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Frontiers in Cellular and Infection Microbiology logoLink to Frontiers in Cellular and Infection Microbiology
. 2020 Feb 28;10:85. doi: 10.3389/fcimb.2020.00085

Molecular Characteristics of Klebsiella pneumoniae Isolates From Outpatients in Sentinel Hospitals, Beijing, China, 2010–2019

Bing Lu 1, Changying Lin 1, Haican Liu 2, Xin Zhang 1, Yi Tian 1, Ying Huang 1, Hanqiu Yan 1, Mei Qu 1, Lei Jia 1, Quanyi Wang 1,*
PMCID: PMC7059253  PMID: 32181161

Abstract

Background: Klebsiella pneumoniae is an opportunistic pathogen associated with community-acquired and nosocomial infections. Since 2010, K. pneumoniae testing has been included into an existing diarrhea-syndrome surveillance system for estimating the prevalence of K. pneumoniae in diarrhea-syndrome patients, assessing antibiotic susceptibility, and investigating molecular characteristics of K. pneumoniae.

Methods: Klebsiella pneumoniae strains were isolated from stool specimens from diarrhea-syndrome outpatients in Beijing, China. Isolates were tested for antibiotic susceptibility, and phylogenetic relationships were explored though whole genome sequence analysis. Multi-locus sequence type (MLST) alleles were extracted from the whole genome sequence (WGS) data. A maximum likelihood tree was generated by MEGAX. Genomes were annotated by Prokka; core genes were produced by Roary; a maximum likelihood phylogenetic tree was generated using FastTree.

Results: Forty-four K. pnuemoniae strains were isolated from 2010 to July 2019; of these 37 were K. pneumoniae and seven were K. variicola. Antibiotic susceptibility testing showed that all 44 strains were sensitive to gentamicin, imipenem, amikacin, meropenem, kanamycin; 97.73% were sensitive to cefoxitin andlavo-ofloxacin; the highest antibiotic resistance rate was 79.55%, which was to ampicillin. We found three extended-spectrum beta-lactamase (ESBL) producing strains; we identified high-virulence ST types, including ST307 and ST65; and we found that ST23 has been the epidemic clone since 2010. MLST and core genome sequence analysis showed two distinct clusters of 44 K. pnuemoniae; 40 alleles were identified in core genome sequence analysis, while 36 alleles were identified in MLST typing.

Conclusions: There is an urgent need for epidemiological and molecular studies to understand the dynamics of antibiotic resistance and virulence gene transmission to guide strategies for K. pneumoniae surveillance. WGS analysis provided high discrimination power and reliable and robust data useful for molecular epidemiology.

Keywords: Klebsiella pneumoniae, multi-locus sequencing type (MLST), whole genome sequencing (WGS), molecular typing, ESBL

Background

Klebsiella pneumoniae is ubiquitous in the environment. K. pneumoniae is a Gram-negative opportunistic pathogen associated with community-acquired and nosocomial infections (Moradigaravand et al., 2017). Clinically, K. pneumoniae causes pneumoniae, abscesses, bacteremia, urinary tract infections (Podschun and Ullmann, 1998; Wyres and Holt, 2016), and occasionally, diarrhea (Moradigaravand et al., 2017). Nosocomial infections caused by K. pneumoniae impose an increasing risk of community infection.

Since 2010, K. pneumoniae testing has been included in an existing enteric pathogen surveillance system focused on diarrhea-syndrome outpatients of all ages in 245 sentinel hospitals of the 16 districts of Beijing (Lu et al., 2017). The aim of the system is to monitor the prevalence of K. pneumoniae in diarrhea-syndrome outpatients, assess antimicrobial resistance, and explore molecular characteristics of community-acquired K. pneumoniae infection strains.

Methods

Identification of Bacterial Strains

From 2010 to July 2019, stool specimens collected from diarrhea-syndrome outpatients in sentinel hospitals were analyzed using a reverse transcription polymerase chain reaction (RT-PCR) for diarrhea-generating viruses (e.g., rotavirus, norovirus, and calicivirus) (Deng et al., 2012; Gao et al., 2012; Ying et al., 2017) and cultured for isolation of diarrhea-generating bacteria. Any isolated bacteria strains were further tested to identify the pathogens (e.g., Salmonella, Shigella, Escherichia coli, Vibrio parahemolyticus, or K. pneumoniae) usingVitek2 Compact Instrument (bioMérieux; Marcy, France).

Isolated K. pneumoniae strains were tested for antibiotic susceptibility, deoxyribonucleic acid (DNA) extraction, whole-genome sequencing (WGS) analysis, and determination of their molecular characteristics.

Antimicrobial Resistance Testing

Antimicrobial resistance testing for K. pneumoniae strains was assessed using the minimal inhibitory concentration (MIC) method. MICs were interpreted in accordance with the Clinical and Laboratory Standards Institute (CLSI) document, M100-S29:2019. Twenty-seven antimicrobials obtained from Shanghai Xingbai Co. (AST Panel for Aerobic Gram Negative bacilli) were used for antimicrobial resistance testing: ampicillin, ampicillin-sulbactam, amoxicillin with clavulanate potassium, cephazoline, cefepime, cefotaxime, cefoxitin, ceftazidime, aztreonam, imipenem, meropenem, gentamicin, amikacin, kanamycin, azithromycin, tetracycline, minocycline, doxycycline, nalidixic acid, ciprofloxacin, lavofloxacin, gemifloxacin, trimethoprim-sulphamethoxazole, sulfisoxazole, chloramphenicol, cefotaxime with clavulanate, and ceftazidime with clavulanate. Escherichia coli ATCC 25922 was used as a quality-control strain. MIC levels at 2 μg/mL or above for cefotaxime indicated a possible extended-spectrum beta-lactamase (ESBLs)-producing strain, requiring further confirmation. MIC for ceftazidime combined with clavulanatede creasing at least three two-fold concentrations compared with the MIC value for ceftazidime alone (e.g., ceftazidime MIC = 8 μg/mL; ceftazidime-clavulanate MIC = 1 μg/mL) confirmed an ESBL-producing strain.

DNA Extraction and WGS

DNA was extracted by QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). Quantification of extracted genomic DNA (gDNA) was determined on a NanoDrop spectrophotometer, with verification by agarose gel electrophoresis and fluorometric analysis (Qubit2.0).

Multiplexed paired-end libraries (2 × 300 bp) were prepared for DNA sequencing using the NEBNext®Ultra™ DNA Library Prep Kit for Illumina (NEB, USA). Sequences were determined on an Illumina PE150 platform with 100 × coverage at Beijing Novogene technology Co., Ltd.

Raw sequencing data were checked for quality, trimmed, and assembled de novo into contiguous segments using CLC Genomics Workbench version 10.1.1 (CLC, Bio-QIAGEN, Aarhus, Denmark) and SPAdes version 3.13 (Bankevich et al., 2012).

The WGS data were matched in the NCBI BLAST database to identify three distinct species of K. pneumoniae: K. pneumoniae (KpI), K. quasipneumoniae (KpII), and K. variicola (KpIII) (Holt et al., 2015).

Plasmid, Antimicrobial Resistant Genes and Multi-Locus Sequence Type (MLST) Analysis

The genomic analysis was based on the Center for Genomic Epidemiology web server (https://cge.cbs.dtu.dk/services/cge/), in which web-based multi-locus sequence type (MLST) 2.0 (Larsen et al., 2012), ResFinder 3.2 (Zankari et al., 2012), and PlasmidFinder 2.1 (Carattoli et al., 2014) were used for cluster sequencing types, investigating antimicrobial resistant genes, and defining content of plasmid replicon types, respectively.

MLST analyses were performed using seven housekeeping genes (gapA, infB, mdh, pgi, phoE, rpob, and tonB) to characterize diversity and epidemiology of K. pneumoniae isolates (Diancourt et al., 2005). WGS data were used to generate MLST assignments for each isolate; unknown STs were sent to the Klebsiella pneumoniae MLST database at the Pasteur Institute (https://bigsdb.pasteur.fr/klebsiella/klebsiella.html). Genotyping analysis was based on MLST sequences; maximum likelihood trees were generated by MEGA-X (Kumar et al., 2018).

Annotation and Core Genome Analysis

Genomes were annotated by Prokka, a tool for rapid prokaryotic genome annotation (Seemann, 2014). Phylogenetic analyses were produced by Roary, a tool that rapidly builds large-scale pan genomes and identifies core genes (shared by all strains) and accessory genes (Page et al., 2015). A maximum likelihood phylogenetic tree was generated by FastTree version 2.1.10 (Price et al., 2010) to assess relatedness among genomes in the isolated bacteria and to approximate the species tree.

Results

Surveillance led to isolation of 1 to 11 K. pneumoniae strains each year, identifying 44 K. pneumoniae strains from 25,411 stool specimens in 10 years, the detection rate was 0.17% (44/25,411).

Antimicrobial Resistance

All 44 K. pneumoniae strains were sensitive to gentamicin, imipenem, amikacin, meropenem, kanamycin; 97.7% were sensitive to cefoxitin andlavo-ofloxacin; 95.5% were sensitive to nalidixic acid, azithromycin, and ciprofloxacin; 79.6% of isolated K. pnuemoniae strains manifested resistance to ampicillin, and 13.6% of isolated staring showed resistance to sulfisoxazole, trimethoprim, and sulphame-thoxazole (Table 1). Three K. pneumoniae strains were confirmed as ESBL-producing strains (Table 2).

Table 1.

Antibiotic susceptibility results for 44 K. pneumoniae strains.

Antibiotic Resistant n Intermediate n Susceptible n
Penicilins Ampicillin 35, 79.55% 7,15.91% 2, 4.55%
β-Lactam/β-lactamase inhibitor combinations Amoxicillin with clavulanate potassium 2, 4.55% 3,4.55% 40, 90.91%
Ampicillin-sulbactam 4, 9.09% 2, 4.55% 28, 86.36%
Cephems Cephazoline 4, 9.09% 3, 6.82% 37, 84.09%
Cefepime 3, 6.82% 0, 0 41, 93.18%
Cefotaxime 4, 9.09% 0, 0 40, 90.91%
Cefoxitin 1, 2.27% 0, 0 43, 97.73%
Ceftazidime 0, 0 3, 6.82% 41, 93.18%
Monobactams Aztreonam 3, 6.82% 0, 0 41, 93.18%
Carbapenems Imipenem 0, 0 0, 0 44,100.00%
Meropenem 0, 0 0, 0 44,100.00%
Aminoglycosides Gentamicin 0, 0 0, 0 44,100.00%
Amikacin 0, 0 0, 0 44,100.00%
Kanamycin 0, 0 0, 0 44,100.00%
Macrolides Azithromycin 2, 4.55% 0, 0 42, 95.45%
Tetracyclines Tetracycline 5, 11.36% 2, 4.55% 37, 84.09%
Minocycline 2, 4.55% 13, 29.55% 29, 65.91%
Doxycycline 3, 6.82% 4, 9.09% 37, 84.09%
Quinolons and fluoroquinolones Nalidixic acid 2, 4.55% 0, 0 42, 95.45%
Ciprofloxacin 1, 2.27% 1, 2.27% 42, 95.45%
Lavo-floxacin 1, 2.27% 0, 0 43, 97.73%
Gemifloxacin 2, 4.55% 1, 2.27% 41, 93.18%
Folate pathway inhibitors Trimethoprim-sulphamethoxazole 6, 13.64% 0, 0 38, 86.36%
Sulfisoxazole 6, 13.64% 0, 0 38, 86.36%
Phenicols Chloramphenicol 4, 9.09% 1, 2.27% 39, 88.64%

Table 2.

Summary of species, and genotypic characteristics for 44 K. pneumoniae strains.

Strain ID Isolation year Species MLST type Plasmid replicon type ESBL strain Antibiotic resistance genes
Aminoglycoside Beta-lactam Quinolone Fosfomycin Phenicol Sulphonamide Tetracycline Trimethoprim Macrolide Rifampicin
BJ2010005-S1 2010 Klebsiella variicola ST2362 ColRNAI blaLEN13 oqxA,oqxB fosA
BJ2011355-S2 2011 Klebsiella variicola ST197 blaLEN16 oqxA,oqxB fosA
BJ2011367-S32 2011 Klebsiella pneumoniae ST23 blaSHV-36 oqxA,oqxB fosA
BJ2011375-S36 2011 Klebsiella pneumoniae ST2363 ColRNAI, ColpVC blaSHV-1 oqxA,oqxB fosA
BJ2012015-S3 2012 Klebsiella pneumoniae ST23 blaSHV-36 oqxA,oqxB fosA
BJ2012035-S4 2012 Klebsiella pneumoniae ST2364 blaSHV-11 oqxA,oqxB fosA
BJ2012036-S33 2012 Klebsiella pneumoniae ST218 blaSHV-1 oqxA,oqxB fosA
BJ2013059-S5 2013 Klebsiella pneumoniae ST20 ColRNAI blaSHV-83 fosA
BJ2013082-S34 2013 Klebsiella pneumoniae ST412 blaSHV-11 oqxA,oqxB fosA
BJ2013086-S7 2013 Klebsiella pneumoniae ST1660 blaSHV-36 oqxA,oqxB fosA
BJ2013261-S8 2013 Klebsiella pneumoniae ST1310 ColRNAI, Col(MGD2) blaSHV-1 oqxA,oqxB fosA
BJ2014008-S21 2014 Klebsiella pneumoniae ST23 blaSHV-36 oqxA,oqxB fosA
BJ2014021-S10 2014 Klebsiella pneumoniae ST65 blaSHV-11 oqxA,oqxB fosA
BJ2014039-S57 2014 Klebsiella pneumoniae ST2367 ColRNAI, Col(MGD2) blaSHV-11 oqxA,oqxB fosA
BJ2014085-S12 2014 Klebsiella pneumoniae ST592 ColRNAI blaSHV-26 oqxA,oqxB fosA
BJ2014086-S13 2014 Klebsiella pneumoniae ST34 ColRNAI blaSHV-26 oqxA,oqxB fosA
BJ2014087-S14 2014 Klebsiella pneumoniae ST2369 ColRNAI, Col(MGD2) blaSHV-1 oqxA,oqxB fosA
BJ2014199-S15 2014 Klebsiella pneumoniae ST17 blaSHV-11 oqxA,oqxB fosA
BJ2014201-S35 2014 Klebsiella pneumoniae ST2370 ColRNAI, IncR aadA2,aph(3″)-Ib blaSHV-11 oqxA,oqxB fosA strA sul1 tet(A) dfrA12 mph(A)
BJ2015035-S16 2015 Klebsiella pneumoniae ST345 blaSHV-1 oqxA,oqxB fosA
BJ2016012-S17 2016 Klebsiella pneumoniae ST485 blaSHV-27 oqxA,oqxB fosA
BJ2016022-S18 2016 Klebsiella pneumoniae ST35 ColRNAI, Col(MGD2) blaSHV-33 oqxA,oqxB fosA
BJ2017019-S19 2017 Klebsiella variicola ST4448 blaLEN13 oqxA,oqxB fosA
BJ2017021-S20 2017 Klebsiella pneumoniae ST23 blaSHV-36 oqxA,oqxB fosA
BJ2018022-S9 2018 Klebsiella pneumoniae ST307 ColRNAI Yes aac(6′)lb-cr, aph(3″)-Ib, aph(6)-Id blaCTX-M-15, blaSHV-28, blaOXA-1, blaTEM-1B aac(6′)-Ib-cr,oqxA,oqxB,qnrB1 fosA sul2 tet(A) dfrA14
BJ2018060-S11 2018 Klebsiella variicola ST4447 blaLEN22 oqxA,oqxB fosA
BJ2018062-S23 2018 Klebsiella pneumoniae ST1307 IncR, Col(MGD2) aac(3)-IV, aac(6′)-Ib-cr, aadA1, aadA2, aph(4)-Ia blaDHA-1, blaOXA-1, blaSHV-11 aac(6′)-Ib-cr, qnrB4 fosA catB3,floR,cmlA1 sul1,sul2,sul3 tet(A) dfrA12 mph(A) ARR-3
BJ2018066-S24 2018 Klebsiella pneumoniae ST4449 blaSHV-1 oqxA,oqxB fosA
BJ2018083-S25 2018 Klebsiella pneumoniae ST3277 blaSHV-1 oqxA,oqxB fosA
BJ2018090-S26 2018 Klebsiella variicola ST360 blaLEN13 oqxA,oqxB fosA
BJ2018100-S27 2018 Klebsiella variicola ST4450 blaLEN24 oqxA,oqxB fosA
BJ2018102-S28 2018 Klebsiella pneumoniae ST309 blaSHV-11 oqxA, oqxB, QnrS1 fosA floR sul2 tet(A) dfrA14
BJ2018103-S29 2018 Klebsiella variicola ST4451 blaLEN24 oqxA,oqxB fosA
BJ2018104-S30 2018 Klebsiella pneumoniae ST4452 ColRNAI Yes blaSHV-11, blaCTX-M-15, blaTEM-1B oqxA,oqxB fosA
BJ2018114-S31 2018 Klebsiella pneumoniae ST36 ColRNAI, IncR, Col(MGD2) blaSHV-11 oqxA,oqxB fosA
BJ2019005-S58 2019 Klebsiella pneumoniae ST564 blaSHV-11 oqxA,oqxB fosA
BJ2019024-S59 2019 Klebsiella pneumoniae ST742 blaSHV-11 oqxA,oqxB fosA
BJ2019046-S95 2019 Klebsiella pneumoniae ST101 ColRNAI,IncR blaSHV-1 oqxA,oqxB fosA dfrA15
BJ2019047-S96 2019 Klebsiella pneumoniae ST39 ColRNAI,IncQ2 blaSHV-11 oqxA,oqxB fosA
BJ2019059-S97 2019 Klebsiella pneumoniae ST412 blaSHV-1 oqxA,oqxB fosA
BJ2019060-S98 2019 Klebsiella pneumoniae ST1537 blaSHV-1 oqxA,oqxB fosA
BJ2019061-S99 2019 Klebsiella pneumoniae ST17 ColRNAI Yes aac(6′)-Ib-cr, aph(3″)-Ib, aph(6)-Id blaCTX-M-15, blaOXA-1, blaTEM-1B, blaSHV-11 aac(6′)-Ib-cr,oqxA,oqxB,qnrB1 fosA catB3 sul2 tet(A) dfrA14
BJ2019062-S100 2019 Klebsiella pneumoniae ST23 blaSHV-36 oqxA,oqxB fosA
BJ2019070-S103 2019 Klebsiella pneumoniae ST584 IncR blaSHV-38 oqxA,oqxB fosA

WGS NCBI Blast Results

Forty-four K. pneumoniae strains were disambiguated into two species: 37 K. pneumoniae (KpI) strains and 7 K. variicola (KpIII) strains. Surveillance did not identify any K. quasipneumoniae (KpII) strains (Table 2).

MLST Results and MEGA Analysis

MLST of the 44 strains revealed 36 different sequence types (STs), including ST23, which has been detected five times in Beijing in the most recent 10 years, and ST4447, ST4448, ST4449, ST4450, ST4451, and ST4452, which were seen for the first time in the global database. The maximum likelihood tree identified 36 MLST alleles, and 44 strains were disambiguated into two clonal groups: Cluster M1 (containing 7 strains, K. variicola strains) and Cluster M2 (containing 37 strains, K. pneumoniae strains) (Figure 1).

Figure 1.

Figure 1

Molecular phylogenetic analysis by maximum likelihood method based on MLST sequences of 44 K. pneumoniea strains.

Plasmid and Drug Resistance Genes Identification

ColRNAI, Col(MGD2), ColpVC, IncR, and IncQ2 plasmid replicons were identified, encompassing 40.9, 13.6, 2.3, 11.4, and 2.3% of the 44 strains, respectively. Among the resistance genes to Beta-lactams, Quinolone, Fosfomycin, Phenicol, Sulphonamide, Tetracycline, Trimethoprim, Macrolide, and Rifampicin, resistance genesto Beta-lactam, Quinolone, and Fosfomycin were predominant. Among the resistance genes identified from 3 ESBL-producing strains, blaCTX-M-15 and blaTEM-1B were unique resistance genes to Beta-lactams (Table 2).

Core Genome Analysis

The whole genome sequence of the 44 strains identified 3,428 core genes. In maximum-likelihood phylogenies trees, these core genome sequences showed 40 allele differences that grouped into two distinct clusters: cluster C1 (containing7 K. varricola strains), and cluster C2 (containing 37 K. pneumoniae strains) (Figure 2).

Figure 2.

Figure 2

The maximum likelihood phylogenetic tree based on the core genome sequences of 44 K. pneumoniae strains.

Discussion

K. pneumoniae has been reported to be a leading cause of hospital associated infections and a common cause of community-acquired infections in many countries (Pendleton et al., 2013; Moradigaravand et al., 2017; Musicha et al., 2017). Beijing outpatient-based diarrhea-syndromes surveillance detected K. pneumoniae every year since 2010 demonstrating the existence of community-acquired infection caused by K. pneumoniae. Detection of five ST23 strains from 2010 to 2019 further demonstrated that the ST23 strain has persisted in Beijing throughout these years. Our results should alert public health officials since ST23 of K. pneumoniae has well-known virulence and is able to cause severe disease in otherwise healthy individuals (Turton et al., 2007; Brisse et al., 2009; Holt et al., 2015). It typically carries all four acquired siderophore systems as well as rmpA (Brisse et al., 2009). K. pneumoniae ST23 is the most predominant sequence type causing invasive community-acquired infections in Asia (Chung et al., 2012). Surveillance also detected an ST65 strain, which carries colibactin and rmpA (Brisse et al., 2009), and which is associated with lethal infections in humans and marine mammals (Liao et al., 2014).

The three community-acquired K. pneumoniae ESBL-producing strains (ST307, ST4452, and ST17) that were identified in the most recent 2-years period provide a significant signal of drug resistance in the population. All three ESBLs producing strains harbor blaCTX-M-15 and blaTEM-1B antibiotic resistance genes. CTX-M-15 belonged to the CTX-M-1 group, and is widespread in east Asia (Bonnet, 2004). The blaCTX-M was first reported in 1990 in a cefotaxime resistant E. coli strain isolated from the fecal flora of a laboratory dog (Bauernfeind et al., 1990). Since then, the CTX-M enzymes have formed a rapidly growing family of ESBLs distributed over wide geographic areas and among a wide range of clinical bacteria, particularly among members of the Enterobacteriaceae family (Bonnet, 2004). Outbreaks have been described in several countries (Yan et al., 2000; Baraniak et al., 2002). Since 1999, CTX-M has been reported to have become the most frequent ESBL in the Enterobacteriaceae in China (Chanawong et al., 2002; Xiong et al., 2002; Wang et al., 2003). Notably, the K. pneumoniae ST307 ESBL-producing strain has a novel lineage with potential to become an epidemic or “high-risk” clone. It has been recognized as a candidate for becoming one of the most clinically-relevant clones since its worldwide emergence during recent years (Villa et al., 2017). The ST307 lineage displays an association with CTX-M-15- and Carbapenemase (KPC)-producing encoding plasmids (Villa et al., 2017). The K. pneumoniae ST307 detected in our study did not harbor the blaKPC gene, but KPC producing factor could be acquired through horizontal plasmids transfer. The ability of this clone lineage to acquire novel genetic features may contribute to its increased persistence in the environment and highlights its potential public health threat of dramatically disseminated multiple drug resistance among bacteria.

MLST and core genomes sequences consistently differentiated 44 K. pneumoniae into 7 K. varricola strains and 37 K. pneumoniae strains. However, the core genome sequences increase discriminatory power for bacterial pathogen subtyping. For example, BJ2013086-S7 strain is very close to BJ2014039-S57 in an MLST molecular phylogenetic tree (see Figure 1), however, BJ2013086-S7 was separated from BJ2014039-S57in the phylogenetic tree generated by the core genome, and was closer to ST23 strain. Similar distinction was made for BJ2013261-S8 and BJ2019005-S58 stains, BJ2019059-S97 and BJ2013082-S34, and BJ2019061-S99 and BJ2014199-S15. Since WGS consists of sequencing chromosome information, both inherited from ancestors and their mutations, in theory, this powerful tool can deduce the chains of potential cross transmission of K. pneumoniae infection (Croucher and Didelot, 2015) and facilitate study of the population structure and pathogen evolution (Bialek-Davenet et al., 2014; Struve et al., 2015; Zhou et al., 2017). However, its discriminatory power relies on reliable, and robust, and long-term WGS data from different geographic areas. It will be valuable to establish a K. pneumoniae identification network for information sharing.

This study suffers two main limitations. First, the sentinel surveillance could have under-estimated the prevalence of K. pneumoniae in diarrhea-syndrome outpatients since K. pneumoniae in most of the circumstance is not the predominant causative-pathogen. Second, lack of comparation with molecular characteristics of hospital-acquired K. pneumoniae infection strains encourages more effort should be made to provide complete molecular spectrum in future studies.

Conclusions

Outpatient-based diarrhea-syndrome surveillance in Beijing China identified 3 ESBLs-producing strains in 2018 and 2019 that had not been detected previously. We identified high virulence ST types, such as ST307 and ST65, and we showed that ST23 has been the epidemic clone since 2010. There is an urgent need for epidemiological and molecular studies to understand the dynamics of antibiotic resistance and virulence gene transmission to guide strategies for K. pneumoniae surveillance. WGS analysis provides high discrimination power, and reliable and robust data for molecular epidemiology.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

Ethics Statement

The study was approved by the Ethics Committee of the Beijing Center for Disease Prevention and Control.

Author Contributions

BL participated in data analysis and drafted the manuscript. CL and HL managed the bio information analysis. XZ and YH carried out the molecular genetic studies. HY participated in sample isolation. LJ and YT managed the strains and data collection. MQ and QW participated in the design of the study. All authors read and approved the final manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank the team of curators of the Institute Pasteur MLST and whole genome MLST databases for curating the data and making them publicly available at http://bigsdb.pasteur.fr/. We thank the epidemiological investigation teams of all 16 districts in Beijing, China.

Glossary

Abbreviations

K. pneumoniae

Klebsiella pneumonia

K. quasipneumoniae

Klebsiella quasipneumoniae

K. variicola

Klebsiella variicola

MLST

multi-locus sequence typing

RT-PCR

reverse transcription polymerase chain reaction

DNA

deoxyribonucleic acid

WGS

whole genome sequence

CLSI

Clinical and Laboratory Standards Institute

ESBL

extended-spectrum beta-lactamase

MIC

minimal inhibitory concentration

STs

sequence types

KPC

Carbapenemase.

Footnotes

Funding. This work was supported by National Science and Technology Support Projects for the Thirteenth Five-Year Plan for Infectious Diseases of China (2018ZX10714002-003-002).

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