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. 2026 May 8;17(1):2668179. doi: 10.1080/21505594.2026.2668179

Genomic insights into multidrug-resistant bacteria: Emergence of mcr-1.1 in Escherichia coli, blaKPC-2 in Klebsiella pneumoniae and Serratia marcescens from clinical settings

Muhammad Fazal Hameed a,b,c, Muhammad Shoaib a,b,✉, Kai Peng a,b, Zhiqiang Wang a,b, Ruichao Li a,b,✉
PMCID: PMC13166193  PMID: 42102272

ABSTRACT

This study presents a comprehensive genomic analysis of multidrug-resistant (MDR) clinical isolates from Anhui Province, China, focusing on Escherichia coli, Klebsiella pneumoniae, and Serratia marcescens. The E. coli strain EC385 belong to ST1011 and rST1640 harbors multiple resistance and virulence determinants and five plasmids, including IncI2 and IncHI2, with a co-occurrence of mcr-1.1 with blaTEM-141, qnrS1, fosA3, rmtB, and dfrA14. Among K. pneumoniae isolates, KP304 (ST15/rST19202) and KP297 (ST15/rST19202) were carrying IncFII(pBK30683) and IncFIB plasmids, while KP69 (ST11/rST31218) harbored five plasmids, including IncHI1B and IncR. Notably, KP304, KP297, and KP69 exhibited MDR due to acquisition of blaKPC-2 along with other multiple resistance determinants including fosA6, tet(A), blaTEM-1B, blaCTX-M, aac(6)-Ib-cr (KP304 and KP297), and qnrS1 (KP69). In the current finding, S. marcescens is reported to carry blaKPC-2, alongside IncFII(pBK30683) and IncR plasmids. These findings highlight the genomic diversity and alarming spread of resistance mechanisms in clinical pathogens, emphasizing the urgent need for surveillance to combat the antimicrobial resistance.

KEYWORDS: Multidrug-resistance, whole genome sequencing, colistin resistance, carbapenem resistance, extended-spectrum beta-lactamases

Introduction

The emergence of multidrug-resistant (MDR) bacteria poses a severe threat to public health, leading to substantial financial losses, high morbidity, and mortality [1]. Antibiotic-resistant bacteria can be MDR (resistant to at least one antimicrobial in three or more classes), extensively drug-resistant (XDR, bacteria resistant to at-least one agent in all classes but remain susceptible to only one or two classes), and pandrug-resistant (PDR, isolates resistant to all antimicrobial classes) [2]. A few new bacterial resistance categories have been identified, such as difficult-to treat resistance (DTR) and modified-DTR [3]. However, among them, MDR bacteria are the most common and predominant in One Health settings [4,5].

The emergence of MDR Enterobacterales often linked with the production of extended-spectrum beta-lactamases (ESBLs) such as ESBL-producing Escherichia coli (E. coli) [6], colistin resistant Gram-negative bacteria including E. coli [7,8], and carbapenemase-producing Enterobacterales (CRE) including carbapenemase-producing Klebsiella pneumoniae (K. pneumoniae) represents an increasing global health threat [9]. Recently, carbapenemase-producing Serratia marcescens (S. marcescens) also possess multidrug-resistance which cause hospital-acquired as well as community-acquired infections [10]. Carbapenem-resistant K. pneumoniae (CRKp) and carbapenem-resistant E. coli (CREC) are the predominant opportunistic pathogens in representative hospitals from 27 provinces in China [11]. Transmissible mobile genetic elements and conjugative plasmids are associated with the spread of antimicrobial resistance genes among the various Enterobacterales [12–14].

The constant dissemination of bacterial drug resistance among the healthy population and hospitalized patients needs continuous surveillance, diagnosis, and healthcare management. Managing, controlling, and treating MDR-associated infections depend on rapid and reliable diagnostic measures [15]. The higher burden of antimicrobial resistance (AMR), likely the MDR strains, among the low-income, middle-income, and developing countries can result in the non-availability of alternative antibiotics to treat the infections. The research on AMR infections plays a pivotal role in managing and controlling the AMR. Beyond phenotypic surveillance, whole-genome sequencing (WGS) offers a powerful genetic approach to AMR research. WGS not only uncovers the specific genetic determinants of resistance but also elucidates pathogen evolution and population dynamics across diverse temporal and spatial scales [15,16]. Therefore, the current study was designed to demonstrate the comprehensive whole genome sequencing and epidemiological analysis of pathogenic strains, highlighting the necessity of surveillance-based preventive and clinical treatment options. In this study, we have performed the whole genome sequencing of human bacterial resistant isolates and in-depth genomic analysis and phylogeny of K. pneumoniae, E. coli, and S. marcescens isolates from clinical settings.

Materials and methods

Sample collection, bacterial isolation, and antibiotic susceptibility testing

A subset of 54 clinical samples including sputum, urine, wound, and blood were collected from the First Affiliated Hospital of the University of Science and Technology of China (USTC), a tertiary A-level hospital in Anhui province, China between March 2021 and August 2021. The samples were directly streaked on MacConkey agar followed by overnight incubation at 37 °C, and single isolated representative colony was further cultured on Mueller-Hinton agar (MHA) until purification. The purified isolates were subjected to species identification by 16S rDNA sequencing. All of the isolates were processed for antibiotic susceptibility testing (AST) to a panel of antibiotics including meropenem (lot #: K1802033), colistin (lot # F1814051), metronidazole (lot # B197651337769), norfloxacin (lot # B180121337769), nitrofurantoin (lot # 68,417), linezolid (lot # A518111337769), vancomycin (lot # C641741343D10), chloramphenicol (lot # H1921040), and gentamycin (lot # C12038664). The AST was performed using the broth microdilution assay according to the guidelines of Clinical and Laboratory Standard Institute (CLSI) [17] and European Committee for Antimicrobial Susceptibility Testing (EUCAST) [18]. Briefly, the bacterial suspensions (105 CFU/mL) in Cation-Adjusted Mueller-Hinton Broth (CAMHB) broth were incubated with two-fold dilutions of antibiotics in 96-well plates at 36°C for 16–20 h. Minimum inhibitory concentration (MIC) was recognized visually and compared to CLSI and EUCAST breakpoints to declare resistant, intermediate, and susceptible phenotype. The MDR strains were declared based on their resistance to at least ≥ 3 antibiotic classes [2].

Sample selection, preparation, and DNA extraction for WGS

A total of five isolates (male, n = 4; female, n = 1) isolated from urine (n = 2) and sputum (n = 3) (Table 1) were selected for WGS, which showed resistance to at-least three antibiotic classes including resistance to colistin or meropenem (Table 2). The five selected isolates were prepared for WGS according to the standard protocol provided by Illumina HiSeq (Wuhan Kangxi Technology Co., Ltd). An appropriate amount of bacteria was collected in a 50 mL centrifuge tube and centrifuged at low speed (3000 g − 5000 g) at 4 °C for 10 min. After centrifugation, the supernatant was removed and the pellet was washed with 5–10 mL of sterile water twice. The bacterial pellet was retained after 10 min of centrifugation at 1500 rpm at 4 °C for 10 min in a 1.5 or 2.0 mL tube. Finally, the pellet was presered at −80 °Cuntil further processing. The genomic DNA of all isolates were extracted using the Vazyme Bacterial DNA Kit (Vazyme, Beijing, China) and the qualitative analysis was carried out using the Nanodrop 2000 (ThermoFisher Scientific, USA). DNA integrity was tested by 1% agarose gel electrophoresis.

Table 1.

Metadata of selected isolates for whole-genome sequencing.

Isolate ID Bacterial Species Host Gender Age (years) Sample type Sample collection date
SM66 S. marcescens Homo sapiens Male 51 Urine 2021
KP69 K. pneumoniae Homo sapiens Male 30 Urine 2021
EC385 E. coli Homo sapiens Male 64 Sputum 2021
KP297 K. pneumoniae Homo sapiens Female 26 Sputum 2021
KP304 K. pneumoniae Homo sapiens Male 78 Sputum 2021
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Table 2.

Minimum inhibitory concentrations (MICs) of the MDR isolates against various antibiotics (mg/L).

Samples MET KAN NOR GM NFN CHL LIN VAN COL MER
EC385 >512 >512 128 >512 16 128 256 8 4 S
KP304 256 128 512 32 128 32 >512 16 S 256
KP297 >512 64 256 16 128 32 >512 8 S 256
KP69 256 256 128 128 32 S 32 16 32 64
SM66 256 4 S S 16 S 128 64 >512 51
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MET: metronidazole; KAN: kanamycin; NOR: norfloxacin; GM: gentamycin; NFN: nitrofurantoin; CHL: chloramphenicol; LIN: linezolid; VAN: vancomycin; COL: colistin; MER: meropenem. “S”represents susceptibility.

Genome sequencing and bioinformatics analysis

The WGS was performed on Illumina HiSeq by Wuhan Kangxi Technology Co., Ltd as per the manufacturer guidelines. Quality evaluation of the raw reads were performed through FastQC version 0.12.0 (https://github.com/s-andrews/FastQC, accessed on 10 April 2024). The low-quality reads such as adapter above the threshold and overlapping/low-quality bases were filtered out using the Trimmomatic v.0.11.8 [19]. Furthermore, the de novo assembly of the clean data into contigs were done by SPAdes v.4.0.0 [20], followed by an assessment of each assembly through QUAST v.1.13a (https://github.com/ablab/quast, accessed on 15 April 2024). Annotation of the assembled genomes were done by Comprehensive Genome Analysis tool under the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) (https://www.bv-brc.org/, accessed on 20 April 2024) tool. The serotyping of Escherichia coli genome was done by SeroTypeFinder v.2.0.1 [21] while the plasmid replicon typing (PRT) and identification of other mobile genetic elements (MGEs) for all genomes were done by PlasmidFinder v.2.1 and MobileElementFinder v.1.0.3, respectively under the Center for Genomic Epidemiology (CGE) online server (https://www.genomicepidemiology.org/, accessed on 20 April 2024). The multi-locus and ribosomal sequence typing were determined using the PubMLST online (https://pubmlst.org/, accessed on 22 April 2024). Moreover, the antibiotic resistance genes (ARGs) were identified using the Resistance Gene Identifier (RGI) under the Comprehensive Antibiotic Resistance Database (CARD) online (https://card.mcmaster.ca/home, accessed on 25 April 2024) and visualized using the Proksee (https://proksee.ca/, accessed on 27 April 2024) web-based tool. The ResFinder was also used to identify the ARGs under the Center for Genomic Epidemiology (CGE) online server (https://www.genomicepidemiology.org/, accessed on 20 April 2024). The virulence genes (VGs) were identified using the VFanalyzer under the Virulence Factor Database (VFDB) [22] web server (https://www.mgc.ac.cn/VFs/, accessed on 25 April 2024). The linear genetic context of resistance gene was constructed using the EasyFig v.2.2.5 [23].

Phylogenetic analysis

The phylogenetic trees were created using the Bacterial Genome Tree tool in Phylogenomics services section under the BV-BRC [24]online server (https://www.bv-brc.org/, accessed on 30 April 2024). The Codon Tree pipeline builds the tree by using the nucleotide or amino acid sequences from a defined BV-BRC Global Protein Families (PGFams) [25] number. The sequences were selected randomly to first construct the alignment and then generate a tree relying on the differences between selected sequences. The nucleotide coding gene sequences alignment were done by Codon_align function of BioPython [26] while the protein sequences were aligned using the MUSCLE v.5.2 [27]. The concatenated alignment of all proteins and nucleotides were written to a PHYLIP format file and then a partition file for RAxML version 8.0 [28] using the GTR+GAMMA substitution model in RAxML with support values of 100 rounds of the “Rapid” bootstrapping [29]. Finally, the resulting newick tree files were viewed using the Archaeopteryx (https://www.bv-brc.org/docs/quick_references/services/archaeopteryx.html).

Results

Antibiotic susceptibility testing

The antimicrobial susceptibility testing (AST) of the 49 other isolates susceptible to colistin and carbapenem is presented in Table S1 while the AST of five MDR isolates resistant to colistin or meropenem is shown in Table 2. These five isolates were further selected for WGS and in-depth genomic analysis.

Genomic analysis of mcr-1.1 harboring E. coli EC385

Genomic features and functional annotation of E. coli EC385

The genome of E. coli EC385 was assembled into 170 contigs, an estimated genome size of 5,292,580 bp and an average GC content of 50.24 %. The N50 length (length of the shortest contig) was 140,224 bp. The E. coli EC385 genome consisted of 5,279 coding sequences (CDS), 72 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. The annotation included 719 hypothetical proteins and 4,560 proteins with functional assignments. The proteins distributed to other functional categories included were 1,294 proteins with Enzyme Commission (EC) numbers, 1,067 with Gene Ontology (GO), and 907 proteins mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The EC385 genome also consisted of 5,067 proteins that belong to the PATRIC genus-specific protein family (PLFam) and 5,137 proteins that belong to the PATRIC cross-genus protein family (PGFams) (Table S2).

ARGs, VGs, and MGEs identified in E. coli EC385

The genomic analysis of E. coli EC385 revealed that a total of 54 ARGs were identified using the CARD database. These ARGs involved multiple resistance mechanisms including multiple efflux pumps (Figure 1). Further, ARGs analysis of EC385 using the ResFinder revealed some important mechanisms including colistin (mcr-1.1), rifampicin (arr-2), quinolone (qnrS1), trimethoprim (dfrA14), beta-lactam (blaTEM-141), florfenicol (floR), aminoglycosides [rmtB, aac(3)-IId, aph(6)-Id, aph(3”)-Ia, ant(3”’)-Ia], fosfomycin (fosA3), sulfonamides (sul3), tetracycline [tet(A)], and macrolide [lnu(F), mph(A), mdf(A)] resistance genes (Table 3). Among the MGEs, plasmid analysis revealed that EC385 was harboring 5 plasmid replicon types including IncI2, IncFIC (FII), IncFIB(AP001918), IncHI2, and ColRNAI (Table 3). The other MGEs carried by EC385 included numerous insertion sequences (ISs) and miniature Inverted-repeat transposable elements (MITE) are listed in Table S3 (Dataset 1). Further VGs analysis revealed that EC385 contained a set of 65 VGs belong to different virulence factor (VF) categories including adherence-related, invasion, siderophore, toxin, and non-LEE encoded type three secretion system (TTSS) effectors (Table 3). The E. coli EC385 belonged to serotype H10:O40 (Table 3).

Figure 1.

A diagram showing the circular genome of E. coli EC385 with ARGs and GC content. The diagram illustrates the complete circular genome of E. coli EC385. From the outermost to the innermost circle, the first circle displays genome contigs, marked by gray segments. The second circle represents the GC content, shown in black, with a value of fifty point twenty-four percent. The third circle indicates the GC skew, with green representing positive skew and purple representing negative skew. Red annotation arrows highlight the ARGs. The central label indicates the strain ID 'Escherichia coli EC385'. The diagram provides a comprehensive view of the genetic features, including resistance genes and GC content, of the E. coli EC385 strain.

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Complete circular genome of mcr-1.1-positive E. coli EC385. From outside to inside, the first circle indicate the genome contigs (170), GC content (black, 50.24%) and GC skew (green and purple). The mcr-1.1 and other ARGsresults from CARD are shown as red annotation arrows. The figure was generated using the proksee web server (https://proksee.Ca/).

Table 3.

ARGs, PRTs,serotype, and VGs identified in the genome of E. coli EC385.

Antibiotic class ARGs VF category VGs
β-lactam blaTEM-141 Adherence-related fimA/B/C/D/E/F/G/H/I, ompA, csgB/D/F/G, ecpA/B/C/D/R, fdeC, papB/I
Quinolone qnrS1 Non-LEE-encoded TTSS effectors espY1/Y2/Y3/Y4, espX1/X2/X4, espL1, espR1
Polymyxin B mcr-1.1 Invasion aslA
Sulfonamides sul3 Siderophore entA/B/C/D/F/S, fepA/B/C/D/G, chuU/V/W/X/Y, shuA/S/T, iucA/B/C/D, iutA, iroB/C/D/E/N
Tetracycline tet(A) Toxin astA
Fosfomycin fosA3  
Rifamycin arr-2
Macrolide lnu(F), mph(A)
Aminoglycosides rmtB, aac(3)-IId, aph(6)-Id, aph(3”)-Ia, ant(3”’)-Ia
Phenicol floR
Trimethoprim dfrA14
Macrolide lnu(F), mph(A), mdf(A)
PRTs IncI2, IncFIB(AP001918), IncFIC (FII), IncHI2, ColRNAI
Serotype H10:O40
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ARGs: antibiotic-resistance genes; VF: virulence factor; VGs: virulence genes; PRTs: plasmid replicon types. These ARGs were identified using the ResFinder.

The genetic context of mcr-1.1 identified in E. coli EC385 was compared with other related plasmid incompatibility types from NCBI database. The comparative analysis of mcr-1.1-carrying contig in this study strain E. coli EC385 found highly similar with plasmids pQDFD216.1 (Accession number: CP053211) and pCSZ4 (Accession number: KX711706.1) belong to IncI2 type. It was found that some conjugative transfer system genes (virD4, virD2, virB1-6, virB8-11, and traG) also identified. Moreover, the identification of insertion sequence IS26 may play an important role in the spread of mcr-1.1 gene (Figure 2).

Figure 2.

Linear genetic context of mcr-1.1 in E. coli EC385 contig, pQDFD216.1, and pCSZ4 plasmids from NCBI with gene annotations and similarity shading. The image shows a linear genetic context comparison of mcr-1.1 identified in E. coli EC385 and related plasmids pQDFD216.1 (Accession number: CP053211) and pCSZ4 (Accession number: KX711706.1). The diagram includes directional arrows representing genes: red for mcr-1.1, green for pap2, pink for papA and golden for other genes. The genes are labeled as pir, pap2, mcr-1.1, papA, IS26, HNS, topB, csg12, VirD4, VirD2, VirB1, VirB2, VirB3, VirB4, VirB5, VirB6, VirB8, VirB9, VirB10, VirB11, traG, hscB and dnaJ. Shading between sequences indicates similarity, with a gradient showing 100 percent to 99 percent similarity. The figure illustrates the genetic arrangement and similarity between these plasmids, constructed using the EasyFig v.2.2.5.

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Linear genetic context of mcr-1.1 identified in E. coli EC385 and other related mcr-1.1-bearing plasmids, pQDFD216.1 (Accession number: CP053211) and pCSZ4 (Accession number: KX711706.1) from NCBI. Red arrow indicates the mcr-1.1 gene, green represents pap2, pink arrows represent parA, and golden arrows indicates other genes. The figure was constructed using the EasyFig v.2.2.5.

Sequence typing and phylogenetic analysis of E. coli EC385

The current study E. coli EC385 strain belonged to multi-locus sequence type (MLST) ST1011 and ribosomal sequence type (rST1640). The phylogenetic tree analysis based on PATRIC database showed that the E. coli EC385 isolate made a cluster with Shigella dysenteriae Sd197 as shown in the Figure 3.

Figure 3.

Phylogenetic tree showing the E. coli EC385 clustering with Shigella dysentriae Sd197. The phylogenetic tree is oriented vertically, showing evolutionary relationships among various strains. At the top, Shigella boydii Sb227 and Shigella flexneri 2a.str.301 form a sister group with 100 percent similarity. Below, Escherichia coli 0104:H4 branches off with 67 percent similarity, followed by Shigella sp.D9 with 47 percent. Further down, Shigella sonnei H140920393 and Shigella sonnei Ss046 form a sister group with 100 percent similarity. Shigella dysentriae Sd197 and Escherichia coli EC385 cluster together with 63 percent similarity. Below them, Escherichia coli 0157 and Escherichia coli UMN026 form a sister group with 98 percent and 94 percent similarity, respectively. At the bottom, K-12 branches off with 22 percent similarity. The scale bar at the bottom represents 0.002 tree scale.

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Phylogenetic tree of the E. coli EC385 showing the similarity with Shigella dysentriae Sd197. The tree was constructed using the BV-BRC online server (https://www.bv-brc.org/).

Genomic analysis of blaKPC-2-positive K. pneumoniae isolates

Genomic features and functional annotation of K. pneumoniae isolates

The whole genome of K. pneumoniae KP304 consisted of 105 contigs with an estimated genome length of 5,575,143 bp and an average GC content of 57.16%. The N50 length of the genome was 147,773 bp. The K. pneumoniae KP304 genome consisted of 5,457 CDS, 69 tRNAgenes, and 4 rRNAgenes. Furthermore, the number of hypothetical proteins were 732, while the number of functional assignment proteins were 4,725. The proteins with functional assignments included 1,461 proteins in the EC category, the number of GO and KEGG proteins were 1,209 and 1,055 proteins, respectively. Except this, the KP304 genome also consisted of 5,277 proteins that belong to the PLFam and 5,322 proteins that belong to the PGFams (Table S4).

Similarly, the whole genome of K. pneumoniae KP297 consisted of 102 contigs with an estimated genome length of 5,525,636 bp and an average GC content of 57.14%. The N50 length of the genome was 173,353 bp. The K. pneumoniae KP297 genome consisted of 5,386 CDS, 69 tRNA) genes, and 4 rRNAgenes. Furthermore, the number of hypothetical proteins were 703, while the number of functional assignment proteins were 4,683. The proteins with functional assignments included 1,445 proteins in the EC category, the number of GO and KEGG proteins were 1,193 and 1,093 proteins, respectively. Except this, the KP297 genome also consisted of 5,222 proteins that belong to the PLFam and 5,261 proteins that belong to the PGFams (Table S5).

The K. pneumoniae KP69 genome consisted of 139 contigs with an estimated genome length of 5,758,590 bp and an average GC content of 57.06%. The N50 length of the genome was 114,857 bp. The K. pneumoniae KP69 genome consisted of 5,808 CDS, 70 tRNAgenes, and 4 rRNAgenes. Furthermore, the number of hypothetical proteins were 873, while the number of functional assignment proteins were 4,935. The proteins with functional assignments included 1,470 proteins in the EC category, the number of GO and KEGG proteins were 1,209 and 1,067 proteins, respectively. Moreover, the KP69 genome consisted of 5,593 proteins that belong to the PLFam and 5,660 proteins that belong to the PGFams (Table S6).

ARGs, VGs, and MGEs identified in K. pneumoniae isolates

The genomic analysis of K. pneumoniae KP304 revealed that a total of 42 ARGs using the CARD database. These ARGs involved multiple resistance mechanisms including multiple efflux pumps (Figure 4). Further, ARGs analysis of KP304 using the ResFinder revealed important resistome including carbapenem (blaKPC-2), other beta-lactam (blaTEM-1B, blaSHV-106, blaCTX-M-15, blaOXA-1), quinolone (aac(6’)-Ib-cr, oqxAB), aminoglycosides [aac(3)-IId], fosfomycin (fosA6), tetracycline [tet(A)], and macrolide [mph(A)] resistance genes (Table 4). Among the MGEs, plasmid analysis revealed that KP304 was harboring 2 plasmid replicon types including IncFII(pBK30683) and IncFIB(K) (Table 4). The other MGEs carried by KP304 included numerous ISs and MITE are listed in Table S7 (Dataset 1). Further, VGs analysis revealed that KP304 contained a set of 21 VGs belong to adherence and siderophores (Table 4).

Figure 4.

Circular genome map of K. pneumoniae KP304 showing contigs, GC content, GC skew and ARGs distribution. The circular genome map of K. pneumoniae KP304 displays several concentric tracks. The outermost track shows the genome contigs with tick marks indicating the positions in the megabase pairs from 0.5 to 5.5. The next track represents the GC content, with variable peaks and troughs indicating the regions of higher or lower GC content. Inside, the GC skew track alternates between positive (green) and negative (purple) values, reflecting the leading and lagging strands of DNA replication. Red arrows annotate antibiotic resistance genes (ARGs) from the CARD database, including AAC(6’)-Ib-cr5, tet(A), blaKPC-2, blaTEM-1, blaCTX-M-15 and blaOXA-1, among others. These annotations highlight regions of resistance gene clustering. The map provides insights into the genomic structure and resistance profile of the organism, with notable ARG distribution between 1.0 and 4.5 megabase pairs.

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Complete circular genome of blaKPC-2-positive K. pneumoniae KP304. From outside to inside, the first circle indicate the genome contigs (105), GC content (black, 57.16%) and GC skew (green and purple). The blaKPC-2 and other ARGs results from CARD are shown as red annotation arrows. The figure was generated using the proksee web server (https://proksee.Ca/).

Table 4.

ARGs, PRTs, ST, and VGs identified in the genome of K. pneumoniae isolates.

Antibiotic class KP304 KP297 KP69
ARGs      
β-lactam blaTEM-1B, blaKPC-2, blaSHV-106, blaCTX-M-15, blaOXA-1 blaTEM-1B, blaKPC-2, blaSHV-106, blaCTX-M-15, blaOXA-1 blaTEM-1B, blaKPC-2, blaSHV-12, blaCTX-M-65
Quinolone aac(6’)-Ib-cr, oqxAB aac(6’)-Ib-cr, oqxAB qnrS1
Tetracycline tet(A) tet(A) tet(A)
Fosfomycin fosA6 fosA6 fosA6
Sulfonamides — — sul2
Aminoglycosides aac(3)-IId aac(3)-IId rmtB, aadA2
Macrolide mph(A) mph(A) —
Trimethoprim — — dfrA14
VGs      
Adherence-related ecpA/B/C/D/E/R, ompA ecpA/B/C/D/E/R, ompA ecpA/B/C/D/E/R, ompA
Siderophore fepC, entA/B, fyuA, ybtA/E/P/Q/S/T/U/X, irp1/2 fepC, entA/B, fyuA, ybtA/E/P/Q/S/T/U/X, irp1/2 fepC, entA/B, fyuA, ybtA/E/P/Q/S/T/U/X, irp1/2, iucA/B/C, iutA
PRTs IncFII(pBK30683), IncFIB(K) IncFII(pBK30683), IncFIB(K) IncHI1B(pNDM-MAR), IncR, IncFIB(K), IncFII(pCRY), ColRNAI
MLST ST15 ST15 ST11
rST 19202 19202 31218
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ARGs: antibiotic-resistance genes; VGs: virulence genes; PRTs: plasmid replicon types; ST: sequence type; MLST: multi-locus sequence type; rST: ribosomal sequence type. These ARGs were identified using the ResFinder.

The K. pneumoniae KP297 genomic analysis revealed that a total of 42 ARGs using the CARD database. These ARGs involved multiple resistance mechanisms including multiple efflux pumps (Figure 5). Further, ARGs analysis of KP297 using the ResFinder revealed important resistome including carbapenem (blaKPC-2), other beta-lactam (blaTEM-1B, blaSHV-106, blaCTX-M-15, blaOXA-1), quinolone (aac(6’)-Ib-cr, oqxAB), aminoglycosides [aac(3)-IId], fosfomycin (fosA6), tetracycline [tet(A)], and macrolide [mph(A)] resistance genes (Table 4). Among the MGEs, plasmid analysis revealed that KP297 was harboring 2 plasmid replicon types including IncFII (pBK30683) and IncFIB(K) (Table 4). The other MGEs carried by KP297 included numerous ISs and MITE are listed in Table S8 (Dataset 1). Further, VGs analysis revealed that KP297 contained a set of 21 VGs belonged to adherence and siderophores (Table 4).

Figure 5.

A diagram showing the circular genome of K. pneumoniae KP297 with GC content and ARGs. The diagram illustrates the complete circular genome of K. pneumoniae KP297. From the outside to the inside, the first circle represents genome contigs, marked with 102 segments. The second circle shows the GC content in black, with a percentage of 57.14. The third circle displays the GC skew, with green indicating positive skew and purple indicating negative skew. Red annotation arrows represent antibiotic resistance genes from the comprehensive antibiotic resistance database. These genes include blaKPC-2, blaTEM-1, blaSHV-106, blaCTX-M-15, blaOXA-1, aac(6’)-Ib-cr, oqxAB, aac(3)-IId, fosA6, tet(A) and mph(A), among others. The diagram also includes labels for various genes such as rsmA, ompK37, kpnE, kpnF and others, positioned around the genome. The central label indicates strain ID 'Klebsiella pneumoniae KP297'.

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Complete circular genome of blaKPC-2-positive K. pneumoniae KP297. From outside to inside, the first circle indicate the genome contigs (102), GC content (black, 57.14%) and GC skew (green and purple). The blaKPC-2 and other ARGs results from CARD are shown as red annotation arrows. The figure was generated using the proksee web server (https://proksee.Ca/).

The K. pneumoniae KP69 genomic analysis revealed that a total of 41 ARGs using the CARD database. These ARGs involved multiple resistance mechanisms including multiple efflux pumps (Figure 6). Further, ARGs analysis of KP69 genome using the ResFinder revealed important resistome including carbapenem (blaKPC-2), other beta-lactam (blaTEM-1B, blaSHV-12, blaCTX-M-65), quinolone (qnrS1), aminoglycosides (rmtB, aadA2), fosfomycin (fosA6), tetracycline [tet(A)], sulfonamide (sul2), and trimethoprim (dfrA14) resistance genes (Table 4). Among the MGEs, plasmid analysis revealed that KP69 was harboring 5 plasmid replicon types including IncHI1B (pNDM-MAR), IncR, IncFIB (K), IncFII(pCRY), and ColRNAI (Table 4). The other MGEs carried by KP69 included numerous ISs and MITE are listed in Table S9 (Dataset 1). Further, VGs analysis revealed that KP69 contained a set of 25 VGs belong to adherence and siderophores (Table 4).

Figure 6.

A circular genome plot of K. pneumoniae KP69 showing contigs, GC metrics, and ARGs. Circular genome map of K. pneumoniae KP69 features. The outermost ring displays 139 genome contigs as segmented blocks. Inside, a GC content track shows an average GC content of 57.06%. The GC skew track, labeled GC Skew plus and minus, highlights guanine versus cytosine bias through alternating positive and negative lobes. An ARG annotation track, labeled ARGs-CARD, marks specific genome positions with outward arrows. Notable antibiotic resistance genes include blaKPC-2, blaCTX-M-65, blaSHV-12, blaTEM-1, sul2, tet(A), qnrS1, rmtB, aadA3, dfrA14, fosA6 and qacE delta1. Additional loci such as acrAB-tolC-marR, acrBacrB, marA, ompA, gyrA and parC are also labeled around the circle.

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Complete circular genome of blaKPC-2-positive K. pneumoniae KP69. From outside to inside, the first circle indicate the genome contigs (139), GC content (black, 57.06%) and GC skew (green and purple). The blaKPC-2 and other ARGs results from CARD are shown as red annotation arrows. The figure was generated using the proksee web server (hehttps://proksee.Ca/).

Sequence typing and phylogenetic analysis of K. pneumoniae isolates

The current study KP297 and KP304 genomes were belonged to ST15 and rST19202. The K. pneumoniae KP69 belonged to ST11 and rST31218. The phylogenetic tree analysis of KP297 and KP304 revealed their clustering in the same clade with K. pneumonia IS46 as shown in Figures 7 and 8, respectively while the K. pneumoniae KP69 was aligned with K. pneumoniae HS11286 isolate (Figure 9).

Figure 7.

Phylogenetic tree of Klebsiella pneumoniae KP297 showing the evolutionary relationships. The phylogenetic tree is oriented vertically, displaying genetic relationships among various K. pneumoniae isolates and related species. At the top, Klebsiella pneumoniae IS39 branches off with a 74 percent similarity. Below, Klebsiella pneumoniae DSM30104 and ISC21 showed 31 percent and 41 percent similarity, respectively. Klebsiella pneumoniae HS11286 and IS46 both exhibited 100 percent similarity, with Klebsiella pneumoniae KP297 clustering closely with Klebsiella pneumoniae IS46. Klebsiella pneumoniae MGH78578 showed 39 percent similarity. Further down, Klebsiella variicola AT-22, Enterobacter aerogenes KCTC2190, Raoultella planticola GCSL-DIFS-295 and Klebsiella oxytoca CAV1374 each displayed 100 percent similarity within their respective branches. The scale bar at the bottom represents a genetic distance of 0.03.

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Phylogenetic tree of the K. pneumoniae KP297 showing similarity with K. pneumoniae IS46 isolate. The tree was constructed using the BV-BRC online server (https://www.bv-brc.org/).

Figure 8.

A depiction of the evolutionary relatedness within K. pneumoniae and other closely-related lineages. The phylogenetic tree is oriented vertically, displaying genetic relationships among various strains. At the top, Klebsiella pneumoniae IS46 has shown with a 100 percent similarity. Below it, K. pneumoniae KP304 is marked in green with a 39 percent similarity. Further down, Klebsiella pneumoniae MGM78578 showed a 9 percent similarity, followed by Klebsiella pneumoniae IS39 with 31 percent and Klebsiella pneumoniae DSM30104 with 8 percent. Klebsiella pneumoniae ISC21 and Klebsiella pneumoniae HS11286 both showed 100 percent similarity. The tree continues with Klebsiella variicola AT-22, Enterobacter aerogenes KCTC2190, Klebsiella oxytoca CAV1374 and Raoultella planticola GCSL-DIFS-295, each with 100 percent similarity. A scale bar at the bottom represents a genetic distance of 0.03.

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Phylogenetic tree of the K. pneumoniae KP304 showing similarity with K. pneumoniae IS46 isolate. The tree was constructed using the BV-BRC online server (https://www.bv-brc.org/).

Figure 9.

Phylogenetic tree showing relationships among Klebsiella and other related species. The phylogenetic tree is oriented vertically, displaying evolutionary relationships among various Klebsiella species and related bacteria. At the top, Klebsiella pneumoniae MGH78578 branches off with a 43 percent similarity. Below, Klebsiella pneumoniae IS46 diverges with 7 percent, followed by Klebsiella pneumoniae IS39 at 36 percent. Klebsiella pneumoniae DSM30104 and Klebsiella pneumoniae ISC21 both showed 100 percent similarity, aligning closely with K. pneumoniae KP69, which is highlighted in green. Klebsiella pneumoniae HS11286 also showed 100 percent similarity. Furthermore, Klebsiella variicola AT-22, Enterobacter aerogenes KCTC2190, Raoultella planticola GCSL-DIFS-295 and Klebsiella oxytoca CAV1375 each branch off with 100 percent similarity. A scale bar at the bottom left indicates a genetic distance of 0.03.

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Phylogenetic tree of the K. pneumoniae KP69 showing similarity with K. pneumoniae HS11286 isolate. The tree was constructed using the BV-BRC online server (https://www.bv-brc.org/).

Genomic analysis of blaKPC-2 carrying S. marcescens SM66

Genomic features and functional annotation of S. marcescens SM66

The S. marcescens SM66 genome consisted of 51 contigs with an estimated genome length of 5,298,482 bp and an average GC content of 59.83%. The N50 length of the genome was 287,946 bp. The S. marcescens SM66 genome consisted of 5,160 CDS, 77 tRNA genes, and 3 rRNA genes. Furthermore, the annotation number of hypothetical proteins were 869, while the number of functional assignment proteins were 4,291. The proteins with functional assignments included 1,326 proteins in the EC category, the number of GO and KEGG proteins were 1,094 and 953 proteins, respectively. Moreover, the SM66 genome consisted of 4,933 proteins that belong to the PLFam and 4,978 proteins that belong to the PGFams (Table S10).

ARGs, VGs, and MGEs identified in S. marcescens SM66

The S. marcescens SM66 genomic analysis revealed that a total of 18 ARGs using the CARD database. These ARGs involved multiple resistance mechanisms including some multiple efflux pumps (Figure 10). Further, ARGs analysis of SM66 using the ResFinder revealed carbapenem (blaKPC-2), other beta-lactam (blaSRT-2), quinolone (oqxB), and aminoglycoside [aac(6’)-Ic] genes (Table 5). Among the MGEs, plasmid analysis revealed that SM66 was harboring 2 plasmid replicon types including IncFII (pBK30683) and IncR (Table 5). The other MGEs carried by SM66 included numerous ISs and MITE are listed in Table S11 (Dataset 1). Further, VGs analysis revealed that SM66 only carried 3 VGs belong to adherence, motility, and secretion systems (Table 5).

Figure 10.

A diagram showing a circular genome map of S. marcescens SM66 with GC tracks and ARG labels. A circular genome map of S. marcescens SM66 features concentric rings with a key listing ARGs-CARD, GC Content and GC Skew. The outermost ring shows genome contigs, followed by red annotation arrows with gene names like blaKPC-2, adeF, msbA, vanG, rsmA, PBP3, qacG, CRP, aac(6’)-Ic, fosA8, arnT, kpnF, SRT-2, kpnH and emrR. Inside, a jagged plot labeled GC content encircles the genome, with an inner ring showing GC skew as green and purple deviations. The innermost scale ring has tick marks labeled in megabase pairs from 0.5 to 5.0 .

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Complete circular genome of blaKPC-2-positive S. marcescens SM66. From outside to inside, the first circle indicate the genome contigs (51), GC content (black, 59.83%) and GC skew (green and purple). The blaKPC-2 and other ARGs results from CARD are shown as red annotation arrows. The figure was generated using the proksee web server (https://proksee.Ca/).

Table 5.

ARGs, VGs, ST, and PRTs identified in the genome of S. marcescens SM66.

Antibiotic class ARGs VF category VGs
β-lactam blaKPC-2, blaSRT-2 Adherence and motility cheY
Quinolone oqxB Secretion system fliM, fliG
Aminoglycosides aac(6’)-Ic    
PRTs IncFII(pBK30683), IncR
rST 8002
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ARGs: antibiotic-resistance genes; VF: virulence factor; VGs: virulence genes; PRTs: plasmid replicon types; ST: sequence type; rST: ribosomal sequence type. These ARGs were identified using the ResFinder.

Sequence typing and phylogenetic analysis of S. marcescens SM66

The MLST of S. marcescens SM66 revealed that it belongs to rST8002. The phylogenetic tree analysis based on the WGS showed high identity and clustering with the S. marcescens Db11 strain (Figure 11).

Figure 11.

Phylogenetic tree showing relationships among Serratia species. Klebsiella species were identified in separate clade. The phylogenetic tree is oriented vertically, showing evolutionary relationships among various bacterial strains. At the top, Serratia plymuthica S13 and Serratia plymuthica 4Rx13 are sister taxa, both supported by 100 percent similarity. Below them, Serratia sp. AS12 and Serratia plymuthica AS9 also form a sister group with 100 percent similarity. These two groups converge with Serratia plymuthica PRI-2C, which is also supported by 100 percent. Moving down, S. marcescens SM66 is closely related to Serratia marcescens Db11, both supported by 100 percent. Further down, Serratia marcescens Fg194 and Serratia odorifera DSM4582 are shown as sister taxa with 100 percent similarity. At the base, Klebsiella oxytoca CAV1374 and Klebsiella pneumoniae MGH78578 form a sister group supported by 100 percent similarity in a separate clade and can be considered outlier. The scale bar at the bottom left indicates a genetic distance of 0.06.

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Phylogenetic tree of the S. marcescens SM66 showing similarity with S. marcescens Db11 isolate. The tree was constructed using the BV-BRC online server (https://www.bv-brc.org/).

Discussion

MDR Enterobacterales, including E. coli, K. pneumoniae, and S. marcescens, are resistant to multiple antibiotics. They are often associated with the production of ESBLs, and carbapenemase-production, which are enzymes that can break down certain types of antibiotics [30]. These bacteria pose a significant global threat to public health, as they can cause serious infections that are difficult to treat. Experts generally recommend using a combination of antibiotics to treat MDR-related infections and taking steps to prevent the spread of these bacteria, such as practicing good hand hygiene and using isolation precautions for infected patients [30]. It is also important to use antibiotics judiciously to prevent the emergence and spread of antibiotic-resistant bacteria. The current study evaluates the whole genome sequences of clinically-associated pathogenic MDR isolates of E. coli, K. pneumoniae, and S. marcescens from the Anhui province of China to analyze in-depth antimicrobial resistance and epidemiological characteristics. The current study revealed that isolated MDR E. coli, K. pneumoniae, and S. marcescens harbored multiple ARGs including critical resistance genes (CRGs) such as blaKPC-2 or mcr-1.1. Other important genes identified were β-lactamase resistance genes (blaCTX-M, blaTEM), quinolone-resistance (qnrS1), folate pathway antagonist (dfrA14, sul2, sul3), aminoglycoside (rmtB, aph(3)-la, aph(6)-ld), macrolide-resistance (lun(F), and chloramphenicol resistance (floR) genes.

The current study observed that the E. coli EC385 possess ARGs associated with resistance to most of the antibiotics, including quinolone (qnrS1), trimethoprim (dfrA14), beta-lactam (blaTEM-141), florfenicol (floR), aminoglycosides [rmtB, aac(3)-IId, aph(6)-Id, aph(3”)-Ia, ant(3”’)-Ia], fosfomycin (fosA3), sulfonamides (sul3), etc. as reported by earlier studies from China, India, Thailand, Poland, and Egypt [31–35]. Resistance to multiple antibiotics might be due to the rapid evolution, spread, and adaptability of ARGs carrying bacteria. The ARGs can be acquired, accumulate, and disseminate through MGEs, such as plasmids and transposons within and between the bacterial species [36,37]. The identification of astA virulence gene in E. coli EC385 directly relates it’s potential of pathogenicity because this gene encodes for thermostable EnteroAggregative Stable Toxin 1 (EAST-1) [38]. Moreover, the existence of various plasmids such as IncI2, IncFIC(FII), IncFIB(AP001918), IncHI2, and ColRNAI in the E. coli EC385 isolate from the current study might carry such genes and can play an important role in their spread [39–43]. A major pathway for the spread of AMR is the transfer of resistant bacteria from contaminated environments to humans. These bacteria, found in soil, water, animals, and foodstuffs, can readily enter human settlements [44,45]. Consequently, the pollution of drinking water and common consumer products poses a severe risk, facilitating the swift transmission of resistance into vulnerable settings like hospitals and densely populated areas [46,47]. China has the world’s second-highest antibiotic usage, with overall antibiotic consumption continuing to rise, potentially aiding the spread of antibiotic resistance [41].

This study also observed that the E. coli EC385 harboring mcr-1.1 belongs to ST1011, serotype H10:O40, and rST1640 which was clustered with Shigella dysenteriae Sd197. The relationship between Shigella and E. coli is a complex and contentious issue in bacterial systematics. The conventional view is that Shigella is a distinct genus within the family Enterobacteriaceae that evolved from within the E. coli species; however, some researchers argue that Shigella should be considered a subclade or a pathovar of E. coli rather than a separate genus. It is believed to be related to acquiring a specific set of virulence genes that enable Shigella to invade and colonize the intestinal epithelium. Regardless of whether Shigella is considered a distinct genus or a subclade of E. coli, it is clear that the relationship between these two groups is complex and multifaceted [48].

Further research into the genetic and evolutionary basis for their differences and similarities is needed to understand the nature of this relationship [48]. The origin and evolution of Shigella and its relationship with Enteroinvasive E. coli (EIEC) is a topic of ongoing debate and research in microbiology. There are two conflicting theories regarding the origin of Shigella, the multiple independent origins theory and the single clonal origin theory [49–53]. The study by Pupo et al. [49] used a small set of housekeeping genes to analyze the phylogenetic relationship between Shigella and E. coli strains. The authors found that Shigella strains clustered into three distinct groups within the larger E. coli phylogeny. This suggests that these three groups of Shigella strains may have arisen from independent acquisitions of virulence genes by different ancestral E. coli strains. According to this theory, the virulence plasmid that carries the genes responsible for Shigella‘s pathogenicity would have been independently acquired by these ancestral E. coli strains through lateral transfer of a Pathogenicity Island (PAI) (a mobile genetic element that can be horizontally transferred between bacteria and carries a set of virulence genes that enable the bacteria to cause disease). Escobar-Páramo et al. [53] proposed that a single ancestral virulence plasmid gave rise to all Shigella strains. They suggested that a single E. coli ancestor acquired this plasmid through horizontal transfer and that subsequent genetic changes and adaptations led to the emergence of Shigella as a distinct pathogen. Studies by Touchon and Ogura et al. [54] suggested that while some Shigella species are closely related and have evolved clonally from a common ancestor, others have arisen through the independent acquisition of virulence genes by distantly related E. coli strains [54,55]. These studies highlight the complexity of the evolutionary history of Shigella and its relationship with E. coli, and suggest that the emergence of Shigella as a distinct pathogen involved a combination of clonal evolution and horizontal gene transfer.

The rapid emergence and spread of drug-resistance in K. pneumoniae is becoming a serious global concern for antibiotic management [56–58]. In the current study, the three K. pneumoniae isolates (KP304, KP297, and KP69) were MDR similar to that of other reports from China, Germany, Slovenia, Turkey, Taiwan, and Iran [59–63]. However, evolution is a prominent factor in the bacterial population because continuous antibiotic exposure exerts pressure, giving rise to the evolvement of multiple genetic mechanisms [64]. Over the years, the constant evolution in antibiotic resistance strains led to the emergence of XDR and MDR strains of Enterobacteriaceae [65]. These strains resist nearly all available antibiotics leading to a scarcity of possible therapeutic options and posing a recognized global threat [64].

The three K. pneumoniae isolates (KP304, KP297, and KP69) from the current study harbored β-lactamase, aminoglycosides, fluoroquinolone, and other resistance and virulence genes, as well as mobile genetic elements. Similarly, several studies reported a high percentage of β-lactamase-resistance genes through WGS [48,58,66,67], fluoroquinolones, aminoglycosides, and folate pathway inhibitors in K. pneumoniae isolates [68–70]. Globally, several reports revealed the presence of blaCTX-M-type β-lactamase genes (like blaCTX-M-14 and blaCTX-M-15) [71]. Likewise, a recent chinese study reported the blaCTX-M-14 (14.3%) [72], while another study from Scotland reported the presence of blaCTX-M-15 among K. pneumoniae isolated from hospitalized patients [73]. According to a survey conducted in Korea, blaSHV-1 and blaSHV-11 genes and other blaSHV genes from Brazil were reported in K. pneumoniae isolates [74,75]. The hospital-associated K. pneumoniae is instantly exposed to many antibiotics, which inserts a constant selective pressure responsible for a number of positively selected mutations [76]. This study revealed a diverse number of continuously evolved ARGs by studying the resistome of K. pneumoniae isolates. However, the difference in resistome of K. pneumoniae is reported differently from different geographic locations, different cultural populations, possible resistance reservoirs and antibiotic stewardship, which increase the flexibility of accumulation and switching of resistances [76]. Appealingly, the resistome containing ARGs is present on the plasmid or chromosomes of bacterial isolates and can be transferred within a single genome from chromosomes to plasmid and vice versa. Horizontal transfer of plasmid-mediated transposons and resistome among bacterial species and within K. pneumoniae strains have also been reported [77].

This study found that two K. pneumoniae isolates (KP304 and KP297) belonged to ST15 and rST19202. Other studies from China also reported the K. pneumoniae (ST15) as a high-risk emerging clone becoming a serious public health risk that can lead to the emergence and transmission of a wide range of drug-resistant and virulent heterozygous plasmids [78,79]. In addition, with the widespread use of carbapenems, ST15 CRKP has emerged in recent years in China, India, Japan, and Iran at several places [79–82]. Multiple β-lactamase resistance genes, including blaKPC-2, blaCTX-M-15, blaSHV-106, blaTEM-1B, and blaOXA-1 have been reported in CRKP (ST15) isolates from this study which is in consistence to other previously reported findings in K. pneumoniae isolates from China [78,83]. Other studies from China also reported blaOXA-48-producing ST15, while ESBL-producing ST15 and ST11, where ST15 was associated with ESBL and carbapenemases, leading to complexity in the treatment [78,83]. This study showed that CRKP (ST15) were highly similar to isolates from Zhejiang and Jiangsu provinces, suggesting that ST15 CRKP is widely spread in East China, including the Anhui region [78]. The outbreaks of β-lactamases and carbapenemase-carrying K. pneumoniae (ST15) in a specific area may be similar. However, the difference in antibiotic resistance pattern of K. pneumoniae (ST15) isolates from different study area suggesting that K. pneumoniae (ST15) acquire a high potential of different resistance genes substantially [84].

K. pneumoniae (KP69) belong to ST11 and rST31218, similarly, the predominant CRKP ST11 results in a fatal outbreak of carbapenem-resistant hypervirulent K. pneumoniae ST11 were observed in China [85,86]. The emergence of new carbapenem-resistant hypervirulent-K pneumoniae strains of ST11 causes fatal hospital infections. Acquiring virulence plasmid by carbapenem-resistant K pneumoniae strains ST11 could lead to MDR, and hypervirulent strains that could transmit their resistance. Therefore, it is considered a real superbug [86]. Carbapenem-resistant K pneumoniae (ST11) is the dominant clone in Asia, where China alone reports up to 60% of carbapenem-resistant K. pneumoniae [87]. Recently, the most transmissible clone of higher prevalence in China is the carbapenem-resistant K. pneumoniae ST11. Besides the ST11 type, the ST258 is a hybrid clone composed of 20% of the ST442 genome and 80% of the ST11 genome disseminated worldwide since its emergence in the early 2000s and has become particularly prevalent in several European countries, Latin America, and North America [88–90]. The current observation can be justified as blaNDM-carrying K. pneumoniae ST11 has strong adaptability and can locally replace blaKPC-carrying K. pneumoniae to become an epidemic strain. The control and prevention of infection should focus on high-risk K. pneumoniae ST11 strains [91].

The current study noted that S. marcescens SM66 exhibited resistance to most antibiotics recognized as MDR. Some of the studies in China also reported similar findings [92]. S. marcescens is an intrinsically multidrug-resistant, opportunistic nosocomial pathogen. Its resilience stems from a high number of efflux pump genes and the production of diverse extracellular enzymes and metabolites, enabling adaptation to hostile and fluctuating environments [93]. Furthermore, S. marcescens exhibits a concerning capacity for rapidly acquiring additional ARGs such as, blaKPC, from its surroundings, primarily through the uptake of plasmids [94]. In the current study, two plasmids, including IncFII(pBK30683) and IncR were detected in S. marcescens originating from human origin. The previously described gene structure surrounding blaKPC-2 in the plasmids was validated by a MGE, ISKpn19, and indicating horizontal antibiotic resistance gene transfer through non-typing plasmid [95]. The gene structure around blaKPC-2 in plasmids by a mobile genetic element including blaSRT-2 and ISKpn27 in the forward strand, a different insertion sequence than that previously described by tertiary hospital in Hangzhou, China [96].

Phylogenetic tree analysis of the currently isolated S. marcescens SM66 showed similarity with S. marcescens Db11 strain and belonged to rST8002. S. marcescens strain Db11 was isolated from Drosophila melanogaster (D. melanogaster), considered an insect pathogen, a non-pigmented mutant of streptomycin-resistant Db10 [97]. The Db11 strain is used in Caenorhabditis elegans (nematode) to study the in-vivo and in-vitro host-pathogen interaction and innate immunity stimulation [98]. Being an opportunistic pathogen of humans, it causes a wide range of infections, including nosocomial diseases becoming an efficient public health concern. Due to the scarcity of the available genetic tools for in-depth characterizations of Db11 strains, genetic tool enhancement is needed to track its genetic characteristics and thoroughly explore the importance of the Db11 strain in invertebrate infection models. Furthermore, the most commonly used strain by researchers yet, comparatively little is known about its pathogenicity factors and no single strain of S. marcescens with completely known characteristic is available [98].

The resistance genotype of our isolates has immediate implications for patient management. The dominance of blaCTX-M renders penicillins and cephalosporins ineffective for empirical therapy. More critically, the detection of blaKPC-2 and mcr-1.1 creates a scenario where both carbapenems and colistin may fail, leaving novel agents like ceftazidime-avibactam or combination therapies as the few viable options. Carbapenems (e.g. ertapenem, meropenem) remain the treatment of choice for serious infections caused by ESBL-producing pathogens e.g. ESBL-producing E. coli [99] and use of novel beta-lactam/beta-lactamase inhibitor (BL/BLI) combinations which includes ceftazidime-avibactam and meropenem-vaborbactam are active against carbapenem-resistant Enterobacterlaes [100]. This underscores the necessity for rapid molecular diagnostics in our setting to guide initial therapy. From a stewardship perspective, our data argue for a careful, genotype-informed approach: reserving carbapenems for confirmed ESBL or KPC producers while emphasizing de-escalation when such resistance is absent.

Conclusion

Our study reveals the emergence of MDR Escherichia coli, Klebsiella pneumoniae, and Serratia marcescens strains in Chinese clinical settings. Integrating WGS with traditional microbiology provided a critical, high-resolution characterization of these pathogens, uncovering complex resistance profiles that phenotypic methods alone failed to resolve. We report the co-occurrence of the plasmid-mediated colistin resistance gene mcr-1.1 with the extended-spectrum beta-lactamase gene blaTEM-141 in E. coli, a convergence that threatens last-line treatment options. Furthermore, we identified K. pneumoniae isolates co-harboring the fluoroquinolone-modifying gene aac(6’)-Ib-cr, blaCTX-M, and the carbapenemase gene blaKPC-2 and confirmed blaKPC-2 in S. marcescens. These findings highlight the role of mobile genetic elements in disseminating multi-mechanism resistance. This genomic approach is essential for tracking the evolution of MDR clones. To combat this threat, future efforts must prioritize the development of rapid molecular diagnostics for these key resistance combinations, the discovery of novel antimicrobials, and the strengthening of international surveillance networks. Such actions are vital to inform stewardship policies and preserve the efficacy of existing antibiotics.

Ethics statement

The ethical committee of the First Affiliated Hospital of the University of Science and Technology of China (USTC) has authorized this study (approval number 2020KY-191). The written informed consent was waived by the Ethics Committee, as the samples analyzed in this study were collected as a part of routine clinical checkups and these samples were obtained solely for diagnostic purposes during the standard clinical care, and no specific human participants were recruited or selected for this research. The study utilized such samples for MDR bacterial screening, and no additional interventions or procedures were performed on patients for the purpose of this study. Consequently, the research did not involve direct interaction with human participants, and the use of these samples was covered under the ethical approval granted by the Hospital’s Ethics Committee, in accordance with the principles of the Declaration of Helsinki. Moreover, the participants were verbally informed that residual sample may be used for research purposes, provided there is no harm or additional risk to them. In this case, verbal consent was deemed sufficient by the hospital’s Ethics Committee, as the sample collection was part of routine clinical care, noninvasive, and posed no physical or psychological harm to participants.

Supplementary Material

QVIR-2025-0162.R1 - Table S3.xlsx
KVIR_A_2668179_SM3871.xlsx (10.2KB, xlsx)
Table S5.docx
KVIR_A_2668179_SM3870.docx (15.1KB, docx)
Table S6.docx
KVIR_A_2668179_SM3869.docx (15KB, docx)
QVIR-2025-0162.R1 - Table S9.xlsx
KVIR_A_2668179_SM3868.xlsx (10.2KB, xlsx)
QVIR-2025-0162.R1 - Table S8.xlsx
KVIR_A_2668179_SM3867.xlsx (9.8KB, xlsx)
Table S2.docx
KVIR_A_2668179_SM3866.docx (14.7KB, docx)
Table S4.docx
KVIR_A_2668179_SM3865.docx (15KB, docx)
QVIR-2025-0162.R1- Table S11.xlsx
KVIR_A_2668179_SM3864.xlsx (9.5KB, xlsx)
QVIR-2025-0162.R1 - Table S7.xlsx
KVIR_A_2668179_SM3863.xlsx (10.6KB, xlsx)
Table S1.docx
KVIR_A_2668179_SM3862.docx (24.5KB, docx)
Table S10.docx
KVIR_A_2668179_SM3861.docx (15.1KB, docx)

Funding Statement

This work was supported by the Outstanding Youth Foundation of Jiangsu Province of China (Grant No: BK20231524), National Natural Science Foundation of China [Grant No: 32473095, 12411530085 and 32373061], National Natural Science Foundation of China for International Young Scientists [Grant No: 201012443] and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21505594.2026.2668179.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The whole genome sequence data of five MDR isolates of this study have been deposited in NCBI (accessible at: https://www.ncbi.nlm.nih.gov/) repository under BioSample IDs: SAMN54564534, SAMN54564553, SAMN54564576, SAMN54564892, and SAMN54564960 for EC385, KP304, KP297, KP69, and SM66, respectively. Moreover, the other supplemental data related to this study have also been uploaded to figshare (an online open-access data repository) and is now available publicly at https://doi.org/10.6084/m9.figshare.28616705 [101].

References

  • [1].Noster J, Thelen P, Hamprecht A.. Detection of multidrug-resistant Enterobacterales—from ESBLs to carbapenemases. Antibiotics. 2021;10(9):1140. doi: 10.3390/antibiotics10091140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Magiorakos AP, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–20. doi: 10.1111/j.1469-0691.2011.03570.x [DOI] [PubMed] [Google Scholar]
  • [3].Alkofide H, Alhammad AM, Alruwaili A, et al. Multidrug-resistant and extensively drug-resistant enterobacteriaceae: prevalence, treatments, and outcomes–a retrospective cohort study. IDR. 2020;Volume 13:4653–4662. doi: 10.2147/IDR.S283488 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4].Ohia CMD, Falodun OI, Adebudo LI, et al. A one health perspective on multidrug-resistant bacterial infections: integrated approaches for surveillance, policy and innovation. Front Cell Infect Microbiol. 2025;15:1614232. doi: 10.3389/fcimb.2025.1614232 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Shoaib M, Gul S, Majeed S, et al. Pathogenomic characterization of multidrug-resistant Escherichia coli strains carrying wide efflux-associated and virulence genes from the dairy farm environment in Xinjiang, China. Antibiot (Basel). 2025;14(5):511. doi: 10.3390/antibiotics14050511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Shoaib M, Tang M, Awan F, et al. Genomic characterization of extended-spectrum β-lactamase (ESBL) producing E. coli harboring blaOXA−1-catB3-arr-3 genes isolated from dairy farm environment in China. Transbound Emerg Dis. 2024;2024(1):3526395. doi: 10.1155/2024/3526395 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Zeb S, Nazir A, Hameed MF, et al. Colistin resistance in gram-negative bacteria: mechanisms, transmission, and novel intervention strategies. Microorganisms. 2026. [cited 14(1):173. doi: 10.3390/microorganisms14010173 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Li H, Lin H, Fu Q, et al. Co-transfer of mcr-1 and mcr-3 variant in Escherichia coli ST1632 isolate in China: silence is not always golden. Pak Vet J. 2025;45(2):913–916. [Google Scholar]
  • [9].Bassetti M, Pecori D, Sibani M, et al. Epidemiology and treatment of MDR Enterobacteriaceae. Curr Treat Options Infect Dis. 2015;7(4):291–316. doi: 10.1007/s40506-015-0065-1 [DOI] [Google Scholar]
  • [10].Pérez-Viso B, Hernández-García M, Ponce-Alonso M, et al. Characterization of carbapenemase-producing Serratia marcescens and whole-genome sequencing for plasmid typing in a hospital in Madrid, Spain (2016–18). J Antimicrob Chemother. 2021;76(1):110–116. doi: 10.1093/jac/dkaa398 [DOI] [PubMed] [Google Scholar]
  • [11].Zhang R, Chan EW-C, Zhou H, et al. Prevalence and genetic characteristics of carbapenem-resistant Enterobacteriaceae strains in China. Lancet Infect Dis. 2017;17(3):256–257. doi: 10.1016/S1473-3099(17)30072-5 [DOI] [PubMed] [Google Scholar]
  • [12].Munir A, Li C, Kolenda R, et al. Exploring the diversity and dissemination dynamics of antimicrobial resistance genes in Enterobacteriaceae plasmids across varied ecological niches. Pak Vet J. 2025;45(2):662-672. [Google Scholar]
  • [13].Tansirichaiya S, Goodman RN, Guo X, et al. Intracellular transposition and capture of mobile genetic elements following intercellular conjugation of multidrug resistance conjugative plasmids from clinical Enterobacteriaceae isolates. Microbiol Spectr. 2022;10(1):e02140–21. doi: 10.1128/spectrum.02140-21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Al-Ouqaili MTS. Identification of an OprD and blaIMP gene-mediated carbapenem resistance in Acinetobacter baumannii and Pseudomonas aeruginosa among patients with wound infections in Iraq. Asian J Pharm (AJP). 2018;12(3):959-965. [Google Scholar]
  • [15].Boutal H, Vogel A, Bernabeu S, et al. A multiplex lateral flow immunoassay for the rapid identification of NDM-, KPC-, IMP- and VIM-type and OXA-48-like carbapenemase-producing Enterobacteriaceae. J Antimicrob Chemother. 2018;73(4):909–915. doi: 10.1093/jac/dkx521 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16].NGHRUoGso AMR. Whole-genome sequencing as part of national and international surveillance programmes for antimicrobial resistance: a roadmap. BMJ Glob Health. 2020;5(11):e002244. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].CLSI . Performance standards for antimicrobial susceptibility testing, 34th ed. CLSI supplement M100. Malvern, PA: Clinical and Laboratory Standards Institute. 2024. [Google Scholar]
  • [18].European Committee on Antimicrobial Susceptibility Testing (EUCAST) . Breakpoint tables for interpretation of MICs and zone diameters, version 14.0. Växjö, Sweden: European Society of Clinical Microbiology and Infectious Diseases (ESCMID); 2024. [Google Scholar]
  • [19].Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–2120. doi: 10.1093/bioinformatics/btu170 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Bankevich A, Nurk S, Antipov D, et al. Spades: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–477. doi: 10.1089/cmb.2012.0021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Joensen KG, Tetzschner AMM, Iguchi A, et al. Rapid and easy in silico serotyping of Escherichia coli isolates by use of whole-genome sequencing data. J Clin Microbiol. 2015;53(8):2410–2426. doi: 10.1128/JCM.00008-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [22].Chen L, Zheng D, Liu B, et al. Vfdb 2016: hierarchical and refined dataset for big data analysis—10 years on. Nucleic Acids Res. 2016;44(D1):D694–7. doi: 10.1093/nar/gkv1239 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Sullivan MJ, Petty NK, Beatson SA. Easyfig: a genome comparison visualizer. Bioinformatics. 2011;27(7):1009–1010. doi: 10.1093/bioinformatics/btr039 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Olson RD, Assaf R, Brettin T, et al. Introducing the bacterial and viral bioinformatics resource center (BV-BRC): a resource combining PATRIC, IRD and ViPR. Nucleic Acids Res. 2023;51(D1):D678–D689. doi: 10.1093/nar/gkac1003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Davis JJ, Gerdes S, Olsen GJ, et al. PattyFams: protein families for the microbial genomes in the PATRIC database. Front Microbiol. 2016;7:118. doi: 10.3389/fmicb.2016.00118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Cock PJA, Antao T, Chang JT, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422–1423. doi: 10.1093/bioinformatics/btp163 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [27].Edgar RC. Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–1797. doi: 10.1093/nar/gkh340 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Stamatakis A. Raxml version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–1313. doi: 10.1093/bioinformatics/btu033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web servers. Syst Biol. 2008;57(5):758–771. doi: 10.1080/10635150802429642 [DOI] [PubMed] [Google Scholar]
  • [30].Bassetti M, Peghin M, Pecori D. The management of multidrug-resistant Enterobacteriaceae. J Curr Opin Infect Dis. 2016;29(6):583–594. doi: 10.1097/QCO.0000000000000314 [DOI] [PubMed] [Google Scholar]
  • [31].Liang G, Rao Y, Wang S, et al. Co-occurrence of NDM-9 and MCR-1 in a human gut colonized Escherichia coli ST1011. J Infect Drug Resist. 2021;Volume 14:3011–3017. doi: 10.2147/IDR.S321732 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Karade S, Sen S, Shergill SPS, et al. Whole genome sequence of colistin-resistant Escherichia coli from western India. J Med J Armed Forces India. 2021;77(3):297–301. doi: 10.1016/j.mjafi.2020.10.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [33].Wangchinda W, Pati N, Maknakhon N, et al. Collateral damage of using colistin in hospitalized patients on emergence of colistin-resistant Escherichia coli and Klebsiella pneumoniae colonization and infection. Antimicrob Resist Infect Control. 2018;7(1):1–12. doi: 10.1186/s13756-018-0375-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Majewski P, Gutowska A, Smith DGE, et al. Plasmid mediated mcr-1.1 colistin-resistance in clinical extraintestinal Escherichia coli strains isolated in Poland. Front Microbiol. 2021;12:547020. doi: 10.3389/fmicb.2021.547020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [35].Farhan SM, El-Baky RMA, Abdalla S, et al. In vitro and in vivo effect of amikacin and imipenem combinations against multidrug-resistant E. coli. TropicalMed. 2022;7(10):281. doi: 10.3390/tropicalmed7100281 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [36].Evans DR, Griffith MP, Sundermann AJ, et al. Systematic detection of horizontal gene transfer across genera among multidrug-resistant bacteria in a single hospital. J Elife. 2020;9:e53886. doi: 10.7554/eLife.53886 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Xanthopoulou K, Carattoli A, Wille J, et al. Antibiotic resistance and mobile genetic elements in extensively drug-resistant Klebsiella pneumoniae sequence type 147 recovered from Germany. J Antibiot. 2020;9(10):675. doi: 10.3390/antibiotics9100675 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [38].Veilleux S, Holt N, Schultz BD, et al. Escherichia coli EAST1 toxin toxicity of variants 17–2 and O 42. Comp Immunol Microbiol Infect Dis. 2008. Nov;31(6):567–578. doi: 10.1016/j.cimid.2007.10.003 [DOI] [PubMed] [Google Scholar]
  • [39].Hussein NH, Al-Kadmy IMS, Taha BM, et al. Mobilized colistin resistance (mcr) genes from 1 to 10: a comprehensive review. Mol Biol Rep. 2021;48(3):2897–2907. doi: 10.1007/s11033-021-06307-y [DOI] [PubMed] [Google Scholar]
  • [40].Rozwandowicz M, Brouwer MSM, Fischer J, et al. Plasmids carrying antimicrobial resistance genes in Enterobacteriaceae. J J Antimicrob Chemother. 2018;73(5):1121–1137. doi: 10.1093/jac/dkx488 [DOI] [PubMed] [Google Scholar]
  • [41].Atterby C, Ramey AM, Hall GG, et al. Increased prevalence of antibiotic-resistant E. coli in gulls sampled in Southcentral Alaska is associated with urban environments. Infect Ecol & Epidemiol. 2016;6(1):32334. doi: 10.3402/iee.v6.32334 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [42].Viñes J, Cuscó A, Napp S, et al. Transmission of similar mcr-1 carrying plasmids among different Escherichia coli lineages isolated from livestock and the farmer. J Antibiot. 2021;10(3):313. doi: 10.3390/antibiotics10030313 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [43].Chen C-W, Tang H-J, Chen C-C, et al. The microbiological characteristics of carbapenem-resistant Enterobacteriaceae carrying the mcr-1 gene. J J Clin Med. 2019;8(2):261. doi: 10.3390/jcm8020261 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [44].Mayor S. Doctors to get real time data to support antibiotic prescribing and reduce resistance. Br Med J Publishing Group. 2019:l406. doi: 10.1136/bmj.l406 [DOI] [PubMed] [Google Scholar]
  • [45].Balali GI, Yar DD, Afua Dela VG, et al. Microbial contamination, an increasing threat to the consumption of fresh fruits and vegetables in today’s world. J Int J Microbiol. 2020;2020(1):1–13. doi: 10.1155/2020/3029295 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Kraemer SA, Ramachandran A, Perron GG. Antibiotic pollution in the environment: from microbial ecology to public policy. J Microorganisms. 2019;7(6):180. doi: 10.3390/microorganisms7060180 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Laxminarayan R, Duse A, Wattal C, et al. Antibiotic resistance—the need for global solutions. Lancet Infect Dis. 2013;13(12):1057–1098. doi: 10.1016/S1473-3099(13)70318-9 [DOI] [PubMed] [Google Scholar]
  • [48].Oliver A, Pérez-Díaz JC, Coque TM, et al. Nucleotide sequence and characterization of a novel cefotaxime-hydrolyzing β-lactamase (CTX-M-10) isolated in Spain. Antimicrob Agents Chemother. 2001;45(2):616–620. doi: 10.1128/AAC.45.2.616-620.2001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [49].Pupo GM, Lan R, Reeves PR. Multiple independent origins of Shigella clones of Escherichia coli and convergent evolution of many of their characteristics. Proc Natl Acad Sci USA. 2000;97(19):10567–10572. doi: 10.1073/pnas.180094797 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [50].Yang J, Nie H, Chen L, et al. Revisiting the molecular evolutionary history of Shigella spp. J Mol Evol. 2007;64(1):71–79. doi: 10.1007/s00239-006-0052-8 [DOI] [PubMed] [Google Scholar]
  • [51].Haggerty LS, Martin FJ, Fitzpatrick DA, et al. Gene and genome trees conflict at many levels. Phil Trans R Soc B. 2009;364(1527):2209–2219. doi: 10.1098/rstb.2009.0042 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [52].Rolland K, Lambert-Zechovsky N, Picard B, et al. Shigella and enteroinvasive Escherichia coli strains are derived from distinct ancestral strains of E. coli. J Microbiol. 1998;144(9):2667–2672. doi: 10.1099/00221287-144-9-2667 [DOI] [PubMed] [Google Scholar]
  • [53].Escobar-P?ramo P, Giudicelli C, Parsot C, et al. The evolutionary history of Shigella and enteroinvasive Escherichia coli revised. J J Mol Evol. 2003;57(2):140–148. doi: 10.1007/s00239-003-2460-3 [DOI] [PubMed] [Google Scholar]
  • [54].Touchon M, Hoede C, Tenaillon O, et al. Organised genome dynamics in the Escherichia coli species results in highly diverse adaptive paths. J PLoS Genet. 2009;5(1):e1000344. doi: 10.1371/journal.pgen.1000344 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [55].Ogura Y, Ooka T, Iguchi A, et al. Comparative genomics reveal the mechanism of the parallel evolution of O157 and non-O157 enterohemorrhagic Escherichia coli. Proc Natl Acad Sci USA. 2009;106(42):17939–17944. doi: 10.1073/pnas.0903585106 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [56].Sánchez-Romero I, Asensio Á, Oteo J, et al. Nosocomial outbreak of VIM-1-producing Klebsiella pneumoniae isolates of multilocus sequence type 15: molecular basis, clinical risk factors, and outcome. Antimicrob Agents Chemother. 2012;56(1):420–427. doi: 10.1128/AAC.05036-11 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [57].Ko KS, Lee MY, Song J-H, et al. Prevalence and characterization of extended-spectrum β-lactamase–producing Enterobacteriaceae isolated in Korean hospitals. Diagn Microbiol Infect Dis. 2008;61(4):453–459. doi: 10.1016/j.diagmicrobio.2008.03.005 [DOI] [PubMed] [Google Scholar]
  • [58].Zhang R, Wang XD, Cai JC, et al. Outbreak of Klebsiella pneumoniae carbapenemase 2-producing K. pneumoniae with high qnr prevalence in a Chinese hospital. J J Med Microbiol. 2011;60(7):977–982. doi: 10.1099/jmm.0.015826-0 [DOI] [PubMed] [Google Scholar]
  • [59].Haller S, Kramer R, Becker K, et al. Extensively drug-resistant Klebsiella pneumoniae ST307 outbreak, north-eastern Germany, June to October 2019. J Eurosurveillance. 2019;24(50):1900734. doi: 10.2807/1560-7917.ES.2019.24.50.1900734 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [60].Pirš M, Cerar Kišek T, Križan Hergouth V, et al. Successful control of the first OXA-48 and/or NDM carbapenemase-producing Klebsiella pneumoniae outbreak in Slovenia 2014–2016. J J Hosp Infect. 2019;101(2):142–149. doi: 10.1016/j.jhin.2018.10.022 [DOI] [PubMed] [Google Scholar]
  • [61].Guducuoglu H, Gursoy NC, Yakupogullari Y, et al. Hospital outbreak of a colistin-resistant, NDM-1- and OXA-48-producing Klebsiella pneumoniae: high mortality from pandrug resistance. J Microb Drug Resist. 2018;24(7):966–972. doi: 10.1089/mdr.2017.0173 [DOI] [PubMed] [Google Scholar]
  • [62].Huang Y-H, Chou S-H, Liang S-W, et al. Emergence of an XDR and carbapenemase-producing hypervirulent Klebsiella pneumoniae strain in Taiwan. J J Antimicrob Chemother. 2018;73(8):2039–2046. doi: 10.1093/jac/dky164 [DOI] [PubMed] [Google Scholar]
  • [63].Farhadi M, Ahanjan M, Goli HR, et al. High frequency of multidrug-resistant (MDR) Klebsiella pneumoniae harboring several β-lactamase and integron genes collected from several hospitals in the north of Iran. Ann Clin Microbiol Antimicrob. 2021;20(1):1–9. doi: 10.1186/s12941-021-00476-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [64].Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev. 2010;74(3):417–433. doi: 10.1128/MMBR.00016-10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [65].Li B, Yi Y, Wang Q, et al. Analysis of drug resistance determinants in Klebsiella pneumoniae isolates from a tertiary-care hospital in Beijing, China. J PLOS ONE. PLOS ONE. 2012;7(7):e42280. doi: 10.1371/journal.pone.0042280 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [66].Jemima S, Verghese S. Molecular characterization of nosocomial CTX-M type β-lactamase producing Enterobacteriaceae from a tertiary care hospital in South India. J Indian J Med Microbiol. 2008;26(4):365–368. doi: 10.1016/S0255-0857(21)01816-8 [DOI] [PubMed] [Google Scholar]
  • [67].Kim HB, Park CH, Kim CJ, et al. Prevalence of plasmid-mediated quinolone resistance determinants over a 9-year period. Antimicrob Agents Chemother. 2009;53(2):639–645. doi: 10.1128/AAC.01051-08 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [68].Ramirez MS, Tolmasky ME. Aminoglycoside modifying enzymes. J Drug Resist Updates. 2010;13(6):151–171. doi: 10.1016/j.drup.2010.08.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [69].Leavitt A, Chmelnitsky I, Ofek I, et al. Plasmid pKpqil encoding KPC-3 and TEM-1 confers carbapenem resistance in an extremely drug-resistant epidemic Klebsiella pneumoniae strain. J J Antimicrob Chemother. 2010;65(2):243–248. doi: 10.1093/jac/dkp417 [DOI] [PubMed] [Google Scholar]
  • [70].Younes A, Hamouda A, Dave J, et al. Prevalence of transferable blaCTX-M-15 from hospital- and community-acquired Klebsiella pneumoniae isolates in Scotland. J J Antimicrob Chemother. 2011;66(2):313–318. doi: 10.1093/jac/dkq453 [DOI] [PubMed] [Google Scholar]
  • [71].Wang L, Gu H, Lu X. A rapid low-cost real-time PCR for the detection of Klebsiella pneumoniae carbapenemase genes. Ann Clin Microbiol Antimicrob. 2012;11(1):1–6. doi: 10.1186/1476-0711-11-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [72].Goswami C, Fox S, Holden MTG, et al. Origin, maintenance and spread of antibiotic resistance genes within plasmids and chromosomes of bloodstream isolates of Escherichia coli. J Microb Genomics. 2020;6(4):e000353. doi: 10.1099/mgen.0.000353 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [73].Jeong SH, Bae IK, Kim D, et al. First outbreak of Klebsiella pneumoniae clinical isolates producing GES-5 and SHV-12 extended-spectrum β-lactamases in Korea. Antimicrob Agents Chemother. 2005;49(11):4809–4810. doi: 10.1128/AAC.49.11.4809-4810.2005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [74].Veras DL, de Souza Lopes AC, Vaz da Silva G, et al. Ultrastructural changes in clinical and microbiota isolates of Klebsiella pneumoniae carriers of genes bla SHV, bla TEM, bla CTX-M, or bla KPC when subject to β-lactam antibiotics. J Sci World J. 2015;2015(1):572128. doi: 10.1155/2015/572128 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [75].Navon-Venezia S, Kondratyeva K, Carattoli A. Klebsiella pneumoniae: a major worldwide source and shuttle for antibiotic resistance. J FEMS Microbiol Rev. 2017;41(3):252–275. doi: 10.1093/femsre/fux013 [DOI] [PubMed] [Google Scholar]
  • [76].Wyres KL, Wick RR, Judd LM, et al. Distinct evolutionary dynamics of horizontal gene transfer in drug resistant and virulent clones of Klebsiella pneumoniae. J PLoS Genet. 2019;15(4):e1008114. doi: 10.1371/journal.pgen.1008114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [77].Zhao H, He Z, Li Y, et al. Epidemiology of carbapenem-resistant Klebsiella pneumoniae ST15 of producing KPC-2, SHV-106 and CTX-M-15 in Anhui, China. J BMC Microbiol. 2022;22(1):262. doi: 10.1186/s12866-022-02672-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [78].Li R, Cheng J, Dong H, et al. Emergence of a novel conjugative hybrid virulence multidrug-resistant plasmid in extensively drug-resistant Klebsiella pneumoniae ST15. J Int J Antimicrob Agents. 2020;55(6):105952. doi: 10.1016/j.ijantimicag.2020.105952 [DOI] [PubMed] [Google Scholar]
  • [79].Naha S, Sands K, Mukherjee S, et al. Oxa-181-like carbapenemases in Klebsiella pneumoniae ST14, ST15, ST23, ST48, and ST231 from septicemic neonates: coexistence with NDM-5, resistome, transmissibility, and genome diversity. J MSphere. 2021;6(1):20. doi: 10.1128/mSphere.01156-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [80].Soliman AM, Nariya H, Tanaka D, et al. Vegetable-derived carbapenemase-producing high-risk Klebsiella pneumoniae ST15 and Acinetobacter baumannii ST2 clones in Japan: coexistence of bla NDM-1, bla OXA-66, bla OXA-72, and an AbaR4-like resistance island in the same sample. Appl Environ Microbiol. 2021;87(9):02166–20. doi: 10.1128/AEM.02166-20 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [81].Davoudabadi S, Goudarzi H, Goudarzi M, et al. Detection of extensively drug-resistant and hypervirulent Klebsiella pneumoniae ST15, ST147, ST377 and ST442 in Iran. AMicr. 2022;69(1):77–86. doi: 10.1556/030.2021.01562 [DOI] [PubMed] [Google Scholar]
  • [82].Shi Q, Han R, Guo Y, et al. Emergence of ST15 Klebsiella pneumoniae clinical isolates producing plasmids-mediated RmtF and OXA-232 in China. IDR, 2020: p. 3125–3129. Volume 13. doi: 10.2147/IDR.S257298 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [83].Berglund B, Hoang NTB, Tärnberg M, et al. Molecular and phenotypic characterization of clinical isolates belonging to a KPC-2-producing strain of ST15 Klebsiella pneumoniae from a Vietnamese pediatric hospital. Antimicrob Resist Infect Control. 2019;8(1):1–8. doi: 10.1186/s13756-019-0613-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [84].Hu Y, Liu C, Shen Z, et al. Prevalence, risk factors and molecular epidemiology of carbapenem-resistant Klebsiella pneumoniae in patients from Zhejiang, China, 2008–2018. Emerging Microbes Infections. 2020;9(1):1771–1779. doi: 10.1080/22221751.2020.1799721 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [85].Gu D, Dong N, Zheng Z, et al. A fatal outbreak of ST11 carbapenem-resistant hypervirulent Klebsiella pneumoniae in a Chinese hospital: a molecular epidemiological study. Lancet Infect Dis. 2018;18(1):37–46. doi: 10.1016/S1473-3099(17)30489-9 [DOI] [PubMed] [Google Scholar]
  • [86].Zhang R, Liu L, Zhou H, et al. Nationwide surveillance of clinical carbapenem-resistant Enterobacteriaceae (CRE) strains in China. J EBioMedicine. 2017;19:98–106. doi: 10.1016/j.ebiom.2017.04.032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [87].Chen L, Mathema B, Chavda KD, et al. Carbapenemase-producing Klebsiella pneumoniae: molecular and genetic decoding. J Trends Microbiol. 2014;22(12):686–696. doi: 10.1016/j.tim.2014.09.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [88].Chen L, Mathema B, Pitout JDD, et al. Epidemic Klebsiella pneumoniae ST258 is a hybrid strain. J MBio. 2014;5(3):355–14. doi: 10.1128/mBio.01355-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [89].Meatherall BL, Gregson D, Ross T, et al. Incidence, risk factors, and outcomes of Klebsiella pneumoniae bacteremia. J Am J Med. 2009;122(9):866–873. doi: 10.1016/j.amjmed.2009.03.034 [DOI] [PubMed] [Google Scholar]
  • [90].Duan Q, Wang Q, Sun S, et al. St11 carbapenem-resistant Klebsiella pneumoniae clone harboring bla NDM replaced a bla KPC clone in a tertiary hospital in China. J Antibiot. 2022;11(10):1373. doi: 10.3390/antibiotics11101373 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [91].Zhong Y, Liu W, Yuan P, et al. Occurrence of Serratia marcescens carrying bla IMP-26 and mcr-9 in southern China: new insights in the evolution of megaplasmid IMP-26. J Antibiot. 2022;11(7):869. doi: 10.3390/antibiotics11070869 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [92].Shirshikova TV, Sierra-Bakhshi CG, Kamaletdinova LK, et al. The ABC-type efflux pump MacAB is involved in protection of Serratia marcescens against aminoglycoside antibiotics, polymyxins, and oxidative stress. J MSphere. 2021;6(2):21. doi: 10.1128/mSphere.00033-21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [93].Mahlen SD. Serratia infections: from military experiments to current practice. Clin Microbiol Rev. 2011;24(4):755–791. doi: 10.1128/CMR.00017-11 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [94].Jiang Y, Wang Y, Hua X, et al. Pooled plasmid sequencing reveals the relationship between mobile genetic elements and antimicrobial resistance genes in clinically isolated Klebsiella pneumoniae. Genomics, Proteomics Bioinf. 2020;18(5):539–548. doi: 10.1016/j.gpb.2020.12.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [95].Tang B, Zhao H, Li J, et al. Detection of clinical Serratia marcescens isolates carrying blaKPC-2 in a hospital in China. J Heliyon. 2024;10(8):e29702. doi: 10.1016/j.heliyon.2024.e29702 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [96].Flyg C, Kenne K, Boman HG. Insect pathogenic properties of Serratia marcescens: phage-resistant mutants with a decreased resistance to cecropia immunity and a decreased virulence to Drosophila. J Microbiol. 1980;120(1):173–181. doi: 10.1099/00221287-120-1-173 [DOI] [PubMed] [Google Scholar]
  • [97].Schulenburg H, Ewbank JJ. Diversity and specificity in the interaction between Caenorhabditis elegans and the pathogen Serratia marcescens. BMC Evol Biol. 2004;4(1):1–8. doi: 10.1186/1471-2148-4-49 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [98].Petty NK, Foulds IJ, Pradel E, et al. A generalized transducing phage (ϕ IF3) for the genomically sequenced Serratia marcescens strain Db11: a tool for functional genomics of an opportunistic human pathogen. J Microbiol. 2006;152(6):1701–1708. doi: 10.1099/mic.0.28712-0 [DOI] [PubMed] [Google Scholar]
  • [99].Gutiérrez-Gutiérrez B, Rodríguez-Baño J. Current options for the treatment of infections due to extended-spectrum beta-lactamase-producing Enterobacteriaceae in different groups of patients. Clin Microbiol Infect. 2019. Aug;25(8):932–942. doi: 10.1016/j.cmi.2019.03.030 [DOI] [PubMed] [Google Scholar]
  • [100].Mourabiti F, Jouga F, Sakoui S, et al. Mechanisms, therapeutic strategies, and emerging therapeutic alternatives for carbapenem resistance in Gram-negative bacteria. Arch Microbiol. 2025. Feb 13;207(3):58. doi: 10.1007/s00203-025-04252-z [DOI] [PubMed] [Google Scholar]
  • [101].Hameed MF. Genomic insights into multidrug-resistant bacteria: emergence of mcr-1.1 in Escherichia coli, blaKPC-2 in Klebsiella pneumoniae and Serratia marcescens in clinical settings in China. figshare. 2025. doi: 10.6084/m9.figshare.28616705.v2 Dataset. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

QVIR-2025-0162.R1 - Table S3.xlsx
KVIR_A_2668179_SM3871.xlsx (10.2KB, xlsx)
Table S5.docx
KVIR_A_2668179_SM3870.docx (15.1KB, docx)
Table S6.docx
KVIR_A_2668179_SM3869.docx (15KB, docx)
QVIR-2025-0162.R1 - Table S9.xlsx
KVIR_A_2668179_SM3868.xlsx (10.2KB, xlsx)
QVIR-2025-0162.R1 - Table S8.xlsx
KVIR_A_2668179_SM3867.xlsx (9.8KB, xlsx)
Table S2.docx
KVIR_A_2668179_SM3866.docx (14.7KB, docx)
Table S4.docx
KVIR_A_2668179_SM3865.docx (15KB, docx)
QVIR-2025-0162.R1- Table S11.xlsx
KVIR_A_2668179_SM3864.xlsx (9.5KB, xlsx)
QVIR-2025-0162.R1 - Table S7.xlsx
KVIR_A_2668179_SM3863.xlsx (10.6KB, xlsx)
Table S1.docx
KVIR_A_2668179_SM3862.docx (24.5KB, docx)
Table S10.docx
KVIR_A_2668179_SM3861.docx (15.1KB, docx)

Data Availability Statement

The whole genome sequence data of five MDR isolates of this study have been deposited in NCBI (accessible at: https://www.ncbi.nlm.nih.gov/) repository under BioSample IDs: SAMN54564534, SAMN54564553, SAMN54564576, SAMN54564892, and SAMN54564960 for EC385, KP304, KP297, KP69, and SM66, respectively. Moreover, the other supplemental data related to this study have also been uploaded to figshare (an online open-access data repository) and is now available publicly at https://doi.org/10.6084/m9.figshare.28616705 [101].

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