A 20-Year Study of Capsular Polysaccharide Seroepidemiology, Susceptibility Profiles, and Virulence Determinants of Klebsiella pneumoniae from Bacteremia Patients in Taiwan

Genomic Profile of a Multidrug-Resistant Klebsiella pneumoniae Strain Isolated from a Urine Specimen

Klebsiella pneumoniae is an opportunistic pathogen mostly found in health care-associated infections but can also be associated with community-acquired infections and is in critical need of new antimicrobial agents for strains resistant to carbapenems. The prevalence of carbapenemase-encoding genes varies among studies. Multidrug-resistant K. pneumoniae strains can harbor several antimicrobial-resistant determinants and mobile genetic elements (MGEs), along with virulence genetic determinants in community settings. We aim to determine the genetic profile of a multidrug-resistant K. pneumoniae strain isolated from a patient with community-acquired UTI. We isolated a K. pneumoniae strain UABC-Str0120, from a urine sample of community-acquired urinary tract infection. Antimicrobial susceptibility tests and Whole-genome sequencing (WGS) were performed. The phylogenetic relationship was inferred by SNPs calling and filtering. UABC-Str0120 showed resistance toward β-lactams, combinations with β-lactamase inhibitors, and carbapenems. WGS revealed the presence of genes conferring resistance to aminoglycosides, β-lactams, carbapenems, quinolones, sulfonamides, phosphonates, phenicols, and quaternary ammonium compounds, 77 subsystems of virulence genes were identified, and an uncommon sequence type ST5889 was also determined. The sequenced strain harbors several MGEs. The UABC-Str0120 recovered from a urine sample harbors several virulence and antimicrobial resistance determinants, which assembles an endangering combination for an immunocompromised or a seemly healthy host, given its presence in a community setting.

Carbapenem and colistin-resistant hypervirulent Klebsiella pneumoniae: An emerging threat transcending the egyptian food chain

BACKGROUND

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a great public health problem and is associated with many disease outbreaks and high mortality rates. Alarmingly, K. pneumoniae has been isolated from food in several recent studies. This study aimed to investigate the prevalence and characteristics of CRKP in food samples from Egypt.

METHODS

A total of 311 food samples (including 116 minced meat, 92 chicken meat, 75 diced meat, and 28 mutton) were collected from local markets in Egypt and were screened for CRKP with the determination of their antimicrobial resistance profiles. The whole genome sequence was done for 23 CRKP isolates to clarify the relationship between CRKP from food and human cases in Egypt using the SNP core genome. The conjugation probability of the blaNDM-5 harboring plasmid was identified using oriTfinder RESULTS: CRKP was isolated from 11% (35/311) of the samples, with 45.71% (16/35) of them showing resistance to colistin, one of the last-resort options for treating CRKP-mediated infections. In addition to the carbapenem and colistin resistance, the CRKP isolates frequently exhibited resistance to multiple antimicrobials including β-lactams, fluoroquinolones, aminoglycosides, tetracyclines, and chloramphenicol. In addition, most of the CRKP were potentially hypervirulent K. pneumoniae (HvKP) identified as phylogroup Kp1 and of high-risk groups as detected in STs reported in many human outbreaks globally, such as ST383 and ST147. The core-genome phylogeny showed similarities between the isolates from this study and those previously isolated from clinical human samples in Egypt. In addition, analysis of the plasmid on which blaNDM is encoded revealed that several antimicrobial resistance genes such as blaOXA-9, blaCTX-M-15, aac(6')-Ib, qnrS1, and several virulence genes are encoded on the same plasmid.

CONCLUSIONS

This study is significant for food safety and public health and is important to further identify the change in the epidemiology of CRKP infections, especially the consumption of contaminated food products.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.