Investigation of possible clonal transmission of carbapenemase-producing Klebsiella pneumoniae complex member isolates in Denmark using core genome MLST and National Patient Registry Data

Antibiotic resistance monitoring in wastewater in the Nordic countries: A systematic review

The Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden) have effectively kept lower antibiotic-resistant bacterial (ARB) pathogen rates than many other countries. However, in recent years, these five countries have encountered a rise in ARB cases and challenges in treating infections due to the growing prevalence of ARB pathogens. Wastewater-based surveillance (WBS) is a valuable supplement to clinical methods for ARB surveillance, but there is a lack of comprehensive understanding of WBS application for ARB in the Nordic countries. This review aims to compile the latest state-of-the-art developments in WBS for ARB monitoring in the Nordic countries and compare them with clinical surveillance practices. After reviewing 1480 papers from the primary search, 54 were found relevant, and 15 additional WBS-related papers were included. Among 69 studies analyzed, 42 dedicated clinical epidemiology, while 27 focused on wastewater monitoring. The PRISMA review of the literature revealed that Nordic countries focus on four major WBS objectives of ARB: assessing ARB in the human population, identifying ARB evading wastewater treatment, quantifying removal rates, and evaluating potential ARB evolution during the treatment process. In both clinical and wastewater contexts, the most studied targets were pathogens producing carbapenemase and extended-spectrum beta-lactamase (ESBL), primarily Escherichia coli and Klebsiella spp. However, vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) have received more attention in clinical epidemiology than in wastewater studies, probably due to their lower detection rates in wastewater. Clinical surveillance has mostly used culturing, antibiotic susceptibility testing, and genotyping, but WBS employed PCR-based and metagenomics alongside culture-based techniques. Imported cases resulting from international travel and hospitalization abroad appear to have frequently contributed to the rise in ARB pathogen cases in these countries. The many similarities between the Nordic countries (e.g., knowledge exchange practices, antibiotic usage patterns, and the current ARB landscape) could facilitate collaborative efforts in developing and implementing WBS for ARB in population-level screening.

Resistance to aminoglycoside and quinolone drugs among Klebsiella pneumoniae clinical isolates from northern Jordan

This study aimed to identify phenotypic and genotypic aminoglycoside and quinolone non-susceptibility and the prevalence of aminoglycoside-modifying enzymes and plasmid-mediated quinolone resistance genes among K. pneumoniae clinical isolates from northern Jordan. K. pneumoniae isolates (n = 183) were tested for antimicrobial susceptibility using the Kirby-Bauer disk diffusion method. The double-disk synergy test was used for the detection of the extended-spectrum beta-lactamase phenotype. Polymerase chain reaction was used to detect genes encoding aminoglycoside-modifying enzyme (aac (3')-II, aac (6')-II, aac (6')-Ib, ant (3″)-I, aph (3')-VI, armA, and rmtB), and plasmid-mediated quinolone resistance (qnrA, qnrB, qnrC, qnrD, qnrS, acc(6')-Ib-cr, qepA, and oqxAB) genes. Multi-locus sequence typing was used to elucidate the genetic diversity of selected isolates. The non-susceptibility percentages to aminoglycosides and quinolones were 65.0 % and 61.7 %, respectively. The most frequent aminoglycoside-modifying enzyme gene was ant (3″)-I at 73.8 %, followed by aac (6')-Ib at 25.1 %, aac (3')-II at 17.5 %, aph (3')-VI at 12.0 %, armA at 9.8 %, and rmtB at 0.5 %. Aac (6')-II was not detected among the isolates. The most frequent plasmid-mediated quinolone resistance gene was oqxAB at 31.7 %, followed by qnrS at 26.2 %, qnrB at 25.7 %, and aac(6')-Ib-cr at 25.7 %. QnrA, qnrD, qebA, and qnrC were not detected among the isolates. Aac (3')-II, aac (6')-Ib, aph (3')-VI, armA, qnrB, qnrS, and acc(6')-Ib-cr were significantly associated with non-susceptibility to aminoglycosides, quinolones, and beta-lactams. Among 27 randomly selected K. pneumoniae isolates, the most common sequence type was ST2096, followed by ST348 and ST1207. Overall, 19 sequence types were observed, confirming a high level of genetic diversity among the isolates. High percentages of non-susceptibility to the studied antimicrobials were found and were associated with the presence of several resistance genes. Similar studies should be periodically carried out to monitor changes in the prevalence of resistance phenotypes and genotypes of isolates.

Genomic Epidemiology and Characterization of Carbapenem-Resistant Klebsiella pneumoniae in ICU Inpatients in Henan Province, China: a Multicenter Cross-Sectional Study

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has disseminated globally and is difficult to treat, causing increased morbidity and mortality rates in critically ill patients. We conducted a multicenter cross-sectional study of intensive care unit (ICU) inpatients in 78 hospitals to investigate the prevalence and molecular characteristics of CRKP in Henan Province, China, a hyperepidemic region. A total of 327 isolates were collected and downsampled to 189 for whole-genome sequencing. Molecular typing revealed that sequence type 11 (ST11) of clonal group 258 (CG258) was predominant (88.9%, n = 168), followed by ST2237 (5.8%, n = 11) and ST15 (2.6%, n = 5). We used core genome multilocus sequence typing (cgMLST) to further classified the population into 13 subtypes. Capsule polysaccharide (K-antigen) and lipopolysaccharide (LPS; O-antigen) typing revealed that K64 (48.1%, n = 91) and O2a (49.2%, n = 93) were the most common. We studied isolates collected from both the airway and the gut of the same patients and showed that intestinal carriage was associated with respiratory colonization (odds ratio = 10.80, P < 0.0001). Most isolates (95.2%, n = 180) showed multiple drug resistance (MDR), while 59.8% (n = 113) exhibited extensive drug resistance (XDR), and all isolates harbored either blaKPC-2 (98.9%, n = 187) or blaCTX-M and blaSHV extended-spectrum beta-lactamases (ESBLs) (75.7%, n = 143). However, most were susceptible to ceftazidime-avibactam (CZA) (94.7%, n = 179) and colistin (97.9%, n = 185). We found mgrB truncations in isolates conferring resistance to colistin and mutations in blaSHV and OmpK35 and OmpK36 osmoporins in CZA-resistant isolates. Using a regularized regression model, we found that the aerobactin sequence type and the salmochelin sequence type, among others, were predictors of the hypermucoviscosity phenotype. IMPORTANCE In this study, we address the ongoing epidemic of carbapenem-resistant Klebsiella pneumoniae, a critical threat to public health. The alarming genotypic and phenotypic convergence of multidrug resistance and virulence highlights the increasingly aggravated threat posed by K. pneumoniae. This calls for a combined effort of physicians and scientists to study the potential mechanisms and establish guidelines for antimicrobial therapies and interventions. To this end, we have conducted a genomic epidemiology and characterization study using isolates collected in a coordinated effort of multiple hospitals. Innovative biological discoveries of clinical importance are made and brought to the attention of clinical researchers and practitioners. This study presents an important advance in the application of genomics and statistics to recognize, understand, and control an infectious disease of concern.

Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary

BACKGROUND

Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.

METHODS

We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.

RESULTS

Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.

CONCLUSIONS

WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.