Comprehensive Characterization of Carbapenemase Genes in Carbapenem-Resistant Enterobacter cloacae (CREC) in Guangdong

Study Background and Research Question

The global escalation of antibiotic resistance in Gram-negative bacteria, especially among Enterobacteriaceae, continues to challenge clinical management of infections. In China, carbapenem-resistant Enterobacter cloacae (CREC) is one of the most prevalent carbapenem-resistant Enterobacteriaceae (CRE), following Klebsiella pneumoniae and Escherichia coli. The COVID-19 pandemic exacerbated this problem by increasing antibiotic use and disrupting healthcare delivery, creating a critical need to understand the molecular mechanisms driving resistance and its spread. The key research question addressed by Chen et al. (2025) is: What are the carriage characteristics and transmission dynamics of carbapenemase-encoding genes (CEGs) in CREC strains isolated from multiple hospitals in Guangdong Province during the pandemic period?

Key Innovation from the Reference Study

This work stands out for its systematic, multi-center analysis of CREC isolates, focusing on the localization of major CEGs (notably bla_NDM-1, bla_IMP, and bla_KPC-2) across both chromosomal and plasmid DNA. By coupling molecular genotyping, plasmid transfer experiments, and epidemiological data, the study elucidates not only the prevalence of these resistance determinants but also their efficient dissemination mechanisms—critical for antibiotic resistance research and infection control planning.

Methods and Experimental Design Insights

The investigators collected 54 non-duplicate CREC isolates from eight teaching hospitals between December 2022 and June 2024. The workflow included:

• Detection of CEGs via PCR and variable temperature Sodium Dodecyl Sulfate (SDS) plasmid elimination to determine gene localization (plasmid vs. chromosome).
• Broth microdilution assays to assess susceptibility profiles for key antibiotics, including imipenem, cefepime, gentamicin, ceftazidime/avibactam, ciprofloxacin, and levofloxacin.
• Plasmid conjugation experiments to test the transferability of CEGs among strains.
• Mobile genetic element (MGE) mapping to identify vectors facilitating gene mobility, with particular attention to insertion sequences such as ISEcp1.
• ERIC-PCR genotyping and cluster analysis using NTSYS software to define strain relatedness and potential outbreak clusters.

Protocol Parameters

• Isolate collection: December 2022–June 2024 from eight tertiary hospitals; non-duplicate, clinical CREC isolates.
• Plasmid elimination: Variable temperature SDS treatment to distinguish plasmid- vs. chromosome-encoded CEGs.
• PCR conditions: Targeting bla_NDM-1, bla_IMP, bla_KPC-2 for gene detection and localization.
• Antibiotic susceptibility testing: Broth microdilution according to CLSI guidelines, including assessment of response to bacterial protein synthesis inhibitors such as aminoglycosides.
• Conjugation assays: Filter mating for plasmid transferability, with PCR confirmation of successful gene transfer.
• ERIC-PCR genotyping: Strain typing and cluster analysis using NTSYS software; Dice coefficient for similarity assessment.

Core Findings and Why They Matter

Key results from the study include:

• High prevalence of CEGs: 85.19% of CREC isolates carried carbapenemase-encoding genes. The bla_NDM-1 gene was the most prevalent, found on both chromosomes and plasmids in 33.33% of isolates, and exclusively on plasmids in 46.30%.
• Multidrug resistance: CEG-positive strains showed significantly higher resistance rates to key antibiotics, including both carbapenems and bacterial protein synthesis inhibitors (e.g., gentamicin), compared to CEG-negative strains.
• Efficient horizontal transfer: Plasmid-mediated conjugation experiments demonstrated a 95.65% success rate for CEG transfer, underscoring the risk of rapid spread across bacterial populations.
• Mobile genetic elements: Six MGE types were identified; ISEcp1 was most prevalent (87.04%), and co-carriage of multiple MGEs in single isolates was common, facilitating gene mobilization.
• Clonal diversity and outbreaks: ERIC-PCR classified isolates into 17 genotypes, with types E and G most frequent and distributed across multiple hospitals, suggesting inter-departmental or inter-hospital dissemination.
• Epidemiological risk groups: Highest detection rates of CEGs were in male and elderly patients, respiratory medicine units, and sputum samples, highlighting at-risk populations and clinical contexts.

These insights highlight the urgent need for vigilant surveillance and targeted intervention in healthcare settings to curb the spread of plasmid-encoded resistance genes among opportunistic pathogens.

Comparison with Existing Internal Articles

Several internal resources provide complementary perspectives:

• "Transmission of Carbapenemase Genes in CREC: Genomic Insights from Guangdong" distills similar findings regarding the extensive dissemination of CEGs in CREC and emphasizes genomic surveillance as a cornerstone for infection control, aligning directly with the reference study's approach.
• For practical laboratory research, "Amikacin (BAY416651) Aminoglycoside Antibiotic in Lab Assays" and "Amikacin (BAY416651) in Antibiotic Resistance Research Workflows" offer protocol guidance for employing aminoglycoside antibiotics, highlighting the importance of selecting inhibitors resistant to modifying enzymes when dissecting resistance mechanisms in multidrug-resistant Enterobacteriaceae, including Enterobacter cloacae and Klebsiella pneumoniae.
• "Amikacin (BAY416651): Applied Workflows for Resistance Research" provides protocols and troubleshooting advice for using amikacin in resistance and bacterial protein synthesis inhibition studies, which can be adapted to the multidrug-resistant profiles identified in the reference study.

Collectively, these articles and the reference study reinforce the need for integrated molecular, phenotypic, and workflow approaches in antibiotic resistance research.

Limitations and Transferability

While the study by Chen et al. provides a robust, multi-hospital snapshot of CREC resistance in Guangdong, several limitations should be considered:

• Geographic and temporal scope: Data are limited to eight hospitals in one province over an 18-month period; findings may not generalize to other regions or timeframes.
• Lack of full genome sequencing: While PCR and MGEs were mapped, whole genome sequencing could provide finer resolution of resistance gene context and evolutionary dynamics.
• Clinical outcomes: The study focused on molecular and epidemiological data, with limited linkage to patient outcomes or treatment efficacy, which is critical for translational impact.
• Antibiotic panel: The susceptibility profile did not include all clinically relevant antibiotics or novel therapeutic combinations now under consideration for CREC and multidrug-resistant Enterobacteriaceae.

Nevertheless, the high rate of successful CEG transfer and the wide diversity of MGEs underscore the relevance of these findings for antibiotic resistance surveillance and laboratory research in similar contexts worldwide.

Research Support Resources

Researchers aiming to investigate resistance mechanisms or optimize laboratory protocols for multidrug-resistant Enterobacteriaceae can leverage robust tools such as Amikacin (BAY416651) Aminoglycoside Antibiotic (SKU B3431). This semi-synthetic aminoglycoside is widely used in antibiotic resistance research due to its activity as a bacterial protein synthesis inhibitor and its resistance to most aminoglycoside-modifying enzymes, except for select AAC (6')-I types. Protocols and workflow enhancements for using Amikacin in the study of CREC and Klebsiella pneumoniae are discussed in detail in referenced internal articles, supporting reproducible and high-fidelity experimental designs. When working with multidrug-resistant isolates, selection of well-characterized agents like BAY416651—available from APExBIO—can support consistent resistance profiling and mechanistic studies.