Skip to main content

Investigation of in vitro susceptibility and resistance mechanisms to amikacin among diverse carbapenemase-producing Enterobacteriaceae

Abstract

Objective

This study aims to assess the in vitro drug susceptibility of various Carbapenemase-Producing Enterobacteriaceae (CPE) genotypes and elucidate the underlying mechanisms of amikacin resistance.

Methods

A total of 72 unique CPE strains were collected from the Second Hospital of Jiaxing between 2019 and 2022, including 51 strains of Klebsiella pneumoniae, 11 strains of Escherichia coli, 6 strains of Enterobacter cloacae, 2 strains of Klebsiella aerogenes, 1 strain of Citrobacter freundii, and 1strain of Citrobacter werkmanii. Among these strains, 24 carried blaKPC gene, 20 carried blaNDM gene, 23 carried blaOXA−48−like gene, and 5 carried both blaKPC and blaNDM. We measured the in vitro activity of amikacin and other common antibiotics. Strains carrying blaOXA−48-like gene were selected for whole genome sequencing (WGS) via next-generation sequencing to identify genes related to antimicrobial resistance (AMR) and virulence factor (VF).

Results

Out of the 72 CPE strains tested, 41.7% exhibited resistance to amikacin. The drug resistance rates for K. pneumoniae, E. coli, and Enterobacter spp. were 51.0%, 27.3%, and 10.0%, respectively. The majority of the CPE strains (> 90%) displayed resistance to cephalosporins and carbapenems, while most of them were sensitive to polymyxin B and tigecycline (97.2% and 94.4%). The amikacin resistance rate was 100% for strains carrying blaOXA−48, 20.8% for those with blaKPC, 5.0% for those with blaNDM, and 20.0% for those with both blaKPC and blaNDM. These differences were statistically significant (P < 0.05). Through sequencing, we detected aminoglycoside resistance genes rmtF and aac(6’)-Ib, VF genes iucABCD and rmpA2 in OXA-48-producing multidrug resistance and highly virulent strains. These genes were located on a IncFIB- and IncHI1B-type plasmid, respectively. Both plasmids were highly homologous to the plasmid from OXA-232 strains in Zhejiang province and Shanghai province. Integration of these resistance genes into the IncFIB plasmid, facilitated by the IS6 and/or Tn3 transposons, resulted in OXA232-producing K. pneumoniae with amikacin resistance.

Conclusion

This study identified significant amikacin resistance in CPE strains, particularly in those carrying the blaOXA−48 gene. Resistance genes rmtF and aac(6’)-Ib were identified on plasmids. These results highlight the need for careful monitoring of amikacin resistance.

Peer Review reports

Introduction

The rise of antimicrobial resistance (AMR) among pathogenic bacteria presents a significant challenge to public health globally. Among the multidrug-resistant organisms, Carbapenemase-Producing Enterobacteriaceae (CPE) are particularly concerning due to their capacity to hydrolyze a broad spectrum of β-lactam antibiotics, including carbapenems, which are often considered the last line of defense against severe bacterial infections [1]. This resistance compromises treatment efficacy and limits therapeutic options, leading to increased morbidity and mortality [2].

Carbapenemase enzymes, such as Klebsiella pneumoniae carbapenemase (KPC), New Delhi metallo-β-lactamase (NDM), and oxacillinase-48 (OXA-48), are widely recognized contributors to the resistance phenotype in Enterobacteriaceae. The spread of these resistance genes, often facilitated by plasmids, poses a significant threat in both hospital and community settings [3]. While much attention has been focused on the resistance conferred by these enzymes against β-lactam antibiotics, the increasing prevalence of resistance to other critical antibiotic classes, such as aminoglycosides, has also become a pressing concern [4].

Amikacin, an aminoglycoside antibiotic, has been utilized as a treatment option for infections caused by multidrug-resistant Enterobacteriaceae, including CPE [5]. However, resistance to amikacin is emerging, further complicating the management of these infections [6]. The mechanisms underlying amikacin resistance in CPE are multifaceted, involving enzymatic modification, target site alterations, and efflux pump overexpression [7]. Given the already limited therapeutic options against CPE, understanding the specific mechanisms of resistance to amikacin within this context is crucial for informing effective treatment strategies.

This study aims to evaluate the in vitro drug susceptibility of various CPE genotypes and elucidate the underlying mechanisms of amikacin resistance. By analyzing 72 unique CPE strains collected from the Second Hospital of Jiaxing between 2019 and 2022, we seek to characterize the resistance patterns and identify key genetic factors contributing to amikacin resistance. Our findings will enhance the understanding of resistance mechanisms and support the development of targeted interventions to manage infections caused by CPE.

Materials and methods

Sample collection

A total of 72 unique CPE strains were collected from the Second Hospital of Jiaxing between 2019 and 2022. These strains consisted of 51 Klebsiella pneumoniae, 11 E. coli, 6 Enterobacter cloacae, 2 Klebsiella aerogenes, 1 Citrobacter freundii, and 1 Citrobacter werkmanii. The carbapenem-resistant strains (CRE) were identified according to the Clinical and Laboratory Standards Institute (CLSI) M100-S32 document, with a minimal inhibitory concentration (MIC) of imipenem ≥ 2.0 mg/L or meropenem ≥ 2.0 mg/L and ertapenem ≥ 0.5 mg/L [3]. Species identification was confirmed by MALDI-TOF/MS system. These CRE strains were isolated from various sources, including sputum (32, 44.4%), urine (21, 29.2%), bile (7, 9.7%), wound secretions (3, 4.2%), catheter drainage fluid (3, 4.2%), bronchoalveolar lavage fluid (2, 8.0%), blood (2, 8.0%), cerebrospinal fluid (1, 1.4%) and hydrothorax (1, 1.4%.). We identified carbapenemase genes (blaKPC, blaNDM, blaIMP, blaVIM, and blaOXA−48-like) in the CRE strains using multiplex PCR, followed by a preliminary screening of carbapenemase expression via colloidal gold immunochromatography. Escherichia coli ATCC 25,922 served as the quality control strain. This study was approved by the hospital ethics committee (Approval No: JXEY-2021SW044).

Instruments and reagents

The following instruments and reagents were exploited in our study: MALDI-TOF MS (Biomerieux, France); Phoenix M50 Automated microbial System (BD, USA); Carbapenemase detection kit (colloidal gold immunochromatography) (CARBA 5, Shanghai Fosun Diagnostics); Source of DNA extraction kit (Beijing Tiangen Biological Co., LTD.); Broth microdilution drug sensitivity reagent (Wenzhou Kangtai Biotechnology Co., LTD.); NovaSeqTM 6000 (Illumina, USA) and PacBio Sequel (PacBio, Inc.) were used for next-generation sequencing and third-generation sequencing, respectively.

Antimicrobial susceptibility testing

We conducted antimicrobial susceptibility testing (AST) using the broth microdilution method as recommended by the Clinical and Laboratory 64 Standards Institute (CLSI) [8]. We assessed the susceptibility of 72 CPE strains to a range of antimicrobial agents, including: cephalosporins (ceftazidime, ceftriaxone, cefepime), β-lactam/β-lactamase inhibitor combinations (cefoperazone-sulbactam, piperacillin-tazobactam, ceftazidime-avibactam), carbapenems (ertapenem, imipenem, meropenem), monobactam (aztreonam), fluoroquinolones (ciprofloxacin, levofloxacin), folate metabolic pathway inhibitors 68 (sulfamethoxazole), aminoglycosides (amikacin and gentamicin), polymyxin B, and tigecycline. We determined the MICs for these 17 antimicrobial agents. The cefoperazone-sulbactam refers to the break point of cefoperazone, and for tigecycline, we used the MIC breakpoints for Enterobacteriaceae (susceptible, ≤ 2 mg/L; resistant, ≥ 8 mg/L) issued by the Food and Drug Administration as our reference points. Quality control strains for AST included Escherichia coli ATCC 25,922, E. coli ATCC 35,218 and K. pneumoniae ATCC 700,603.

Detection of carbapenemase gene by enzyme Immunochromatography

Three freshly isolated colonies were selected, resuspended in 100 µL of sample diluent, and added ten drops of this solution to the test wells. After 10 min, the presence or absence of bands was observed as an indication of carbapenem resistance.

Confirmation of carbapenemase genotype

The monoclonal CPE strain was cultured on solid LB medium at 37℃ for 24 h. A single colony was selected and incubated in LB liquid medium overnight at 37℃ and 220 rpm. A bacterial culture of 1 mL was centrifuged at 10,000 rpm for 1 min, and the supernatant was removed, leaving the bacterial pellet. Genomic DNA was extracted using the Wizard® Genomic DNA Purification Kit (Promega, Madison, WI). For isolates showing non-susceptibility to carbapenems, we screened for common carbapenemase genes (blaKPC, blaNDM, blaOXA− 48, blaVIM, and blaIMP) through PCR amplification using specific primers based on the work of Rehman MU (as shown in Table 1). The reaction system consisted of 20 µL: Premix TaqTM 6 µL, 1 µL each of upstream and downstream primers (50 µmol/L), 2 µL DNA template, and 2 µL sterile double-distilled water. The reaction conditions were as follows: 94 ℃ for 5 min; 94 ℃ for 30 s, 57 ℃ for 40 s, and 72 ℃ for 1 min, for 35 cycles; and 72 ℃ for 7 min.

Table 1 Primers used for carbapenemase detection

Short-read and long-read whole genome sequencing

Upon the initial growth of transferred colonies over a span of two weeks, we scraped two rings of medium slant, placed them in a 1.5 ml centrifuge tube with 300 µl of deionized water, and subjected them to inactivation at 80 °C for 30 min.

For short-read sequencing, genomic DNA was extracted from the inactivated bacterial cells using the Qiagen DNeasy Blood & Tissue Kit, following the manufacturer’s instructions. DNA quality and concentration were assessed using a NanoDrop spectrophotometer and Qubit fluorometer, respectively. The DNA library was then prepared using the NEB Next Ultra II DNA Library Prep Kit for Illumina. The library preparation included fragmentation of the DNA to an average insert size of approximately 350 bp, followed by end repair, adapter ligation, and PCR enrichment. The libraries were sequenced on the Illumina NovaSeq 6000 platform, generating paired-end reads of 150 bp (PE150). The sequencing run produced a total of approximately 0.6 to 1.2 Gb of data per sample, with an average coverage depth of 100x. Raw reads were quality-trimmed using fastp v0.23.2, and the resulting clean reads were assembled with Unicycler v0.5.0 under default settings [9, 10].

For long-read sequencing, high molecular weight genomic DNA was isolated using the phenol-chloroform extraction method to ensure integrity. The DNA library for third-generation sequencing was prepared using the PacBio SMRTbell Express Template Prep Kit 2.0. The library was size-selected for fragments larger than 10 kb using the BluePippin system. Sequencing was performed on the PacBio Sequel platform, producing continuous long reads (CLR). On average, approximately 5 Gb of long-read data was generated per sample, with an N50 read length of around 15 kb. Raw PacBio long reads were quality-filtered using Filtlong v0.2.1 (https://github.com/rrwick/Filtlong). A hybrid assembly was then performed with the trimmed long and short reads using Unicycler v0.5.0 under default settings, producing a complete genome assembly.

Detection of aminoglycoside antimicrobial resistance genes

Assembly of sequencing raw data fragments was carried out using Unicycler v0.5.0 assembly software, while Prokka v1.14.6 software was utilized for genome annotation of the assembled results [10, 11]. RGI v5.2.1 software was employed for drug resistance gene functional annotation based on the CARD database [12]. The identification of aminoglycoside resistance genes was conducted using the “strict” detection mode in RGI, with cutoff values of ≥ 95% identity and ≥ 80% coverage to ensure high confidence in gene detection.

Detection of mobile genetic elements

The assembled plasmid sequences were identified with the PLSDB database using the ‘screen’ command of Mash [13]. For plasmid screening, a maximum p-value of 1e-5 and a minimum identity of 90% were applied to ensure accurate identification while minimizing biases. The mobility and genotyping of plasmids were predicted by MOB-suite [14]. To compare the plasmids, we performed a megaBLAST search against the NCBI GenBank database. For other types of Mobile genetic elements (MGEs), Phigaro, ICEfinder, digIS, and IslandPath-DIOMB were utilized with default parameters to detect prophage, integrative and conjugative element (ICE), insertion sequences (IS), and genomic island (GI), correspondingly [15,16,17,18].

Statistical methods

The statistical analysis was performed using SPSS 18.0 software. Count data were expressed as rates, and group comparisons was analyzed using the χ2 test. Rank data were analyzed using the rank sum test (Wilcoxon two-sample comparison method). P-values less than 0.05 were considered statistically significant.

Results

Drug susceptibility testing of 72 CPE strains to amikacin

Among the enrolled 72 CPE strains, all were found to possess carbapenemase genes. Of these, 24 strains carried blaKPC, 23 carried blaOXA−48−like, 20 carried blaNDM, and 5 strains carried both blaKPC and blaNDM genes (Supplementary Table 1). Each of these genes was expressed, confirming that all strains were capable of producing carbapenemases and contributing to the observed resistance profiles. When testing 72 CPE strains for their susceptibility to amikacin, we found that 40.3% of them were resistant to the drug (Table 2). Specifically, K. pneumoniae had the highest amikacin-resistance rate at 51.0%, followed by Escherichia coli at 27.3%, and Enterobacter spp. at 10.0%.

Table 2 Antibacterial activity of amikacin against all strains (MICs, mg/L)

In vitro antimicrobial susceptibility

The majority of CPE strains (> 90%) exhibited resistance to various antibiotics, including cephalosporins, cefoperazone-sulbactam, piperacillin-tazobactam, aztreonam, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, and carbapenems (Table 3). Among the isolates, 27.8% (20/72) were resistant to ceftazidime-avibactam, 41.7% (30/72) to amikacin, and 79.2% (57/72) to gentamicin. Remarkably, polymyxin B and tigecycline exhibited strong antibacterial activity against CPE strains, with sensitivity rates of 97.2% and 94.4%, respectively. In this set of 72 CPE strains, the amikacin resistance rate was influenced by the type of carbapenemase gene present. Specifically, blaOXA−48-like carrying isolates showed a 100% resistance rate to amikacin, while for blaKPC-carrying strains, the resistance rate was 20.8%. Among blaNDM-carrying strains, the resistance rate was 5.0%, and for strains carrying both blaKPC and blaNDM genes, the resistance rate was 20.0%.

Table 3 Susceptibility of strains carrying different β-lactamase genes to clinical commonly used antibiotics and amikacin (%)

Prevalence of aminoglycoside resistance genes in bla OXA−48-like strains

All 23 CPE strains carrying blaOXA−48 were identified as K. pneumoniae, and DNA sequencing results revealed that they were blaOXA−232, ST15 clones. More importantly, all strains encode the 16 S rRNA methyltransferase rmtF, which confers high-level resistance to multiple aminoglycosides, and the aminoglycoside 6’-N-acetyltransferase aac(6’)-Ib, which confers dual resistance to aminoglycosides and fluoroquinolones through its fluoroquinolone-acetylating activity.

Genetic context of plasmids carrying aminoglycoside resistance genes

We randomly selected 14 strains for whole genome sequencing using the Illumina platform. These strains were chosen to represent a range of antimicrobial resistance profiles and genetic backgrounds. One of these strains was then further sequenced using the PacBio platform. All strains were MDR K. pneumonia with multiple AMR genes including gryA mutations, rmtF, aac(6’)-Ib, blaCTX−M−15, SHV-28, arr-2, and blaOXA−232. An average number of AMR genes among these strains was 40 (between 39 and 44). Plasmid profiling revealed that all these strains had the same plasmid pattern. In addition, we successfully obtained the complete genome sequence of one representative strain through hybrid assembly. We identified a IncFIB-type plasmid (plas2) within the complete genome carrying the aac(6’)-Ib and rmtF genes. Plas2 was classified as an IncFIB-type plasmid, which was non-mobilizable for lacking relaxase, mate-pair formation and oriT sequences. Online BLASTn analysis of the NCBI nucleic acid database revealed five highly homologous plasmids for plas2 sequences, as shown in Table 4. The results demonstrated that most of these plasmids were derived from ST15 K. pneumoniae strains, with only one plasmid being isolated from K. pneumoniae strain 47,733 of ST147. The earliest isolation of these plasmids’ dates back to 2011.

Table 4 Plasmids with high homology with plas2 in NCBI database

Within the plasmid, a genomic island (GI) sequence spanning 8,553 base pairs was identified, encompassing both the aac(6’)-Ib and rmtF genes. Furthermore, insertion sequence (IS) analysis unveiled the presence of an IS6 family transposon (IS6100), and its end was immediately followed by a Tn3 family transposon (ISXc4). To compare plas2 with other plasmids, whole-genome alignments were conducted for pWSD411_4, p47733_IncFIB, p1605752FIB_2, and pPMK1-B, and the results were visualized using BRIG software [19]. The locations of antimicrobial resistance genes and IS transposons were distinctly marked, as illustrated in Fig. 1. The findings revealed that, except for plas2 and pWSD411_4, the remaining three IncFIB-type plasmids previously isolated from K. pneumoniae lacked the sequence segment encompassing the GI.

Fig. 1
figure 1

Genome comparison circle of plas2 and its homologous plasmids

Note: The inner circle represents the position coordinate of the plas2 plasmid genome sequence. From inside to outside: Genomic GC content; 2. Genomic GC Skew value; 3. Comparison of pWSD411_4, p47733_lncFIB, p1605752FIB_2 and pPMK1-B with plas2 plasmid; 4. Location of resistance genes aac(6’)-Ib and rmtF, transposons IS6100 and ISXc4 on plas2 plasmid genome

Convergence of virulence and resistance in a IncF-type plasmid

An average number of VFs among 14 genomes were 51.8 (between 50 and 52). Notably, all sequenced strains were hypervirulent for carrying aerobactin operons iucABCD and an activator for capsular polysaccharide (CPS) synthesis rmpA2, as aerobactin is specifically associated with growth in blood and is a stronger predictor of the hypervirulence phenotype. The genomic localization analysis revealed these VF genes were located on a IncHI1B-type plasmid (plas1). After the online BLAST search of the NCBI database, we retrieved seven homologous plasmids. Despite the heterogeneity observed in these plasmids, using plas1 as the reference sequence, the sequence coverage varies from 53 to 99% (Fig. 2). However, the average sequence identity and coverage for iucABCD and rmpA2 are 95.3% and 99%, respectively. In addition, this VF plasmid was predicted to be non-mobilizable for lacking relaxase, mate-pair formation and oriT sequences.

Fig. 2
figure 2

Genome comparison circle of IncHI1B-type plas1 and its homologous plasmids

Note: The inner circle represents the position coordinate of the plas1 plasmid genome sequence. From inside to outside: Genomic GC content; 2. Genomic GC Skew value; 3. Comparison of pWSD411_2, p2723-175k, p2018C06-156-223k, pkp7450-1, pCRKP_35 and pBA6740_1 with plas2 ; 4. Location of VF genes iucABCD and rmpA2 on plas1 plasmid genome

Discussion

Carbapenemase production is the most common resistance mechanism of Enterobacteriaceae bacteria against carbapenems [20]. In clinical settings, the most commonly encountered carbapenemase belong to three Ambler classes: Ambler A serine hydrolases (such as KPC), Ambler B metalloenzymes (such as NDM), and Ambler D serine hydrolases (such as OXA-48). This group of data and related literatures suggested that the CPE had a high resistance rate to commonly used antibiotics in the clinic [21, 22]. This study showed that most of the CPE strains (> 90%) were resistant to cephalosporins, cefoperazone sulbactam, piperacillin-tazobactam, aztreonam, ciprofloxacin, trimethoprim-sulfamethoxazole, and carbapenems. Interestingly, 72.2% and 58.3% strains were susceptible to ceftazidime-avibactam and amikacin, respectively. However, aminoglycoside susceptibility varied among different CPE isolates. For instance, KPC-2-producing K. pneumoniae strains isolated in Taiwan, China, exhibited a 69% resistance rate to amikacin, while E. coli strains showed only 3% resistance rate [23]. Our study results indicate a 41.7% resistance rate of 72 CPE strains to amikacin (with K. pneumoniae demonstrating a resistance rate of 51.0%, and E. coli demonstrating a resistance rate of 27.3%).These findings are consistent with a domestic report by Hu Fumin et al., which demonstrated resistance rates of 49.6% [24].

Table 3 indicates that the drug susceptibility of Carbapenemase-producing Enterobacteriaceae strains carrying different carbapenemase-encoding genes to amikacin varies significantly in vitro. Avibactam in ceftazidime-avibactam has a wide range of inhibitory activities against B-lactamases such as various class A enzymes (such as CTX-M-15, KPC-2, etc.), class C enzymes (AmpC) and some class D enzymes (such as OXA-48). The resistance rate of blaOXA−48-like carrying K. pneumoniae to amikacin was 100%, and it cannot inhibit the B-type metalloenzyme (NDM-1), which leads to ceftazidime-avelbactam resistance to the CPE carrying blaNDM [25]. It’s worth noticing though, amikacin resistance in blaOXA−48-like K. pneumoniae was 100%, with extremely high resistance levels (MIC values ≥ 1024ug/mL), consistent with the results reported by Han R [24]. In this study, WGS showed that all strains carried the aac(6’)-Ib aminoglycoside modifying enzyme and 16 S rRNA methylase gene rmtF. However, only 5% of the 20 Enterobacteriaceae strains carrying the blaNDM genotype were resistant to amikacin, with MIC values ranging from 0.5 to 32ug/mL. aac(6’)-Ib and rmtF genes were not further detected in the amikacin-resistant E. coli strains.

In this study, we observed that CPE strains carrying blaOXA−48 exhibited an extremely high level of resistance to amikacin, with both the MIC50 and MIC90 exceeding 1024 ug/mL. The aac(6’)-Ib gene encodes an acetyltransferase enzyme that modifies aminoglycosides, including amikacin, by adding an acetyl group. This modification impairs the antibiotic’s ability to bind to bacterial ribosomes, thereby reducing its effectiveness. The rmtF methylase gene encodes a methyltransferase enzyme that specifically methylates the 16 S rRNA within the ribosomal RNA, preventing the binding of aminoglycosides like amikacin. Both of these mechanisms contribute to the resistance of bacteria to aminoglycosides by altering the drug’s target site or modifying the drug itself [26].

Ten groups of methylases have been found, including armA, RmtABCDEFGH, npmA. Among those, armA is dominant in Europe, armA and RmtB are dominant in 191 North America, and RmtD is dominant in Latin America [26]; In China, armA and RmtB are the main methylases. However, the presence of rmtF, as a new member of the aminoglycoside 16 S rRNA N7 G1405 methyltransferase family, was quite rare in China previously. In fact, recent reports have shown its emergence, often in conjunction with the blaOXA−232 carbapenemase gene [27, 28]. Importantly, the prevalence of rmtF is significantly associated with carbapenemase genotypes and ST clones of strains in different regions. For instance, rmtF is mainly isolated from Enterobacteriaceae bacteria producing blaNDM-type carbapenemase in India and the United Kingdom, while in Switzerland, it is mainly isolated from CPE strains producing blaKPC−2 and blaOXA−232, with ST231 as the dominant clone [29].

The identification of the IncFIB-type plasmid (plas2) carrying the aac(6’)-Ib and rmtF genes has significant clinical implications, particularly in the context of treatment strategies for infections caused by multidrug-resistant K. pneumoniae. The presence of these resistance genes within a non-mobilizable plasmid suggests a potential for stable inheritance within bacterial populations, which could lead to persistent resistance issues in clinical settings [30]. Understanding the plasmid’s genomic features, such as the presence of GIs and transposons, allows for better prediction of gene transfer events and the spread of resistance. This knowledge could inform targeted therapeutic interventions, such as the development of inhibitors that block the activity of these specific resistance genes or the use of combination therapies to overcome the resistance conferred by these plasmids [31]. Moreover, monitoring the spread of such plasmids in clinical isolates could help in tailoring antibiotic stewardship programs and improving patient outcomes by preventing the dissemination of highly resistant strains [32].

This study revealed the presence of both virulence and AMR determinants on two F-type plasmids. Beisde, amidoglycoside resistance genes aac(6’)-Ib and rmtF were found only in the plasmids from China. In terms of time, aminoglycoside resistance genes were only found in the plasmid after 2018, and it was preliminarily speculated that the plasmid was exogenously acquired. Further detection of mobile genetic elements suggested that these two aminoglycoside resistance genes might have been acquired from K. pneumoniae and integrated into the IncFIB plasmid through IS sequences. Since the IncFIB plasmid is non-mobilizable and based on the data from the NCBI nucleic acid database, there is no evidence that the aminoglycoside resistance phenotype of K. pneumoniae strains isolated in this project is caused by the transfer of plasmids carrying these resistance genes. These findings suspected that there is a clone of ST15 MDR and hypervirulent K. pneumoniae that has recently spread aminoglycoside resistance in eastern China. Therefore, attention should be paid to the clonal spread of strains from regions outside the local area in clinical practice.

Conclusion

The epidemic strains of CPE associated with different types of carbapenemase vary from one country or region to another, and their resistance to amikacin also differs. In clinical practice, monitoring amikacin resistance involves assessing drug resistance phenotype, determining MIC values, and identifying specific resistance genes. Additionally, plasmid analysis serves as an effective complementary tool for medical institutions to efficiently screen drug resistance genes and understand their potential for transmission. Based on these findings, appropriate monitoring strategies and infection control measures can be implemented to prevent the occurrence of nosocomial (hospital-acquired) infections. This proactive approach is crucial for addressing the evolving landscape of antibiotic resistance and safeguarding patient safety.

Data availability

Genome sequences of all 14 strains have been deposited in the NCBI Genbank database under BioProject accession no. PRJNA975316.

References

  1. Nordmann P, Dortet L, Poirel L. Carbapenem resistance in Enterobacteriaceae: here is the storm! Trends in molecular medicine. 2012;18:263–72.

  2. Oli AN, Itumo CJ, Okam PC, Ezebialu IU, Okeke KN, Ifezulike CC, et al. Carbapenem-resistant enterobacteriaceae posing a dilemma in effective healthcare delivery. Antibiotics. 2019;8:156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Arcari G, Carattoli A. Global spread and evolutionary convergence of multidrug-resistant and hypervirulent Klebsiella pneumoniae high-risk clones. Pathogens Global Health. 2023;117:328–41.

    Article  CAS  PubMed  Google Scholar 

  4. Bush K, Bradford PA. Epidemiology of β-Lactamase-producing pathogens. Clin Microbiol Rev. 2020;33:e00047–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Farhan SM, Raafat M, Abourehab MAS, Abd El-Baky RM, Abdalla S, EL-Gendy AO et al. Effect of Imipenem and Amikacin Combination against Multi-drug Resistant Pseudomonas aeruginosa. Antibiotics. 2021;10.

  6. Atamna-Mawassi H, Huberman-Samuel M, hershcovitz S, Karny-Epstein N, Kola A, Cortés LEL, et al. Interventions to reduce infections caused by multidrug resistant Enterobacteriaceae (MDR-E): a systematic review and meta-analysis. J Infect. 2021;83:156–66.

    Article  CAS  PubMed  Google Scholar 

  7. Shakil S, Khan R, Zarrilli R, Khan AU. Aminoglycosides versus bacteria – a description of the action, resistance mechanism, and nosocomial battleground. J Biomed Sci. 2008;15:5–14.

    Article  CAS  PubMed  Google Scholar 

  8. CLSI C. Performance standards for antimicrobial susceptibility testing. Clin Lab Stand Inst. 2016;35:16–38.

    Google Scholar 

  9. Chen S, Zhou Y, Chen Y, Gu J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–90.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol. 2017;13:e1005595.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.

    Article  CAS  PubMed  Google Scholar 

  12. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 2019. gkz935.

  13. Schmartz GP, Hartung A, Hirsch P, Kern F, Fehlmann T, Müller R, et al. PLSDB: advancing a comprehensive database of bacterial plasmids. Nucleic Acids Res. 2022;50:D273–8.

    Article  CAS  PubMed  Google Scholar 

  14. Robertson J, Nash JH. MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb Genomics. 2018;4.

  15. Starikova EV, Tikhonova PO, Prianichnikov NA, Rands CM, Zdobnov EM, Ilina EN, et al. Phigaro: high-throughput prophage sequence annotation. Bioinformatics. 2020;36:3882–4.

    Article  CAS  PubMed  Google Scholar 

  16. Puterová J, Martínek T. digIS: towards detecting distant and putative novel insertion sequence elements in prokaryotic genomes. BMC Bioinformatics. 2021;22:258.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Liu M, Li X, Xie Y, Bi D, Sun J, Li J, et al. ICEberg 2.0: an updated database of bacterial integrative and conjugative elements. Nucleic Acids Res. 2019;47:D660–5.

    Article  CAS  PubMed  Google Scholar 

  18. Bertelli C, Brinkman FS. Improved genomic island predictions with IslandPath-DIMOB. Bioinformatics. 2018;34:2161–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Alikhan N-F, Petty NK, Zakour NLB, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics. 2011;12:402.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lee Y-L, Chen H-M, Hii M, Hsueh P-R. Carbapenemase-producing enterobacterales infections: recent advances in diagnosis and treatment. Int J Antimicrob Agents. 2022;59:106528.

    Article  CAS  PubMed  Google Scholar 

  21. Chakraborty T, Sadek M, Yao Y, Imirzalioglu C, Stephan R, Poirel L, et al. Cross-border emergence of Escherichia coli producing the carbapenemase NDM-5 in Switzerland and Germany. J Clin Microbiol. 2021;59:10–1128.

    Article  Google Scholar 

  22. Zhang Y, Chen C, Wu J, Jin J, Xu T, Zhou Y, et al. Sequence-based Genomic Analysis Reveals Transmission of Antibiotic Resistance and virulence among carbapenemase-producing Klebsiella pneumoniae strains. mSphere. 2022;7:e00143–22.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lee C-M, Liao C-H, Lee W-S, Liu Y-C, Mu J-J, Lee M-C, et al. Outbreak of Klebsiella pneumoniae Carbapenemase-2-Producing K. pneumoniae sequence type 11 in Taiwan in 2011. Antimicrob Agents Chemother. 2012;56:5016–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Han R, Shi Q, Wu S, Yin D, Peng M, Dong D, et al. Dissemination of Carbapenemases (KPC, NDM, OXA-48, IMP, and VIM) among carbapenem-resistant Enterobacteriaceae isolated from adult and children patients in China. Front Cell Infect Microbiol. 2020;10:314.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li X, Zhao D, Li W, Sun J, Zhang X. Enzyme inhibitors: the best strategy to tackle Superbug NDM-1 and its variants. Int J Mol Sci. 2021;23:197.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sellera FP, Fuentes-Castillo D, Furlan JPR. One health spread of 16S ribosomal RNA methyltransferase-harboring gram-negative bacterial genomes: an overview of the Americas. Pathogens. 2023;12:1164.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wu X, Li X, Yu J, Shen M, Fan C, Lu Y et al. Outbreak of OXA-232-producing carbapenem-resistant Klebsiella pneumoniae ST15 in a Chinese teaching hospital: a molecular epidemiological study. Frontiers in Cellular and Infection Microbiology.

  28. Jia H, Zhang Y, Ye J, Xu W, Xu Y, Zeng W, et al. Outbreak of Multidrug-resistant OXA-232-Producing ST15 Klebsiella pneumoniae in a Teaching Hospital in Wenzhou, China. IDR. 2021;14:4395–407.

    Article  CAS  Google Scholar 

  29. Mancini S, Poirel L, Tritten M-L, Lienhard R, Bassi C, Nordmann P. Emergence of an MDR Klebsiella pneumoniae ST231 producing OXA-232 and RmtF in Switzerland. J Antimicrob Chemother. 2018;73:821–3.

    Article  CAS  PubMed  Google Scholar 

  30. Robertson J, Schonfeld J, Bessonov K, Bastedo P, Nash JHE. A global survey of Salmonella plasmids and their associations with antimicrobial resistance. Microb Genomics. 2023;9.

  31. Baquero F, Martínez JL, Lanza F, Rodríguez-Beltrán V, Galán J, San Millán JC. Evolutionary pathways and trajectories in Antibiotic Resistance. Clin Microbiol Rev. 2021;34:e00050–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mathers AJ, Peirano G, Pitout JDD. The role of epidemic resistance plasmids and international high-risk clones in the spread of Multidrug-Resistant Enterobacteriaceae. Clin Microbiol Rev. 2015;28:565–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work was supported by the Zhejiang Health Science and Technology Project (grant 2021KY1109) and Science and Technology Bureau of Jiaxing City (grant 2021AD30104).

Author information

Authors and Affiliations

Authors

Contributions

XS.L and C.F conceived of the presented idea. X.W, J.Y and M.S carried out the experiment. XC.L prepared figures. X.W and XS.L wrote the main manuscript text. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Xiaosi Li or Chenliang Fan.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethical Committee of the Second Affiliated Hospital of Jiaxing University. Informed consent was obtained from all of the participants involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, X., Li, X., Yu, J. et al. Investigation of in vitro susceptibility and resistance mechanisms to amikacin among diverse carbapenemase-producing Enterobacteriaceae. BMC Med Genomics 17, 240 (2024). https://doi.org/10.1186/s12920-024-02016-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12920-024-02016-0

Keywords