This study aimed to investigate the epidemiological characteristics and trends over time of carbapenemase-producing (e.g., KPC, NDM, VIM, IMP, and OXA-48) Gram-negative bacteria (CPGNB). Non-duplicated multi-drug resistant Gram-negative bacteria (MDRGNB) were collected from the First Affiliated Hospital of Zhengzhou University from April 2019 to February 2023. Species identification of each isolate was performed using the Vitek2 system and confirmed by matrix-assisted laser desorption ionization-time of flight mass spectrometry according to the manufacturer\'s instructions. PCR detected carbapenem resistance genes in the strains, strains carrying carbapenem resistance genes were categorized as CPGNB strains after validation by carbapenem inactivation assay. A total of 5705 non-repetitive MDRGNB isolates belonging to 78 different species were collected during the study period, of which 1918 CPGNB were validated, with the respiratory tract being the primary source of specimens. Epidemiologic statistics showed a significant predominance of ICU-sourced strains compared to other departments. Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa were the significant CPGNB in Henan, and KPC and NDM were the predominant carbapenemases. Carbapenem-resistant infections in Henan Province showed an overall increasing trend, and the carriage of carbapenemase genes by CPGNB has become increasingly prevalent and complicated. The growing prevalence of CPGNB in the post-pandemic era poses a significant challenge to public safety.

Antimicrobial resistance (AMR) is a critical threat to human health. Escherichia coli and Klebsiella pneumoniae are clinically the most important species associated with AMR and are the most common carbapenemase-producing (CP) Enterobacterales detected in human specimens in Finland. Wastewater surveillance has emerged as a potential approach for population-level surveillance of AMR, as wastewater could offer a reflection from a larger population with one sample and minimal recognized ethical issues. In this study, we investigated the potential of wastewater surveillance to detect CP E. coli and K. pneumoniae strains similar to those detected in human specimens.
Altogether, 89 composite samples of untreated community wastewater were collected from 10 wastewater treatment plants across Finland in 2021-2022. CP E. coli and K. pneumoniae were isolated using selective culture media and identified using MALDI-TOF MS. Antimicrobial susceptibility testing was performed using disk diffusion test and broth microdilution method, and a subset of isolates was characterized using whole-genome sequencing.
CP E. coli was detected in 26 (29.2%) and K. pneumoniae in 25 (28.1%) samples. Among E. coli, the most common sequence type (ST) was ST410 (n = 7/26, 26.9%), while ST359 (n = 4/25, 16.0%) predominated among K. pneumoniae. Globally successful STs were detected in both E. coli (ST410, ST1284, ST167, and ST405) and K. pneumoniae (ST512, ST101, and ST307). K. pneumoniae carbapenemases (KPC) were the most common carbapenemases in both E. coli (n = 11/26, 42.3%) and K. pneumoniae (n = 13/25, 52.0%), yet also other carbapenemases, such as blaNDM-5, blaOXA-48, and blaOXA-181, were detected. We detected isolates harboring similar ST and enzyme type combinations previously linked to clusters in Finland, such as E. coli ST410 with blaKPC-2 and K. pneumoniae ST512 with blaKPC-3.
Our study highlights the presence of clinically relevant strains of CP E. coli and K. pneumoniae in community wastewater. The results indicate that wastewater surveillance could serve as a monitoring tool for CP Enterobacterales. However, the specificity and sensitivity of the methods should be improved, and technologies, like advanced sequencing methods, should be utilized to distinguish data with public health relevance, harness the full potential of wastewater surveillance, and implement the data in public health surveillance.

BACKGROUND: Here, we describe an integrative method to detect carbapenemase-producing Gram-negative bacteria (gn-Cp) on surfaces/fomites in the patient environment. We examined environmental samples from 28 patient rooms occupied with patients who were proven to be colonised with gn-Cp by rectal screening.
METHODS: We took samples after 24 h, 72 h and one week. For sampling, we divided the patient environment into four parts and took samples from near- and extended patient areas. To obtain a representative bacterial swab from a larger surface, such as the patient cabinet, we used Polywipes. Bacterial DNA was isolated. Carbapenemase was detected with specific qPCR primers.
RESULTS: With this culture- and molecular-based approach, we could control the effectiveness of cleaning and disinfection in everyday clinical practice. Therefore, we could track the spread of gn-Cp within the patient room. The number of positive detections fluctuated between 30.5% (mean value positive results after 72 h) and 35.2% (after 24 h and one week).
CONCLUSIONS: The method used to detect multidrug-resistant bacteria in the environment of patients by using PolywipesTM is reliable and can therefore be used as an effective, new tool in hygiene and infection control.

A rapid and accurate detection of carbapenemase-producing Gram-negative bacteria (CPGNB) has an immediate demand in the clinic. Here, we developed and validated a method for rapid detection of CPGNB using Blue-Carba combined with deep learning (designated as AI-Blue-Carba). The optimum bacterial suspension concentration and detection wavelength were determined using a Multimode Plate Reader and integrated with deep learning modeling. We examined 160 carbapenemase-producing and non-carbapenemase-producing bacteria using the Blue-Carba test and a series of time and optical density values were obtained to build and validate the machine models. Subsequently, a simplified model was re-evaluated by descending the dataset from 13 time points to 2 time points. The best suitable bacterial concentration was determined to be 1.5 optical density (OD) and the optimum detection wavelength for AI-Blue-Carba was set as 615 nm. Among the 2 models (LRM and LSTM), the LSTM model generated the higher ROC-AUC value. Moreover, the simplified LSTM model trained by short time points (0-15 min) did not impair the accuracy of LSTM model. Compared with the traditional Blue-Carba, the AI-Blue-Carba method has a sensitivity of 95.3% and a specificity of 95.7% at 15 min, which is a rapid and accurate method to detect CPGNB.

BACKGROUND: An electronic reporting system (ERS) for the enhanced surveillance of carbapenemase-producing Gram-negative bacteria (CPGNB) was launched by Public Health England in May 2015.
OBJECTIVE: This evaluation aimed to assess uptake, timeliness and completeness of data provided and explore potential barriers and facilitators to adopting the system.
METHODS: The evaluation comprised a retrospective analysis of surveillance data and semi-structured interviews with ERS users.
RESULTS: The proportion of organisms referred for investigation of carbapenem resistance via ERS increased over the first 12 months post-implementation from 35% to 73%; uptake varied widely across regions of England. Completeness of enhanced data fields was poor in 78% of submitted isolates. The median number of days to report confirmatory test results via ERS was 1 day for the regional service and nine days for the national reference laboratory, which additionally conducts phenotypic testing to confirm carbapenemase negativity. Hindrances to ERS utility included: a lack of designated, ongoing resource for system maintenance, technical support and development; uncertainty about how and when to use ERS and workload. Incomplete data prevented gaining a better understanding of important risk factors and transmission routes of CPGNB in England.
CONCLUSIONS: The ERS is the only surveillance system in England with the potential to gather intelligence on important risk factors for CPGNB to inform public health measures to control their spread. Although the ERS captures more information on CPGNB than other surveillance systems, timeliness and completeness of the enhanced data require substantial improvements in order to deliver the desired health benefits.

We evaluated a rapid biochemical screening test β-CARBA™ for detection of Gram-negative carbapenemase producers. The sensitivity of the test after 30min incubation was 98.2%, but increased to 100% after 1h. β-CARBA™ proved reliable for carbapenemase screening in Acinetobacter spp. for which currently no commercial phenotypic assays are available.

We evaluated RAPIDEC® CARBA NP, Neo-Rapid CARB, chromID® CARBA SMART (CARB/OXA), Brilliance™ CRE/ESBL, ChromArt CRE and BBL™ CHROMagar™ CPE for the detection of carbapenemase-producing bacteria. The analytical sensitivity of RAPIDEC® CARBA NP was better than that of Neo-Rapid CARB. A combination of carbapenemase and ESBL screening plates could be advantageous.