Skip to main content
NCBI home page
BMC Genomics logoLink to BMC Genomics
. 2026 Feb 26;27:334. doi: 10.1186/s12864-026-12635-9

Genomic and phenotypic characterization of Vibrio cholerae strain SU109: a genomic investigation of a shrimp-associated strain from Bangladesh

Kazi Chamonara 1, Md Habib Ullah Masum 2,✉, Mohammad Sharif Uddin 3, Afifa Siddiqua 4, Sumaia Sultana 3, Sajedul Islam 3
PMCID: PMC13040912  PMID: 41749098

Abstract

Background

Shrimp exports generate substantial employment opportunities and revenue in Bangladesh. Nevertheless, the occurrence of Vibrio-associated epidemics remains a significant public health concern, with broader socio-economic consequences. This study characterizes the genomic and pathogenic features of the V. cholerae strain associated with local seafood market in Bangladesh. We employed whole-genome sequencing (WGS) using Nanopore long-read sequencing technology to investigate the genetic diversity, antimicrobial resistance, and virulence determinants of V. cholerae isolated from giant freshwater shrimps in Noakhali, Bangladesh.

Results

The genome of V. cholerae strain SU109 was assembled with high completeness (97.63%) and contiguity (L50 = 1). Functional and pathway investigations revealed that the strain possesses a sophisticated network of genes and metabolic processes, demonstrating its survival capabilities across various conditions. The pathway analysis identified numerous biosynthetic gene clusters (ectoine, vibriobactin, terpene, isocyanide, and β-lactone) associated with the synthesis of secondary metabolites, suggesting environmental resilience, iron acquisition, stress adaptation, microbial competitiveness, and may contribute to the strain’s virulence and ecological fitness. Pangenome studies identified 2,120 core genes, highlighting substantial genetic diversity and adaptability. A phylogenetic study indicated a close evolutionary link between shrimp and clinical strains, suggesting potential genome conservation across environmental and clinical isolates.

Conclusion

These findings indicate that V. cholerae strain SU109 may serve as a reservoir of virulence- and resistance-associated traits in seafood, highlighting the need for continued surveillance, stringent hygiene practices, and careful interpretation of genomic predictions to evaluate public health risks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-026-12635-9.

Keywords: Macrobrachium rosenbergii, Antimicrobial resistance, Whole genome analysis, Pangenome, Nanopore sequencing, Environmental isolate

Introduction

Bangladesh is one of the world’s major fish producers, with an expected yield of over 5 million metric tons in 2023–24. The fisheries industry accounts for 2.53% of the national gross domestic product (GDP), 22.26% of agricultural GDP, and 0.90% of export earnings [1]. This country exported 25% of its fish and fishery products, including shrimp from aquaculture [2]. The giant freshwater shrimp, Macrobrachium rosenbergii, commonly known as the “Golda Chingri”, is a species of considerable economic and nutritional significance. In Bangladesh, especially in the southwestern region, the cultivation of M. rosenbergii substantially influences the national economy, generating approximately US $500 million annually and contributing 3.78% to the GDP [3]. Although shrimp exports generate substantial revenue and employment opportunities, Vibrio outbreaks pose significant socio-economic and health risks [4]. Among the bacterial pathogens found in shrimp, Vibrio species are most commonly associated with human infections [5]. Vibrio cholerae, the species responsible for cholera, can infect individuals through contact with fish, shellfish, or water [6]. More than 200 serogroups of V. cholerae have been found; however, only the pathogenic O1/O139 serogroups are linked to cholera. Nonetheless, V. cholerae from the non-O1/non-O139 serogroups may cause gastroenteritis and have been associated with infrequent foodborne outbreaks rather than extensive epidemics [7]. These species are commonly found in marine products and throughout post-harvest seafood handling, and can persist and multiply under favorable conditions [8]. These strains are often detected in market seafood, especially shrimp and shellfish, where poor cold storage, cross-contamination, and extended exposure to ambient temperatures promote their growth and lead to spoilage [8, 9]. In these environments, V. cholerae is both part of the natural microbiota and a potential contaminant that can compromise product quality and safety [8]. While non-O1/non-O139 strains are not linked to epidemic cholera, their presence in seafood markets is concerning. They can produce enzymes and by-products that accelerate spoilage, reduce shelf life, and sometimes carry virulence factors that may cause sporadic gastrointestinal illness if contaminated products are consumed [10, 11]. Thus, market-associated seafood serves as a critical interface at which bacterial proliferation directly impacts food safety and public health [12]. The genomic features that allow non-O1/non-O139 V. cholerae to survive, adapt, and possibly express spoilage or virulence traits in seafood matrices remain poorly characterized [13]. Although identifying these strains in shrimp from retail and wet markets is increasing, comprehensive genome-level studies remain limited.

This study will characterize the whole genome of shrimp-associated V. cholerae isolates from local fish markets in Noakhali, Bangladesh, to assess their genetic composition and identify factors linked to spoilage and pathogenicity. Pangenome analysis will further reveal virulence features and genomic diversity in both clinical and non-clinical isolates, providing insight into seafood safety risks from post-harvest contamination.

Methods

Sample collection, processing and antibiotic resistance profiling

Samples of shrimps (n = 241) (Macrobrachium rosenbergii, Penaeus monodon, and Litopenaeus vannamei) were aseptically obtained from Noakhali fish markets. The samples were preserved in sterile zipper containers and transported on ice at temperatures below 4 °C to the Department of Microbiology (Noakhali Science and Technology University) for immediate processing. The samples were homogenized and enriched in alkaline peptone water at 37 °C. Enriched cultures were subsequently inoculated onto thiosulfate–citrate–bile salts–sucrose (TCBS) agar plates and incubated for 18–24 h at 37 °C [14]. Vibrio isolates were initially identified based on morphological characteristics (dimensions, form, and pigmentation). Direct microscopy and biochemical methods were then used to confirm putative isolates. Species-level identification of the isolates was conducted using polymerase chain reaction (PCR) targeting the species-specific groEL gene. Amplification utilized the primer pair groVc1 (5′-GATCTTGACTGGCGGTGTTGTG-3′) and groVc2 (5′-GTCACCCACCAGAGAAGAGAGT-3′) under primer-specific PCR conditions [15]. Among the V. cholerae isolates, the experimental isolate was selected based on its antimicrobial resistance profile. Antibiotic resistance of the experimental isolate was assessed using standardized protocols from the Clinical and Laboratory Standards Institute (CLSI, M45) [16], European Committee on Antimicrobial Susceptibility Testing (EUCAST, v.16.0) [17], and Clinical and Laboratory Standards Institute (CLSI, M100) [18]. Fourteen antibiotics were tested to determine the isolate’s susceptibility profile (Supplementary Table S1).

Whole genome sequencing, base calling and quality control

Total DNA was extracted from the isolates using the QIAamp® DNA Mini Kit (QIAGEN, Germany) and quantified with a Qubit 4 fluorometer (Thermo Fisher Scientific, USA). For library preparation prior to DNA sequencing, a native barcoding kit (SQK.NBD.114.24) was employed. Sequencing was conducted on the Oxford Nanopore MinION™ Mk1C platform using the FLO-MIN114 (R10.4.1) flow cell. Data acquisition was performed with the MINKNOW application (1.11.5). To obtain pass reads (FASTQ format) with an average quality score above 9, MinION™ Mk1C sequencing data (FAST5 files) were basecalled using Guppy (v.6.3.2) in high accuracy mode. Trimming was performed using Porechop (v.0.2.4) to exclude the adapter and barcode sequences [19]. Leveraging Nanofilt, low-quality bases (q < 15) were successfully excluded [20].

Genome assembly, quantification and strain identification

De novo assembly was performed using Flye (v.2.9.4) [21], which assembles long sequencing reads from platforms such as PacBio and Oxford Nanopore by applying a repetition graph approach to address the higher error rates of long reads [21]. Genome polishing was performed in three rounds using Racon (v.1.5.0) to improve the assembled genome’s quality [22]. Species identity was confirmed by the Type (Strain) Genome Server (TYGS), an accessible web server for prokaryotic taxonomy based on genomic data. TYGS generates genome-scale phylogenetic trees and provides advanced estimates of species and subspecies boundaries using identified closest-type genome sequences [23]. Genome contamination and completeness were assessed with CheckM (v.1.2.4) [24] and Benchmarking Universal Single-Copy Orthologs (BUSCO, v.6.0.0) [25], respectively. Genome statistics were calculated using Quality Assessment Tool (QUAST, v.5.2.0) [26], and average nucleotide identity (ANI) was determined with FastANI [27].

Genome annotation and mapping

Genome annotation was conducted using Prokka (v. 1.14.6) [28], the Rapid Annotations using Subsystem Technology Toolkit (RASTtk) [29], and the Prokaryotic Genome Annotation Pipeline (PGAP, v.6.10) tools [30]. The annotated genome was mapped using the Proksee server [31].

Subsystem and metabolic pathway analysis

The subsystems and functional metabolic pathways of the strain were predicted using the Patric [32] and RAST [29]. Biosynthetic gene clusters are responsible for the production of secondary metabolites, with significant ecological and physiological roles [33]. The biosynthetic gene clusters in the assembled genome were analyzed using antiSMASH (v.8.0) [34].

Antimicrobial resistance gene, mobile genetic elements, and virulence gene analysis

Antimicrobial resistance genes were identified using the Comprehensive Antibiotic Resistance Database (CARD, v.6.03) tool [35]. Mobile genetic elements (MGEs) were subsequently analyzed using mobileOG-db (v.1.1.3) [36]. The Phage integration within the assembled genomes was evaluated using the PHAge Search Tool Enhanced Release (PHASTER) [37] and the PHAge Search Tool with Enhanced Sequence Translation (PHATEST) [38]. Finally, the virulence genes were predicted using Victors [39].

Pangenome analysis

A comprehensive pangenome analysis was performed to elucidate the genetic diversity of the target strain. Thirty-one complete genome sequences of V. cholerae, obtained from both human and non-human sources in multiple countries, were retrieved from the Bacterial and Viral Bioinformatics Resource Center (BV-BRC). High-quality, publicly available V. cholerae genomes were selected to ensure broad geographic representation, diverse clinical and environmental sources, multiple sampling periods, inclusion of O1/O139, and non-O1/non-O139 serogroups, and suitability for comparative genomic analyses. Explicit accession-based selection criteria were applied to ensure reproducibility and to capture the global genetic diversity of the species for pan-genome and evolutionary studies (Supplementary Data S1). Subsequently, these genomes were analyzed with Roary (v. 3.13.0) using stringent clustering criteria [40]. Roary was executed using BLASTP-based clustering at 95% protein identity, with core genes defined as those present in at least 99% of genomes.

Results

Multidrug resistance profile of V. cholerae strain SU109

Among the V. cholerae isolates (n = 34), SU109 was selected as the experimental isolate for further analysis due to its multidrug resistance. The isolate exhibited resistance to ceftazidime, nitrofurantoin, meropenem, ampicillin, and cefotaxime. Intermediate resistance to amikacin and imipenem was observed. However, the isolate remained susceptible to erythromycin, gentamicin, ciprofloxacin, nalidixic acid, chloramphenicol, azithromycin, and levofloxacin. Resistance to at least one agent in three or more antimicrobial categories led to its classification as a multidrug-resistant strain (Supplementary Table S1).

Genome quality and functional profile

The sequencing and analysis of the V. cholerae strain SU109 genome were conducted to assess its structural and functional characteristics (Fig. 1A). A total of 385,028 reads were obtained, yielding a sequencing depth of 109.1x. The total genome size was approximately 4.04 Mbp, consistent with reference genomes of V. cholerae (strain RFB16), and exhibited a GC content of 47.67%. The assembly exhibited a low contamination level of 0.46% and a completeness of 97.63%. BUSCO analysis indicated a high level of genome completeness, with 99.2% of the genome identified as complete. Of these, 98.4% were complete and single-copy, and 0.8% were complete and duplicated. Furthermore, 0.8% of the genome was classified as fragmented, with no missing values observed. The genome assembly produced two circular contigs, with a contig N50 of 2,870,474 bp. Furthermore, the ANI analysis revealed 98.24% similarity to the reference strain RFB16 (Fig. 1B, C; Table 1). The isolate SU109 was designated as “Vibrio cholerae strain SU109.” The complete genome sequence of the strain has been submitted to GenBank at NCBI, assigned the GenBank accession number, and assembly accession numbers, JBQWLZ000000000.1and GCF_052545415.1, respectively (Table 1).

Fig. 1.

Fig. 1

Open in a new tab

The genome profile of the V. cholerae strain SU109. A The genome plot of the strain SU109, (B) the ANI profile of the SU109 with the reference genome strain RFB16, and (C) the comparative genome plot of the strain SU109 and RFB16

Table 1.

The genomic features of the V. cholerae strain SU109

Features Vibrio cholerae strain SU109
No. of reads 385,028
Genome coverage (x) 109.1
Genome size (Mbp) 4.04
Completeness (%) 97.63
Contamination (%) 0.46
No. of contigs 2
Contig N50 (bp) 2,870,474
Contig L50 1
GC content (%) 47.67
ANI score (%) 98.24
Open in a new tab

The identified genes were categorized as coding sequences (CDS), ribosomal RNA (rRNA), and transfer RNA (tRNA). Prokka annotation identified 3,695 genes, while the RASTk server and the PGAP pipeline reported 3,878 and 3,743 genes, respectively. Prokka detected 3,558 CDSs, RASTk predicted 3,743 CDSs, and PGAP found 3,602 CDSs. All three tools detected 106 tRNA genes. Prokka and PGAP identified 31 rRNA genes, whereas RASTk detected 29 (Fig. 2). The Prokka-annotated genome was selected for all subsequent downstream analyses due to its compatibility with downstream tools.

Fig. 2.

Fig. 2

Open in a new tab

The genome features of the V. cholerae strain SU109. The features, including CDS, rRNA, tRNA, tmRNA, GC content are depicted in different color codes

Core identity and toxigenic markers of V. cholerae strain SU109

The V. cholerae strain SU109 was classified as a non-O1/non-O139 lineage through whole-genome comparative analysis. ANI analysis revealed genomic similarity (98.24%) to the non-O1/non-O139 reference strain RFB16, supporting this taxonomic assignment. Screening for toxigenic determinants confirmed the absence of the ctxAB operon, which encodes cholera toxin. Additionally, classical biotype–associated virulence markers, such as tcpA and other genes within the toxin-coregulated pilus (TCP) and Vibrio pathogenicity island (VPI), were not detected, indicating a non-toxigenic genomic profile.

Subsystem and metabolic profile

Superclass analysis of V. cholerae strain SU109 identified diverse functional gene categories, including those involved in protein folding, modification, and degradation. The metabolism category encompasses pathways for carbohydrates, amino acids, lipids, and nucleotides (Fig. 3A, Supplementary Data S2). The strain also contains genes related to stress response, defense, cell envelope structure, regulation, and cell signaling. Class-level functional classification indicates extensive metabolic and regulatory capabilities. Several ABC transporters (YeiABEF, YadGH, YxeMNO, and tungstate transporters) and tripartite multidrug efflux systems of the resistance-nodulation-division (RND) and major facilitator superfamily (MFS) types were also identified in the strain. The strain also had toxin–antitoxin (YoeB-YefM, HigAB) and the type VI secretion systems. The lipopolysaccharide transport (Lpt) and the translocation and assembly module (TAM) transport system were also predicted. Genes conferring copper and chromium tolerance were identified. Quorum-sensing, proteasome, and phage shock operons were also predicted in the strain (Fig. 3A, Supplementary Data S2).

Fig. 3.

Fig. 3

Open in a new tab

The subsystem analysis of the V. cholerae strain SU109. (A) The class, and (B) subsystem analysis of the strain SU109

Further, structural genome analysis of V. cholerae strain SU109 identified several conserved biosynthetic gene clusters involved in the synthesis of secondary metabolites, such as ectoine, NRP-metallophore, terpene precursors, isocyanides, and β-lactone biosynthetic pathways (Fig. 4).

Fig. 4.

Fig. 4

Open in a new tab

The major biosynthetic gene cluster within the genome of V. cholerae strain SU109

Antimicrobial resistance genes, and mobile genetic elements analysis

The antimicrobial resistance genes CRP, rsmA, varG, almF, almG, almE, parE, and QnrVC4 were detected in the V. cholerae strain SU109 (Fig. 5A, Supplementary Data S3). The CRP gene, part of the RND efflux system, was also detected. Additionally, the multidrug resistance gene rsmA was identified. The genomic map of V. cholerae strain SU109 reveals the spatial organization of key MGEs involved in replication, recombination, repair, motility, and defense. Several distinct functional clusters are present, including genes for replication and recombination (dnaA, gyrB, recG, polA, ftsZ, recJ, parE, uvrA, uvrB), as well as MGEs such as integrases (int), transposases, and phage-associated sequences (oppA, orf46, Fi_ORF45). The presence of toxin–antitoxin systems (relE), stress response chaperones (clpB, groL, dnaK), and restriction-modification genes (hsdR, hsdM) indicates active processes for maintaining genomic stability and defense. Additionally, the widespread distribution of integration, excision, and transfer-related genes throughout the genome suggests a robust capacity for horizontal gene transfer. The diversity of phage, stability, and repair-associated loci underscores the strain’s adaptability and genomic plasticity (Fig. 5B).

Fig. 5.

Fig. 5

Open in a new tab

The functional genomic features of the V. cholerae strain SU109. A The antimicrobial resistance genes predicted by CARD, (B) the mobile genetic elements (MGEs), and (C) the phage-related genes in the genome of SU109

Multiple phage-associated genes were detected in the genome of V. cholerae strain SU109, suggesting the existence of prophage remnants (Fig. 5C). One intact prophage region (Region 1) measuring 42.3 kb was detected, with a completeness score of 100. This region spans coordinates 851,291 to 893,591 and contains hallmark phage-associated genes, including integrase, terminase, portal, capsid, and tail proteins. However, no RNA genes were found. Of the 43 predicted proteins, 25 are phage-related, and 4 are hypothetical, totaling 67.4% of the region. The remaining 14 proteins are annotated as bacterial. Additionally, the presence of an attachment (att) site supports prophage integration into the host genome. Comparative analysis showed homology to 20 phage species, with PHAGE_Escher_ArgO145 (9 hit genes) most frequently matched, followed by PHAGE_Escher_Lys12581Vzw and PHAGE_Stx2_c_Stx2a_F451 (8 hit genes each). The most common phage accounted for 20.93% of total phage hits, and the region’s GC content was 45.26% (Supplementary Table S2).

Further analysis revealed several antibiotic resistance genes located near MGEs, including QnrVC4, vanT, CRP, rsmA, and parE. The vanT gene was associated with MGEs such as rep and dnaB, while the CRP regulatory gene was identified in close proximity to the MGEs dam_1 and rnr. The rsmA gene, which may contribute to reduced susceptibility to fluoroquinolones, diaminopyrimidines, and phenicols, was located near several MGEs, including mutS, recA, diaA, and sspA. The parE gene, which confers quinolone resistance, was found near other MGEs, such as cca., xerD, and recJ (Fig. 6).

Fig. 6.

Fig. 6

Open in a new tab

The co-existence of antimicrobial resistance genes and mobile genetic elements (MGEs) in the genome of V. cholerae SU109. A The circular map illustrates the co-existence of antimicrobial resistance genes and MGEs, and (B-F) the linear genome view illustrates the antibiotic resistance genes adjacent to the MGEs

Virulence associated gene analysis

More than 100 virulence-associated genes were identified in the genome of their V. cholerae strain SU109. The virulence-associated genes identified can be categorized into functional groups based on their biological roles. A substantial number of these genes play roles in regulation and signal transduction, including toxR, crp, rpoS, rpoE, ompR, arcA, relA, hfq, sspA, cyaA, and fur. The genome also contained genes implicated in toxin production and secretion, including rtxA, tolC, and tolB. The genome contained several genes involved in metabolic and energy-related pathways, including aceF, pykF, deoC, sucA, and pta. Genes associated with stress response, such as trxA, trxB, clpB, and gshB, were also identified. However, many virulence-associated genes remain classified as hypothetical or uncharacterized (e.g., VC0727, VC1639, VCA0583, VCA0910, VC2660, VCA0600) (Supplementary Data S4).

Comparative genome analysis and genome-wide pathogenicity profiling

A comprehensive pangenome and comparative genomics analysis was performed using 31 whole-genome sequences of V. cholerae isolates collected from diverse countries and origins, including those analyzed in this study (Supplementary Data S1). The phylogenetic analysis of the pangenome showed that V. cholerae strains from non-human sources exhibited significant genomic and evolutionary relationships with clinical isolates associated with human disease. The V. cholerae strain SU109, sourced from Bangladesh, exhibited a notable phylogenetic association with the clinical isolates (V. cholerae strain 22 VB00037-2 and 22 VB00037-1) from Germany. Additionally, the V. cholerae strain M18C4, originated from a migratory bird in China, along with the strain Vc306, a fish isolate, were categorized within the same clade, suggesting a notable level of phylogenomic relatedness (Fig. 7A). Pangenome analysis identified a core genome of 2,120 genes, including 420 soft core genes, 1,398 shell genes, and 4,925 cloud genes. This investigation identified a total pangenome of 8,863 genes (Fig. 7B, C).

Fig. 7.

Fig. 7

Open in a new tab

The pangenome and genome-wide analysis of the 31 V. cholerae strains. A The phylogenetic analysis of the Vibrio strains from different sources and origins, (B) the pangenome composition of the strains comprising the core, shell, cloud and soft genes, and (C) the heatmap depicts the conserved genes among the Vibrio isolates

Discussion

Shrimp farming and marketing contribute significantly to Bangladesh’s economy; however, post-harvest microbiological risk assessments remain limited by insufficient genome-scale data [4, 13]. The occurrence of non-O1/non-O139 V. cholerae in market-available shrimp underscores a persistent yet frequently overlooked food safety concern. These strains are often disregarded due to their lack of association with epidemic cholera [10, 11]. Nevertheless, their recurrent presence in retail seafood demonstrates their ability to persist and proliferate under suboptimal storage and handling conditions [12]. Integrating whole-genome and pangenome approaches, this work elucidates the genetic determinants underlying spoilage potential and pathogenic traits in shrimp-associated V. cholerae, with direct implications for post-harvest seafood safety assessment. The high-quality genome assembly of the V. cholerae strain SU109 provides a strong foundation for subsequent comparative and functional analyses. The achieved sequencing depth (109.1x) exceeds the minimum coverage required for accurate bacterial genome reconstruction, thereby increasing confidence in assembly continuity, gene prediction, and structural integrity [41]. The genome size (~ 4.04 Mbp) and GC content (47.67%), which are consistent with the reference strain RFB16, further support the taxonomic assignment of SU109 as V. cholerae and indicate the absence of major genomic aberrations or extensive horizontal gene acquisitions that would significantly increase genome length [42]. Quality metrics, such as low contamination (0.46%) and high completeness (97.63%), indicate the reliability of the assembled genome and reduce the risk of misleading annotations due to foreign DNA [24]. BUSCO results further support this conclusion, demonstrating 99.2% completeness and no missing orthologs, which suggests that the core genomic repertoire of V. cholerae is comprehensively represented in SU109 [25]. ANI analysis demonstrated a high degree of nucleotide-level similarity (98.24%) between SU109 and the reference strain RFB16, situating SU109 within the species boundary of V. cholerae [43]. However, the observed genomic divergence aligns with patterns seen in environmental or market-associated non-O1/non-O139 strains, which frequently display significant accessory genome variation despite conserved core genomes [44].

Subsystem analyses revealed the presence of genes associated with stress response, defense, and virulence, suggesting potential mechanisms that may support environmental persistence and adaptive capacity in V. cholerae strain SU109 [45]. Additionally, genes involved in cell envelope structure, regulatory processes, and cell signaling may contribute to maintaining cellular integrity and facilitating responsiveness to changing environmental conditions [46]. The strain contained a complex set of genes related to antimicrobial resistance, stress tolerance, and virulence. Several ABC transporters (YeiABEF, YadGH, YxeMNO), and tungstate transporters, along with tripartite multidrug efflux systems of the RND and MFS types, are likely to contribute to the strain’s resistance to diverse antimicrobials and hazardous substances [47, 48]. The presence of toxin–antitoxin systems (YoeB–YefM and HigAB), along with components of the type VI secretion system, suggests potential roles in stress tolerance and interbacterial interactions [49, 50]. Moreover, genes encoding the Lpt and the TAM systems were identified in V. cholerae strain SU109, which are likely involved in outer membrane maintenance and may contribute to the secretion or stability of virulence-associated proteins [51]. The strain had also genes conferring copper and chromium tolerance, which could support membrane integrity under adverse environmental conditions [52, 53]. Furthermore, the identification of quorum-sensing, proteasome, and phage shock operons suggests that the strain SU109 may possess regulatory and stress-response mechanisms that enhance environmental adaptability and cellular resilience [54]. Further metabolic pathway analyses of the V. cholerae strain SU109 identified several conserved biosynthetic gene clusters, notable for their resilience to environmental conditions, which are deemed to affect the virulence and ecological viability of the strain, either directly or indirectly [55]. The ectABC operon facilitates ectoine synthesis, which is essential for osmoregulation and the stabilization of cellular structures and proteins in hyperosmotic environments. The synthesis of ectoine is essential for the survival of Vibrio species under saline and osmotic stress, therefore facilitating persistence inside host tissues [56]. This adaptation may increase the virulence of V. cholerae strain SU109 by maintaining bacterial viability in adverse environments. In contrast, the NRPS-type biosynthetic loci of V. cholerae are primarily known for producing vibriobactin, a catecholate siderophore that enables iron acquisition under limited conditions. Vibriobactin acts as a chelator, binding environmental iron and enabling its uptake via specific transporters. Siderophore production likely increases the survival of V. cholerae strain SU109 under iron-limited conditions and promotes its colonization and competitive advantage over other bacteria [57]. In various microbial species, gene clusters associated with terpenes encode enzymes that produce terpene precursors. These precursors are subsequently transformed into a wide range of terpenoids by terpene cyclases. Microbial terpenoids serve multiple functions, including facilitating small-molecule signaling, regulating membrane integrity, protecting against oxidative stress, providing interspecific chemical defense, and modulating host responses. Therefore, this gene cluster may contribute to the increased virulence of the V. cholerae strain SU109 [58]. Natural compounds containing isocyanides are synthesized by isocyanide synthases (isnA/isnB-type genes) and demonstrate a wide range of bioactivities, such as bacterial digestion and metal chelation. In the V. cholerae strain SU109, these byproducts likely function as electrophilic molecules that bind metals or interact with proteins, thereby increasing the species’ competitiveness within its environment [59]. In addition, β-lactone biosynthetic gene clusters encode enzymes that produce β-lactones. This diverse class of bioactive compounds inhibits proteolytic enzymes and influences microbial interactions [60]. The presence of these clusters could potentially influence the modulation of host-pathogen interactions or interbacterial competition in the V. cholerae strain SU109.

In the genome of V. cholerae strain SU109, the presence of alm gene (alm E, alm F, and alm G) cluster is linked to the modification of lipid A, resulting in alterations to the lipopolysaccharide structure within the bacterial outer membrane. The changes could impact membrane stability, the ability to resist host-derived antimicrobial peptides, and the overall survival of bacteria in challenging environmental conditions [61]. The CRP gene is recognized as a part of RND efflux systems, which confer resistance to various types of antibiotics, such as macrolides, and tetracyclines [62]. However, phenotypic antimicrobial susceptibility testing revealed susceptibility to the two major macrolides evaluated, erythromycin and azithromycin (Supplementary Table S3). The discrepancy between the presence of CRP and phenotypic susceptibility to macrolides can be attributed to the regulatory function of CRP, which does not directly confer resistance [62]. Efflux pump activity is frequently condition-dependent and may not be induced under in vitro testing conditions; furthermore, these systems may exhibit limited activity against erythromycin and azithromycin [63]. Additionally, the lack of alternative macrolide resistance mechanisms may explain the observed susceptibility. The presence of vanT genes within the vanG cluster indicates potential resistance mechanisms involving alterations to cell wall targets, as well as a possible resistance pattern to vancomycin [64]. Additional multidrug resistance–associated genes were identified, including rsmA, which is implicated in the regulation of RND efflux pumps and has been associated with resistance to phenicols such as chloramphenicol (Supplementary Table S3) [65]. Despite this genetic association, phenotypic antimicrobial susceptibility testing demonstrated that the strain remained susceptible to chloramphenicol. The observed susceptibility to chloramphenicol, despite the presence of rsmA, likely results from its regulatory function rather than direct resistance activity. The expression of RND efflux systems is typically subject to stringent regulation and is dependent on specific environmental conditions, which may not be replicated during standard in vitro testing. Furthermore, the absence of additional resistance mechanisms or insufficient efflux efficiency against chloramphenicol may account for the lack of a resistant phenotype [66].

The QnrVC4 gene confers low-level resistance to fluoroquinolones, including ciprofloxacin, levofloxacin, and nalidixic acid, through the production of a pentapeptide repeat protein that protects DNA gyrase and topoisomerase IV [67]. However, phenotypic antimicrobial susceptibility testing revealed susceptibility to these major fluoroquinolones evaluated (Supplementary Table S3). The presence of QnrVC4 without corresponding phenotypic resistance may reflect its role in conferring only low-level protection, which often requires additional resistance mechanisms to produce a detectable phenotype [68]. Furthermore, condition-dependent gene expression and regulatory factors may limit its phenotypic impact under standard testing conditions [69]. The identification of varG in the strain’s genome, which encodes a subclass B1 beta-lactamase, suggests a potential mechanism of carbapenem resistance via antibiotic inactivation. Subclass B1 beta-lactamases are metallo-β-lactamases that hydrolyze a wide range of β-lactam antibiotics, including carbapenems such as meropenem [70]. Phenotypic testing demonstrated resistance to meropenem, consistent with the genomic prediction (Supplementary Table S3). These genomic and phenotypic findings highlight the potential for carbapenemase-mediated resistance in V. cholerae strain SU109, with significant implications for treatment strategies, especially in clinical and environmental settings where carbapenems serve as last-resort antibiotics. Overall, these findings demonstrate the strains’ ability to withstand antimicrobial treatments, emphasizing their clinical significance and the challenges in managing Vibrio infections [71].

The presence of replication and terminase genes suggests a capacity for phage DNA packaging and replication, while integrase genes indicate potential integration into the bacterial chromosome, thereby facilitating horizontal gene transfer [72]. Identification of fiber and attachment-related proteins highlights the importance of these phage components in host recognition and attachment, which may affect bacterial virulence and environmental adaptability [73]. Collectively, these phage-associated genes demonstrate the potential influence of bacteriophages on the genomic structure, diversity, and ecological adaptability of V. cholerae strain SU109 [74]. The absence of the ctxAB genes indicates that the genome likely lacks the classical CTXΦ prophage. However, the detection of prophage-related genes, including homologs of PHAGE_Escher_ArgO145, PHAGE_Escher_Lys12581Vzw, and PHAGE_Stx2_c_Stx2a_F451, may indicate shared phage modules, mosaic prophage architectures, or historical horizontal gene transfer [72]. These findings align with previous studies showing that V. cholerae often contains diverse non-CTX temperate phages, which increase genome plasticity, support environmental adaptation, and contribute to multifactorial virulence rather than classical cholera toxigenicity [74, 75]. Several antibiotic resistance genes were identified in proximity to MGEs, suggesting genomic regions that could support horizontal gene transfer and adaptive evolution. The vanT gene, linked to glycopeptide resistance, was associated with MGEs, indicating a possible mechanism for its genomic dissemination [76]. Similarly, the CRP regulatory gene was identified adjacent to MGEs (dam_1 and rnr), a genomic arrangement that may contribute to the spread or coordinated regulation of multiple antibiotic resistance determinants [76]. This association suggests that MGEs contribute to the dissemination of resistance across diverse antibiotic classes, including macrolides, fluoroquinolones, penams, and tetracyclines [77]. The rsmA gene was found near several MGEs, including mutS, recA, diaA, and sspA [76]. These findings suggest a genomic environment where recombination and horizontal gene transfer could contribute to bacterial adaptability under antimicrobial pressure [78]. The parE gene, which confers quinolone resistance, was directly associated with MGEs, including cca., xerD, and recJ. These spatial associations underscore the potential role of MGEs in enabling the acquisition, maintenance, and dissemination of antibiotic resistance determinants within the genome of V. cholerae strain SU109 [78].

The identified regulatory genes are involved in the regulation of virulence-associated proteins, stress response pathways, and quorum-sensing systems, which may support bacterial adaptation to changing environmental and host conditions [79–84]. Apart from these genes, the presence of rtxA suggests the potential for RTX toxin production, which may contribute to the virulence of V. cholerae strain SU109 [85]. Meanwhile, tolC and tolB were detected in the genome of V. cholerae strain SU109, indicating potential secretion system–associated functions related to the export of toxins and antimicrobial compounds [86]. However, the presence of a large number of hypothetical genes suggests the potential for uncharacterized functional components within the genome. Hypothetical proteins are identified from open reading frames (ORFs) whose translated products are undefined and lacking functional annotation [87]. Comprehensive analysis of these proteins in V. cholerae may reveal novel biological functions and facilitate the identification of novel diagnostic biomarkers or therapeutic targets for infection management. Future research should prioritize the functional characterization of these genes and their products through advanced computational approaches, including homology modeling, protein–protein interaction analysis, and machine learning-based prediction tools [88, 89]. The genes involved in critical metabolic and cellular pathways (aceF, pykF, deoC, sucA, and pta) facilitate the efficient use of available carbon sources and may serve as the growth-promoting factors of the strain under diverse nutritional conditions [90]. The strain has also a robust ability to withstand oxidative and environmental challenges present in the host. The genes trxA and trxB, which encode thioredoxin and thioredoxin reductase, are essential for maintaining intracellular redox balance and may enable the strain to counteract oxidative bursts generated by the host immune system [91]. The stress response gene (clpB), which encodes a molecular chaperone, facilitates protein refolding and inhibits protein aggregation after thermal or oxidative stress. Similarly, gshB, which is involved in glutathione production, boosts the cell’s antioxidant capacity by neutralizing Reactive Oxygen Species (ROS) and regulating cellular redox [92]. Collectively, the identification of these genes in V. cholerae strain SU109 points to genetic features that may support adaptation to oxidative and environmental stresses. The comparative pangenome analysis of 31 V. cholerae genomes revealed substantial genomic diversity and close evolutionary relationships between clinical and non-human isolates. Notably, several environmental and animal-derived strains clustered with human clinical isolates, suggesting genetic relatedness across different ecological niches. The strain SU109 grouped with clinical isolates from Germany, while the migratory bird–derived strain M18C4 clustered with the fish isolate Vc306, indicating potential shared lineages among aquatic and animal hosts. These findings suggest possible conservation of genomic features across geographically diverse strains, which may reflect shared evolutionary histories and the influence of horizontal gene transfer [93].

Conclusion

This research underscores the importance of baseline monitoring of V. cholerae strain SU109 in seafood-associated and food-handling environments for food safety and environmental surveillance. The presence of putative virulence-associated factors, antimicrobial resistance traits, and distinctive metabolic features may support the strain’s persistence in food matrices and along the sea food supply chain under environmental and antimicrobial selective pressures. The identification of biosynthetic gene clusters related to stress tolerance, metal acquisition, and competitive interactions further suggests an enhanced capacity for environmental survival. Comparative genomic and phylogenetic analyses reveal genetic diversity and relatedness to strains of clinical interest, suggesting a possible link between environmental and human-associated lineages rather than direct evidence of zoonotic transmission. Overall, these findings suggest that V. cholerae strain SU109 could serve as a potential reservoir of virulence- and resistance-associated traits in sea food-associated contexts, underscoring the importance of continued surveillance, improved hygiene practices, and cautious interpretation of genomic predictions when assessing public health risk.

Limitation

This study presents certain limitations that should be acknowledged. The analysis focused on a single Vibrio cholerae strain isolated from market-associated shrimp, which may restrict the generalizability of the results to other strains or geographic regions. While multiple antibiotic resistance and virulence genes were predicted from the genome, these results were not validated through phenotypic assays. Furthermore, the study is primarily descriptive; functional experiments are required to confirm the biological significance of the identified genomic features. Sampling from only one location may also fail to capture the broader geographic diversity of V. cholerae associated with shrimp.

Supplementary Information

12864_2026_12635_MOESM1_ESM.docx (17KB, docx)

Supplementary Material 1. Supplementary Table S1. Interpretative criteria used to determine antimicrobial susceptibility with the disk diffusion test in the V. cholerae strain SU109.

12864_2026_12635_MOESM2_ESM.docx (15.2KB, docx)

Supplementary Material 2. Supplementary Table S2. The characteristics of a predicted prophage region in the genome of V. cholerae strain SU109.

12864_2026_12635_MOESM3_ESM.docx (15.9KB, docx)

Supplementary Material 3. Supplementary Table S3. Phenotypic–genotypic reconciliation of the V. cholerae strain SU109.

12864_2026_12635_MOESM4_ESM.xlsx (15.7KB, xlsx)

Supplementary Material 4. Supplementary Data S1. Genome features of 31 V. cholerae genome selected for pangenome analysis

12864_2026_12635_MOESM5_ESM.xlsx (139.4KB, xlsx)

Supplementary Material 5. Supplementary Data S2. Subsystem analysis of the V. cholerae strain SU109.

12864_2026_12635_MOESM6_ESM.xlsx (21.9KB, xlsx)

Supplementary Material 6. Supplementary Data S3. Antimicrobial resistance gene profile of the V. cholerae strain SU109.

12864_2026_12635_MOESM7_ESM.xlsx (19.7KB, xlsx)

Supplementary Material 7. Supplementary Data S4. Virulence gene profile of the V. cholerae strain SU109.

Acknowledgements

We are thankful to the “Research cell”, Noakhali Science and Technology University for the immense support during the study.

Abbreviations

GDP

Gross domestic product

TCBS

Thiosulfate–citrate–bile salts–sucrose

PCR

Thiosulfate–citrate–bile salts–sucrose

CLSI

Clinical and Laboratory Standards Institute\

EUCAST

European Committee on Antimicrobial Susceptibility Testing

TYGS

Type (Strain) Genome Server

BUSCO

Benchmarking Universal Single-Copy Orthologs

QUAST

Genome statistics were calculated using Quality Assessment Tool

ANI

Average nucleotide identity

RASTtk

Rapid Annotations using Subsystem Technology Toolkit

PGAP

Prokaryotic Genome Annotation Pipeline

CARD

Comprehensive Antibiotic Resistance Database

MGEs

Mobile genetic elements

PHASTER

PHAge Search Tool Enhanced Release

PHATEST

PHAge Search Tool with Enhanced Sequence Translation

BV-BRC

Bacterial and Viral Bioinformatics Resource Center

CDS

Coding sequences

rRNA

Ribosomal RNA

tRNA

Transfer RNA

RND

Resistance-nodulation-division

MFS

Major facilitator superfamily

LPT

Lipopolysaccharide transport

TAM

Translocation and assembly module

Att.

Attachment

ORFs

Open reading frames

ROS

Reactive Oxygen Species

Authors’ contributions

**M.S.U., K.C.,** and **M.H.U.M.** Conceptualized and designed the study outline, performed all the analyses, prepared the figures, wrote and revised the manuscript; **A.S., S.S.,** and **S.I.** performed the analyses, wrote the manuscript; **M.S.U.** Supervised the study and revised the manuscript; All authors have agreed with the manuscript and provided their consent for publication.

Funding

This research is funded by the “Research cell, Noakhali Science and Technology University.

Data availability

All sequencing data generated in this study have been deposited in the NCBI BioProject database under accession number [PRJNA1294324](https:/www.ncbi.nlm.nih.gov/bioproject/PRJNA1294324) , and are publicly available through the Sequence Read Archive (SRA) ( [SRR34709124](https:/trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR34709124&display=metadata) ). The complete genome data have been submitted to NCBI GenBank with the accession [JBQWLZ000000000.1](https:/www.ncbi.nlm.nih.gov/nuccore/JBQWLZ000000000) , while the assembly data have been deposited with the genome accession, [GCF\_052545415.1](https:/www.ncbi.nlm.nih.gov/datasets/genome/GCA_052545415.1).

Declarations

Ethics approval and consent to participate

The Ethics Approval Committee of Noakhali Science and Technology University (NSTUEC). reviewed and authorized the study protocol (Approval no. NSTU/SCI/EC/2025/451).

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

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

References

  • 1.Fisheries Resources Survey System (FRSS). Department of fisheries, ministry of fisheries and Livestock. Yearbook of fisheries statistics of Bangladesh 2023–24. Dhaka: Department of Fisheries; 2024. p. 140. [Google Scholar]
  • 2.Hooper C, Debnath PP, Stentiford GD, Bateman KS, Salin KR, Bass D. Diseases of the giant river Prawn Macrobrachium rosenbergii: a review for a growing industry. Rev Aquac. 2023;15(2):738–58. 10.1111/raq.12754. [Google Scholar]
  • 3.Rahman M. Shrimp export marketing of Bangladesh. Bangladesh Res Publ J. 2013;8:146. [Google Scholar]
  • 4.Haque Z, Islam MS, Sabuj A, Pondit A, Sarkar A, Hossain MG, Saha S. Molecular detection and antibiotic resistance of Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio alginolyticus from shrimp (Penaeus monodon) and shrimp environments in Bangladesh. Aquac Res. 2023;2023:5436552. 10.1155/2023/5436552.
  • 5.Baker-Austin C, Oliver JD, Alam M, Ali A, Waldor MK, Qadri F, Martinez-Urtaza J. Vibrio spp. Infections. Nat Rev Dis Primers. 2018;4:8. 10.1038/s41572-018-0005-8. [DOI] [PubMed] [Google Scholar]
  • 6.Haque ZF, Islam MS, Sabuj AAM, Pondit A, Sarkar AK, Hossain MG, Saha S. Molecular detection and antibiotic resistance of vibrio cholerae, Vibrio parahaemolyticus and Vibrio alginolyticus from shrimp (Penaeus monodon) and shrimp environments in Bangladesh. Aquac Res. 2023;2023:5436552. 10.1155/2023/5436552. [Google Scholar]
  • 7.Faruque SM, Albert MJ, Mekalanos JJ. Epidemiology, genetics, and ecology of toxigenic Vibrio cholerae. Microbiol Mol Biol Rev. 1998;62(4):1301–14. 10.1128/MMBR.62.4.1301-1314.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Brauge T, Mougin J, Ells T, Midelet G. Sources and contamination routes of seafood with human pathogenic Vibrio spp.: a farm-to-fork approach. Compr Rev Food Sci Food Saf. 2024;23(1):13283. 10.1111/1541-4337.13283. [DOI] [PubMed] [Google Scholar]
  • 9.Chintagari S, Hazard N, Edwards G, Jadeja R, Janes M. Risks associated with fish and seafood. Microbiol Spectr. 2017;5(1). 10.1128/microbiolspec.PFS-0013-2016. [DOI] [PMC free article] [PubMed]
  • 10.Fernández-Delgado M, García-Amado MA, Contreras M, Edgcomb V, Vitelli J, Gueneau P, Suárez P. Vibrio cholerae non-O1, non-O139 associated with seawater and plankton from coastal marine areas of the Caribbean sea. Int J Environ Health Res. 2009;19(4):279–89. 10.1080/09603120802460368. [DOI] [PubMed] [Google Scholar]
  • 11.Zhang Q, Alter T, Strauch E, Hammerl JA, Schwartz K, Borowiak M, Deneke C, Fleischmann S. Genetic and phenotypic virulence potential of non-O1/non-O139 Vibrio cholerae isolated from German retail seafood. Microorganisms. 2023;11(11):2751. 10.3390/microorganisms11112751. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Koutsoumanis K, Allende A, Alvarez-Ordóñez A, et al. Public health aspects of Vibrio spp. Related to the consumption of seafood in the EU. EFSA J. 2024;22(7):8896. 10.2903/j.efsa.2024.8896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Qin X, Yang L, Xu Y, Xie L, Wang Y, Chen L. Growth and genome features of non-O1/O139 Vibrio cholerae isolated from three species of common freshwater fish. Diversity. 2024;16(5):268. 10.3390/d16050268. [Google Scholar]
  • 14.World Health Organization. Selection and application of methods for the detection and enumeration of human-pathogenic halophilic vibrio spp. In seafood. Geneva: WHO; 2016. [Google Scholar]
  • 15.Hossain MT, Kim EY, Kim YR, Kim DG, Kong IS. Development of a GroEL gene–based species-specific multiplex PCR assay for simultaneous detection of Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus. J Appl Microbiol. 2013;114(2):448–56. 10.1111/jam.12056. [DOI] [PubMed] [Google Scholar]
  • 16.Clinical and Laboratory Standards Institute. Methods for antimicrobial Dilution and disk susceptibility testing of infrequently isolated or fastidious bacteria. CLSI; 2016. [DOI] [PubMed]
  • 17.EUCAST. Clinical breakpoints and dosing of antibiotics, version 16.0. 2026.
  • 18.Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing. CLSI; 2024.
  • 19.Wick RR, Volkening JD et al. Porechop: adapter trimmer for Oxford Nanopore reads. 2018.
  • 20.De Coster W, D’Hert S, Schultz DT, Cruts M, Van Broeckhoven C. Bioinformatics. 2018;34(15):2666–9. 10.1093/bioinformatics/bty149. NanoPack: visualizing and processing long-read sequencing data. [DOI] [PMC free article] [PubMed]
  • 21.Kolmogorov M, Yuan J, Lin Y, Pevzner PA. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol. 2019;37(5):540–6. 10.1038/s41587-019-0072-8. [DOI] [PubMed] [Google Scholar]
  • 22.Vaser R, Sović I, Nagarajan N, Šikić M. Fast and accurate de Novo genome assembly from long uncorrected reads. Genome Res. 2017;27(5):737–46. 10.1101/gr.214270.116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Meier-Kolthoff JP, Göker M. TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat Commun. 2019;10(1):2182. 10.1038/s41467-019-10210-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25(7):1043–55. 10.1101/gr.186072.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Manni M, Berkeley MR, Seppey M, Zdobnov EM. BUSCO: assessing genomic data quality and beyond. Curr Protoc. 2021;1(12):323. 10.1002/cpz1.323. [DOI] [PubMed] [Google Scholar]
  • 26.Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29(8):1072–5. 10.1093/bioinformatics/btt086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High-throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9(1):5114. 10.1038/s41467-018-07641-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9. 10.1093/bioinformatics/btu153. [DOI] [PubMed] [Google Scholar]
  • 29.Aziz RK, Bartels D, Best AA, et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75. 10.1186/1471-2164-9-75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Tatusova T, DiCuccio M, Badretdin A, et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. 2016;44(14):6614–24. 10.1093/nar/gkw569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Grant JR, Enns E, Marinier E, et al. Proksee: in-depth characterization and visualization of bacterial genomes. Nucleic Acids Res. 2023;51(W1):W484–92. 10.1093/nar/gkad326. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Gillespie JJ, Wattam AR, Cammer SA, et al. PATRIC: the comprehensive bacterial bioinformatics resource with a focus on human pathogenic species. Infect Immun. 2011;79(11):4286–98. 10.1128/IAI.00207-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Cimermancic P, Medema MH, Claesen J, et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014;158(2):412–21. 10.1016/j.cell.2014.06.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Blin K, Shaw S, Augustijn HE, et al. AntiSMASH 7.0: improved predictions for detection, regulation, chemical structures and visualisation. Nucleic Acids Res. 2023;51(W1):W46–50. 10.1093/nar/gkad344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.McArthur AG, Waglechner N, Nizam F, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother. 2013;57(7):3348–57. 10.1128/AAC.00419-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Brown CL, Mullet J, Hindi F, et al. mobileOG-db: a manually curated database of protein families mediating the life cycle of bacterial mobile genetic elements. Appl Environ Microbiol. 2022;88(18):00991–22. 10.1128/aem.00991-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Arndt D, Grant JR, Marcu A, et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016;44(W1):W16–21. 10.1093/nar/gkw387. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Wishart DS, Han S, Saha S, et al. PHASTEST: faster than PHASTER, better than PHAST. Nucleic Acids Res. 2023;51(W1):W443–50. 10.1093/nar/gkad382. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Sayers S, Li L, Ong E, et al. Victors: a web-based knowledge base of virulence factors in human and animal pathogens. Nucleic Acids Res. 2019;47(D1):D693–700. 10.1093/nar/gky999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Page AJ, Cummins CA, Hunt M, et al. Roary: rapid large-scale prokaryote Pan genome analysis. Bioinformatics. 2015;31(22):3691–3. 10.1093/bioinformatics/btv421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Rojas-Miranda H, Madrigal-Ly V, Molina-Mora JA. Benchmarking genome assemblers for four bacterial models. Sci Rep. 2025;15(1):42858. 10.1038/s41598-025-26847-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Mishra S, Lercher MJ. Horizontal gene transfer inference: gene presence–absence outperforms gene trees. Mol Biol Evol. 2025;42(7):msaf166. 10.1093/molbev/msaf166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Arahal DR. Whole-genome analyses: average nucleotide identity. Methods Microbiol. 2014;41:103–22. 10.1016/bs.mim.2014.07.002. [Google Scholar]
  • 44.Kang DY, Islam MT, Bouba RW, et al. Environmental non-O1/O139 Vibrio cholerae from Northern Cameroon. PLoS Negl Trop Dis. 2025;19(4):0012890. 10.1371/journal.pntd.0012890. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Fuentes DE, Acuña LG, Calderón IL. Stress response and virulence factors in bacterial pathogens relevant for Chilean aquaculture. Biol Res. 2022;55(1):21. 10.1186/s40659-022-00391-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Silhavy TJ, Kahne D, Walker S. The bacterial cell envelope. Cold Spring Harb Perspect Biol. 2010;2(5):000414. 10.1101/cshperspect.a000414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Lubelski J, Konings WN, Driessen AJ. Distribution and physiology of ABC-type transporters contributing to multidrug resistance. Microbiol Mol Biol Rev. 2007;71(3):463–76. 10.1128/MMBR.00001-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Nikaido H, Takatsuka Y. Mechanisms of RND multidrug efflux pumps. Biochim Biophys Acta. 2009;1794(5):769–81. 10.1016/j.bbapap.2008.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Song X, Lin Z, Yuan W. Toxin–antitoxin systems in pathogenic Vibrio species. 3 Biotech. 2022;12(6):125. 10.1007/s13205-022-03178-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Yin R, Cheng J, Lin J. Role of the type VI secretion system in stress resistance. Stress Biol. 2024;4(1):16. 10.1007/s44154-024-00151-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Zhang X, Tian X, Wang Y, et al. Application of lipopolysaccharide in Establishing inflammatory models. Int J Biol Macromol. 2024;279:135371. 10.1016/j.ijbiomac.2024.135371. [DOI] [PubMed] [Google Scholar]
  • 52.Hao X, Zhu J, Rensing C, et al. Recent advances in exploring the heavy metal(loid) resistant Microbiome. Comput Struct Biotechnol J. 2021;19:94–109. 10.1016/j.csbj.2020.12.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Oleńska E, Małek W, Swiecicka I, et al. Bacteria under metal stress. Int J Mol Sci. 2025;26(12):5716. 10.3390/ijms26125716. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Tan D, Svenningsen SL, Middelboe M. Quorum sensing determines antiphage defense strategies. mBio. 2015;6(3):00627–15. 10.1128/mBio.00627-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Johnston I, Osborn LJ, Markley RL, et al. Essential genes for Aryl polyene biosynthesis in Escherichia coli. NPJ Biofilms Microbiomes. 2021;7(1):56. 10.1038/s41522-021-00226-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Ongagna-Yhombi SY, Boyd EF. Ectoine biosynthesis is critical for osmotic stress survival. Appl Environ Microbiol. 2013;79(16):5038–49. 10.1128/AEM.01008-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Butterton JR, Choi MH, Watnick PI, et al. Vibrio cholerae VibF is required for vibriobactin synthesis. J Bacteriol. 2000;182(6):1731–8. 10.1128/JB.182.6.1731-1738.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Kakumu Y, Chaudhri AA, Helfrich EJN. Tailoring enzymes in bacterial terpenoid biosynthesis. Nat Prod Rep. 2025;42(3):501–39. 10.1039/d4np00048j. [DOI] [PubMed] [Google Scholar]
  • 59.Scheuer PJ. Isocyanides and cyanides as natural products. Acc Chem Res. 1992;25(10):433–9. 10.1021/ar00022a001. [Google Scholar]
  • 60.Böttcher T, Sieber SA. β-Lactones as inhibitors of ClpP attenuate virulence factor production. J Am Chem Soc. 2008;130(44):14400–1. 10.1021/ja8051365. [DOI] [PubMed] [Google Scholar]
  • 61.Needham BD, Trent MS. Lipid A remodeling and bacterial pathogenesis. Nat Rev Microbiol. 2013;11(7):467–81. 10.1038/nrmicro3047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Nishino K, Senda Y, Yamaguchi A. CRP regulator modulates multidrug resistance in E. coli. J Antibiot. 2008;61(3):120–7. 10.1038/ja.2008.120. [DOI] [PubMed] [Google Scholar]
  • 63.Blanco P, Hernando-Amado S, Reales-Calderon JA, et al. Bacterial multidrug efflux pumps. Microorganisms. 2016;4(1):14. 10.3390/microorganisms4010014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Stogios PJ, Savchenko A. Molecular mechanisms of Vancomycin resistance. Protein Sci. 2020;29(3):654–69. 10.1002/pro.3819. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Mulcahy H, O’Callaghan J, O’Grady EP, et al. RsmA regulates type III secretion in Pseudomonas aeruginosa. Infect Immun. 2006;74(5):3012–5. 10.1128/IAI.74.5.3012-3015.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Webber MA, Piddock LJV. Importance of efflux pumps in antibiotic resistance. J Antimicrob Chemother. 2003;51(1):9–11. 10.1093/jac/dkg050. [DOI] [PubMed] [Google Scholar]
  • 67.Hooper DC, Jacoby GA. Fluoroquinolone mechanisms of action and resistance. Cold Spring Harb Perspect Med. 2016;6(9):025320. 10.1101/cshperspect.a025320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Juraschek K, Deneke C, Schmoger S, et al. Properties of fluoroquinolone-resistant E. coli from the German food chain. Microorganisms. 2021;9(6):1308. 10.3390/microorganisms9061308. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Ooi WF, Ong C, Nandi T, et al. Condition-dependent transcriptional landscape of Burkholderia Pseudomallei. PLoS Genet. 2013;9(9):1003795. 10.1371/journal.pgen.1003795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Lin HV, Massam-Wu T, Lin CP, et al. Vibrio cholerae var Regulon encodes a metallo-β-lactamase and efflux pump. PLoS ONE. 2017;12(9):0184255. 10.1371/journal.pone.0184255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Poole K. Efflux-mediated resistance to fluoroquinolones. Antimicrob Agents Chemother. 2000;44(9):2233–41. 10.1128/AAC.44.9.2233-2241.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Alqurainy N, Miguel-Romero L, Moura de Sousa J, et al. Phage-inducible chromosomal Islands steal bacteriophage Tails. Cell Host Microbe. 2023;31(1):69–825. 10.1016/j.chom.2022.12.001. [DOI] [PubMed] [Google Scholar]
  • 73.Ouyang R, Ongenae V, Muok A, et al. Phage fibers and spikes. Curr Opin Microbiol. 2024;77:102429. 10.1016/j.mib.2024.102429. [DOI] [PubMed] [Google Scholar]
  • 74.Ndiaye M, Bonilla-Rosso G, Mazel F, Engel P. Phage diversity mirrors bacterial strain diversity. Nat Commun. 2025;16(1):9738. 10.1038/s41467-025-64706-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Gherlan GS, Lazar DS, Florescu SA, et al. Non-toxigenic Vibrio cholerae. Arch Clin Cases. 2025;12(1):5–16. 10.22551/2025.46.1201.10305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76.Partridge SR, Kwong SM, Firth N, Jensen SO. Mobile genetic elements associated with antimicrobial resistance. Clin Microbiol Rev. 2018;31(4):00088–17. 10.1128/CMR.00088-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77.van Hoek AHAM, Mevius D, Guerra B, et al. Acquired antibiotic resistance genes. Front Microbiol. 2011;2:203. 10.3389/fmicb.2011.00203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Tokuda M, Shintani M. Microbial evolution through horizontal gene transfer. Microb Biotechnol. 2024;17(1):14408. 10.1111/1751-7915.14408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Canals A, Pieretti S, Muriel-Masanes M, et al. ToxR activates Vibrio cholerae virulence genes. Proc Natl Acad Sci USA. 2023;120(29):2304378120. 10.1073/pnas.2304378120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Mey AR, Wyckoff EE, Kanukurthy V, et al. Iron and fur regulation in Vibrio cholerae. Infect Immun. 2005;73(12):8167–78. 10.1128/IAI.73.12.8167-8178.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Vincent HA, Henderson CA, Ragan TJ, et al. Characterization of Vibrio cholerae Hfq. J Mol Biol. 2012;420(1–2):56–69. 10.1016/j.jmb.2012.03.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82.Nielsen AT, Dolganov NA, Otto G, et al. RpoS controls the Vibrio cholerae mucosal escape response. PLoS Pathog. 2006;2(10):109. 10.1371/journal.ppat.0020109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Haralalka S, Nandi S, Bhadra RK. Mutation in rela affects virulence factor expression. J Bacteriol. 2003;185(16):4672–82. 10.1128/JB.185.16.4672-4682.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Kunkle DE, Bina XR, Bina JE. Vibrio cholerae OmpR contributes to virulence repression. Infect Immun. 2020;88(6):00141–20. 10.1128/IAI.00141-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85.Cordero CL, Kudryashov DS, Reisler E, Satchell KJF. Actin cross-linking by Vibrio cholerae RTX toxin. J Biol Chem. 2006;281(43):32366–74. 10.1074/jbc.M605275200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Weng Y, Fields EG, Bina TF, et al. Vibrio cholerae TolC is required for ToxR Regulon expression. Infect Immun. 2021;89(10):e00242–21. 10.1128/IAI.00242-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87.Talukder A, Rahman MM, Masum MHU. Biocomputational characterization of MBO_200107 protein. J Biomol Struct Dyn. 2023;41(15):7204–23. 10.1080/07391102.2022.2118167. [DOI] [PubMed] [Google Scholar]
  • 88.Masum MHU, Ferdous J. Subtractive proteomics identifies a cell wall protein target in Candidozyma auris. Silico Res Biomed. 2025;1:100034. 10.1016/j.insi.2025.100034. [Google Scholar]
  • 89.Masum MHU, Rajia S, Bristi UP, et al. In Silico functional characterization of a hypothetical protein. Bioinform Biol Insights. 2023. 10.1177/11779322231184024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90.Castaño-Cerezo S, Pastor JM, Renilla S, et al. Role of phosphotransacetylase in Escherichia coli. Microb Cell Fact. 2009;8:54. 10.1186/1475-2859-8-54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91.Uziel O, Borovok I, Schreiber R, et al. Regulation of thioredoxin genes in Staphylococcus aureus. J Bacteriol. 2004;186(2):326–34. 10.1128/JB.186.2.326-334.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.Maciel-Guerra A, Babaarslan K, Baker M, et al. Core and accessory genomic traits of Vibrio cholerae O1. Nat Commun. 2024;15(1):8231. 10.1038/s41467-024-52238-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Wiedenbeck J, Cohan FM. Origins of bacterial diversity through horizontal genetic transfer. FEMS Microbiol Rev. 2011;35(5):957–76. 10.1111/j.1574-6976.2011.00292.x. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

12864_2026_12635_MOESM1_ESM.docx (17KB, docx)

Supplementary Material 1. Supplementary Table S1. Interpretative criteria used to determine antimicrobial susceptibility with the disk diffusion test in the V. cholerae strain SU109.

12864_2026_12635_MOESM2_ESM.docx (15.2KB, docx)

Supplementary Material 2. Supplementary Table S2. The characteristics of a predicted prophage region in the genome of V. cholerae strain SU109.

12864_2026_12635_MOESM3_ESM.docx (15.9KB, docx)

Supplementary Material 3. Supplementary Table S3. Phenotypic–genotypic reconciliation of the V. cholerae strain SU109.

12864_2026_12635_MOESM4_ESM.xlsx (15.7KB, xlsx)

Supplementary Material 4. Supplementary Data S1. Genome features of 31 V. cholerae genome selected for pangenome analysis

12864_2026_12635_MOESM5_ESM.xlsx (139.4KB, xlsx)

Supplementary Material 5. Supplementary Data S2. Subsystem analysis of the V. cholerae strain SU109.

12864_2026_12635_MOESM6_ESM.xlsx (21.9KB, xlsx)

Supplementary Material 6. Supplementary Data S3. Antimicrobial resistance gene profile of the V. cholerae strain SU109.

12864_2026_12635_MOESM7_ESM.xlsx (19.7KB, xlsx)

Supplementary Material 7. Supplementary Data S4. Virulence gene profile of the V. cholerae strain SU109.

Data Availability Statement

All sequencing data generated in this study have been deposited in the NCBI BioProject database under accession number [PRJNA1294324](https:/www.ncbi.nlm.nih.gov/bioproject/PRJNA1294324) , and are publicly available through the Sequence Read Archive (SRA) ( [SRR34709124](https:/trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR34709124&display=metadata) ). The complete genome data have been submitted to NCBI GenBank with the accession [JBQWLZ000000000.1](https:/www.ncbi.nlm.nih.gov/nuccore/JBQWLZ000000000) , while the assembly data have been deposited with the genome accession, [GCF\_052545415.1](https:/www.ncbi.nlm.nih.gov/datasets/genome/GCA_052545415.1).

Articles from BMC Genomics are provided here courtesy of BMC

RESOURCES