https://orcid.org/0009-0005-3055-3321
Figures
Abstract
Pseudomonas aeruginosa is an opportunistic pathogen in which motility, biofilm formation, and stress adaptation contribute to virulence. Drug repurposing represents a practical strategy for identifying compounds that influence these processes. In this study, the effects of 5-fluorouracil (5-FU) on motility, extracellular DNA (eDNA) production, and gene expression were examined in P. aeruginosa PAO1. Swimming, swarming, and twitching motility assays were performed in the presence of increasing concentrations of 5-FU. Transcriptional responses of motility, rhamnolipid, and DNA repair-associated genes were evaluated using quantitative real-time PCR. eDNA levels were quantified using fluorescence-based assays and visualized by confocal laser scanning microscopy. Exposure to 5-FU resulted in concentration-dependent reductions in swimming, swarming, and twitching motility. These changes were associated with downregulation of multiple genes involved in flagellar and type IV pili function, including motA, flhA, fliD, pilA, and pilI, and reduced expression of lasB and rhlAB. At 24 h, eDNA levels were decreased relative to untreated controls, whereas at 48 h, higher concentrations of 5-FU were associated with increased eDNA accumulation and upregulation of several DNA repair genes, including xthA, nth, recJ, sbcB, and eddB. These results indicate the multifaceted effects of 5-FU on important virulence factors of P. aeruginosa.
Citation: Niazy AA, Alrashed MM, Lambarte RNA, Sumague TS, Niazy AA (2026) 5-Fluorouracil modulates motility and biofilm-associated gene expression in Pseudomonas aeruginosa. PLoS One 21(7): e0354473. https://doi.org/10.1371/journal.pone.0354473
Editor: Mohammad Faezi Ghasemi, Islamic Azad University, IRAN, ISLAMIC REPUBLIC OF
Received: January 30, 2026; Accepted: July 8, 2026; Published: July 23, 2026
Copyright: © 2026 Niazy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Healthcare-associated infections are a growing global challenge that strain healthcare systems and worsen patient outcomes. Among opportunistic pathogens, Pseudomonas aeruginosa is notable for its environmental adaptability, metabolic versatility, and ability to persist in hospital reservoirs while causing disease in both immunocompromised and immunocompetent hosts [1,2]. Its success as a pathogen is largely attributed to a broad spectrum of virulence factors that facilitate adhesion, colonization, immune evasion, biofilm formation and tissue damage [3]. This threat is further exacerbated by the intrinsic resistance of P. aeruginosa to multiple antibiotics and its extraordinary ability to acquire additional resistance mechanisms, which limit treatment options [4,5]. Consequently, both the World Health Organization and the Centers for Disease Control and Prevention have listed P. aeruginosa as a priority pathogen requiring urgent development of new therapeutic strategies [6,7].
Motility plays a critical role during the early stages of P. aeruginosa infection by facilitating surface exploration and initial attachment, which precede stable adhesion and subsequent biofilm development on host tissues and implanted medical devices [8,9]. Accordingly, impairing motility has emerged as an attractive antivirulence strategy aimed at disrupting bacterial coordination rather than bacterial viability [8,10,11]. In parallel, extracellular DNA (eDNA) is a critical structural component of P. aeruginosa biofilms, contributing to matrix cohesion, mechanical stability, and persistence, while also reflecting physiological stress and adaptive responses during biofilm maturation [12,13]. Current evidence indicates that eDNA originates from multiple sources including the membrane vesicles released by viable cells and autolysis of a subpopulation that contributes matrix material to support community integrity [14]. Because motility, rhamnolipid production, and eDNA release contribute to early biofilm development and are regulated by shared stress and virulence pathways, disruption of these processes represents a rational antivirulence-oriented strategy for impairing the ability of the organism to cause infection without exerting strong bactericidal pressure [3,15].
As antimicrobial resistance intensifies, drug repurposing has emerged as an efficient strategy for identifying new antibacterial agents by leveraging existing pharmacological and safety data to reduce development time, cost, and risk [16–19]. Among anticancer compounds, 5-fluorouracil (5-FU) has drawn attention for its antibacterial and antivirulence activity [20,21]. Related fluoropyrimidine and small-molecule studies have also reported inhibition of virulence-associated functions in P. aeruginosa [22–25]. Furthermore, synergistic effects between 5-FU and conventional antibiotics such as gentamicin have been reported suggesting its potential as an adjuvant therapy [26,27]. However, the precise molecular mechanisms underlying its antibiofilm and antivirulence effects remain poorly understood.
This study aimed to elucidate the effects of 5-FU on biofilm-associated phenotypic and transcriptional traits in P. aeruginosa PAO1. Specifically, we investigated its impact on bacterial motility using phenotypic and gene expression analyses. We then evaluated its influence on rhamnolipid gene expression and eDNA production, and explored the transcriptional response of DNA repair genes. Additionally, molecular docking was performed to provide complementary and structure-informed hypotheses regarding potential drug-protein interactions that may underlie observed transcriptional and phenotypic changes. By integrating these findings, we sought to provide a comprehensive understanding of how 5-FU affects P. aeruginosa virulence-related pathways, thus contributing to the broader goal of identifying novel therapeutic strategies against resilient P. aeruginosa infections.
Materials and methods
Bacterial strain, drug, and growth media
All experiments were performed using Pseudomonas aeruginosa PAO1 kindly provided by Dr. Lee Hughes (University of North Texas, Denton, USA). The strain was maintained at −80 °C in tryptic soy broth containing 10% glycerol. For culture revival, the stock was streaked onto tryptic soy agar (TSA) and incubated aerobically at 37 °C for 18–20 h. A single, well-isolated colony was then transferred into 10 mL of Pseudomonas minimal medium (PsMM) following the previously described method [28]. The bacterial culture was used for subsequent experiments once it reached the mid-logarithmic growth phase corresponding to an optical density at 600 nm (OD₆₀₀) of 0.5–0.6, as measured with a spectrophotometer (Libra S22, Biochrom Ltd., Cambridge, UK).
5-FU powder (Ebewe Pharma, FAREVA Unterach GmbH, Austria) was reconstituted in sterile saline (Pharmaceutical Solutions Industry, Saudi Arabia) to prepare a 5 mg/mL stock solution following the manufacturer’s instructions. The resulting suspension remained stable at −5 °C for up to 28 days [29].
Motility assays
Preparation of standardized bacterial inoculum.
To ensure consistency across all motility assays, the bacterial inoculum was standardized for every plate. The primary objective was to normalize the initial bacterial load in each motility medium so that any observed differences reflected the true effect of the drug rather than variations in inoculum density. This approach minimized experimental bias attributable to inoculum variability. The procedure was performed according to published protocols [30–32] with modifications. Briefly, 1 mL of the mid-logarithmic-phase culture of PAO1 was transferred into a microcentrifuge tube and centrifuged at 10,000 rpm for 2 min. The supernatant was discarded, and the bacterial pellet was resuspended in 50 µL of PsMM. A 5 µL aliquot of this suspension was used to inoculate the motility media according to the specific assay procedures.
Incorporation of drug into motility media
For all motility assays, 5-FU was incorporated into the motility media at final concentrations of 0.1, 0.5, 12, and 100 µg/mL prior to solidification. Following autoclaving, the molten medium was divided into five sterile flasks corresponding to the untreated control and the four different 5-FU concentrations. The drug was added to each flask once the medium had cooled to approximately 50–55 °C, just before solidification, to ensure uniform distribution without affecting agar integrity. After thorough mixing, the media were poured into sterile Petri dishes and allowed to solidify at room temperature without refrigeration. Once solidified, PAO1 was inoculated according to the specific protocol for each motility assay [30–32].
Swarming motility assay
Swarming motility was evaluated on semi-solid Luria broth medium containing 0.5% agar and 0.5% glucose. A 5 µL aliquot of the previously prepared PAO1 suspension was inoculated onto the surface of the agar. Plates were incubated aerobically at 37 °C for 20–23 h without inversion, and the swarming zone was measured across the diameter of the motility area [30].
Swimming motility assay
The swimming agar plates contained 1.0% tryptone, 0.5% sodium chloride, and 0.3% agar. After incorporation of the drug and solidification of media, 5 µL of the prepared bacterial suspension was inoculated onto the surface of the medium. Plates were then incubated without inversion at 30 °C for 20–23 h. Swimming motility was evaluated by measuring the diameter of the motility zone [31].
Twitching motility assay
Twitching motility was assessed on Luria broth medium (MOLEQULE-ON, Auckland, New Zealand) solidified with 1.5% agar. After incorporation of the drug and solidification of media, 5 µL of the prepared bacterial suspension was inoculated beneath the agar surface at a 45° angle. Plates were incubated aerobically at 37 °C for 20–23 h. Following incubation, the agar layer was carefully removed, and the plates were stained with 2% crystal violet for 20 min at room temperature for visualization. The twitching zone was measured across the diameter of the motility area [32,33].
Quantitative real-time PCR (qPCR)
Six-well culture plates (Greiner bio-One, Frickenhausen, Germany) containing standardized PAO1 cultures as described above, and four concentrations of 5-FU (0.1, 0.5, 12, 100 µg/mL) were incubated for 24 or 48 h at 37 °C in static conditions. After incubation, the wells were gently washed with sterile phosphate-buffered saline (PBS) to remove planktonic cells, and the remaining biofilm cells were scraped and resuspended in PsMM. Next, 1 mL of the scraped biofilm cells was centrifuged at 10,000 rpm for 5 min, and total RNA was extracted using the Quick-RNA fungal/bacterial miniprep kit (Zymo Research, cat# R2014, Irvine, CA, USA) according to the manufacturer’s instructions with minor modifications. RNA concentration and purity were verified using a BioSpectrometer® basic (Eppendorf, Germany).
Quantitative real-time PCR was used to assess the expression of biofilm- and motility-related genes in PAO1; the genes used in expression analysis are listed in Table 1. For both 24 and 48 h biofilms, three independent biological replicates were performed, with each biological replicate analyzed in technical triplicates. Extracted RNA samples were stored at −80 °C until cDNA synthesis and qPCR analysis. Total RNA samples were reverse-transcribed into cDNA using the Haven Scientific RT Ace First-Strand cDNA synthesis kit (KAUST, Thuwal, Saudi Arabia) according to the manufacturer’s protocol. qPCR was subsequently performed with Haven Scientific EverGreen Universal Real-Time PCR master mix (KAUST, Thuwal, Saudi Arabia) on an ABI 7500 Real-time PCR system (Applied Biosystems, USA) under the following cycling conditions: 94 °C for 12 min; 40 cycles of 95 °C for 15 s, 65 °C for 30 s, and 72 °C for 30 s. The expression levels of the target genes were measured relative to the untreated control and normalized to the expression of the endogenous reference gene (16S ribosomal RNA gene). Relative expression levels were calculated using the 2−ΔΔCt method [43].
Extracellular DNA (eDNA) Quantification
Biofilms of PAO1 were cultivated in six-well plates (Greiner bio-One, Frickenhausen, Germany) containing PAO1 suspensions and 5-FU at final concentrations of 0.1, 0.5, 12, 100 µg/mL and incubated at 37 °C for 24 or 48 h under static conditions. Following incubation, eDNA was measured following the protocol of Zatorska et al. with some modifications [44]. Briefly, planktonic cells were gently removed by washing with sterile PBS buffer. The remaining biofilms were stained with 1 µM TOTO®-1 iodide (Thermo Fisher, Waltham, MA, USA) for 20 min in the dark at room temperature. The stained biofilm was then carefully scraped from the well surface and transferred to a black 96-well microplate. Fluorescence intensity was measured at excitation/emission wavelengths of 514/531 nm using a microplate reader system from BioTek Instruments (Winooski, VT, USA) and fluorescence intensity was expressed relative to the untreated control.
Confocal laser scanning microscopy (CLSM) of eDNA
PAO1 biofilms treated with different concentrations of 5-FU were cultured on coverslips in six-well culture plates at 37 °C for 24 or 48 h. After incubation, the broth was removed, and the biofilms were gently washed three times with PBS to remove planktonic cells. The coverslips were carefully transferred to a new six-well plate, and 200 µL of 2 µM TOTO®-1 iodide (Thermo Fisher, Waltham, MA, USA) was added onto each coverslip, followed by incubation for 20 min in the dark at room temperature according to the manufacturer’s instructions. The PAO1 biofilms were imaged using a Nikon C2 confocal laser scanning microscope (Nikon Instruments Inc., Tokyo, Japan) using 488 nm/ < 550 for TOTO®-1 iodide. The representative images were captured using a 20 × air objective lens (0.75 NA) and NIS-Elements Advanced Research Software (version 4.0, Nikon, Japan).
Protein-protein interaction (PPI) network analysis
The list of PAO1 genes was input in the Search Tool for the Retrieval of Interacting Genes database (STRING; version 12.0) [45] through the web interface; we specified the organism using “Pseudomonas aeruginosa PAO1”. Gene names were mapped according to STRING database annotation; due to organization and regulatory relationships, rhlAB was represented by its transcriptional regulator rhlR. The protein-protein interaction network was constructed using the default minimum interaction score of 0.4 and without additional interactors. The generated PPI network was further analyzed with Cytoscape (version 3.10.3) [46] using cytoHubba (version 0.1). The Maximal Clique Centrality (MCC) algorithm identified the key nodes in the network. Edge betweenness centrality analysis was performed using NetworkAnalyzer (version 4.5.0) to identify key node-to-node connections within the network. The node color, size, and shape were visualized by mapping the gene regulation, fold change, and node rank, respectively; network edge thickness values were drawn according to the EdgeBetweenness score.
Molecular docking analysis
The protein crystal structures of transcriptional regulator FleQ (fleQ) (Protein Data Bank (PDB) ID: 5EXP), flagellin type B (fliC) (PDB ID: 8erm), flagellar capping protein FliD (fliD) (PDB ID: 5fhy), elastase LasB (lasB) (PDB ID: 8r1b), and type IV fimbrial precursor PilA (pilA) (PDB ID: 8v7p) were obtained from the Protein Data Bank [47]. The protein three-dimensional (3D) structure of extracellular DNA degradation protein (eddB), flagellar biosynthesis protein FlhA (flhA), chemotaxis protein MotA (motA), twitching motility protein PilI (pilI), two-component sensor PilS (pilS), rhamnosyltransferase 2 (rhlC), endonuclease III (nth), exodeoxyribonuclease I (sbcB), exodeoxyribonuclease III (xthA), and single-stranded-DNA-specific exonuclease Rec (recJ) were predicted using Iterative Threading Assembly Refinement (I-TASSER) [48] based on their amino acid sequences obtained from the Pseudomonas Genome Database [49]. PAO1 protein locus tags used in this study are outlined in S1 Table. Protein structures were prepared using the Protein Repair and Analysis Server (PRAS) and AutoDock tool protocol [50,51]. The 3D structure of 5-FU was downloaded from the PubChem database (PubChem ID: 3385) [52]. The ligand was optimized using Avogadro software (version 1.2.0) [53] and then exported to mol2 format. All PDBQT files for VINA docking for receptor proteins and ligands were generated using AutoDock Tools. The grid box dimensions, center coordinates, and VINA parameters are outlined in S2 Table. AutoDock Vina software (version 1.2.7) [54] was used to perform molecular docking, and the best docking scores were selected. The output complex poses were visualized using PyMol software (version 3.0.3). Discovery Studio 2024 Client (Dassault Systemes BIOVIA, version 24.1.0) [55] was used to visualize 3D protein-ligand interactions and to identify different non-covalent interactions. ChimeraX software (version 1.7.1) was used to generate the protein-ligand complex 3D conformations.
Statistical analysis
All data are presented as mean ± standard deviation (SD). Values were derived from the average of three independent biological replicates, with each condition measured in technical triplicate. Statistical differences were assessed using one-way analysis of variance (ANOVA) based on the investigated variables followed by either Dunnett’s or Bonferroni’s post hoc analysis test to evaluate differences across the treatment groups. Statistical analyses were conducted utilizing GraphPad Prism (version 10.6.1 (799), La Jolla, CA, USA; https://www.graphpad.com). A p-value of < 0.05 was deemed statistically significant.
Results
Motility
Swarming motility was significantly affected by 5-FU in a concentration-dependent pattern. The mean swarming diameter in the control was 35.11 ± 0.60 mm with a significant increase at 0.1 µg/mL (39.83 ± 1.17 mm) and 0.5 µg/mL (38.56 ± 1.01 mm) followed by a gradual reduction to 35.22 ± 0.44 mm at 12 µg/mL and 22.78 ± 2.64 mm at 100 µg/mL (Fig 1B).
The figure shows representative images for swarming, swimming and twitching motility, and the graph shows measurements of motility zone diameter (mm) of the treated sample versus untreated control (n = 3). Asterisks indicate levels of statistical significance: p < 0.0001 (****). Data represent the mean ± SD of three independent experiments.
Similarly, swimming motility of PAO1 was influenced by 5-FU. The mean swimming diameter in the untreated control was 78 ± 16.6 mm whereas exposure to 0.1, 0.5, and 12 µg/mL of 5-FU significantly reduced motility to 51 ± 5.7 mm, 35.6 ± 1.1 mm, and 2 ± 1.6 mm, respectively. At 100 µg/mL, no detectable swimming zone or visible bacterial growth was observed on the agar surface (Fig 1A and 1C).
Twitching motility was also affected in a concentration-dependent manner. The mean twitching zone diameter of the control (25.78 ± 0.83 mm) showed a significant increase at 0.1 µg/mL (32.25 ± 1.39 mm) but decreased progressively at higher concentrations reaching 26.44 ± 2.30 mm at 0.5 µg/mL, 23.44 ± 2.07 mm at 12 µg/mL, and 14.56 ± 3.13 mm at 100 µg/mL (Fig 1D).
eDNA
Quantification of eDNA revealed a concentration- and time-dependent response to 5-FU treatment. After 24 h, eDNA levels showed a significant reduction at all tested concentrations versus the untreated control. By 48 h, however, low concentrations of 5-FU (0.1 and 0.5 µg/mL) maintained reduced eDNA levels, while treatment with 12 and 100 µg/mL resulted in a significant increase in eDNA fluorescence intensity (Fig 2).
(A) Representative CLSM images of PAO1 biofilms after treatment for 24 and 48 h with 5-FU. Biofilms of untreated control and treatment with 0.1, 0.5, 12.0, and 100 µg/mL 5-FU. Scale bar: 50 µm. (B) eDNA fluorescence intensity in 24 and 48 h PAO1 biofilms treated with increasing concentrations of 5-FU. Fluorescence was measured at Ex/Em = 514/531 nm using TOTO®-1 iodide staining. Data represent mean ± SD from three independent experiments. Asterisks indicate levels of statistical significance: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).
Gene expression analysis
At the transcriptional level, exposure of 24 h PAO1 biofilms to 5-FU resulted in a significant downregulation of type IV pili genes pilA, pilI, and pilS. Genes involved in flagellar motility such as flhA, fliD, and motA were downregulated, while fliC was upregulated at 100 µg/mL of 5-FU; fleQ was unchanged. The virulence-associated gene lasB was also downregulated. Treatment with 5-FU resulted in a significant downregulation of rhlAB, while the expression of rhlC remained largely unchanged (Fig 3). In 48 h PAO1 biofilms, treatment with 5-FU significantly upregulated selected DNA repair and stress-associated genes, including nth, xthA, recJ, sbcB, and eddB (Fig 3).
(A) Differential gene expression at 24 and (B) 48 h relative to untreated controls. (C) PPI network constructed from all analyzed genes. Node color indicates transcriptional direction (red, downregulated; green, upregulated); node size reflects the magnitude of the fold-change value. Triangular nodes represent proteins with the highest maximal clique centrality (MCC) scores, thus identifying topologically critical nodes. The edge thickness corresponds to the edge betweenness centrality, thus highlighting interactions that act as major connectors within the network. (D) Degree centrality analysis showing the number of direct interactions per node within the network. Hub genes were identified using topological analyses, including MCC and edge betweenness analyses. MCC was used to identify densely interconnected nodes, where higher scores indicate greater functional importance. Edge betweenness depicts the critical interactions reflecting the important role in different protein networks. Higher protein MCC and edge betweenness values indicate significant topological relevance within the biological network system.
Molecular Docking
Across all proteins, 5-FU showed predicted moderate and relatively uniform binding with docking energies ranging from −4.5 to −6.3 kcal/mol and hydrogen-bond interactions ranging from 1 to 6; and the detailed results are outlined in S3 Table. Moderate predicted binding scores were observed for pilI, fliC, and flhA of −4.9, −5.2, and −5.4 kcal/mol, each showing more than two hydrogen-bond interactions were observed, respectively; whereas the predicted weak binding affinity score for fleQ, motA, and fliD of −4.8, −4.5, and −4.5 kcal/mol were observed, respectively, showing minimum of 1 hydrogen-bond interaction. In addition, sbcB, recJ, and xthA predicted moderate affinity score of −5.6, −6.1, and −6.3 kcal/mol, respectively, and each showing more than 3 hydrogen-bond interactions. Moreover, the predicted contact residues for 5-FU, as shown in Fig. 4, include fliC (ALA183, PHE376, VAL355, and ALA186 ranging 2.0–2.84 Å distance); pilI (ARG20, PRO26, ARG17, ALA31, and VAL131 ranging 2.26–5.40 Å distance); flhA (LEU409, PHE408, SER403, GLY407, and THR488 ranging 1.43–3.43 Å distance); motA (ALA208, PRO215, ALA214, and ALA223 ranging 2.2–4.96 Å distance); fliD (THR72, THR70, GLU233, and PHE69 ranging 2.37–5.12 Å distance); and fleQ (ARG363, GLY177, GLU181, ASP245, HIS287, and LYS180 ranging 1.93–2.70 Å distance). Overall, 31 contacts involving 28 unique residues were identified and interaction distances ranging from 1.93 to 2.98 Å for hydrogen bond and from 1.43 to 5.98 Å for non-covalent hydrophobic/π interactions were predicted. These findings are based on in silico predictions and do not confirm direct protein inhibition, requiring further experimental validation (Fig 4).
The left panel (i) shows the protein surface with predicted binding site in the white circle; pink represents the helices, orange represents the β strands, and green indicates loops. The middle panel (ii) shows the predicted hydrogen bonding surface interactions of the protein and ligand. The green dashed lines represent hydrogen bonds; blue dashed lines denote halogen interactions, and yellow dashed lines denote π-stacking interactions. Pink areas represent hydrogen bond donors, and green areas represent hydrogen acceptors. The right panel (iii) shows the interaction diagrams between 5-FU and the PAO1 target receptors.
Discussion
Antimicrobial resistance remains a major global health challenge, and P. aeruginosa continues to pose a significant threat due to its intrinsic resistance mechanisms [56] and its ability to form persistent biofilms [57–59]. Biofilms protect bacterial cells from immune clearance and antimicrobial agents, thus enabling chronic and hard-to-treat infections [60,61]. Given the slow pace and high cost of developing new antibiotics, drug repurposing has emerged as a practical strategy for identifying anti-infective candidates with known pharmacological properties [18,62]. The anticancer drug 5-FU has shown antimicrobial and antibiofilm activity against both Gram-positive and Gram-negative organisms [17,19,26,63,64] and has also demonstrated synergy with gentamicin [26] and reversal of meropenem resistance [27]. Its antibacterial mechanisms have also been investigated in Escherichia coli using biochemical and transcriptomic analyses [65]. However, the molecular and phenotypic effects associated with 5-FU exposure on P. aeruginosa biofilm development have not been elucidated.
Pseudomonas aeruginosa virulence is organized within highly complex and multilayered regulatory networks that integrate numerous genes involved in motility, biofilm development, secretion systems, quorum sensing, and stress adaptation. Accordingly, virulence arises through coordinated changes across interconnected gene networks underscoring the integrated systems-level control of pathogenicity [66–68]. The molecular basis of 5-FU-mediated virulence modulation remains poorly defined, and this study examined its effects across key virulence-associated processes focusing on motility phenotypes, the expression of core motility genes, and the related virulence determinants that indirectly contribute to surface colonization. Given that 5-FU is a DNA-targeting pyrimidine analog, its impact on extracellular DNA production was evaluated at both early (24 h) and mature (48 h) biofilm stages alongside transcriptional changes in selected DNA repair-associated genes. The results provide an integrated framework to assess how DNA-targeting compounds influence virulence-related bacterial behavior.
Swimming, swarming, and twitching were significantly suppressed with 5-FU treatment consistent with downregulation of flagellar- and pili-associated genes. The increase in motility observed at the lowest 5-FU concentration suggests a non-linear hormetic response, where sub-inhibitory chemical stress may transiently enhance bacterial motility and virulence-associated behaviors through adaptive stress signaling pathways [69,70]. Consistent with the motility inhibition, motA, a core component of the MotA/MotB stator complex that generates flagellar torque and contributes to surface sensing and early biofilm initiation, was downregulated [71–73]. In parallel, reduced fliD expression, which is essential for FliC polymerization and proper filament assembly, is known to compromise motility, adhesion, and biofilm establishment [74,75]. In this context, the observed upregulation of fliC may reflect compensatory transcriptional regulation within the flagellar regulatory hierarchy rather than functional restoration of filament assembly [76,77]. Consistent with the loss of twitching motility, downregulation of pilA and pilI indicates impaired type IV pili-associated dynamics; pilA encodes the major pilin subunit, and suppression of type IV pili has been shown to disrupt twitching motility, surface adhesion and alter early biofilm formation in Pseudomonas aeruginosa [8,78,79].
The suppression of lasB and rhlAB by 5-FU likely further contributes to the observed motility defects. In addition to encoding elastase, lasB has been implicated in surface-associated biofilm behaviors, and lasB-deficient mutants display reduced bacterial attachment and impaired microcolony development [80,81]. Additionally, pharmacological inhibition of lasB has been shown to reduce bacterial burden and improve outcomes in infection models particularly during early stages when motility-driven colonization is essential, thus supporting its role in functional virulence and motility [82,83]. Similarly, rhamnolipids are a key modulator of surface motility, particularly swarming, by reducing surface tension and enabling coordinated cell movement [84,85]. The observed downregulation of rhlAB with rhlC unchanged suggests a reduction in total rhamnolipid output because rhlC depends on rhlAB-derived mono-rhamnolipids to synthesize di-rhamnolipids [86,87].
5-FU is a pyrimidine analog known to interfere with nucleotide metabolism and DNA synthesis, and our findings suggest that this activity is associated with a time-dependent change in eDNA dynamics during biofilm development. At 24 h, a stage at which eDNA accumulation is typically enhanced, 5-FU treatment resulted in a significant reduction in eDNA levels relative to untreated control. In contrast, at 48 h, higher concentrations of 5-FU were associated with increased eDNA accumulation, coinciding with upregulation of selected DNA repair- and stress-associated genes. However, these findings do not demonstrate that DNA repair directly caused the increase in eDNA. Rather, the concurrent increase in eDNA and the upregulation of selected DNA repair-associated gene expression suggests a stress-related transcriptional response following prolonged 5-FU exposure, rather than confirming direct activation of a specific DNA repair or SOS pathway. In bacterial cells, fluoroquinolones have been reported to activate SOS-associated and subsequently induce DNA repair pathways in Gram-negative bacteria such as Escherichia coli and Acinetobacter baumannii [88,89].
In eukaryotic systems, 5-FU induces a DNA damage response through thymidylate synthase inhibition and nucleotide imbalance, resulting in replication stress and activation of DNA repair pathways [90,91]. Furthermore, some studies have demonstrated that SOS induction in Gram-negative bacteria has been linked to increased extracellular DNA release largely through enhanced cell lysis and stress-induced DNA extrusion [92,93]. Putting all this together, we hypothesize that the increased eDNA and DNA repair gene upregulation observed at 48 h may likely represent a secondary consequence of 5-FU-associated DNA damage response and genomic stress. This interpretation is further supported by previous observations of increased dead-cell populations under the same treatment conditions [26].
Across both time points, 5-FU exposure produced coordinated but non-uniform transcriptional changes in P. aeruginosa genes associated with motility and stress-related pathways. PPI analysis demonstrated that transcriptionally affected genes were not isolated but embedded within a connected network where a limited subset of nodes exhibited higher degrees, MCC, and edge betweenness. Molecular docking suggested that 5-FU can associate with multiple proteins represented in the network with comparable binding patterns rather than a single dominant target, thus supporting a multi-target mode of interaction. Taken together, the data support that 5-FU influences P. aeruginosa at the systems level by simultaneously modulating gene expression and engaging multiple network-connected proteins rather than acting through a narrowly defined molecular target.
Collectively, these findings integrating phenotypic and molecular data (Fig 5) indicate that 5-FU can impair motility, rhamnolipid-associated pathways, and reduce eDNA availability within the first 24 h of exposure. At 48 h, 5-FU is associated with increased eDNA accumulation and upregulation of DNA repair genes consistent with a stress-driven response. Together, these findings support a model in which 5-FU initially suppresses virulence-linked traits and biofilm formation as reported in previous studies [19,26,63], but with prolonged exposure may induce nucleotide stress responses that coincide with DNA damage that promotes upregulation of DNA repair genes and eDNA release. The increased eDNA levels observed at 48 h are most likely attributable to passive release resulting from cell lysis, consistent with our previous findings demonstrating increased cell death under 5-FU exposure [26]. Nevertheless, the potential contribution of active eDNA secretion by viable cells cannot be excluded and requires further experimental validation. Future studies using clinical isolates and in vivo models will help advance these findings toward translational relevance. In parallel, chemical optimization of 5-FU [25] or its combination with complementary agents may enhance antibacterial efficacy [26,27], in addition to its potential use as an early-stage adjunct therapy. Collectively, these observations highlight the potential of 5-FU as a candidate for repurposing in strategies aimed at combating multidrug-resistant infections.
The schematic illustrates the impact of 5-FU on type IV pili, flagellar structures, rhamnolipid synthesis, LasB protease production, extracellular DNA (eDNA) levels, DNA repair genes, and biofilm-associated phenotypes. Elements displayed in red with downward arrows represent downregulated or reduced genes or phenotypes. Elements shown in green with upward arrows indicate upregulated or increased expression or phenotypes. Elements shown in black indicate no significant change. The left panel summarizes the molecular and phenotypic changes observed at 24 h, while the right panel shows the responses detected at 48 h. Created with BioRender.com.
This study has several limitations. Transcriptional data provide insight into regulatory responses but do not confirm functional outcomes for each gene; complementary proteomic or targeted genetic approaches would strengthen the mechanistic conclusions. Another limitation is the use of a single reference gene for RT-qPCR normalization. Although 16S rRNA is commonly used in P. aeruginosa gene expression studies, its stability under 5-FU exposure was not independently validated. Future studies should validate multiple reference genes under the same treatment conditions. In addition, the docking analysis provides theoretical insight and cannot establish direct protein interactions without experimental confirmation. Experiments were conducted on a single strain under defined laboratory conditions, which may not fully reflect clinical variability or represent the diversity of clinical isolates. The findings are limited to in vitro conditions, and in vivo studies are required to evaluate efficacy and potential toxicity within a complex biological environment before clinical translation. A further limitation is that the highest test concentration (100 µg/mL) may not be suitable for systemic clinical use due to potential host toxicity. Future work may investigate localized application, combination therapies, or chemical optimization of 5-FU to improve its antibacterial efficacy against P. aeruginosa. Additionally, long-term adaptation to 5-FU was beyond the scope of this work. Resistance development was not assessed; thus, the potential for 5-FU to induce resistance tolerance over prolonged exposure remains unclear. Future studies should examine whether prolonged exposure promotes tolerance, persistence, or resistance, and should define the dosing strategies and administration frequency required to maintain antibacterial efficacy. Despite these limitations, the findings of this study advance understanding of the phenotypic and transcriptional responses associated with the effects of 5-FU on P. aeruginosa, which may inform its translation toward clinical applications.
Supporting information
S1 Fig. Relative expression of 24 h P. aeruginosa biofilm-associated genes after treatment with increasing concentrations of 5-FU.
Gene expression was quantified by quantitative real-time PCR, normalized to the 16S rRNA reference gene, and calculated using the 2-ΔΔCt method. Values are expressed as fold change relative to the untreated control. Data represent mean ± SD from two independent experiments. Asterisks indicate significance levels: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).
https://doi.org/10.1371/journal.pone.0354473.s001
(TIF)
S2 Fig. Relative expression of 48 h P. aeruginosa biofilm-associated genes after treatment with increasing concentrations of 5-FU.
Gene expression was quantified by quantitative real-time PCR, normalized to the 16S rRNA reference gene, and calculated using the 2-ΔΔCt method. Values are expressed as fold change relative to the untreated control. Data represent mean ± SD from three independent experiments. Asterisks indicate significance levels: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).
https://doi.org/10.1371/journal.pone.0354473.s002
(TIF)
S3 Fig. Schematic diagram of PAO1 genes FC ratio treated with different 5-FU concentrations at 24 and 48 h exposure.
Arrow depicts the direction and relative gene FC ratio for each regulation group. Green color indicates upregulation; and red indicates downregulation. Relative fold‑change ratios at 24 h showing upregulation of fliC and rhlC; and downregulation of fleQ, pilS, flhA, lasB, motA, pilA, rhlAB, pilI, and pilD. Relative FC ratios at 48 h showing upregulation of nth, sbcB, xthA, recJ, and eddB. The fixed height ratio of each regulations and genes were calculated and illustrated according to (1) fold regulation group ratio; and (2) the ratio of each gene FC value from the sum of FC on respective regulation group.
https://doi.org/10.1371/journal.pone.0354473.s003
(TIF)
S4 Fig. VINA docking results complex of 5-FU and PAO1 receptor.
Molecular-docked complexes interaction of (A) lasB (B) xthA, (C) recJ, (D) pilS, (E) rhlR, (F)sbcB, (G) pilA, (H) rhlC, (I) eddB, (J) nth, with 5-FU ligand. The left panel (i) shows the protein surface with predicted binding site in the white circle; pink represents the helices, orange represents the β strands, and green indicates loops. The middle panel (ii) shows the hydrogen bonding surface interaction of protein and ligand. The green dashed lines represent hydrogen bonds; blue dash lines denote halogen interaction, and yellow dash lines denote pi-stacking interaction. Pink areas represent hydrogen bond donors, and green areas represent hydrogen acceptors. The right panel (iii) shows the interaction diagram of 5-FU and PAO1 receptors.
https://doi.org/10.1371/journal.pone.0354473.s004
(TIF)
S2 Table. Receptor grid coordinates, box dimensions, and AutoDock VINA parameters.
https://doi.org/10.1371/journal.pone.0354473.s006
(PDF)
S3 Table. Detailed molecular docking results obtained using AutoDock VINA.
https://doi.org/10.1371/journal.pone.0354473.s007
(PDF)
Acknowledgments
The authors would like to acknowledge the staff and facilities of the Molecular and Cell Biology Laboratory, a core research facility of the King Saud University College of Dentistry, in collaboration with the Prince Naif bin AbdulAziz Health Research Center, for their significant contributions to this publication.
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