. Executive summary of the AVMA One Health Initiative Task Force report. J Am Vet Med Assoc 233:259–261. doi: 10.2460/javma.233.2.259. [DOI] [PubMed] [Google Scholar]
  • 37.Nordmann P, Naas T, Poirel L. 2011. Global spread of carbapenemase-producing Enterobacteriaceae. Emerg Infect Dis 17:1791–1798. doi: 10.3201/eid1710.110655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Rodrigues C, Passet V, Rakotondrasoa A, Brisse S. 2018. Identification of Klebsiella pneumoniae, Klebsiella quasipneumoniae, Klebsiella variicola, and related phylogroups by MALDI-TOF mass spectrometry. Front Microbiol 9:3000. doi: 10.3389/fmicb.2018.03000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Passet V, Brisse S. 2018. Description of Klebsiella grimontii sp. nov. Int J Syst Evol Microbiol 68:377–381. doi: 10.1099/ijsem.0.002517. [DOI] [PubMed] [Google Scholar]
  • 40.Van Kregten E, Westerdaal NAC, Willers J. 1984. New, simple medium for selective recovery of Klebsiella pneumoniae and Klebsiella oxytoca from human feces. J Clin Microbiol 20:6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Passet V, Brisse S. 2015. Association of tellurite resistance with hypervirulent clonal groups of Klebsiella pneumoniae. J Clin Microbiol 53:1380–1382. doi: 10.1128/JCM.03053-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Ohtomo R, Saito M. 2003. A new selective medium for detection of Klebsiella from dairy environments. Microb Environ 18:138–144. doi: 10.1264/jsme2.18.138. [DOI] [Google Scholar]
  • 43.Wyres KL, Holt KE. 2016. Klebsiella pneumoniae population genomics and antimicrobial-resistant clones. Trends Microbiol 24:944–956. doi: 10.1016/j.tim.2016.09.007. [DOI] [PubMed] [Google Scholar]
  • 44.Plassart P, Terrat S, Thomson B, Griffiths R, Dequiedt S, Lelievre M, Regnier T, Nowak V, Bailey M, Lemanceau P, Bispo A, Chabbi A, Maron P-A, Mougel C, Ranjard L. 2012. Evaluation of the ISO standard 11063 DNA extraction procedure for assessing soil microbial abundance and community structure. PLoS One 7:e44279. doi: 10.1371/journal.pone.0044279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Criscuolo A. 2019. A fast alignment-free bioinformatics procedure to infer accurate distance-based phylogenetic trees from genome assemblies. Res Ideas Outcomes 5:e36178. doi: 10.3897/rio.5.e36178. [DOI] [Google Scholar]
  • 46.López-Gutiérrez JC, Henry S, Hallet S, Martin-Laurent F, Catroux G, Philippot L. 2004. Quantification of a novel group of nitrate-reducing bacteria in the environment by real-time PCR. J Microbiol Methods 57:399–407. doi: 10.1016/j.mimet.2004.02.009. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental file 1
AEM.02711-19-s0001.pdf (3.5MB, pdf)
Supplemental file 2
AEM.02711-19-sd002.xlsx (21.3KB, xlsx)

Data Availability Statement

The detailed ZKIR qPCR operating procedure was made publicly accessible to the scientific community through the protocols.io platform (https://doi.org/10.17504/protocols.io.7n6hmhe). Genomic sequences generated in this study were submitted to the European Nucleotide Archive and are accessible under the BioProject number PRJEB34643.


Articles from Applied and Environmental Microbiology are provided here courtesy of American Society for Microbiology (ASM)

RESOURCES