Core genome MLST and resistome analysis of Klebsiella pneumoniae using a clinically amenable workflow

Automated whole genome sequencing platform for bacterial strain typing in clinical microbiology laboratories

Nosocomial outbreaks impact patient safety and place an economic burden on healthcare facilities. Laboratory testing plays a crucial role in outbreak investigation and guides containment efforts. In recent years, whole genome sequencing (WGS) methods have replaced traditional typing methods due to higher resolution and simplified workflows. Though an improvement from previous methods, bacterial WGS is time-consuming with manual DNA extraction and library preparation and long sequencing times for paired-end sequence data. Here, a fully automated library preparation and sequencing solution, the Clear DxTM WGS platform (Clear Labs, San Carlos, CA), was compared to a more manual library preparation and sequencing approach using 226 isolates representing 18 bacterial species. Sequence data were analyzed using SeqSphere+ (Ridom, Münster, Germany), and the results of the two methods were compared. Of the 224 isolate sequences analyzed, 222 (99%) showed concordant isolate groupings, and, overall, the results of the two approaches were statistically similar by comparison of distance matrices. The automated workflow reduced turnaround time by 16-19 h and eliminated 3 h of manual labor while decreasing costs by an estimated 34%-57% depending on the number of isolates run. This study demonstrates the advantages of integrating automation into bacterial WGS workflows.IMPORTANCEAn automated platform for bacterial nucleic acid extraction and whole genome sequencing was compared to a manual method for bacterial strain typing. The two approaches yielded nearly equivalent results, with the automated approach providing improvement in turnaround time and cost, with less manual pipetting.

High Prevalence of Cefiderocol Resistance Among New Delhi Metallo-β-Lactamase Producing Klebsiella pneumoniae High-Risk Clones in Hungary

BACKGROUND/OBJECTIVES

The global spread of carbapenemase-producing K. pneumoniae (CPKP) strains represent a severe public health threat due to very limited choice of antibacterial therapy. Cefiderocol, a novel siderophore-cephalosporin, may represent a new therapeutic option but resistance is increasingly being described. Our aim was to investigate in vitro cefiderocol susceptibility among CPKP strains in Hungary and assess correlations between resistance, carbapenemase types, and clonal lineages.

METHODS

The study was performed on 420 CPKP strains from 34 Hungarian healthcare institutes (HCIs) submitted to the National Reference Laboratory of Antimicrobial Resistance (March 2021 to April 2023). The disk diffusion method (Liofilchem, Via Scozia, Italy) was used for in vitro cefiderocol susceptibility testing (according to EUCAST guidelines). For molecular epidemiologic investigation, we used whole genome sequencing (Illumina MiSeq, 150 bp paired-end) and pulsed-field gel electrophoresis (PFGE). Carbapenemase gene type was determined by multiplex PCR. Statistical analysis was performed in R (v.4.2.0).

RESULTS

Dominant high-risk clones (ST147, ST395, ST258) exhibited regional distribution, with ST147/NDM-1 strains showing the highest cefiderocol resistance (75%). Overall resistance was 65%. Carbapenemase gene types occurred as follows: 35 blaVIM, 53 blaKPC, 57 blaOXA-48-like, 153 blaNDM, and 122 blaOXA-48-like+blaNDM. Cefiderocol resistance rates by carbapenemase type were 20%, 44%, 70%, and 75% in the case of blaVIM, blaOXA-48-like, blaKPC, blaNDM, and blaOXA-48-like+blaNDM.

CONCLUSIONS

The results show a high prevalence of cefiderocol resistance in CPKP in Hungary, with different rates of resistance in different carbapenemase gene-carrying high-risk clones, highlighting the growing challenge in treating these infections.

Core Genome Multilocus Sequence Typing and Antibiotic Susceptibility Prediction from Whole-Genome Sequence Data of Multidrug-Resistant Pseudomonas aeruginosa Isolates

Over the past decade, whole-genome sequencing (WGS) has overtaken traditional bacterial typing methods for studies of genetic relatedness. Further, WGS data generated during epidemiologic studies can be used in other clinically relevant bioinformatic applications, such as antibiotic resistance prediction. Using commercially available software tools, the relatedness of 38 clinical isolates of multidrug-resistant Pseudomonas aeruginosa was defined by two core genome multilocus sequence typing (cgMLST) methods, and the WGS data of each isolate was analyzed to predict antibiotic susceptibility to nine antibacterial agents. The WGS typing and resistance prediction data were compared with pulsed-field gel electrophoresis (PFGE) and phenotypic antibiotic susceptibility results, respectively. Simpson's Diversity Index and adjusted Wallace pairwise assessments of the three typing methods showed nearly identical discriminatory power. Antibiotic resistance prediction using a trained analytical pipeline examined 342 bacterial-drug combinations with an overall categorical agreement of 92.4% and very major, major, and minor error rates of 3.6, 4.1, and 4.1%, respectively. IMPORTANCE Multidrug-resistant Pseudomonas aeruginosa isolates are a serious public health concern due to their resistance to nearly all or all of the available antibiotics, including carbapenems. Utilizing molecular approaches in conjunction with antibiotic susceptibility prediction software warrants investigation for use in the clinical laboratory workflow. These molecular tools coupled with antibiotic resistance prediction tools offer the opportunity to overcome the extended turnaround time and technical challenges of phenotypic susceptibility testing.

Core Genome Multilocus Sequence Typing and Prediction of Antimicrobial Susceptibility Using Whole-Genome Sequences of Escherichia coli Bloodstream Infection Isolates

In total, 50 Escherichia coli bloodstream isolates from the clinical laboratory and 12 E. coli isolates referred for pulsed-field gel electrophoresis (PFGE) were sequenced, assessed for clonality using core genome multilocus sequence typing (cgMLST), and evaluated for genomic susceptibility predictions using ARESdb. Results of sequence typing using whole-genome sequencing (WGS)-based MLST and sequence type (ST)-specific PCR were identical. Overall categorical agreement between genotypic (ARESdb) and phenotypic susceptibility testing for 62 isolates and 11 antimicrobial agents was 91%. Among the referred isolates, high major error rates were found for ceftazidime, cefepime, and piperacillin-tazobactam.

Antibacterial Resistance Leadership Group 2.0 - Back to Business

In December 2019, the Antibacterial Resistance Leadership Group (ARLG) was awarded funding for another seven-year cycle to support a clinical research network on antibacterial resistance. ARLG 2.0 has three overarching research priorities: (1) infections caused by antibiotic resistant (AR) Gram-negative bacteria; (2) infections caused by AR Gram-positive bacteria, and (3) diagnostic tests to optimize use of antibiotics. To support the next generation of AR researchers, the ARLG offers three mentoring opportunities: the ARLG Fellowship, Early Stage Investigator Seed Grants, and the Trialists in Training Program. The purpose of this article is to update the scientific community on the progress made in the original funding period and to encourage submission of clinical research that addresses one or more of the research priority areas of ARLG 2.0.