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

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.