Genomic dataset of eighteen Burkholderia pseudomallei strains isolated from clinical and environmental settings in Malaysia

Highlights

• •B. pseudomallei is a Gram-negative bacillus inhabiting natural environment such as soil and water in endemic regions.
• •Melioidosis is highly endemic in Northern Australia and Southeast Asia regions including Malaysia and its neighbouring countries
• •The genome of B. pseudomallei consists of two distinct chromosomes, with an average length of 7,823, 977 bp, with an average GC content of 67.4%.
• •One of the crucial virulence gene found in the strains is the Type VI Secretion System 5 (T6SS-5) gene clusters which is located on chromosome two of the B. pseudomallei genome.
• •Antimicrobial resistance (AMR) gene detection revealed one predicted resistance profile, the Carbapenem-hydrolysing class D beta-lactamase 59 (blaOXA-59) gene, conferring predicted resistance to ampicillin, beta-lactam antibiotics.

Abstract

Burkholderia pseudomallei is a highly infectious bacterium responsible for melioidosis, a systemic disease prevalent in Northern Australia and Southeast Asia. Melioidosis is a community-acquired infectious disease caused by B. pseudomallei, which thrives in tropical regions.

This study presents the complete genome sequences of 18 B. pseudomallei isolates from clinical and environmental settings in Kelantan, Malaysia. Clinical isolates were characterized based on patient outcomes: recovery (n=6), relapse (n=4), and death due to melioidosis (n=6), with two environmental isolates that were obtained from soil samples. Draft genome sequences of the isolates were generated using Illumina HiSeq sequencing technology.

The 18 B. pseudomallei genomes have an average length of 7,823, 977 bp (7,587,408-8,243,305 bp), an average GC content of 67.4%, with a mean N50 length and contigs of 47,798 bp and 2,882, respectively. RAST identified an average of 9,671 CDS and 64 RNAs per genome. A total of 144 virulence genes were identified across the dataset, including bimA, bipD, bopA, hcp, and vgrG genes. Antimicrobial resistance gene detection revealed a predicted resistance profile involving the blaOXA-59 gene, conferring resistance to beta-lactam antibiotics, present in all 18 genomes. MLST profiles revealed ST54 as the most common sequence type, corresponding to isolates USM003, USM010, USM011, USM013, and USM014. The 18 draft genomes also showed a close phylogenetic relationship with other genomes from Southeast Asia.

In summary, the complete genome sequences of 18 B. pseudomallei isolates have been elucidated and provide a valuable resource to investigate the genetic diversity and virulence profiles of B. pseudomallei.

Graphical abstract

Introduction

Melioidosis is a neglected infectious tropical disease that is endemic in Malaysia. Nevertheless, it is not yet a notifiable disease. As a result, there has been no inclusive representation of the actual incidence, clinical manifestations, and obstacles in the diagnosis and treatment of melioidosis in Malaysia and it might be differ across the country (Mariappan et al., 2022). Burkholderia pseudomallei is a Gram-negative bacillus that inhabits natural environments such as soil and stagnant water in endemic regions of Melioidosis. This possibly life-threatening infectious disease affects approximately 165,000 people globally, resulting in 89,000 deaths (54% mortality) yearly (Limmathurotsakul et al., 2016).

Melioidosis can be transmitted to humans via direct contact with contaminated soil and water, especially through open wounds on the skin. The disease presentation can be latent, acute, or chronic, and individuals with B. pseudomallei infection who develop clinical symptoms are diagnosed with melioidosis (Limmathurotsakul et al., 2016). Melioidosis may result in 85% of acute infections, 11% of chronic infections that may last for more than two months, and 5% of latent infections characterized by silent signs and asymptomatic symptoms (Shafiq et al., 2022, Currie and Cheng, 2010).

Diabetes is the most prevalent predisposing factor for the disease, which may affect any organ in the human body and often manifests as a lung infection or several abscesses in internal organs (Wiersinga et al., 2018). Because of the rapid spread of infection via the blood, melioidosis has a significant mortality rate. Even though the disease's main clinical manifestations are similar across nations, significant regional variances have been noted. The cases reported from Malaysia were comparable to those reported from South and Southeast Asia regarding major presentations of pneumonia and soft tissue abscesses, as well as diabetes as a key risk factor; infection spread to the bloodstream increased the risk of mortality. Immediate diagnosis and treatment, especially in questionable instances, is critical for preventing death (Mariappan et al., 2022).

The genome of B. pseudomallei consists of two distinct chromosomes with a high GC content of approximately 68%. The expansive genome of B. pseudomallei encodes a variety of features that support the pathogen’s survival under harsh conditions, including the host's internal environment (Kong et al., 2023). This complex genome poses a challenge in executing whole genome sequencing. Currently, the genome information for Malaysian B. pseudomallei strains is limited. Therefore, the aim of this present study was to gain insight into the B. pseudomallei genome, particularly the distinction between clinical and environmental isolates, using a Next Generation Sequencing (NGS) platform. Genome variation among clinical isolates and environmental isolates might be correlated with the severity and outcome of the patient’s disease.

Materials and Methods

Sample collection

Eighteen clinical B. pseudomallei isolates were archived samples from melioidosis patients in Hospital Universiti Sains Malaysia (HUSM), while two environmental isolates were collected from soil samples in Bachok, Kelantan. All 20 archived samples of B. pseudomallei, both clinical and environmental isolates were obtained from the Stock Culture Laboratory, Department of Medical Microbiology and Parasitology, USM, and the Institute for Research in Molecular Medicine (INFORMM), USM, respectively.

The clinical samples were randomly selected based on the outcome of the patients’ disease outcomes, including those who recovered, experienced a relapse, or succumbed to melioidosis infection (Table 1).

Table 1.

Characteristics of B. pseudomallei isolates.

Sample name	Isolate name	Date of isolation	Type of isolate	Source of isolate	Outcome of patients
USM001	BUPS 06/14	2014	Clinical	Pus	Recovered
USM002	BUPS 11/17	2017	Clinical	Blood	Recovered
USM003	BUPS 11/18	2018	Clinical	Pus	Recovered
USM004	BUPS 14/19	2019	Clinical	Endotracheal tube	Recovered
USM005	BUPS 22/19	2019	Clinical	Pus	Recovered
USM006	BUPS 36/19	2019	Clinical	Blood	Recovered
USM007	BUPS 11/09	2009	Clinical	Blood	Relapsed
USM008	BUPS 14/14	2014	Clinical	Blood	Relapsed
USM009	BUPS 23/14	2014	Clinical	Pus	Relapsed
USM010	BUPS 01/17	2017	Clinical	Pus	Relapsed
USM011	BUPS 05/18	2018	Clinical	Pus	Relapsed
USM012	BUPS 06/18	2018	Clinical	Pus	Relapsed
USM013	BUPS 04/17	2017	Clinical	Blood	Died
USM014	BUPS 06/17	2017	Clinical	Blood	Died
USM015	BUPS 09/17	2017	Clinical	Blood	Died
USM016	BUPS 26/14	2014	Clinical	Pus	Died
USM017	BUPS 27/14	2014	Clinical	Blood	Died
USM018	BUPS 09/19	2019	Clinical	Blood	Died
USM019	SP32285/S1	2019	Environment	Soil	NA
USM020	SP32285/S2	2019	Environment	Soil	NA

Genomic DNA extraction

All of the B. pseudomallei isolates were sub-cultured on Mueller Hinton (MH) agar and incubated at 37 °C for 24 to 48 hours before proceeding with DNA extraction. Genomic DNAs were prepared using QIAamp DNA Mini extraction kit according to manufacturer’s protocol.

Library preparation and sequencing

The genomic DNA was submitted to NovogeneAIT Genomics in Singapore for high-throughput DNA sequencing technology. Library preparation was performed using the NEBNext® Ultra™ DNA Library Prep Kit for Illumina according to the manufacturer’s instructions (NEB, USA). Sequencing was performed using the Illumina NovaSeq 150PE sequencing platform. The workflow for library preparation and sequencing is shown in Fig. 1.

Fig. 1.

Workflow for library preparation and sequencing.

Genome assembly, annotation, and data analysis

Quality control was performed using FastQC software. Adapter and low-quality sequences, with minimum average quality of 20 and a minimum sequence read length of 20 bases, were removed and trimmed using Trimmomatic (v0.36). Further bioinformatics analysis was performed using Galaxy (https://usegalaxy.eu/), a freely available web-based platform that offers a wide range of tools for evaluating WGS data in an easy-to-use interface (Afgan et al., 2018). The de novo assembly of processed paired-end reads was performed with the SPAdes genome assembler (version 3.14.) utilising the Shovill pipeline (https://github.com/tseemann/shovill) (Bankevich et al., 2012). QUAST was used to calculate assembly statistics such as the number of contigs and the N₅₀ value using default parameters (Gurevich et al., 2013).

Genotyping was performed on assembled genomes using Staramr (Bharat et al., 2022). For genotypic sequence typing, the MLST system from PubMLST was employed, with MLST profiles assigned to each assembled strain. The ResFinder database was used for alignment-based AMR identification (Bortolaia et al., 2020). BLASTn was implemented to align assembled genomes to the database and only results with over ninety percent identity and over sixty percent target coverage were included in the database.

All WGS data for these samples have been deposited in the NCBI GenBank (https://www.ncbi.nlm.nih.gov). The annotation was added by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) version 6.6 with the best-placed reference protein set; GeneMarkS-2+. Default parameters were used for all software unless further stated. Additional annotation and analysis of the draft genome were performed using Rapid Annotation Subsystem Technology (RAST) server. (rast.nmpdr.org) (Aziz et al., 2008). In RAST genome analysis, ‘subsystems’ refer to collections of genes grouped based on their involvement in a specific biological process or cellular function. These subsystems are part of a curated database that helps predict gene functions more accurately by placing genes within a functional context rather than analysing them individually.

The MLST system from PubMLST was employed in the Galaxy platform, with MLST profiles assigned to each assembled strain. The UPGMA phylogenetic tree was constructed based on the concatenated 3401 base pairs of MLST loci from 18 B. pseudomallei strains, representing 9 STs. The phylogenetic tree was generated with 1000 bootstrap replications using MEGA X software.

Results

Out of the 20 samples processed for sequencing, two samples were excluded from bioinformatics analysis due to high percentage mapping to other bacterial species. This might happen due to contamination during extraction or library preparation. Hence, only 18 samples were included with subsequent analysis. Table 2 shows the statistics of pre-processed sequencing data for the 18 B. pseudomallei isolates.

Table 2.

Statistics of Pre-processed Sequencing Data for 18 B. pseudomallei isolates.

Sample name	Raw reads	Raw data(G)	Clean data (G)	Effective (%)	Error (%)	Q20 (%)	Q30 (%)	GC (%)
USM001	12334522	1.9	1.8	99.52	0.03	95.09	88.39	67.25
USM002	10635124	1.6	1.6	99.49	0.03	95.55	89.52	66.85
USM003	10649786	1.6	1.6	99.43	0.03	95.12	88.69	67.31
USM004	11098138	1.7	1.7	99.57	0.03	95.50	89.32	67.21
USM005	11499444	1.7	1.7	99.58	0.03	95.70	89.75	67.41
USM006	12584436	1.9	1.9	99.30	0.03	94.49	87.66	67.50
USM007	13740904	2.1	2.1	99.55	0.03	95.53	89.35	67.44
USM009	14041020	2.1	2.1	99.59	0.03	95.64	89.55	67.28
USM010	15360376	2.3	2.3	99.57	0.03	95.50	89.28	67.3
USM011	11494272	1.7	1.7	99.47	0.03	95.49	89.62	67.15
USM013	15587562	2.3	2.3	99.51	0.03	95.14	88.53	67.19
USM014	12686834	1.9	1.9	99.60	0.03	95.84	89.97	67.03
USM015	13445122	2.0	2.0	99.56	0.03	95.69	89.72	67.08
USM016	13321930	2.0	2.0	99.61	0.03	95.83	89.9	67.23
USM017	16390166	2.5	2.4	99.58	0.03	95.66	89.65	67.38
USM018	17670604	2.7	2.6	99.56	0.03	95.59	89.53	67.25
USM019	13426094	2.0	2.0	99.57	0.03	95.73	89.75	66.97
USM020	12964928	1.9	1.9	99.55	0.03	95.64	89.58	67.36

The 18 B. pseudomallei strains have an average length of 7,823, 977 bp, with an average GC content of 67.4%. The mean N₅₀ length is 47,798 bp and mean contigs numbers of 2882, comprising an average of 9,671 coding sequences (CDSs) and 64 RNAs. The assembly statistics and genomic characteristics for the 18 B. pseudomallei strains are tabulated as in Table 3. The genome assembly of all eighteen B.pseudomallei isolates have been deposited at GenBank with the accession numbers as listed in Table S.

Table 3.

Assembly statistics and genomic characteristics of 18 B. pseudomallei strains on RAST annotation.

Patients’ outcome	Recovered						Relapsed				Died						Environmental
Sample Name	USM 001	USM 002	USM 003	USM 004	USM 005	USM 006	USM 007	USM 009	USM 010	USM 011	USM 013	USM 014	USM 015	USM 016	USM 17	USM 018	USM 019	USM 020
Genome size	7,601,896	7,632,510	7,823,959	7,587,408	7,818,035	7,661,748	7,882,591	7,686,012	7,797,622	7,700,176	7,832,169	7,785,100	8,265,147	7,982,935	8,018,406	8,243,305	7,733,720	7,778,839
GC Content (%)	67.7	67.7	67.5	67.7	67.5	67.7	67.4	67.6	67.5	67.6	67.5	67.5	65.3	67.3	67.2	67.1	67.6	67.5
No. of Contigs	2307	2226	3030	2252	2832	2143	3098	2663	2887	2661	3054	2928	4423	3345	3621	3825	2204	2374
N50	42238	30284	38529	46350	64515	57258	47821	49818	44527	32660	49560	42086	37501	37522	777293	64723	47983	49702
L50	57	71	57	49	36	42	50	48	51	64	51	57	64	58	30	36	46	48
No. of Sub systems	380	382	388	387	387	381	383	389	384	386	387	386	386	393	384	397	382	386
No. of CDS	9085	9172	9855	9083	9727	9180	9892	9434	9681	9453	9787	9685	10010	10264	10405	10865	9177	9325
No. of RNAs	61	62	68	65	64	63	65	64	60	61	65	67	62	67	65	70	64	61

Genome annotation of the representative isolates of USM001, USM007, USM018 and USM020 which include strains from recovered, relapsed and succumbed patients, as well as an environmental isolate, was performed using the RAST server. The annotations revealed 9,085 CDSs with 380 subsystems for USM001, 9,892 CDSs with 383 number of subsystems for USM007, 9,685 CDSs with 386 number of subsystems for USM018 and 9,325 CDSs with 386 subsystems for USM020. Among the identified subsystems are the functional gene groups necessary for amino acids and derivative metabolism, membrane transport, regulation and cell signaling, DNA and nitrogen metabolism and other various metabolic proteins and transporters as well as hypothetical proteins with unknown functions (Fig. 2).

Fig. 2.

Subsystem distributions for the draft genome of the representative clinical and environmental isolates, B. pseudomallei USM001, USM007, USM014 and USM020, respectively. The subsystem distributions were generated using RAST server.

An interesting finding were denoted from the RAST genome annotation, where the genome size of B. pseudomallei isolated from the succumbed patients are larger, with an average size of 8,021,177 bp compared to those from other patient groups (Table 3). This group also contains higher number of CDSs with the average of 10,169 CDSs, as compared to the strains isolated from recovered and relapsed groups. However, as this current study has a limited sample size, further investigation in larger cohorts is needed to validate any potential relationship between genome size and clinical outcomes.

The average genome size for B. pseudomallei isolates from the recovered patients is 7,687,593 bp, remarkably the smallest among the four groups. Meanwhile, the number of CDSs for B. pseudomallei isolated from environmental samples were five times greater than the other strains. One possible reason could be the transition from the diverse soil environment to the more specific conditions within the human body, where certain genes may be lost or downregulated, leading to a reduction in the number of CDSs.

Virulence gene were also detected in the analysis. A total of 144 virulence genes were identified in the entire dataset. These virulence profiles were in accordance to the B. pseudomallei reference strain, K96243. Among the virulence genes detected in the samples are bimA, bipD, bopA, hcp, vgrG genes that responsible for the adhesion and invasion of the bacterium into the host cells as well as intracellular motility and actin polymerization (Sitthidet et al., 2011, Selvam et al., 2021, Gong et al., 2011, Lim et al., 2015).

One of the crucial virulence gene found in the strains is the Type VI Secretion System 5 (T6SS-5) gene clusters which is located on chromosome two of the B. pseudomallei genome (Shafiq et al., 2022). An illustration of the T6SS-5 gene cluster in B. psudomallei is shown in Fig. 3. Antimicrobial resistance (AMR) gene detection revealed one predicted resistance profile. The Carbapenem-hydrolysing class D beta-lactamase 59 (blaOXA-59) gene, conferring predicted resistance to ampicillin, beta-lactam antibiotics, was detected in all 18 genomes.

Fig. 3.

Illustration of the T6SS-5 gene cluster in B. pseudomallei.

The MLST system from PubMLST was employed in the Galaxy platform to assign MLST profiles to each assembled strain. Table 4 illustrates the MLST profiles of all 18 isolates, detailing the allele profiles for each locus alongside their respective sequence type (ST) numbers. The allele profiles indicate the distinct alleles identified at each MLST locus, while the ST numbers represent the unique ST assignments given to individual strains (USM001- USM020) based on their allele combinations. The STs found in this investigation, taken from 18 isolates, were consistent with those reported previously.

Table 4.

Allelic profiles and sequence type of 18 B. pseudomallei strains.

Strain	Allele profile							Sequence type (ST)
	ace	gltB	gmhD	lepA	lipA	narK	ndh
USM001	1	4	2	3	5	2	3	1321a
USM002	3	1	2	1	1	3	3	46 a
USM003	3	1	3	3	1	2	1	54 a
USM004	3	1	3	3	1	4	1	55 a
USM005	3	1	3	3	1	4	1	55 a
USM006	3	1	2	1	1	4	3	50 a
USM007	3	4	11	4	5	4	6	289 b
USM009	3	1	2	3	5	4	3	164 b
USM010	3	1	3	3	1	2	1	54 b
USM011	3	1	3	3	1	2	1	54 b
USM013	3	1	3	3	1	2	1	54 c
USM014	3	1	3	3	1	2	1	54 c
USM015	3	4	11	4	5	4	3	1471 c
USM016	3	1	2	1	1	4	3	50 c
USM017	3	1	2	3	5	4	3	164 c
USM018	3	1	2	1	1	3	3	46 c
USM019	3	1	11	4	5	4	6	84 d
USM020	3	1	11	4	5	4	6	84 d

^aRecovered patients

^bRelapsed patients

^cDeceased patients

^dEnvironmental isolates

Notably, ST54, which corresponds to USM003, USM010, USM011, USM013, and USM014, identified as the most common sequence type. ST84 has been associated to environmental samples (USM019-USM020). Furthermore, all 18 variant strains demonstrated similar resemblance to local Malaysian strains except for USM015 which was found to be related to a Thailand isolate. Other isolates were also found in various countries such as Singapore, Indonesia, Thailand and few other countries as shown in Table 5. Overall, the 18 strains investigated in this study displayed close genetic relationships with Southeast Asian strains.

Table 5.

List of the isolated countries for the sequence types obtained in this study.

Sample name	Sequence type (ST)	Country of Origin
USM001	1321	Malaysia
USM002	46	Malaysia, Thailand, Indonesia, Vietnam, Singapore, Australia, New Zealand, United State of America, China, Bangladesh
USM003	54	Malaysia, Thailand, Singapore, Indonesia, Laos, United Kingdom
USM004	55	Malaysia, China
USM005	55	Malaysia, China
USM006	50	Malaysia, Thailand, China, Singapore
USM007	289	Malaysia, Thailand, Singapore,
USM009	164	Malaysia, Thailand
USM010	54	Thailand, Malaysia, Singapore, Indonesia, Laos, United Kingdom
USM011	54	Thailand, Malaysia, Singapore, Indonesia, Laos, United Kingdom
USM013	54	Thailand, Malaysia, Singapore, Indonesia, Laos, United Kingdom
USM014	54	Thailand, Malaysia, Singapore, Indonesia, Laos, United Kingdom
USM015	1471	Thailand
USM016	50	Malaysia, Thailand, China, Singapore
USM017	164	Malaysia, Thailand
USM018	46	Malaysia, Thailand, Indonesia, Vietnam, Singapore, Australia, New Zealand, United State of America, China, Bangladesh
USM019	84	Malaysia, Thailand, Singapore, Australia
USM020	84	Malaysia, Thailand, Singapore, Australia

Phylogenetic analysis of the B. pseudomallei isolates was performed using MEGA X software to determine the genetic relationships among isolates, based on MLST profiles. Diverse clades indicate a high genetic diversity among the B. pseudomallei isolates. Most isolates were distributed across different clades and branches as shown in Fig. 4. Two strains, USM019 and USM020 had high similarity and were located in the same clade and branch. Both isolates were derived from environmental samples, specifically soil. These soil isolates possessed a unique MLST profile, which was assigned to ST784.

Fig. 4.

The UPGMA phylogenetic tree based on the concatenated 3401 base pairs of MLST loci from 18 B. pseudomallei strains, representing 9 different sequence types (STs).

Discussion

Despite advances in knowledge of melioidosis, an illness caused by B. pseudomallei, the disease still remains a global concern. Whole-genome sequences (WGS) of B. pseudomallei isolates from melioidosis patients and environmental samples could offer valuable insight for future molecular and genetic studies on the mechanisms of melioidosis infection, B. pseudomallei pathogenesis, antimicrobial resistance, as well as understanding the host–pathogen interactions.

The genome of B. pseudomallei is captivating due to its complexity and adaptability. It consists of two circular chromosomes, chromosome 1 and chromosome 2 which span approximately 4 Mb and 3 Mb, respectively. The genes in chromosome 1 involve in the primary cellular functions such as metabolism, replication, and repair, while chromosome 2 contains housekeeping genes which related to environmental adaptation, virulence, and antibiotic resistance. B. pseudomallei genome contains 5,500–7,000 CDS, reflecting its genetic richness and adaptability. Many of these genes are involved in metabolizing diverse compounds, facilitating its survival in various environments, including soil and water.

In this study. the elevated number of predicted coding CDS per genome (>9,000), significantly exceeding the average range reported for B. pseudomallei genomes based on high-quality, complete genome sequences like strain K96243, which comprises approximately 5,900 CDS as reported by Holden et al., 2004 (Holden et al., 2004). This higher CDS count might indicate fragmented assemblies, potentially caused by low-level contamination or the presence of highly repetitive genomic element in which both are known to hinder accurate assembly.

Capsular polysaccharide, biofilm formation, quorum sensing, flagella, fimbriae, lipopolysaccharide, exoproteins, and secretion system genes such as type II, type III, and type VI secretion systems are among the virulence factors implicated in the pathogenicity of B. pseudomallei (Galyov et al., 2010). Each of these factors plays a crucial role in various intracellular and extracellular interactions with the host as well as in the environmental survival of B. pseudomallei (Singh et al., 2013, Semail et al., 2023).

In this study, the predominant ST found was ST54 which has been previously reported in Malaysia and neighbouring countries. The identification of diverse genotypes with varying frequencies suggests historical introductions and the spread of different B. pseudomallei genotypes, possibly influenced by novel ST strains (Zueter, 2018). The phylogenetic tree revealed that eight strains of B. pseudomallei share distinct nodes and branches. This suggests that melioidosis in the area is caused by a wide genetic variety of B. pseudomallei. Notably, strains USM019 and USM020 exhibit significant similarity and are positioned within the same clade and branch. Originating from environmental sources, particularly soil samples, these isolates demonstrate a distinctive MLST allele profile identified as ST84. Apparently, B. pseudomallei demonstrates varied genotypic advantages according to their geographical location. However, even within the same area, novel genotypes and variants emerge, demonstrating significant genomic plasticity that contributes to genetic diversity (Shafiq et al., 2022).

The AMR gene anaysis of the 18 B. pseudomallei strains in this current study revealed the presence of beta-lactamase-encoding blaOXA-59 gene. This aligns with a study that reported the distribution of this gene and its significance correlation with the outcomes of melioidosis patients in Malaysia. All B. pseudomallei isolates were carbapenem-sensitive; nevertheless, the presence of beta-lactamase-encoding blaOXA genes suggests that treatment failure may have contributed to patient mortality. Further research on the effect of blaOXA genes in vivo is essential (Arushothy et al., 2022). An emergence of blaOXA-59, amrB, amrA, adeF and omp38 as drug resistance genes in melioidosis patients with bacteremic community-acquired pneumonia had been reported in Taiwan (Wu et al., 2023).

WGS is a valuable technique for studying the epidemiology and evolution of highly recombinogenic organisms like B. pseudomallei. Since melioidosis infections are primarily caused by environmental exposure rather than person-to-person transmission, WGS data can provide detailed phylogeographical information. Specifically, WGS addresses the limitations and overcomes the challenges of conventional lower-resolution genotyping methods such as MLST or PFGE (Chapple et al., 2016). It is also more effective and reliable in tracking the epidemiological links among B. pseudomallei strains particularly in cases of melioidosis (Shafiq et al., 2022).

In conclusion, this study reports the complete genome sequences of 18 Burkholderia pseudomallei isolates, which can serve as a valuable reference for researchers investigating the evolutionary dynamics of this pathogen. Although SNP heterogeneity analysis did not provide substantial evidence of contamination linked to the elevated number of CDS, this has been recognized as a potential limitation. Consequently, future studies utilizing this genomic data should interpret findings with caution, taking this factor into account. Additionally, the comprehensive genomic characterization offered here contributes fundamental insights into the virulence and microbial traits that underpin the pathogenicity of B. pseudomallei in Southeast Asia, with a particular focus on Malaysia.

Ethic statement

The current study was approved by the Institutional Review Board of the Human Research Ethics Committee, USM (Registration Number: USM/JEPeM/19090528).

Authors’ contributions

NS was a major contributor in writing the manuscript. YKMI contribute in MLST part. NZNMN, YKMI, AH, AI and ZZD reviewed and edited the manuscript. All authors read and approved the final draft of the manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data will be made available on request.