Unveiling the role of srbA sRNA in biofilm formation by regulating algU, mucA, rhlA, and rsmA in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic bacterial pathogen for causing secondary infections in hospital settings, raising significant global public health concerns as highlighted in the WHO’s 2024 bacterial priority pathogens list [ 1 ]. Its ability to form robust biofilms, to adapt swiftly, and to exhibit high levels of inherent resistance to antimicrobial has positioned it as a critical pathogen across a wide variety of natural and artificial environments, together with various indwelling medical devices [ 2 ]. Biofilm-associated infections pose a major threat to human health in the era of rising antimicrobial resistance [ 3 , 4 ]. Although the genetic mutations often underlie antimicrobial resistance, biofilms also offer an adaptive resistance. Even bacteria sensitive to antibiotics could escape the effect in a biofilm state, however, they may return to a susceptible form once the biofilm disperses [ 5 , 6 ]. Population density-dependent cell–cell communication, referred to as quorum sensing (QS), is essential for the formation of biofilms by P. aeruginosa [ 7 , 8 ]. QS system plays a pivotal in the pathogenesis of P. aeruginosa , starting from the initial colonization in the host to subsequent invasion, infection, spread, evasion of the immune response, and development of drug resistance [ 9 ]. The four primary and interconnected QS networks in P. aeruginosa include the Las, Rhl, Pqs, and Iqs systems. These systems function through a hierarchical framework, facilitating intricate interactions among various cellular signals [ 10 ]. The Las system occupies the highest position in this hierarchy, overseeing the regulation of the other QS systems, while the Rhl system is positioned beneath. The Pqs system activates the Rhl system and is under the regulation of Las, whereas Iqs governs both the Pqs and Rhl systems and is itself activated by Las [ 8 , 11 ]. Through this complex network, the activated Rhl system controls the production of various QS-related virulence factors [ 10 , 12 ]. The relationship between QS system and biofilm formation is indirectly influenced by the nature of motility, as well as the production of various components of biofilm matrix [ 5 ]. Swarming motility, characterized as a coordinated feature of surface movement, is particularly significant during the initial phase of biofilm development and is regulated by the Rhl system in P. aeruginosa [ 13 , 14 ]. A complex regulatory network, acting via transcriptional, post-transcriptional, and post-translational processes in response to environmental and host-derived signals through its QS-system, modulates P. aeruginosa ’s adaptability and pathogenicity [ 5 , 8 ]. The AlgU (σ 22 ) sigma factor, a stress response master regulator and functional counterpart of Escherichia coli σ E , coordinates nearly 300 regulatory genes and plays a crucial role in regulating synthesis of virulence factors and other infection-related processes by affecting QS network [ 15–18 ]. AlgU enhances alginate production by up-regulating the algD operon and activating transcription factors AlgR and AmrZ, those are pivotal for alginate synthesis in mucoid strains [ 16 , 17 ]. The transition from the nonmucoid to the mucoid phenotype is accompanied by a cascade of genetic changes resulting from mucA mutations [ 17 , 18 ]. Under stress-free conditions, AlgU is inhibited by MucA, whereas under stress AlgU becomes relieved to trigger alginate production. mucA- mutant strains of P. aeruginosa have been reported to show increased alginate synthesis with increased biofilm forming ability and stress resistance [ 19–21 ]. The Rhl system of P. aeruginosa regulates biofilm formation through the RhlA protein, which synthesizes rhamnolipids, a glycolipid essential for maintaining the biofilm matrix [ 5 , 8 , 22 , 23 ]. The autoinducer binds to RhlR, resulting enhanced expression of rhlA , which is crucial for the production of rhamnolipids [ 24 ]. Rhamnolipids not only support biofilm structure but also facilitate bacterial dispersion, allowing P. aeruginosa to occupy new ecological niche [ 25 , 26 ]. RsmA, another key regulator in P. aeruginosa , belongs to the CsrA family of RNA-binding proteins, which has been reported to control virulence, motility, biofilm formation, and metabolism by interacting with the target mRNAs [ 27–29 ]. Recently, non-coding small RNAs (sRNAs) have been reported to act as the crucial regulator for the adaptability of P. aeruginosa , including biofilm development and pathogenesis [ 30–33 ]. The Gac/Rsm signaling cascade promotes the production of RsmY and RsmZ , both subsequently relieve the repression by RsmA on the target genes, and thereby facilitates biofilm development [ 34 ]. Another sRNA, PhrS , was reported to regulate the QS system regulator PqsR (MvfR), which is essential for biofilm formation via the PQS signaling pathway [ 35 ]. The CrcZ sRNA is the part of the carbon catabolite repression system and affects biofilm formation by inhibiting Crc expression, especially when carbon sources are limited [ 36 ]. Recently, regulatory role of PA0730 .1 sRNA on the expression of different traits of P. aeruginosa has also been reported to be linked with pathogenicity and biofilm formation [ 32 ]. The srbA sRNA was earlier reported to up-regulate during the stationary phase and biofilm formation in P. aeruginosa PA14, though its precise function in biofilm regulation remained unclear [ 37 ]. More recently, it has been documented that srbA could regulate genes encoding the major enzymes involved in the TCA cycle, thus is responsible in nutritional adaptation in P. aeruginosa PAO1, which was further reported to be linked with the production of various virulence factors [ 33 ]. With this background, the present study was aimed to investigate the possible role of the srbA sRNA in biofilm formation and its regulatory influence on various biofilm-controlling factors by studying srbA deletion and overexpression strains to unveil its molecular targets. Understanding the role of srbA could reveal new insights into the regulation of biofilm development that could help to manage biofilm-associated infections by P. aeruginosa .

Pseudomonas aeruginosa PAO1 (ATCC 15692) used as the experimental model organism in this study. For cloning and translational fusion experiments, Escherichia coli DH5α was used. Details of the plasmids and bacterial strains used in this study are given in Supplementary Table S1 and S2 , respectively. The srbA overexpression (SrbA + ), srbA deletion (ΔSrbA), and plasmid-mediated complementation of srbA deletion (ΔSrbApSrbA) strains, and their respective control, empty vector (pEV), WT, and complementation of deletion strain by empty vector (ΔSrbApEV) strains were constructed earlier [ 33 ] and were used for studying the effect of srbA sRNA on biofilm development in P. aeruginosa PAO1. For the planktonic culture, cells were grown in the LB (Luria Bertani) broth for 3 h in 37°C at 200 rpm shaking condition or till OD 600 of 0.8. For developing substratum-attached biofilm, cells were grown in LB broth and kept at 37°C under static condition for 24 h. The colony biofilm was prepared in LB agar plate, where 5 µl of mid-log phase culture was spot inoculated and was kept for 48 h at 37°C. For the translation fusion analysis, the E. coli cells were grown in the LB broth. Selective antibiotics were supplemented in the specified media as per the experimental requirements and the strains used. The antibiotics were used in this study were carbenicillin 150 µg/ml, gentamycin 100 µg/ml, tetracycline 100 µg/ml for strains of P. aeruginosa , and ampicillin 50 µg/ml, gentamycin 50 µg/ml for the strains of E. coli . The strains pEV, SrbA + , ΔSrbA, ΔSrbApEV, and ΔSrbApSrbA were earlier constructed in the laboratory and were used in this study [ 33 ]. For confocal microscopy, the eCFP reporter-based plasmid pUCP30T-eCFP was electroporated into the WT PAO1 strain, along with pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains. For the translational fusion assay, srbA was inserted into the pUCP18 plasmid [ 33 ], and its target mRNA was cloned into the pUCP30T-eCFP plasmid containing an eCFP reporter gene [ 61 ]. Specified regions of the selected gene, including start codons and SD sequences, were fused upstream of the eCFP gene. For mucA translation fusion, the pUCP30T- mucA -eCFP construct was used [ 32 ]. The pUCP30T- algU -eCFP construct was developed using forward and reverse primers designed from the transcription initiation site and downstream regions of the algU gene, respectively. Similarly, pUCP30T- rhlA -eCFP and pUCP30T- rsmA -eCFP were constructed with corresponding primers for the rhlA and rsmA genes. All primers used for the strain construction are presented in Supplementary Table S3 . Biofilm quantification using the crystal violet assay was conducted as described earlier [ 62 ]. Bacterial cultures (OD 600 = 0.4) from mid-exponential phase of WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains were inoculated in a 96-well microtiter plate and incubated at 37°C without any shaking. After incubation, the culture broth was carefully pipetted out, and the adhered biofilm was gently rinsed with sterile PBS. Biofilms were then fixed with methanol, air-dried, and were stained with 0.1% Hucker crystal violet. Excess dye was removed, and the crystal violet retained by the biofilm was dissolved with 33% glacial acetic acid. The absorbance was measured at 570 nm using a microtiter plate reader (iMARK, Bio-Rad, Japan). Cell viability in biofilms was determined by the MTT assay [ 63 ]. The biofilms formed by WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA in the 96-well microtiter plate were washed with PBS, and 200 μl of LB containing 0.5 mg/ml MTT reagent was poured to each well. After incubation of 2 h at 37°C in the dark, the formazan crystals formed were dissolved with DMSO, and the A 570 was measured by the microtiter plate reader. The amount of EPS in the biofilms was quantified by Congo red binding assay [ 64 ]. Biofilms formed by WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains in a 96-well plate were stained with 1% Congo red, incubated in the dark for 30 min, and were then washed with PBS. Bound dye was dissolved in DMSO, and absorbance was recorded at 490 nm. The alginate production was determined following the method described earlier [ 65 ]. Cells of WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA from the substratum-attached biofilm were suspended in 500 μl PBS. The suspension was then mixed with 500 μl of 1 M NaCl and was vortexed to extract the alginate bound to the cell surface. The resulting mixture was then centrifuged at 8000 × g for 20 min. The supernatant was mixed with cetylpyridinium chloride (2% w/v) and was kept overnight at 4°C. The alginate–cetylpyridinium chloride complex was subsequently collected by centrifugation at 8000 × g for 10 min at 4°C. The supernatant was discarded, and the pellet was dissolved in 500 μL of chilled isopropanol. This mixture was then centrifuged again at 8000 × g for 10 min at 4°C. The pellet was resuspended in 1 M NaCl and was kept overnight at 4°C. The alginate content was quantified using the carbazole method [ 66 ]. For colony morphology, mid-log phase cultures of WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA were point inoculated onto tryptone agar plates having Congo red and Coomassie brilliant blue. After an incubation of 24 h at 37°C, morphological features of the colonies were visualized under a stereo microscope (Zoomstar-II, Dewinter). CLSM and SEM were used to observe biofilm architecture. For both microscopic studies, WT, pEV, SrbA + , and ΔSrbA strains transformed with pUCP30T-eCFP were grown on coverslips in a 24-well plate and were incubated for 24 h. Biofilms were washed to remove unadhered cells, fixed with 2.5% glutaraldehyde, then again washed with PBS, and were air-dried. For CSLM, the images were captured using a confocal microscope (Zeiss LSM 800, Carl Zeiss, Germany) with a 434 nm excitation and 477 nm emission wavelengths to detect eCFP fluorescence in the cells embedded within the biofilm matrices. COMSTAT analysis was performed for measuring the average bio-volume and thickness of the biofilm images. For SEM, the fixed-dried biofilm on the coverslips was dehydrated with a gradient of ethanol and was then dehydrated thrice with absolute ethanol for 10 min each. After platinum coating, the images were captured by a SEM (Evo LS10, Carl Zeiss, Germany). The involvement of srbA on the translational efficiency of selected genes was assessed using translational fusion assay by transforming E. coli DH5α with eCFP reporter plasmid constructs [pUCP30T- algU (-43 to +187)-eCFP, pUCP30T- mucA (-41 to +91)-eCFP, pUCP30T- rhlA (-27 to +103)-eCFP, pUCP30T- rsmA (-41 to +91)-eCFP] co-transformed with SrbA + or EV strains [ 32 , 33 ]. Cells from mid-log phase culture of each strain were inoculated to LB and grown at 37°C to attain an OD 600 of ~0.2. Isopropyl β-d-1-thiogalactopyranoside (IPTG) of a final concentration of 50 µg/ml was added to the growing culture and was kept further for 2 h. The cell pellets were washed using PBS by centrifugation, and the cell suspension in PBS was put on glass slide, and finally the fluorescence was measured using fluorescence microscope (Axio Vert.A1 FL-LED, Carl Zeiss, Germany). The fluorescence intensity of eCFP in the cell suspensions of each strain was determined using an excitation and emission wavelength of 434 nm and 477 nm, respectively, by a fluorescence spectrophotometer (F-7100, Hitachi, Japan). Total RNA from biofilm and planktonic cultures was extracted by the TRIzol MAX Bacterial RNA isolation kit (Ambion Lifetechnology, U.S.A.) and was digested with DNase to remove any DNA contamination. The cDNA was synthesized using 2 µg of RNA and random hexamers, following the manufacturer’s manual (Applied Biosystems, U.S.A.). The real-time PCR (RT-qPCR) was carried out using a thermal cycler (StepOne Real-Time PCR System, Applied Biosystem, U.S.A.). A reaction mixture of 20 μl was prepared using 10 μl of Power UP™ SYBR™ Green Master Mix (Applied Biosystems, U.S.A.), 0.4 μl both of forward and reverse primers (20 μM), 7.2 μL nuclease-free water, and 2 μl cDNA. The cycle of reaction was set with an initial holding stage at 50°C for 2 min and then at 95°C for 2 min, denaturation was done at 95°C for 15 sec. Annealing temperature and extension time were set according to the Tm of the respective primer and amplicon size. Each RT-qPCR study was performed in triplicate. The level of quantitative expression for each selected gene was analyzed comparing that in the respective control set, and rpoD was considered as the reference house-keeping gene for the normalization. The primers used for this RT-qPCR study are listed in Supplementary Table S3 . Pseudomonas PAO1 gene sequences were obtained from the Pseudomonas genome sequence database [ 38 ]. Complementary base-pair analysis of srbA with biofilm regulatory transcripts was carried out using IntaRNA 2.0 [ 42 ], using default set up ( Supplementary Figure S1 ). The RNA secondary structure prediction was done using RNAStructure 6.0.1 [ 67 ]. Data were analyzed for all experiments by descriptive statistics and one-way ANOVA using GraphPad Prism version 9.0. All experiments were done in triplicate, and results are showed as the mean ± SEM.

Pseudomonas genome database reveals the existence of a 239 bp span encoding srbA sRNA, resulting from the transcription of the reverse strand of a locus in between aceA and PA2633 genes of P. aeruginosa PAO1 [ 33 , 38 ], that was earlier coined as pant235 [ 39 ] and PA2633 .1 [ 40 ]. Additionally, srbA sequence data obtained from PAO1 were reported as conserved among other strains of P. aeruginosa , including that in PA14, termed as PA14sr_067 [ 33 , 41 ]. Higher expression level of srbA was earlier documented under biofilm state of P. aeruginosa PA14 [ 37 ]; however, the regulatory role of srbA on biofilm development is still unclear. In this study, expression levels of srbA sRNA in P. aeruginosa PAO1 were studied during substratum-attached biofilm and colony biofilm states and were compared with that in the mid-log planktonic stage. The RT-qPCR data revealed increase level of srbA by ~5.5-fold in colony biofilm and ~9.7-fold in substratum biofilm states in comparison with that in the planktonic cells ( Figure 1A ). Additionally, the abundance of srbA was quantitatively analyzed using srbA overexpression strain SrbA + , srbA deleted strain ΔSrbA, and complementation of deletion strain ΔSrbApSrbA, and their respective control strains, pEV, wildtype (WT), and ΔSrbApEV. In planktonic state, the expression of the srbA was found to be ~5.1 and ~3.6-fold higher in SrbA + and ΔSrbApSrbA, respectively, compared with the WT strain. ( A ) Comparative srbA expression among the substratum-attached biofilm, colony biofilm, and mid-log phase planktonic growth. ( B ) srbA expression in wildtype (WT), empty vector control (pEV), overexpression (SrbA + ), deletion (ΔSrbA), deletion empty vector control (ΔSrbApEV), and complementation of srbA deletion (ΔSrbApSrbA) strains under mid-log planktonic, substratum attached biofilm, and colony biofilm conditions. Fold changes in expression were calculated relative to the WT strain grown in planktonic conditions, regardless of growth state. The level of quantitative expression of srbA was determined using rpoD as the reference house-keeping gene for the normalization. Statistical analysis was performed using one-way ANOVA for each condition, comparing the mean of each group with that of the WT strain. Additionally, the expression levels of the WT strain in different conditions were compared across all groups. Data presented are the mean of three replicates with ±SEM. ‘Ud’ and ‘ns’ stand for undetermined and non-significant, respectively. Statistical significance is indicated by ** P <0.01 and **** P <0.0001. In substratum-attached biofilm state, srbA levels were elevated by ~29.9 and ~19.1-fold in SrbA + and ΔSrbApSrbA, respectively, compared with the WT strain. In contrast, abundance of srbA was increased by ~229.9 and ~211-fold in SrbA + and ΔSrbApSrbA, respectively, in comparison with the WT strain under colony biofilm state. Within each growth condition, WT and pEV strains showed similar levels of srbA ( Figure 1B ). The contribution of srbA on the biofilm formation in P. aeruginosa was analyzed using SrbA + , ΔSrbA, and ΔSrbApSrbA, and respective control strains pEV, WT, and ΔSrbApEV. Crystal violet assay for biofilm formation revealed that the SrbA + produced significantly ~27% more biofilm compared to the WT, whereas deletion of srbA caused a significant decrease in biofilm formation by ~46%. Biofilm forming ability restored in ΔSrbApSrbA construct after plasmid-mediated reintroduction of srbA in deletion strain ( Figure 2A ). Viable cell mass within the biofilms, as measured by MTT assay, significantly declined (~37%) in ∆SrbA which was restored in ΔSrbApSrbA strain; however, no significant alteration in cell viability was observed due to overexpression of srbA compared with the WT strain ( Figure 2B ). The EPS content could indicate the amount of biofilm formed and was quantified using Congo red binding method. Overexpression of the srbA resulted ~15% increase in EPS production; on the contrary, it was sharply decreased (~65%) due to the deletion of srbA ; however, it was found to be restored in the ΔSrbApSrbA strain, resembling that in the SrbA + ( Figure 2C ). Biofilm maturation and its structural integrity largely depend on the amount of alginate present in the matrix; thus, the alginate was quantified in all the test strains. The SrbA + strain exhibited an ~38% increase in alginate production compared with the pEV strain. In contrast, the ∆SrbA showed about a ~46% reduction in alginate levels in comparison with the WT strain. However, the complementation of deletion strain ΔSrbApSrbA was able to restore alginate production to a level comparable with those of the WT strain ( Figure 2D ). ( A ) Biofilm forming capability of WT was measured by CV assay and compared with that of the pEV, SrbA + , ΔSrbApSrbA, and ΔSrbA strains. ( B ) The cell viability of WT strains in the biofilm, as measured by MTT assay, was compared with the pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains. ( C ) Amount of EPS in the biofilm matrix of WT strains, as determined by Congo red staining, was compared with the pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains. ( D ) Amount of alginate determined by carbazole assay in the biofilm of pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains in comparison with the WT strain. ( E ) Comparative morphological nature of the colonies as appeared on the Congo red agar plates of WT, pEV, SrbA + , ΔSrbA, and ΔSrbApSrbA strains, with a quantitative illustration of respective colony diameters. Data presented are the mean of three replications with ±SEM; statistical analysis was performed using one-way ANOVA for each condition, comparing the mean of each group with that of the WT strain. ‘ns’ indicates non-significance, and *, **, ***, and **** correspond to significance at P <0.1, 0.01, 0.001, and 0.0001, respectively. sRNA, small RNA; WT, wildtype. Apparently, slime layer in the bacterial colonies reflects the quantitative level of EPS in the colony biofilm, which was visualized on tryptone agar plates having Congo red, that binds to EPS within the slime layer resulting characteristic colony morphology with red ring around, after an incubation period of 24 h at 37°C. Visibly, SrbA + colony showed higher density of bound dye, suggesting presence of more EPS; on the contrary, ∆SrbA exhibited different colony morphology with smaller diameter and absence of red ring that might be due to the less amount EPS ( Figure 2E ). Effect of deletion was found to be reversed in ΔSrbApSrbA and resembled the colony morphology and diameter like the WT, and SrbA + strains. Overall, WT and pEV strains showed similar features as far as their EPS and biofilm production abilities are concerned. Biofilm formation capacity and architectural feature of both of SrbA + and ΔSrbA were visualized by confocal scanning laser microscopy (CSLM) and scanning electron microscopy (SEM), and comparative analysis was done with their respective control strains, pEV and WT. For CSLM study, P. aeruginosa harboring pUCP30T-eCFP was used to qualitative measurement of cell density in the biofilm by eCFP fluorescence. CSLM images revealed almost similar biofilm thickness in WT and pEV strains, and overexpression srbA resulted thicker and dense biofilm in SrbA + strain with higher Z stack; on the contrary, deletion of srbA resulted significant decrease in bio-volume and biofilm thickness with thinner Z stack ( Figure 3A and Table 1 ). Having consistency with CLSM study, SEM images of both WT and pEV also showed biofilm architecture with highly populated bacterial cells in the well-organized matrix. SEM image of the SrbA + strain showed cells with slightly larger in length, embedded in higher amount of EPS matrix. In contrast, the ΔSrbA strain failed to develop such a complex biofilm architecture, indicating that the absence of srbA severely affected the formation structured biofilms ( Figure 3B ). ( A ) Confocal laser scanning micrographs of the strains harboring pUCP30T-eCFP, were captured for the analysis of biofilm thickness. ( B ) Scanning electron microscopic images of the strains for visualization of biofilm architecture. Data are representative of three observations. WT, wildtype. Data are the mean from three replications with ±SD. Observing the involvement of srbA in the biofilm formation by P. aeruginosa , emphasis was given to find out the genetic target of srbA among different biofilm regulatory genes. Accordingly, base-pair complementarity analyses of srbA sRNA with mRNA region containing Shine–Dalgarno (SD) sequence and start codon of different biofilm regulatory genes, such as algD (-23 to +52), algU (-22 to +6), fimX (-54 to +21), fleQ (-57 to +18), mucA (-19 to +8), pelA (-40 to +35), pslA (-37 to +38), pslB (-54 to +21), rhlA (-21 to +11), and rsmA (-27 to +6), were done using IntaRNA 2.0 using the default settings ( Supplementary Figure S1 ) [ 8 , 10 , 14 , 15 , 18 , 21 , 24 , 27 , 42 ]. Based on significant matching with the regulatory region near the start codon and SD-sequence, algU , mucA , rhlA , and rsmA were selected for their expressional study ( Supplementary Figure S2 and S3 ). The sequence complementarity analysis showed that 84–93 bp, 45–52 bp, 89–113 bp, and 146–156 bp sequences of srbA paired with the transcript regions of algU (-22 to -12), mucA ( + 1 to + 8), rhlA (-12 to +11), and rsmA (-16 to -6), respectively, suggesting a possible function of srbA in regulating the expression of these genes ( Figure 4A ). The expression levels of algU , mucA , rhlA , and rsmA were measured in the WT, pEV, SrbA + , ΔSrbA, ΔSrbApEV, and ΔSrbApSrbA strains using RT-qPCR under mid-log planktonic, substratum-attached biofilm, and colony biofilm conditions. ( A ) Interaction of srbA sRNA with the regulatory region near the start codon and Shine-Dalgarno sequence of algU , mucA , rhlA , and rsmA , as analyzed by IntaRNA software. RT-qPCR analysis of WT, pEV, SrbA + , ΔSrbA, ΔSrbApEV, and ΔSrbApSrbA cells grown in planktonic, substratum-attached biofilm, and colony biofilm states for the expression study of ( B ) algU , ( C ) mucA , ( D ) rhlA , and ( E ) rsmA , taking rpoD as a reference gene. Statistical analysis was performed by one-way ANOVA for each gene under specified condition, comparing the mean of each condition with that of the WT strain. Additionally, the expression levels of the WT strain in different conditions were compared across all groups. Data presented are the mean of three replications with ±SEM; ‘ns’ indicates non-significance, and *, **, ***, and **** correspond to significance at P <0.1, 0.01, 0.001, 0.0001, respectively. sRNA, small RNA; WT, wildtype. Relative abundance of algU was found to be ~2.8-fold higher in the SrbA + strain under planktonic conditions as observed from RT-qPCR analysis, while a ~1.3-fold lower expression level was observed in the ΔSrbA strain in comparison with the WT strain. However, in ΔSrbApSrbA, algU expression was ~2.2-fold higher than the WT, restoring the effect of srbA deletion. Under substratum-attached biofilm conditions, algU expression was ~2.3-fold higher in the SrbA + , while ~1.7-fold lower in ΔSrbA with respect to the WT strain. In ΔSrbApSrbA, algU expression was ~1.56-fold higher compared with the WT, effectively compensating the effect of deletion. In the colony biofilm state, algU expression was up-regulated by ~2.2-fold in the SrbA + , while a ~2.25-fold decrease was observed in ΔSrbA in comparison with the WT strain. However, in ΔSrbApSrbA, algU expression was ~1.71-fold higher in comparison to the WT, overcoming the effect of srbA deletion. Interestingly, the expression of algU was significantly elevated in WT cells at both the substratum-attached biofilm and colony biofilm states compared with its planktonic counterpart, by ~50.9 and ~68.12-fold, respectively. In each growth condition, the WT and ΔSrbA strains exhibited similar expression levels, when compared with their respective empty vector control strains, pEV and ΔSrbApEV ( Figure 4B ). It seems that the copy number of srbA sRNA might contribute a regulatory role in the relative abundance of algU , possibly through direct or indirect effect on algU mRNA stability. Moreover, the substantial up-regulation of algU in both biofilm states suggests its functional importance in biofilm formation and its maintenance. Under planktonic conditions, the expression level of mucA was observed to be ~1.4-fold lower in the SrbA + , and ~1.15-fold higher in the ΔSrbA with respect to the WT strain. Restoration of the srbA deletion effect was observed in ΔSrbApSrbA, where mucA expression was found to be ~1.11-fold higher compared to the WT. At substratum-adhered biofilm state, mucA expression levels were found to be ~1.67-fold lower in SrbA + , and ~1.14-fold higher in ΔSrbA in comparison with the WT strain. ΔSrbApSrbA strain guided to restore the mucA expression level as affected by the srbA deletion. Under colony biofilm condition, mucA expression decreased ~2.9-fold in SrbA + and increased by ~2.6-fold in ΔSrbA with respect to the WT strain. A lower expression level mucA by ~1.4-fold in ΔSrbApSrbA in comparison with the WT suggested reversal of the deletion effect of srbA . Interestingly, the expression of mucA was found to be similar in WT strain both under planktonic and substratum-attached biofilm conditions, whereas at colony biofilm state, mucA expression level decreased by ~28.6-fold in comparison with the planktonic WT cells ( Figure 4C ). Both the WT and ΔSrbA strains showed identical levels of mucA expression in comparison with their respective empty vector control strains, pEV and ΔSrbApEV, in each growth condition. It could be apprehended that the copy number of srbA might contribute in regulating mucA mRNA stability. Expressional analysis revealed an increase of rhlA level by ~12-fold in SrbA + strain and a decrease of ~4.7-fold in ΔSrbA with respect to that in the WT strain under planktonic growth condition, whereas a ~4.5-fold higher rhlA expression level was noted in the ΔSrbApSrbA in comparison with the WT strain, indicated restoration of the effect of srbA deletion. At substratum-adhered biofilm state, rhlA expression became ~3.3-fold increase in SrbA + and ~1.7-fold decrease in ΔSrbA as compared with that in the WT strain. The complementation of srbA in deletion strain resulted a ~2.4-fold higher rhlA expression with respective to the WT strain, suggesting the recovery of the deletion effect. In the colony biofilm state, the expression of rhlA became ~3.0-fold increase in the SrbA + strain and ~1.7-fold decrease in ΔSrbA with respect to the WT strain. The ΔSrbApSrbA strain recovered the effect of srbA deletion and exhibited ~2.1-fold higher compared with the WT strain. Interestingly, the expression of rhlA significantly increased in WT strain both under substratum-attached and colony biofilm conditions in comparison with its planktonic counterpart by ~34.0 and ~28.8-fold, respectively. At each growth condition, the WT and ΔSrbA strains showed apparently the same levels of expression compared with their respective empty vector control strains, pEV and ΔSrbApEV ( Figure 4D ). It is apparent from the result that the copy number of srbA sRNA might play a contributory function in regulating rhlA expression or its stability. Additionally, significant higher expression level of rhlA in both biofilm conditions suggests its regulatory role in biofilm development and maintenance. In the planktonic growth condition, the rsmA expression levels decreased by ~2.3-fold in the SrbA + and increased by ~2.5-fold in ΔSrbA in comparison with that in the WT strain. The expression of rsmA was found ~1.5-fold lower in ΔSrbApSrbA with respect to the WT strain, indicating reversal of deletion effect. Under substratum-attached biofilm condition, rsmA expression became ~1.6-fold decrease in SrbA + and ~3.4-fold increase in ΔSrbA as compared with that in the WT strain. Notably, the complementation of srbA deletion lowered the expression level of rsmA by ~1.7-fold with respective to the WT strain, suggesting the recovery of the deletion effect. In the colony biofilm, the expression of rsmA became approximately four-fold decrease in the SrbA + strain and ~4.3-fold increase in ΔSrbA compared with the WT strain. The srbA deletion effect on the expression level was found to be reversed in the ΔSrbApSrbA strain and showed approximately four-fold lower with respect to the WT strain. The expression of rsmA significantly decreased in the WT strain both under substratum-attached and colony biofilm states in comparison with its planktonic counterpart, by ~20 and ~28-fold, respectively. In each separate growth condition, the WT and ΔSrbA strains showed relatively the similar expression levels of rsmA compared with the corresponding empty vector control strains, pEV and ΔSrbApEV ( Figure 4E ). It seems that the copy number of srbA sRNA might contribute in the regulation of rsmA expression or its stability. The significant decreased expression level of rsmA in both biofilm states suggests its possible regulatory role in biofilm formation and maintenance. Sequence alignment analysis indicated that srbA may influence the translational efficiency of certain biofilm-related genes by interacting with the ribosomal binding sites of algU , mucA , rhlA , and rsmA transcripts ( Figure 4A ). To explore this possibility, a translational fusion assay was performed using pUCP30T-eCFP, a plasmid containing an eCFP reporter gene. The selected gene regions, including their start codons and SD sequences, were fused at the upstream of the eCFP gene ( Supplementary Figure S4-S7 ). These constructs were co-transformed into E. coli DH5α along with either the empty vector pUCP18 (EV) or pUCP18 containing srbA + ( Supplementary Figure S8 and S9 ). The translational efficiency of each fused gene was assessed by measuring the fluorescence intensity of cell suspensions using fluorescence microscope and a spectrofluorometer. For the algU fusion, forward and reverse primers were designed from 43 bp upstream and 187 bp downstream of the start codon, respectively ( Supplementary Figure S4 ). Fluorescence microscopy showed a definite increase in translation efficiency of algU in the presence of srbA ( Figure 5A ). A fluorescence reporter assay further confirmed this finding that showed a ~3.1-fold increase in fluorescence intensity when pUCP30T- algU -eCFP was co-transformed with pUCP18- srbA + in comparison with the empty vector control ( Figure 5B ). The results suggest that the srbA sRNA have regulatory role on the expression of the algU transcript possibly by facilitating ribosome binding. Bioinformatics analysis was further done to unveil the possible RNA–RNA interactions and the stability of the secondary structures involved. The analysis predicted that the ribosome binding site, SD sequence, and start codon of algU formed a highly structured, intramolecular base-paired region, which might hinder ribosome binding and proper translation initiation. However, binding of srbA sRNA with the algU RNA resulted RNA duplex structure, which was appeared to be more stable, with the SD sequence and start codon positioned favorably for ribosome binding. This structural rearrangement seems to enhance the translational initiation of algU by the srbA sRNA ( Figure 5C ). ( A ) Fluorescence micrographs and bright field images of E. coli DH5α cells co-transformed with pUCP30T- algU -eCFP and either pUCP18 (EV) or pUCP18-SrbA + and ( B ) fluorescence intensity of the respective cell suspensions. ( C ) Bioinformatics-derived secondary structures of algU mRNA (1–75 bp) alone and the duplex secondary structure of algU mRNA (1–75 bp), and srbA sRNA (24–119 bp) for visualizing the probable effect of RNA–RNA interaction on the stability of the secondary structure and algU mRNA translation. Values are the mean of three replications with ±SEM, and ** stands significance at P <0.01. For the mucA fusion, forward and reverse primers were designed 41 bp upstream and 93 bp downstream of the start codon, respectively ( Supplementary Figure S7 ). Fluorescence microscopy showed a notable reduction in the translation efficiency of mucA when srbA sRNA was present ( Figure 6A ). This was further supported by the fluorescence reporter assay, which demonstrated a six-fold reduction in fluorescence intensity when pUCP30T- mucA -eCFP was co-transformed with pUCP18- srbA + in comparison with the empty vector control ( Figure 6B ). Results suggest that srbA sRNA might directly interact with the mucA transcript, thus inhibiting ribosome binding, and consequently lowering mucA translation. Further bioinformatics analysis examined the potential RNA–RNA interactions and secondary structure stability of mucA . The analysis revealed that the ribosome binding site, SD sequence, and start codon of mucA were properly aligned for ribosome binding and translation initiation under normal conditions. However, when srbA sRNA binds to mucA RNA, the formation of a more stable RNA duplex structure was observed ( Figure 6C ). The results suggest that srbA sRNA regulates mucA transcript expression possibly by inhibiting ribosome binding and thereby reducing its translation. ( A ) Fluorescence micrographs and bright field images of E. coli DH5α cells co-transformed with pUCP30T- mucA -eCFP and either pUCP18 (EV) or pUCP18-SrbA + , and ( B ) fluorescence intensity of the respective cell suspensions. ( C ) Bioinformatics-derived secondary structures of mucA mRNA (1–75 bp) alone and the duplex secondary structure of mucA mRNA (1–75 bp), and srbA sRNA (10–95 bp) for visualizing the probable effect of RNA–RNA interaction on the stability of the secondary structure and mucA mRNA translation. Values are the mean of three replications with ±SEM, and ** stands significance at P <0.01. For the rhlA fusion, primers were designed from 27 bp upstream and 103 bp downstream of the start codon ( Supplementary Figure S5 ). Fluorescence microscopy showed a notable increase in the translation efficiency of rhlA when srbA sRNA was present ( Figure 7A ). This observation was further confirmed by fluorescence reporter assay, which showed a ~3.7-fold increase in fluorescence intensity when pUCP30T- rhlA -eCFP was co-transformed with pUCP18- srbA + in comparison with the empty vector control ( Figure 7B ). Bioinformatics analysis was explored to find the possible RNA–RNA interactions and the stability of the secondary structures involved. The analysis predicted that the ribosome binding site, SD sequence, and start codon of rhlA formed a highly structured region with intramolecular base pairing, which could hinder ribosome binding and translation initiation. However, when srbA sRNA binds to rhlA RNA, a more stable RNA duplex structure forms, positioning the SD sequence and start codon in a way that facilitates ribosome binding ( Figure 7C ). The results indicate that srbA sRNA enhance the expression of the rhlA transcript likely by promoting ribosome binding and increasing its translation efficiency. ( A ) Fluorescence micrographs and bright field images of E. coli DH5α cells co-transformed with pUCP30T- rhlA -eCFP and either pUCP18 (EV) or pUCP18-SrbA + and ( B ) fluorescence intensity of the respective cell suspensions. ( C ) Bioinformatics-derived secondary structures of rhlA mRNA (1–75 bp) alone and the duplex secondary structure of rhlA mRNA (1–75 bp), and srbA sRNA (1–85 bp) for visualizing the probable effect of RNA–RNA interaction on the stability of the secondary structure and rhlA mRNA translation. Values are the mean of three replications with ±SEM, and ** stands significance at P <0.01. For the rsmA fusion, forward and reverse primers were designed from 41 bp upstream and 91 bp downstream of the start codon, respectively ( Supplementary Figure S6 ). Fluorescence microscopy indicated a substantial decrease in the translation efficiency of rsmA when srbA sRNA was present ( Figure 8A ). This was further validated by fluorescence reporter assay, which showed a ~2.4-fold reduction in fluorescence intensity when pUCP30T- rsmA -eCFP was co-transformed with pUCP18- srbA + in comparison with the empty vector control ( Figure 8B ). Further bioinformatics analysis was investigated to find possible RNA–RNA interactions and secondary structure stability for rsmA . The analysis revealed that, under normal conditions, the ribosome binding site, SD sequence, and start codon of rsmA are well-positioned for ribosome binding and translation initiation. However, when srbA sRNA binds to rsmA RNA, a more stable RNA duplex structure forms, negating ribosome binding through intermolecular base pairing, which likely results to the decrease of rsmA translation in the presence of srbA sRNA ( Figure 8C ). The finding suggests that srbA sRNA may down-regulate rsmA transcript expression probably by preventing ribosome binding, leading to reduced translation. ( A ) Fluorescence micrographs and bright field images of E. coli DH5α cells co-transformed with pUCP30T- rsmA -eCFP and either pUCP18 (EV) or pUCP18-SrbA + and ( B ) fluorescence intensity of the respective cell suspensions. ( C ) Bioinformatics-derived secondary structures of rsmA mRNA (1–75 bp) alone and the duplex secondary structure of rsmA mRNA (1–75 bp), and srbA sRNA (31–132 bp) for visualizing the probable effect of RNA–RNA interaction on the stability of the secondary structure and rsmA mRNA translation. Values are the mean of three replications with ±SEM, and *** stands significance at P < 0.001.

With the alarming emergence of multidrug-resistant P. aeruginosa strains and its versatile adaptability, understanding the regulatory network that allows this bacterium to adapt and thrive in diverse environments is crucial for combating infections. Approximately one tenth of P. aeruginosa genome is dedicated for encoding different transcriptional modulators, along with abundant sRNAs dispersed throughout its genome. In many cases, sRNAs exert their influence through base-pairing with target mRNAs, thus modulate the expressions of the genes. This interaction may occur either in untranslated regulatory regions or coding regions of the mRNA, thereby activating or repressing the translation [ 43–45 ]. The regulatory role of sRNAs in controlling stress adaptation and virulence is well established in P. aeruginosa [ 32 , 33 , 46–48 ]. A sophisticated regulatory machinery, operating via transcriptional, post-transcriptional, and post-translational courses in response to the environmental and host-derived signals through the QS system, modulates adaptability, biofilm formation, motility, and pathogenicity of P. aeruginosa [ 5 , 8 , 10 , 49–52 ]. Understanding these genetic regulatory mechanisms is essential for addressing the molecular basis of pathogenicity and developing strategies to combat the opportunistic infections caused by P. aeruginosa . The srbA sRNA was earlier documented to be up-regulated at the stationary growth phase and biofilm state of P. aeruginosa PA14, though its exact molecular regulatory role in biofilm formation remained unclear yet [ 37 ]. In this study, srbA was found to be up-regulated during biofilm and colony biofilm growth phases in P. aeruginosa PAO1 strains, suggesting its involvement in the development of biofilm. The differences in srbA expression levels observed among the planktonic, substratum-attached biofilm, and colony biofilm states in either SrbA + or ΔSrbApSrbA are intriguing, even though the srbA is overexpressed from the same plasmid ( Figure 1B ). Generally, various factors collectively affect the overall expression profile of genes, be it on bacterial chromosomes or plasmids, depending on their growth conditions. Alteration in critical or limiting factors under different growth conditions may regulate the copy number of srbA through various mechanisms, such as plasmid copy number, promoter activity, and RNA stability. The regulatory role of srbA in biofilm development was further investigated using srbA deletion and overexpression strains. The results revealed that srbA overexpression enhanced biofilm formation, while its deletion reduced biofilm development. The study of colony morphology revealed that the SrbA + colonies exhibited a higher density of EPS, whereas the ∆SrbA colonies displayed a distinct morphology, characterized by a smaller colony diameter and reduced quantity of EPS ( Figure 2E ). This observation aligns with earlier findings on the role of srbA in regulating motility in P. aeruginosa [ 33 ]. Earlier studies on MacS sRNA of E. coli suggested its regulatory role on biofilm formation by controlling bacterial motility and polysaccharide production [ 50 ]. Similarly, in P. aeruginosa , RsmZ and RsmY sRNAs stimulate biofilm formation by inhibiting RsmA activity [ 34 , 53 ], while ErsA regulates biofilm formation by modulating AmrZ at the post-transcriptional level [ 46 ]. Additionally, PA0730.1 sRNA has been reported to regulate biofilm formation through its control over the mucA and rpoS genes in P. aeruginosa [ 32 ]. These findings suggest that srbA might also target specific genes to play diverse roles in biofilm development. AlgU is a critical σ-factor that regulates the expression of numerous genes involved in survival of P. aeruginosa under diverse environmental situations and the production of various virulence factors [ 54 ]. AlgU has an autoregulatory function through its interaction with anti-sigma factor MucA and controls the production of biofilm architectural components, particularly alginate [ 55 ]. MucA is responsible for regulating the mucoid phenotype often associated with chronic lung infections caused by P. aeruginosa [ 21 , 56 , 57 ]. Both algU and mucA are components of the same operon (algUmucABCD), which is transcribed from shared promoters (P1–P5) under the regulatory control of the sigma factor AlgT/U [ 58 , 59 ]. The differential effects of srbA on the transcript levels of algU and mucA suggest that its regulatory role is more likely to occur at a post-transcriptional level, rather than at the transcriptional level. It seems that the observed differences may arise from selective modulation of mRNA stability or processing by srbA . Overexpression of srbA resulted in increased expression of algU , which may explain the enhanced biofilm formation observed in srbA overexpression strains. Furthermore, a significant reduction in mucA translation was detected in strains with higher srbA copy numbers, leading to increased levels of active AlgU. Thus, the combined positive regulation of algU and negative regulation of mucA by srbA likely contributes to its role in biofilm formation by P. aeruginosa . Furthermore, an increase in AlgU levels coupled with a decrease in MucA levels is expected to lead to enhanced mucoid phenotype, which correlates with the findings from the alginate production and colony morphological nature ( Figure 2D and E ). In P. aeruginosa , rhamnolipid production is crucial for maintaining biofilm structure, as it modulates the biofilm surface properties and facilitates microcolony formation [ 8 ]. The enzyme RhlA, which plays a key role in rhamnolipid biosynthesis, is modulated by the Rhl system [ 24 ]. Overexpression of srbA leads to increased expression of rhlA at both the transcriptional and translational levels, which likely explains the enhanced biofilm formation observed in srbA overexpressing strains. Additionally, SrbA + strains were found to produce higher levels of rhamnolipids than WT P. aeruginosa , both in nutrient-rich and nutrient-limited conditions [ 33 ]. Increased rhamnolipid production also correlates with the previous findings on enhanced swarming motility of SrbA + strain [ 33 ]. RsmA, a critical regulator in P. aeruginosa , is part of the CsrA family of RNA-binding proteins and has been shown to control virulence, motility, biofilm formation, and metabolism by interacting with target mRNAs [ 27–29 ]. RsmA inhibits biofilm formation by suppressing the production of EPS such as Psl and Pel, key components of the biofilm matrix, and modulates flagellar motility, promoting bacterial dispersal [ 29 , 60 ]. In srbA overexpressing strains, rsmA expression was reduced at both the transcriptional and translational levels, contributing to the enhanced biofilm formation in these strains. Moreover, changes in rsmA levels could affect virulence traits, which corroborates with previous observations on the role of srbA in regulating the synthesis of various virulence factors in P. aeruginosa [ 33 ]. These findings have unveiled the pivotal role srbA as a modulator of various genes, such as algU , mucA , rhlA , and rsmA , involved in regulatory network for biofilm development in P. aeruginosa ( Figure 9 ). However, to verify a direct interaction, nucleotide substitutions should be performed both in the sRNA and the predicted mRNA interaction region. The functional intricacy of sRNA is seemed to be greater than previously thought about, and it warrants in-depth genetic and structural analyses to understand such regulatory networks controlled by srbA , especially in host-pathogen interactions. The outcome of this study suggests srbA as a promising drug target and to develop oligonucleotide-based therapeutic strategies for combating the threat of multidrug-resistant P. aeruginosa .