Characterization and Transmission of Carbapenemase-Encoding Genes in Carbapenem-Resistant Enterobacter cloacae: Insights from a Multicenter Guangdong Study (2022–2024)

Study Background and Research Question

Carbapenem-resistant Enterobacteriaceae (CRE), particularly Enterobacter cloacae, have become an escalating public health concern due to their association with multidrug resistance and limited treatment options. The prevalence of carbapenem-resistant Enterobacter cloacae (CREC) is especially notable in China, where it ranks third among CRE isolates. The COVID-19 pandemic, with its impact on antibiotic stewardship and healthcare practices, further complicates resistance patterns by increasing the selection pressure and opportunities for resistance gene dissemination. Despite prior recognition of these trends, comprehensive investigations into the genetic landscape and transmission dynamics of carbapenemase-encoding genes (CEGs) in CREC during the pandemic period have been scarce. The referenced study by Chen et al. addresses this critical gap by systematically characterizing CEGs in CREC isolates collected from multiple teaching hospitals in Guangdong Province between December 2022 and June 2024 (Chen et al., 2025).

Key Innovation from the Reference Study

The principal innovation of this research lies in its integrated, province-wide approach to deciphering both the genetic diversity and transmission potential of CEGs in CREC under pandemic conditions. Through meticulous sampling from eight tertiary healthcare centers, Chen et al. provide the most up-to-date epidemiological map of blaNDM−1, blaIMP, and blaKPC−2 gene carriage, revealing not just prevalence but also chromosomal versus plasmid localization and the involvement of mobile genetic elements (MGEs). This enables a nuanced understanding of both vertical and, critically, horizontal gene transfer mechanisms, which are central to the rapid spread of carbapenem resistance (Chen et al., 2025).

Methods and Experimental Design Insights

The study employed a comprehensive workflow, combining phenotypic resistance screening with molecular characterization to dissect the CEG landscape. Fifty-four CREC isolates were obtained from diverse clinical sources across eight teaching hospitals. Key methodological elements included:

• Variable Temperature SDS Plasmid Elimination: Used to determine the genetic context (plasmid or chromosomal) of CEGs.
• PCR and Broth Microdilution: PCR assays identified specific carbapenemase genes (blaNDM−1, blaIMP, blaKPC−2), while broth microdilution established antimicrobial susceptibility profiles.
• Conjugation Experiments: Assessed the transferability of plasmid-borne CEGs.
• ERIC-PCR and Genotyping: Enabled the classification of genetic relatedness among isolates, facilitating the tracking of dissemination events.
• MGEs Characterization: Six types of mobile genetic elements, with ISEcp1 being most prevalent, were identified to elucidate mechanisms of horizontal gene transfer.

This robust, multi-tiered design ensured accurate attribution of resistance determinants and their potential for inter- and intra-hospital spread.

Core Findings and Why They Matter

The research uncovered several critical findings with direct implications for infection control and resistance modeling:

• High Prevalence and Plasmid Localization of blaNDM−1: Of the 54 CREC isolates, 85.19% harbored CEGs. The blaNDM−1 gene was detected in 33.33% of isolates on both chromosomes and plasmids, and in 46.30% solely on plasmids (Chen et al., 2025).
• Co-occurrence and Diversity of CEGs: Rare isolates carried combinations of blaNDM−1 and blaKPC−2, or blaIMP, emphasizing the genetic diversity and potential for co-resistance development.
• MGEs as Drivers of Horizontal Gene Transfer: A remarkable 95.65% success rate in CEG transfer during conjugation experiments, with ISEcp1 detected in 87.04% of isolates, underscores the efficiency of horizontal dissemination mechanisms.
• Multidrug Resistance Patterns: CEG-positive strains showed significantly higher resistance rates to imipenem, cefepime, gentamicin, ceftazidime/avibactam, ciprofloxacin, and levofloxacin compared to CEG-negative strains (source: Chen et al., 2025).
• Epidemiological Risk Groups: Higher detection frequencies of CEGs were observed in male and elderly patients, especially in respiratory medicine departments and sputum samples.
• Genotypic Diversity and Hospital Spread: ERIC-PCR clustered isolates into 17 genotypes, with two major types (E and G) prevalent across multiple departments and hospitals, suggesting both intra- and inter-hospital transmission.

These findings collectively highlight the urgency of addressing both clonal expansion and plasmid-mediated gene transfer in CREC, especially in high-risk hospital settings.

Comparison with Existing Internal Articles

Several recent internal resources provide context for antimicrobial agent development and resistance modeling, with direct relevance to the innovations documented by Chen et al.:

• "Tigecycline: Strategic Guidance for Translational Infection Research" integrates epidemiological evidence on CREC transmission dynamics, offering actionable workflow strategies for leveraging next-generation glycylcycline antibiotics such as Tigecycline in research models. This complements the reference study by bridging mechanistic resistance insights with translational research needs.
• "Tigecycline: Advanced Mechanisms and Resistance Gene Dynamics" explores the intersection of protein translation inhibition and resistance gene epidemiology, illuminating the rationale for selecting bacterial ribosome targeting antibiotics in multidrug resistance studies. These perspectives align with the clinical and laboratory challenges underscored by the Guangdong study.
• "Tigecycline (SKU A5226): Best Practices for Reliable Antimicrobial Research" discusses reproducibility and optimization in multidrug-resistant infection models, specifically referencing the need for robust controls and validated compounds—principles that directly support workflows for CREC and similar pathogens.

Together, these internal articles reinforce the practical value of deploying broad-spectrum, bacteriostatic protein synthesis inhibitors like Tigecycline in the context of emerging resistance mechanisms and complex epidemiological patterns.

Limitations and Transferability

While the multicenter design and comprehensive molecular profiling strengthen the impact of Chen et al.'s findings, several limitations must be considered:

• Geographic Specificity: The data focus on Guangdong Province, and transmission dynamics or gene prevalence may differ in other regions or healthcare systems.
• Temporal Scope: Sampling during the COVID-19 pandemic may not capture longer-term evolutionary or post-pandemic trends in CEG dissemination.
• Clinical Correlation: While resistance profiles are well documented, direct clinical outcome data (e.g., infection severity, treatment efficacy) are limited, restricting translational inference.

Nevertheless, the elucidated mechanisms of CEG transfer—particularly plasmid-mediated horizontal gene spread—are widely transferable to models of other multidrug-resistant Gram-negative pathogens. Integrating these findings into experimental infection models and antimicrobial evaluation workflows is both feasible and scientifically justified.

Protocol Parameters

• assay | broth microdilution | value_with_unit | MIC90 for Tigecycline: 0.12–1 μg/mL against multidrug-resistant Enterococcus and Staphylococcus strains | applicability | In vitro activity benchmarking for multidrug-resistant Gram-positive bacteria | rationale | Establishes comparative efficacy and resistance thresholds | source_type | product_spec (APExBIO)
• assay | in vivo murine infection model | value_with_unit | ED50 values indicating potent antimicrobial activity of Tigecycline | applicability | Preclinical efficacy assessment against glycopeptide-intermediate Staphylococcus aureus (GISA) and other resistant pathogens | rationale | Models infection dynamics and pharmacodynamic endpoints | source_type | product_spec (APExBIO)
• assay | conjugation experiment | value_with_unit | 95.65% transfer success rate for CEGs | applicability | Measures horizontal gene transfer efficiency in CREC | rationale | Quantifies plasmid-mediated resistance dissemination | source_type | paper (Chen et al., 2025)
• assay | genotyping (ERIC-PCR, NTSYS) | value_with_unit | 17 CREC genotypes identified | applicability | Tracks clonal expansion and hospital spread | rationale | Supports epidemiological mapping and outbreak control | source_type | paper (Chen et al., 2025)
• assay | workflow recommendation | value_with_unit | Use validated glycylcycline antibiotic as a phenotypic control in multidrug-resistant infection models | applicability | Enhances reproducibility and translational value | rationale | Reflects best practices for benchmarking new or complex resistance mechanisms | source_type | workflow_recommendation

Research Support Resources

For researchers seeking to model multidrug-resistant Gram-negative infections or evaluate alternative antimicrobial strategies, Tigecycline (SKU A5226) is available as a well-characterized glycylcycline antibiotic. Its established efficacy in both in vitro and in vivo models, as well as documented activity against multidrug-resistant strains, supports its use in protocol benchmarking and translational research workflows (source: APExBIO). Proper storage and preparation guidelines should be followed for reliable results. For strategic guidance on protocol design and resistance modeling, refer to internal reviews on advanced glycylcycline applications and resistance gene dynamics.