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Article

Comprehensive Genomic Analysis of Pseudomonas aeruginosa PSU9449 Isolated from a Clinical Case in Thailand

by
Thitaporn Dechathai
1,
Kamonnut Singkhamanan
1,
Thunchanok Yaikhan
1,
Sarunyou Chusri
2,
Rattanaruji Pomwised
3,
Monwadee Wonglapsuwan
3 and
Komwit Surachat
1,4,*
1
Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
2
Division of Infectious Diseases, Department of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
3
Division of Biological Science, Faculty of Science, Prince of Songkla University, Songkhla 90110, Thailand
4
Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
*
Author to whom correspondence should be addressed.
Antibiotics 2025, 14(6), 530; https://doi.org/10.3390/antibiotics14060530
Submission received: 16 April 2025 / Revised: 14 May 2025 / Accepted: 19 May 2025 / Published: 22 May 2025
(This article belongs to the Special Issue Genetics and Antimicrobial Resistance in Pathogens of Hospital Importance)
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Abstract

:
Background/Objectives: Pseudomonas aeruginosa is one of the most significant multidrug-resistant bacteria. It poses considerable challenges in terms of treatment and causes hospital-acquired infections that lead to high morbidity and mortality. Colonization by P. aeruginosa in a patient without clinical signs of infection is a concern in hospital settings, as it is an opportunistic pathogen and can potentially be a multidrug-resistant strain. The objective of this study was to characterize and provide a detailed genomic analysis of this strain of the P. aeruginosa PSU9449 genome, an isolate obtained from a patient at Songklanagarind Hospital, Thailand. Methods: Whole-genome sequencing (WGS) and bioinformatics analysis were employed to examine the genomic features of P. aeruginosa PSU9449. We performed sequence type (ST) determination through multilocus sequence typing (MLST), identified antimicrobial resistance genes (ARGs), virulence factor genes (VFGs), and analyzed the presence of mobile genetic elements (MGEs). Additionally, we compared the PSU9449 genome with strains from neighboring countries to understand its phylogenetic relationship. Results: The P. aeruginosa PSU9449 genome contained five insertion sequences and several ARGs, including fosA, aph (3’)-IIb, blaOXA-50, and catB7. It also harbored VFGs related to flagella (fli, fle, and flg), the type 6 secretion system (hcpA, tssA, and las), and the type 3 secretion system (exoS, exoU, and exoT). MLST identified PSU9449 as ST3777, which was reported in Thailand for the first time. Phylogenetic analysis based on core gene SNPs revealed that PSU9449 was closely related to P. aeruginosa HW001G from Malaysia and P. aeruginosa MyJU45 from Myanmar, forming a distinct clade. Conclusions: This study presents a comprehensive genomic analysis of P. aeruginosa PSU9449, shedding light on its genetic characteristics, antimicrobial resistance profile, and virulence potential. Interestingly, ST3777, the novel STs from the published genomes of P. aeruginosa in Thailand, were assigned in this study. The findings enhance valuable insights into the expanding knowledge of P. aeruginosa PSU9449 and highlight the importance of ongoing surveillance of its genetic diversity.

1. Introduction

Pseudomonas aeruginosa is a Gram-negative rod bacterium and an opportunistic pathogen classified as one of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter species), a group of multidrug-resistant (MDR) bacteria that play a major role in outbreaks of nosocomial infections worldwide [1]. The MDR-ESKAPE pathogens in Southeast Asian countries are becoming increasingly prevalent [2,3,4]. These pathogens are notorious for their resistance to multiple antibiotics, complicating treatment and leading to prolonged ICU stays, higher healthcare costs, and increased mortality rates [5]. MDR P. aeruginosa was highlighted in the CDC’s 2019 Antibiotic Resistance Threats Report, which noted that in 2017, there were approximately 32,600 hospital-acquired infections caused by MDR P. aeruginosa and approximately 2700 associated deaths in the United States [6]. MDR P. aeruginosa is a significant global health concern and has high prevalence in various regions, particularly in Africa [7,8]. There is high-level resistance to carbapenems, cephalosporins, aminoglycosides, and colistin in some areas. Additionally, MDR P. aeruginosa has a high incidence in Europe and the Asia-Pacific region [9,10,11].
Currently, whole-genome sequencing (WGS) has become popular in several research areas. WGS is a powerful tool for studying comprehensive genetic information, particularly for identifying antimicrobial resistance genes (ARGs), mobile genetic elements (MGEs) and virulence factor genes (VFGs). In 2023, a study provided genomic insights into colonizing isolates of P. aeruginosa in Southern Thailand using WGS. The findings revealed frequently acquired ARGs such as fosA, aph (3’)-IIb, and blaOXA-50, which confer resistance against beta-lactams, aminoglycosides, and fosfomycin. Furthermore, a novel sequence type, ST-3910, was identified for the first time, proving useful for monitoring P. aeruginosa outbreaks across several regions [12]. Despite these advances, a significant knowledge gap remains in understanding the genomic characteristics and regional diversity of MDR P. aeruginosa isolates, particularly in Southeast Asia. While several global studies have provided a broad perspective on MDR strains, comparative genomic analyses at a local level between Thailand and neighboring countries remain limited. Such comparative studies are crucial for identifying unique genetic traits, resistance mechanisms and transmission that may be influenced by regional healthcare practices, environmental factors, or antibiotic usage patterns.
Given the global significance of MDR P. aeruginosa and its impact on public health, this study aimed to characterize the genomic profile of the strain PSU9449, isolated from a patient at Songklanagarind Hospital, Thailand. Using WGS and bioinformatics analysis, we identified ARGs, MGEs, and VFGs. Additionally, a comparative genomic analysis was conducted to examine genetic similarities and variations between PSU9449 and strains from Cambodia, Malaysia, and Myanmar, providing insights into regional genomic diversity. We hypothesize that MDR P. aeruginosa PSU9449 harbors distinct antimicrobial resistance determinants, mobile genetic elements, and virulence factors that contribute to its clinical significance. Furthermore, we expect that comparative genomic analysis will reveal regional variations in genetic composition, influenced by local antibiotic usage patterns, environmental factors, and healthcare practices. These findings will provide critical insights for managing infections and preventing the spread of resistant strains.

2. Results and Discussion

2.1. Clinical Information and Antimicrobial Susceptibility Profiles

Pseudomonas aeruginosa PSU9449 was isolated from the throat swab of a patient in the male medicine ward. The patient was admitted with underlying diseases but without clinical signs of a P. aeruginosa infection. This isolated species was identified as P. aeruginosa, according to routine laboratory procedures. The antimicrobial susceptibility results indicated that the strain was sensitive to all tested antibiotics.

2.2. Genome Characteristics and Species Confirmation

The whole-genome sequencing provided 37 contigs. The genome assembly size of P. aeruginosa PSU9449 was 6,195,518 bp with a GC content of 66.4%. The N50 of the genome was 399,445 bp, while the L50 was contig 6. Genome annotation revealed a total of 5683 genes, including 5607 coding sequences (CDS), 68 tRNAs, four rRNAs, one tmRNA, and three CRISPRs. General information, including 51 predicted antimicrobial resistance genes (ARGs) and 284 predicted virulence factor genes (VFGs), based on bioinformatic analysis of the draft genome assembly, is provided in Table 1. A circular map representing the draft genome and the predicted locations of resistance genes is shown in Figure 1.
To confirm the species, the ANI criterion, most often using values >95%, was compared with the reference strain. In this study, P. aeruginosa PSU9449 exhibited 99.28% ANI to the reference strain P. aeruginosa PAO1. The predicted serotype of P. aeruginosa PSU9449 was O11. This result was consistent with previous studies reporting that the most prevalent serotypes of P. aeruginosa were O6 and O11, both of which were clinical isolates found in patients with nosocomial pneumonia [13]. The probability of P. aeruginosa PSU9449 being a human pathogen was calculated at 0.751, indicating its potential to cause disease in humans, as it matched 581 pathogenic families. Understanding its genetic characteristics is necessary for developing effective treatment strategies and infection control measures, particularly in hospital settings where it poses a significant threat to immunodeficient patients.

2.3. Functional Annotation

The functional annotation analysis by RAST showed that the subsystem features a coverage of 29% distributed in 387 subsystems (Table 2). The most frequently assigned subsystems were amino acids and derivatives = 479 (19.54%); carbohydrates = 258 (10.52%), and protein metabolism = 219 (8.93%). The RAST results were consistent with the top three subsystem distributions in the P. aeruginosa genome reported in previous studies [14,15]. Moreover, amino acids and their derivatives play a crucial role in protein synthesis as building blocks and are associated with the synthesis of various metabolic pathways, such as nucleotides. Moreover, these amino acids are related to survival under stress conditions and can contribute to virulence factor production, host interaction, and immune evasion [16]. Carbohydrates perform several essential functions in bacterial cells, beyond serving as energy sources and structural components. They are key constituents of many virulence factors, such as lipopolysaccharides (LPS), extracellular polysaccharides that form capsules, and biofilms. Carbohydrates are a major component of the extracellular polymeric substance (EPS) matrix, which embeds bacterial cell communities in biofilms. The primary carbohydrates involved in biofilm formation are alginate, Psl, and Pel [17]. In addition, protein metabolism is fundamentally important to survival, adaptability, stress response, enzyme or toxin production, and virulence factor development in P. aeruginosa, contributing significantly to its pathogenicity. Secreted enzymes such as protease, lipase and elastase can degrade host proteins, invade host cells, and produce toxins like Exotoxin A. The delivery of these enzymes or toxins involves protein secretion systems in P. aeruginosa, including five secretion systems (T1SS–T3SS, T5SS–T6SS). They not only facilitate the virulence factor but also enable some strains that produce beta-lactamases and aminoglycoside-modifying enzymes, which inactivate and modify antibiotics, leading to antibiotic resistance [18].
Interestingly, the categories of virulence, disease and defense were found in 63 RAST subsystems (2.57%) and phages, prophages, transposable elements, and plasmids were identified in 11 RAST subsystems (0.45%). These features were desirable aspects of a pathogenic strain.

2.4. Mobile Genetic Elements (MGEs)

In this study, a bioinformatic analysis of the draft genome predicted the presence of five MGEs in P. aeruginosa PSU9449, all of which were insertion sequences (ISs) carrying ARGs, as shown in Table 3. Plasmids were not detected. Node 3 contained three ISs, including ISPa6, ISPa32, and ISPa2, which carried the fosA resistance gene. Node 1 harbored ISPsy29, which carried the blaPAO and aph (3’)-IIb genes. However, no MGEs were identified in nodes 11 and 14, although they carried the blaOXA-50 and catB7 genes, respectively. Additionally, node 18 contained ISPa22 without a resistance gene.
The IS elements are associated with genome rearrangement and plasticity. These elements are surrounded by open reading frames that encode transposases and can insert short DNA fragments into another location within a chromosome. ISs often play a role in mobilization and may carry antibiotic resistance genes. They facilitate the acquisition of resistance genes and transmit via horizontal gene transfer among bacterial populations [19,20]. According to ISfinder, ISPa6 and ISPa2 belong to the ISNCY family and originate from P. aeruginosa, with ISPa2 containing the exotoxin A (toxA) gene [21,22]. ISPa32 also originates from P. aeruginosa while ISPsy29 originates from Pseudomonas syringae, and both are part of the IS3 family [23,24]. The ISs predicted in this strain were similar to those of a previous study that showed the IS elements in P. aeruginosa isolated from patients in Southern Thailand [12].

2.5. Bacteriocin-Encoding Genes

The results of BAGEL4, used to predict bacteriocin-encoding genes, revealed two bacteriocin clusters identified in two Areas of Interest (AOIs). These clusters were in contig 3 (from 275,560 to 297,066 bp) and contig 25 (from 7667 to 27,667 bp) (Figure 2). Contig 3 encoded the pyocin-S2 immunity protein and colicin. Contig 25 contained the bmbF gene, which encoded a bacteriocin in the bottromycin class.
Pyocin, a bacteriocin produced by P. aeruginosa, has the advantage of being able to kill competing bacterial cells, including other strains of P. aeruginosa and other bacteria that share the same colonization niche. The soluble or S-type pyocin, which is colicin-like, is a protease-sensitive protein that exerts its killing effect by degrading chromosomal DNA through DNase activity [25,26]. The mechanism of pyocin S2 involves its entry into non-immune or sensitive P. aeruginosa cells under iron-limited conditions through a specific receptor, the siderophore pyoverdine receptor FpvAI (ferripyoverdine receptor type I) on the surface of P. aeruginosa cells. Additionally, an open reading frame (ORF) encodes an immunity protein (PyocinIm), which can attach to and inhibit the killing protein at the nuclease C-terminal domain, protecting the cell from the pyocin activity [27,28]. The properties of pyocin offer potential for developing new targeted antibacterial strategies, especially for combating antibiotic-resistant bacteria. For instance, a previous study demonstrated the potent activity of pyocin S2 against P. aeruginosa biofilms isolated from cystic fibrosis patients. This study showed that pyocin S2 effectively inhibits biofilm formation by P. aeruginosa and can prevent P. aeruginosa infections [29].
Bottromycins are macrocyclic peptides with strong antibacterial activity against Gram-positive bacteria, particularly MDR strains such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). Bottromycins exert their antibacterial action by binding to the 50S ribosomal subunit and aminoacyl-tRNA binding site (A-site), thereby inhibiting protein synthesis [30].

2.6. CRISPR-Cas and R-M Sites

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) systems offer a bacterial adaptive immune system to protect bacteria against foreign mobile genetic elements, which consists of a CRISPR array and Cas gene [31]. In P. aeruginosa PSU9449, we found five contigs with a CRISPR array, including 1, 24 (with cas6 type IF), 2, 8, and 9. The result is illustrated in Table 4.
CRISPR-Cas can help P. aeruginosa defend against invading genetic elements, such as a bacteriophage, prophage, or plasmid, as spacers in the CRISPR loci that recognize and destroy these elements upon re-invasion. This system can also control horizontal gene transfer, which involves the acquisition of MGEs carrying ARGs or virulence genes. Additionally, it provides evidence for the evolution of infection and can be used for genome editing and engineering novel therapeutics in P. aeruginosa [32,33]. However, R-M sites were not found in this strain.

2.7. Antibiotic Resistance Genes and Virulence Factors Profiling

Genomic analysis identified 51 ARGs with mechanisms including antibiotic inactivation, efflux pumps, antibiotic target alteration, and reduced antibiotic permeability. These genes collectively contribute to resistance against multiple antibiotic classes, including penicillin, macrolides, fluoroquinolones, aminoglycosides, carbapenems, and cephalosporins (Table 5). Based on genomic analysis, P. aeruginosa PSU9449 harbors multiple ARGs predicted to confer resistance to three or more antibiotic classes, suggesting its potential classification as an MDR strain, as it is predicted to be resistant to at least three or more antibiotic classes [34].
Bioinformatic analysis predicted 284 VFGs associated with biofilm formation, protease activity, motility, adherence, secretion systems, nutritional/metabolic factors, exotoxins, and immune modulation (Figure 3). The most prevalent VFGs were associated with flagella, which are crucial for motility, chemotaxis, surface colonization, adhesion to host tissues, and cell invasion [35]. The genes associated with flagellar expression and function, including fli, che, fle, flg, flh, and mot genes, play key roles in the assembly and formation of the basal body-hook complex and the regulation of the bacterial flagellum. Flagella are essential for bacterial motility, contributing to bacterial survival, host colonization, and pathogenicity [36]. The alg and muc genes are critical for the biosynthesis and regulation of alginate and mucopolysaccharides, which contribute to the biofilm matrix, bacterial biofilm formation, and virulence. Biofilm formation enhances bacterial survival and improves the bacteria’s ability to resist environmental stresses. The type 6 secretion system (T6SS) plays an important role in interbacterial competition (hcp gene) and interaction with host cells (vgrG, pldA gene). The T6SS is composed of several proteins that assemble into a structure resembling an inverted phage tail, which can puncture target cell membranes to deliver effector proteins. Additionally, the regulation of T6SS serves multiple virulence functions, including quorum sensing (QS) (las, rhl gene) and biofilm formation (tssA gene) [37]. Moreover, the type 3 secretion system (T3SS) plays an essential role in pathogenicity. It is a needle-like structure that can penetrate host cell membranes to deliver effector proteins into the host cell. These proteins are associated with facilitating disruption of host cell signaling (exoS gene), cytotoxicity (exoU gene), immune evasion (exoT gene), and manipulation of the host cell cytoskeleton (exoY gene) [38].

2.8. Pan-Genome Analysis and Phylogenetic Tree

The results of pan-genome analysis revealed a total number of 28,728 genes. These consisted of 3976 (13.84%) core genes, 908 (3.16%) soft core genes, 1640 (5.7%) shell genes and 22,204 (77.29%) cloud genes (Figure 4). The size of the accessory genome in this study, approximately 86%, is consistent with findings from other research, which report accessory genome sizes ranging approximately from 79% to 90% [12,39]. Generally, P. aeruginosa from various sources contains a wide array of accessory genes, many of which are acquired through horizontal gene transfer via plasmids, bacteriophages, transposons, or insertion sequences. These accessory genes are often associated with ARGs and VFGs [39,40,41]. This genomic plasticity underscores P. aeruginosa’s capacity to adapt to different environments and acquire traits that enhance its pathogenicity and resistance to treatment.
The sequence type (ST) of P. aeruginosa PSU9449 was determined through MLST, a method that analyzed seven housekeeping genes specific to P. aeruginosa. This analysis revealed that the strain belonged to ST3777, which represents a unique sequence type not previously reported in Thailand, as confirmed by data from PubMLST.
In Thailand, various STs are distributed differently, with ST1047 being predominant in Myanmar and ST-235 present in Malaysia, Myanmar, and Thailand. Our strain was closely related to P. aeruginosa HW001G from Malaysia and P. aeruginosa MyJU45 from Myanmar, forming a distinct clade (Figure 5). When compared with HW001G and MyJU45, our strain shared 5247 core genes. The majority of these shared genes are involved in essential biological processes such as metabolism, protein synthesis, energy production, and cell division. Notably, several shared genes are associated with virulence factors, including biofilm formation (e.g., alg, muc, and las genes), flagellar function (e.g., flg, flh, fli, and mot genes), and pyocyanin production (phz genes). Furthermore, these three strains share antimicrobial resistance genes, including mexAB and fosA, which are involved in antibiotic efflux and resistance to fosfomycin, respectively.
However, the unique genes of PSU9449, HW001G, and MyJU45 were 274, 364, and 715, respectively. Additionally, the interesting unique genes of PSU9449 include those related to Cas proteins (cas6f, csy3, csy2, csy1, cas3, and cas1), lasR, bdlA, imm2 and fliS. The lasR gene is a key transcriptional activator in P. aeruginosa that plays a crucial role in the QS system, which is associated with the population density of the bacterial community by detecting and binding to autoinducer molecules [42]. The bdlA gene is a critical regulatory protein in the process of biofilm dispersion, which is the transition from a biofilm state to a free-living, planktonic state [43]. The imm2 gene is a specific immunity protein of P. aeruginosa that protects it from its pyocin S2, as described above in relation to bacteriocin. Another virulence gene, the fliS gene, is involved in the assembly and function of the bacterial flagellum [36]. Therefore, all of these unique genes are related to the virulence factors of P. aeruginosa PSU9449.

3. Materials and Methods

3.1. Bacterial Strain and Antimicrobial Susceptibility Testing

Pseudomonas aeruginosa PSU9449 was isolated in 2017 from a throat swab of a hospitalized patient with underlying diseasesat Songklanagarind Hospital in Songkhla, Thailand. Initial species identification was performed using conventional biochemical tests according to Bergey’s Manual of Systematic Bacteriology, with confirmatory identification using Matrix-Assisted Laser Desorption/Ionization–Time of Flight (MALDI-TOF) mass spectrometry (Bruker Daltonik GmbH, Bremen, Germany). The isolate was cultured on Tryptic Soy Agar (TSA) media (HiMedia, Mumbai, India) and incubated at 37 °C overnight under aerobic conditions. After initial culturing, the strain was preserved in 20% glycerol at –80 °C for long-term storage. The antibiotic susceptibility of P. aeruginosa was tested against eight antimicrobial agents (amikacin, ciprofloxacin, imipenem, meropenem, ceftazidime, gentamicin, cefoperazone/sulbactam, and piperacilina/tazobactam) by the disk diffusion method. The results were evaluated following Clinical and Laboratory Standards Institute (CLSI) 2018 guidelines.

3.2. Genomic DNA Extraction and Whole-Genome Sequencing (WGS)

The GF-1 Bacterial DNA extraction kit (Vivantis, Subang Jaya, Malaysia) was employed for gDNA extraction following the manufacturer’s protocol. The purity and concentration of the gDNA extract were assessed using Thermo Scientific NanoDropTM 2000/2000c (Waltham, MA, USA) Spectrophotometers and confirmed through 1% w/v agarose gel electrophoresis. The purified gDNA was utilized for short-read WGS with 150 bp paired-end reads on the MGISEQ-2000 platform at the Beijing Genomics Institute (BGI, Shenzhen, China).

3.3. Genomic Assembly, Species Confirmation, and Annotation

Genomic reads were de novo assembled using Unicycler v0.5.0 [44], and quality assessment of genome assembly was evaluated using Quast V4.0 [45]. To perform species confirmation, the average nucleotide identity (ANI) was applied using FastANI v1.1.0 [46] compared with the P. aeruginosa PAO1 reference strain. Genome annotation was performed using Prokka v1.1.1 [47]. Functional annotations were assigned using Rapid Annotations using Subsystems Technology (RAST) (https://rast.nmpdr.org/rast.cgi (accessed on 30 October 2023)) [48,49,50] and EggNOG v5.0 [51] as well. The sequence types (STs) against traditional PubMLST typing schemes were identified in PubMLST (https://pubmlst.org/ (accessed on 30 October 2023)) [52].

3.4. Genomic Analysis

The P. aeruginosa serotypes were assigned using PAst 1.0 [53]. Identifying potential human pathogens was predicted using PathogenFinder 1.1 [54]. Bacteriocins were identified using the Bacteriocin Genome Mining Tool (BAGEL4) (http://bagel4.molgenrug.nl/ (accessed on 31 October 2023)) [55]. Mobile genetic elements (MGEs) related to ARGs and VFGs were identified using MobileElementFinder v1.0.3 [56]. CRISPR-Cas regions were investigated using the CRISPRCas Finder (https://crisprcas.i2bc.paris-saclay.fr/CrisprCasFinder/Index (accessed on 31 October 2023)) [57], and restriction-modification sites (R-M sites) were identified using Restriction-ModificationFinder 1.1 [58]. To identify ARGs, we employed ABRicate (https://github.com/tseemann/abricate (accessed on 3 November 2023)) and the Resistance Gene Identifier (RGI) (https://card.mcmaster.ca/analyze/rgi (accessed on 2 October 2023)) [59] against the Comprehensive Antibiotic Resistance Database (CARD) [60]. Virulence factors were detected using ABRicate (https://github.com/tseemann/abricate (accessed on 3 November 2023)) against the Virulence Factors Database (VFDB) [61] and VFanalyzer (http://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi (accessed on 2 October 2023)). All bioinformatic tools were applied with default settings.

3.5. Genomic Diversity and Pangenome Insights Across Neighboring Countries

P. aeruginosa PSU9449 was compared with 185 genome assemblies of P. aeruginosa found in Thailand and neighboring countries (3 strains in Cambodia, 23 strains in Malaysia, 29 strains in Myanmar, and 129 strains in Thailand). These genomes were retrieved from the GenBank database [accessed on 31 October 2023]. The pan-genome profile was analyzed using Roary v3.13.0 with the default settings [62].

3.6. Single Nucleotide Polymorphism (SNP) Phylogenetic Tree Analysis

SNP-sites v2.4.1 was used for SNPs calling from core gene alignments [63]. A circular SNP tree based on core genes was generated by FastTree v2.1 with the default settings [64,65] and visualized using the Interactive Tree of Life (iTOL) v5 [66].

4. Conclusions

In summary, the comprehensive genomic analysis of P. aeruginosa PSU9449, a clinical colonizing isolate from Thailand, revealed important genetic features that contribute to its multidrug resistance and virulence potential. The strain, assigned to the previously unreported sequence type ST3777, carried several antimicrobial resistance genes (fosA, aph (3’)-IIb, blaOXA-50, and catB7) located within mobile genetic elements, along with virulence genes associated with flagellar function, the type VI secretion system (T6SS), and the type III secretion system (T3SS). Although phenotypic antimicrobial susceptibility testing showed susceptibility to all tested antibiotics, genotypic analysis identified resistance genes that may not be actively expressed under current conditions but could potentially confer resistance under selective pressure over time. These findings highlighted the isolate’s potential clinical relevance and underscored its significance within the broader context of regional antimicrobial resistance surveillance. A comparative genomic analysis further demonstrates that PSU9449 shared a close phylogenetic relationship with strains from Malaysia and Myanmar, by sharing some antimicrobial resistance genes (mexAB and fosA genes) and some virulence genes, which are involved in biofilm formation, flagella, and pyocyanin. These findings suggest possible cross-border dissemination and the emergence of regionally adapted lineages. The discovery of a novel sequence type and its genomic context highlights the need for continuous genomic monitoring to better understand the evolution, dissemination, and clinical impact of multidrug-resistant P. aeruginosa in Southeast Asia.

Author Contributions

Conceptualization, T.D. and K.S. (Komwit Surachat); methodology, T.D., K.S. (Komwit Surachat), T.Y. and K.S. (Kamonnut Singkhamanan); software, T.D., T.Y. and K.S. (Komwit Surachat); validation, T.D., K.S. (Komwit Surachat), T.Y. and K.S. (Kamonnut Singkhamanan); formal analysis, T.D., K.S. (Komwit Surachat), T.Y., K.S. (Kamonnut Singkhamanan), S.C., R.P. and M.W.; investigation, T.D., K.S. (Komwit Surachat), T.Y., K.S. (Kamonnut Singkhamanan), S.C., R.P. and M.W.; resources, T.D., K.S. (Komwit Surachat), and K.S. (Kamonnut Singkhamanan); data curation, T.D. and K.S. (Komwit Surachat); writing—original draft preparation, T.D.; writing—review and editing, T.D., K.S. (Komwit Surachat), T.Y. and K.S. (Kamonnut Singkhamanan); visualization, T.D. and K.S. (Komwit Surachat); supervision, T.D., K.S. (Komwit Surachat), T.Y., K.S. (Kamonnut Singkhamanan), S.C., R.P. and M.W.; project administration, K.S. (Komwit Surachat), K.S. (Kamonnut Singkhamanan), S.C., R.P., M.W. and T.D.; funding acquisition, K.S. (Komwit Surachat). All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by a graduate scholarship from the Faculty of Medicine, Prince of Songkla University. In addition, this research was funded by the National Science, Research and Innovation Fund (NSRF), and Prince of Songkla University, Thailand, grant number MED6701384b. Also, this research was supported by the Postdoctoral Fellowship from Prince of Songkla University, Thailand, and has also received funding support from the NSRF via the Program Management Unit for Human Resources and Institutional Development, Research and Innovation, grant number B13F660074.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Human Research Ethics Committee (HREC) of Prince of Songkla University (protocol code: 64-284-14-1, date of approval: 9 June 2021).

Informed Consent Statement

Not applicable.

Data Availability Statement

The genome of P. aeruginosa PSU9449 (MEDPSU_PAT_001) in this study has been deposited in the NCBI GenBank under BioProject number PRJNA1033800, with BioSample number SAMN38044900.

Conflicts of Interest

The authors declare no conflicts of interest.

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Antibiotics 14 00530 g001
Figure 1. Circular draft genome mapping of the Pseudomonas aeruginosa PSU9449 (accession number JAWPGW000000000) revealed a genome size of 6,195,518 bp. The CGView tool visualized the circular genome, which contained genomic features represented from the outer to the inner circle. Circle 1 represents the antimicrobial resistance genes (ARGs) while circles 2,3 represent the forward and reverse strands of CDS, respectively. The innermost circles represent the GC content, GC skew+, and GC skew−.
Figure 1. Circular draft genome mapping of the Pseudomonas aeruginosa PSU9449 (accession number JAWPGW000000000) revealed a genome size of 6,195,518 bp. The CGView tool visualized the circular genome, which contained genomic features represented from the outer to the inner circle. Circle 1 represents the antimicrobial resistance genes (ARGs) while circles 2,3 represent the forward and reverse strands of CDS, respectively. The innermost circles represent the GC content, GC skew+, and GC skew−.
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Figure 2. Prediction of bacteriocin gene clusters in the Pseudomonas aeruginosa PSU9449 genome using the BAGEL4 web server. The locations of the bacteriocin are indicated by red arrows. (A) Bacteriocin genes encoded on Contig 3, including pyocin classes such as pyocinIm and colicin. (B) The BmbF gene encoding bottromycin located on Contig 25.
Figure 2. Prediction of bacteriocin gene clusters in the Pseudomonas aeruginosa PSU9449 genome using the BAGEL4 web server. The locations of the bacteriocin are indicated by red arrows. (A) Bacteriocin genes encoded on Contig 3, including pyocin classes such as pyocinIm and colicin. (B) The BmbF gene encoding bottromycin located on Contig 25.
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Figure 3. Virulence factor genes (VFGs) against virulence factor databases.
Figure 3. Virulence factor genes (VFGs) against virulence factor databases.
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Figure 4. Pan-genome profiles of Pseudomonas aeruginosa PSU9449 (highlighted in red box) compared with 185 genomes from neighboring countries, illustrating genomic diversity.
Figure 4. Pan-genome profiles of Pseudomonas aeruginosa PSU9449 (highlighted in red box) compared with 185 genomes from neighboring countries, illustrating genomic diversity.
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Figure 5. A single-nucleotide polymorphism (SNP) phylogenetic tree indicating the core genes of the Pseudomonas aeruginosa PSU9449 genome compared with 185 genomes in Cambodia, Malaysia, Myanmar, and Thailand. The innermost circles represent ST, country, and isolation source, respectively.
Figure 5. A single-nucleotide polymorphism (SNP) phylogenetic tree indicating the core genes of the Pseudomonas aeruginosa PSU9449 genome compared with 185 genomes in Cambodia, Malaysia, Myanmar, and Thailand. The innermost circles represent ST, country, and isolation source, respectively.
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Table 1. Genome Features of Pseudomonas aeruginosa PSU9449.
Table 1. Genome Features of Pseudomonas aeruginosa PSU9449.
General Features
Genome size (bp)6,195,518
GC content (%)66.4
Number of contigs37
CDS5607
Total RNA (tRNA + rRNA + tmRNA)73 (68 + 4 + 1)
N50399,445
L506
Number of ARGs51
Number of VFGs284
ARGs—Antimicrobial resistance genes, VFGs—Virulence factor genes.
Table 2. General features overview of subsystem information genes by RAST annotation.
Table 2. General features overview of subsystem information genes by RAST annotation.
Subsystem FeaturesCounts%
 Phages, prophages, transposable elements, plasmids110.45
 Cell wall and capsule421.71
 Cofactors, vitamins, prosthetic groups, pigments1967.99
 Sulfur metabolism391.59
 Nitrogen metabolism532.16
 Metabolism of aromatic compounds1184.81
 Fatty Acids, lipids, and isoprenoids1275.18
 Iron acquisition and metabolism512.08
 Miscellaneous451.84
 Nucleosides and nucleotides1024.16
 Amino acids and derivatives47919.54
 Stress response1044.24
 Dormancy and sporulation20.08
 Motility and chemotaxis230.94
 Respiration1144.65
 Protein metabolism2198.93
 Membrane transport1656.73
 Phosphorus metabolism421.71
 Regulation and cell signaling511.84
 Cell division and cell cycle00.00
 Photosynthesis00.00
 DNA metabolism773.14
 RNA metabolism572.32
 Potassium metabolism100.41
 Virulence, disease, and defense632.57
 Secondary metabolism40.16
 Carbohydrates25810.52
Table 3. Mobile genetic elements carrying antibiotic resistance genes.
Table 3. Mobile genetic elements carrying antibiotic resistance genes.
ContigPosition in ContigNumber of MGEsType of ISARGsPhenotype
NODE 3308,921–309,3283ISPa6, ISPa32, ISPa2fosAfosfomycin
NODE 138,184–39,3771ISPsy29blaPAOampicillin, amoxicillin, cefepime, ceftazidime
25,022–25,828 aph (3’)-IIbaminoglycoside
NODE 1197,602–98,3900 blaOXA-50ampicillin, amoxicillin
NODE 14119,289–119,9270 catB7chloramphenicol
NODE 18 1ISPa22
Table 4. CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) systems in P. aeruginosa PSU9449.
Table 4. CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) systems in P. aeruginosa PSU9449.
ContigElementNo. of Spacer/
Cas Gene
(Cas Type)		Repeat Consensus/Cas GenesEvidence Level
Node 1CRISPR12GTTCACTGCCGTATAGGCAGCTAAGAAA4
Node 24CRISPR9GTTCACTGCCGTATAGGCAGCTAAGAAA4
Cas cluster6 (IF)cas1, cas3-cas2, cas6, csy1, csy2, csy3
CRISPR12TTTCTTAGCTGCCTACACGGCAGTGAAC4
Node 2CRISPR1GCGGCGGGTATCGGCGGATAACGCC1
Node 8CRISPR1TCATACCTTGCCCTCCAGTTCTTTGGCC1
Node 9CRISPR1GCCGACAACGGCAGCGAGCAGACCGT1
Table 5. Antibiotic resistance genes against the CARD database.
Table 5. Antibiotic resistance genes against the CARD database.
Predicted Antibiotic Resistance GenesAMR Gene Family
Antibiotic efflux
mexY, mexD, mexA, mexB, mexC, mexE, mexF, mexG, mexH, mexI, mexJ, mexK, mexL, mexV, mexW, mexM, mexN, mexP, mexQ, mexXAntibiotic efflux pump-type resistance-nodulation-cell division (RND)
armR
muxA, muxB, muxC
opmB, ompD, opmH, ompJ, ompM, ompN, opmE
parR, parS
cpxR
triA, triB, triC
yajC
rsmA
pmpMMultidrug and toxic compound extrusion (MATE) transporter
emrEAntibiotic efflux pump type small multidrug resistance (SMR)
basSPmr phosphoethanolamine transferase
bcr-1Antibiotic efflux pump type major facilitator superfamily (MFS)
cprS, cprRPmr phosphoethanolamine transferase
Reduced permeability to the antibiotic
parR, parSOuter Membrane Porin (Opr)
Antibiotic inactivation
fosAFosfomycin thiol transferase
blaOXA-50OXA beta-lactamase
aph(3’)-IIbAPH(3’)
pdc-374PDC beta-lactamase
catB7chloramphenicol acetyltransferase (CAT)
Antibiotic target alteration
arnA, basS, cprR, cprSPmr phosphoethanolamine transferase
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Dechathai, T.; Singkhamanan, K.; Yaikhan, T.; Chusri, S.; Pomwised, R.; Wonglapsuwan, M.; Surachat, K. Comprehensive Genomic Analysis of Pseudomonas aeruginosa PSU9449 Isolated from a Clinical Case in Thailand. Antibiotics 2025, 14, 530. https://doi.org/10.3390/antibiotics14060530

AMA Style

Dechathai T, Singkhamanan K, Yaikhan T, Chusri S, Pomwised R, Wonglapsuwan M, Surachat K. Comprehensive Genomic Analysis of Pseudomonas aeruginosa PSU9449 Isolated from a Clinical Case in Thailand. Antibiotics. 2025; 14(6):530. https://doi.org/10.3390/antibiotics14060530

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Dechathai, Thitaporn, Kamonnut Singkhamanan, Thunchanok Yaikhan, Sarunyou Chusri, Rattanaruji Pomwised, Monwadee Wonglapsuwan, and Komwit Surachat. 2025. "Comprehensive Genomic Analysis of Pseudomonas aeruginosa PSU9449 Isolated from a Clinical Case in Thailand" Antibiotics 14, no. 6: 530. https://doi.org/10.3390/antibiotics14060530

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Dechathai, T., Singkhamanan, K., Yaikhan, T., Chusri, S., Pomwised, R., Wonglapsuwan, M., & Surachat, K. (2025). Comprehensive Genomic Analysis of Pseudomonas aeruginosa PSU9449 Isolated from a Clinical Case in Thailand. Antibiotics, 14(6), 530. https://doi.org/10.3390/antibiotics14060530

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