Overexpression of

Abstract

Objective

Biofilm formation and adhesion are important indicators for evaluating the beneficial effects of probiotics. However, the relationship of specific genes with the biofilm formation and adhesion of Lactiplantibacillus remains unclear. The rbk gene encodes ribokinase, which is involved in ribose metabolism and may be related to biofilm formation and adhesion. This study aims to analyze the effects of rbk overexpression on the biofilm formation and adhesion of Lactiplantibacillus paraplantrum LR-1, explore the role of this gene in the regulation of quorum sensing (QS) and expression of related genes, and reveal the influencing mechanism of rbk overexpression in bacteria from a metabolic profile perspective.

Methods

L. paraplantarum LR-1 was selected as the target strain, and the shuttle vector pMG76e was used to construct the recombinant strain rbk-pMG76e-LR-1. The overexpression of rbk was confirmed by qRT-PCR and the enzyme activity assay. Crystal violet staining, cell adhesion assay, and qRT-PCR were employed to evaluate the effects of rbk overexpression on biofilm formation, adhesion, and expression of tuf, luxS, and rpoN. Furthermore, untargeted metabolomics analysis was conducted to assess the effect of rbk overexpression on the metabolic profile. Finally, the effect on the biofilm formation and adhesion of LR-1 was verified by exogenous addition of metabolites.

Results

The overexpression of rbk increased the biofilm formation of LR-1 and the adhesion to HT-29 cells by 1.55-2.34 folds and 3.58 folds, respectively. Moreover, the overexpression of rbk up-regulated the expression levels of tuf, luxS, and rpoN by 70.30, 96.94, and 45.61 folds, respectively. The untargeted metabolomics analysis revealed that rbk overexpression led to changes in the abundance of 145 metabolites. Finally, the exogenous addition of l-proline, rhamnose, and nicotinamide adenine dinucleotide (NADH) increased the biofilm formation of LR-1 by 1.27, 1.39, and 1.25 folds and the adhesion by 1.40, 1.41, and 1.52 folds, respectively.

Conclusion

This study demonstrates that rbk can serve as a key target for enhancing the biofilm formation and adhesion of Lactiplantibacillus.

Keywords

Lactiplantibacillus; rbk overexpression; biofilm; adhesion; untargeted metabolomics

Lactic acid bacteria (LAB), especially the species of genus Lactobacillus, have recently received attention because of their generally recognized as safe (GRAS) status and their potential health-promoting effects as probiotics^[1]. As probiotics, Lactobacillus plays an important role in maintaining gut microbiota balance, promoting intestinal health, preventing diarrhea and alleviating colitis symptoms, etc^[2]. An important criterion for probiotics is their ability to withstand unfavorable conditions in the gastrointestinal tract and their capacity to adhere and colonize the intestinal mucosa^[1]. In natural environments, many bacteria including LAB can form biofilms to resist adverse external conditions. And in the host’s intestine, the formation of biofilms on the intestinal mucosal epithelial cells allows bacteria to better withstand the cleansing actions caused by intestinal peristalsis and the flushing of intestinal fluids^[3]. Currently, one of the latest probiotic formulation technologies involves preparing probiotics in the form of biofilms to withstand environmental stresses during production and digestion^[4]. Therefore, exploring the key genes associated with biofilm formation in probiotic LAB is of significant importance. Currently, research into the molecular mechanisms of biofilm formation in pathogenic bacteria has progressed significantly; however, studies related to Lactobacillus are still quite limited. It is still very necessary to explore the relationships between specific genes in Lactobacillus and biofilm formation.

Our previous research has identified a series of genes that may be associated with quorum sensing (QS) and biofilm formation in Lactobacillus, including the rbk gene. The enzyme encoded by the rbk gene is ribokinase, which has the fundamental physiological function of degrading d-ribose and ATP to produce ribose-5-phosphate and ADP. The substrate, ribose, has no toxic effects and has structural similarity with autoinducer 2 (AI-2). It is the signal molecules of the LuxS/AI-2 quorum sensing system^[5]. This structural similarity allows the AI-2 receptor to bind with ribose, meaning that the presence of ribose could competitively bind to the AI-2 receptor, thereby blocking the downstream signaling pathways regulating QS-related physiological behaviors, such as biofilm formation^[6]. In addition, ribose, a common monosaccharide in the environment, could present a carbon source for gastrointestinal microbiota components^[7]. And ribose could be used to synthesize nucleotides and amino acids (histidine and tryptophan) and is also an essential energy source^[8]. Among them, purine nucleotide synthesis is related to biofilm formation in Lactobacillus^[9], and l-histidine metabolism has been reported to trigger the biofilm formation of A. baumannii^[10]. Therefore, changes in ribose metabolism can influence bacterial physiological behavior from multiple dimensions, potentially including the physiological behaviors of individual cells as well as those of cell populations, such as biofilm formation and adhesion colonization.

This study selects Lactiplantibacillus paraplantarum LR-1 as the research subject, which is originally isolated from fermented vegetables. This strain has probiotic properties, such as alleviating colitis^[11]. In this study, the rbk gene was recombined with the pMG76e shuttle vector and then introduced into the L. paraplantarum LR-1 strain. The effects of the introduction and overexpression of this gene on the growth and biofilm formation were measured, as well as its influence on the expression of biofilm and QS-related genes tuf, rpoN and luxS. Additionally, the overall metabolic impact of the introduction and overexpression of the rbk gene on the bacterial cells was further assessed through untargeted metabolomics. This study is valuable for understanding the relationship between the rbk gene and the physiological behaviors and metabolism of Lactobacillus.

1 Materials and Methods

1.1 Bacterial strains, cells, and culture conditions

The strain used in this experiment was L. paraplantarum LR-1 (CICC 24809), isolated from Sichuan pickles. The strain was cultured in de Man-Rogosa-Sharpe (MRS) broth (Beijing Land Bridge Technology Co., Ltd.) or MRS-Agar under aerobic conditions at a temperature of 37 ℃. Escherichia coli (E. coli) DH5α (TaKaRa Biotechnology (Dalian) Co., Ltd.) was cultured in Lennox broth (LB) or LB agar under aerobic conditions at a temperature of 37 ℃. E. coli DH5α containing pMG76e vector and L. paraplantarum LR-1 containing pMG76e vector were cultured in LB medium containing 200 μg/mL of erythromycin and in MRS medium containing 3 μg/mL of erythromycin, respectively.

The HT-29 cells were purchased from the American Type Culture Collection (ATCC). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Amresco) containing 10% (V/V) fetal bovine serum (Zhejiang TianHang Biotechnology Co., Ltd.), 1% dual antibodies (penicillin (100 IU/mL, ThermoFisher Scientific) and streptomycin (100 μg/mL, ThermoFisher Scientific)) at 37 ℃ in an atmosphere of 5% CO₂/95% air at constant humidity.

1.2 Construction of plasmids and bacterial strains

The chromosomal DNA of L. paraplantarum LR-1 was extracted using a TIANamp Bacteria DNA Kit (Tiangen Biotech (Beijing) Co., Ltd.) according to the manufacturer’s instructions. Using the genomic DNA as template, the rbk gene was amplified by PCR with primers containing Xba I and Xho I restriction sites (Table 1). The PCR-amplified rbk gene fragment was ligated with the pMD-18T vector (TaKaRa Biotechnology (Dalian) Co., Ltd.) and then introduced into the competent E. coli DH5α cells (TaKaRa Bio technology (Dalian) Co., Ltd.) for amplification. Next, the rbk-pMD-18T recombinant plasmid was double-digested with Xba I and Xho I (ThermoFisher Scientific) to obtain the rbk gene fragment, which was then ligated with the similarly double-digested pMG76e using a Rapid DNA Ligation Kit (ThermoFisher Scientific) to construct the rbk-pMG76e recombinant vector.

Table 1  Primers for PCR in this study

Primers	Sequences (5′→3′)
rbk-1-F	TGCTCTAGAATGAATACGGTAACAGTG
rbk-1-R	CCGCTCGAG TTATTTACCCTCCGCGGC

The competent cells of L. paraplantarum LR-1 were prepared as follows. Briefly, the LR-1 strain was inoculated into MRSS medium (MRS medium containing 0.3 mol/L sucrose) containing 1% glycine and cultured until the OD₆₀₀ reached between 0.4 and 0.6. A 10 mL aliquot of the culture was then centrifuged at 6 000 r/min for 8 min at 4 ℃ to collect the cells. The pellet was resuspended in 2 mL of washing buffer (0.3 mol/L sucrose with 0.1 mol/L MgCl₂) and centrifuged again at 6 000 r/min for 8 min at 4 ℃. Finally, the cells were resuspended in 2 mL of 30% PEG-1500 and centrifuged at 6 000 r/min for 10 min. The final pellet was resuspended in 200 μL of 30% PEG-1500 and kept on ice for further use. The recombinant plasmid rbk-pMG76e was introduced into the competent LR-1 cells by electroporation under the conditions of 1.5 kV and 400 Ω. After the electroporation, the cells were allowed to rest on ice for 5 min before adding 1 mL of MRSSM medium (MRS containing 0.3 mol/L sucrose and 0.1 mol/L MgCl₂) and incubating at 37 ℃ for 2 h. The cells were then spread on MRS plates containing 3 μg/mL of erythromycin and incubated at 37 ℃ for 36-48 h. Positive clones were selected and identified by PCR, confirming the presence of the rbk-pMG76e recombinant strain.

1.3 Real-time quantitative PCR (qRT-PCR)

The strain containing the empty vector pMG76e (pMG76e-LR-1), the recombinant strain with the plasmid rbk-pMG76e (rbk-pMG76e-LR-1), and the wild-type strain LR-1 were cultured overnight at 37 ℃ in MRS medium. Total RNA was extracted using TRIzol Agent (ThermoFisher Scientific) according to the manufacturer’s instructions. The RNA quality was assessed using the A₂₆₀/A₂₈₀ and A₂₆₀/A₂₃₀ ratios. The extracted RNA was converted into cDNA using a TUREscript 1st Strand cDNA Synthesis Kit (Aidlab Biotechnologies Co., Ltd.). The expression levels of the genes rbk, tuf, luxS and rpoN were determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The 16S rRNA gene was used as the reference gene. The primers for the relevant genes (Table 2) were designed using the Primer 3 input online tool (https://primer3.ut.ee/). The relative expression levels of the genes were calculated using the 2^-ΔΔCt method, as described by Livak and Schmittgen^[12].

Table 2  Primers for qRT-PCR in this study

Primers	Sequences (5′→3′)
rbk-2-F	AGGTCCCCGCTGAACTTTTA
rbk-2-R	CACCAGCTGACGTTGTATCG
tuf-F	CGCAACTGATGGTCCTATGC
tuf-R	CGCTGAACCACGGATAACAG
luxS-F	TGATACAGCGGGCTTACACA
luxS-R	CTTCCCACTTAGCTGGACCA
rpoN-F	CCAAGCAATTCGGGACTACG
rpoN-R	TTTCTTCTGCCCGGAGAACT
16S RNA-F	CAACGAGCGCAACCCTTATT
16S RNA-R	GCAGCCTACAATCCGAACTG

1.4 Ribokinase activity assay

The strains rbk-pMG76e-LR-1, pMG76e-LR-1 and the wild-type LR-1 were cultured in MRS without erythromycin for 8 h. The cells were centrifuged at 5 000×g at 4 ℃ for 5 min and washed three folds with PBS. The viable cell counts of the three strains were determined using the plate counting method and standardized. The bacterial cells were then disrupted by ultrasound at 4 ℃ for 20 min (4 s work+6 s break for 120 cycles). The lysed cells were centrifuged at 5 000×g at 4 ℃ for 20 min, and the supernatant was collected.

Ribokinase activity was measured using a Ribokinase (RBKS) Enzyme-linked Immunoassay Kit (Shanghai Jingkang Bioengineering Co., Ltd.) according to the manufacturer’s instructions. Samples were added into microtiter plate coated with purified ribokinase antibodies, and then combined with horseradish peroxidase (HRP)-labeled ribokinase antibodies to form an antibody-antigen-enzyme-labeled antibody complex, which is washed and then added into Tetramethylbenzidine (TMB) to initiate color development. Under the catalytic action of HRP enzyme, TMB will be converted into blue, and finally into yellow under the action of acid. The intensity of the color is directly proportional to the ribokinase concentration in the samples. And the ribokinase activity was quantified by measuring the absorbance at 450 nm and referencing a standard curve.

1.5 Growth curves

The recombinant rbk-pMG76e-LR-1, pMG76e-LR-1 strains and the wild-type LR-1 strain were cultured in MRS without erythromycin. The cell densities were determined at 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, and 36 h by measuring the OD₆₀₀ using a UV-1800 Spectrophotometer (Shimadzu).

1.6 Biofilm formation assay

The biofilm-forming ability of the strains rbk-pMG76e-LR-1, pMG76e-LR-1 and the wild-type LR-1 was determined using the crystal violet (CV) staining method^[6]. In brief, the initial OD₆₀₀ value of the three strains was adjusted to 0.1, and then they were inoculated into a 96-well cell culture plate (Corning Incorporated). After incubating at 37 ℃ for 48 h, the plate was gently washed with PBS, followed by staining with 0.1% CV for 30 min. The plate was then washed with sterile water and allowed to air dry. Finally, 100 μL of 95% ethanol was added to each well to dissolve the CV, and the absorbance at 595 nm was measured using a Synergy 2 Microplate Reader (Winooski). The strains rbk-pMG76e-LR-1, pMG76e-LR-1 and the wild-type LR-1 were cultured in MRS at pH 4.0, with 0.2% bile salt and 8.0% (W/V) NaCl at 37 ℃ for 48 h to form biofilms, and the biofilms were detected as described above.

1.7 Adhesion assay

HT-29 cells were cultured in a 24-well plates (Corning Incorporated) until a monolayer was formed, with approximately 2.5×10⁵ cells per well. The cells were then washed twice with PBS (pH 7.2). At the same time, after overnight culture, the strains rbk-pMG76e-LR-1, pMG76e-LR-1, and the wild-type LR-1 were collected by centrifugation (5 000×g, 4 ℃, 10 min), washed twice with PBS, and resuspended in DMEM at a final concentration of 1×10⁸ CFU/mL. Subsequently, 100 μL of the bacterial suspension was added to each well of the 24-well plate to co-culture with HT-29 cells, at a bacteria-to-cell ratio of 10⁷:2.5×10⁵, and incubated at 37 ℃ for 1.5 h. After the incubation, the plate was washed twice with PBS to remove non-adherent bacteria. Then, Triton X-100 was used to dissociate the adhered bacteria. The adhesion rate was calculated using the formula (1)^[13].

Adhesion ratio=Bacterial counts after adhesion/Bacterial counts before adhesion×100%

(1)

1.8 Untargeted metabolomics analysis

1.8.1 Sample extraction

The rbk-pMG76e-LR-1 and pMG76e-LR-1 strains were cultured in MRS without erythromycin for 8 h. Afterwards, the cells were collected by centrifugation at 5 000×g for 5 min at 4 ℃. Then, 60 mg of each sample was resuspended in 200 μL of water and mixed thoroughly for 60 s. Then, 800 μL of extraction solvent (methanol:acetonitrile=1:1) was added, and the mixture was homogenized for 60 s. This was followed by ultrasound treatment in ice-water for 30 min, which was repeated twice. The samples were then stored at -20 ℃ for 1 h to allow protein precipitation, followed by centrifugation at 12 000×g for 20 min at 4 ℃. The supernatant was dried using a vacuum concentrator and subsequently stored at -80 ℃.

1.8.2 Mass spectrometry

The analyses were performed using UHPLC (Agilent Technologies) coupled with a quadrupole time-of-flight (Sciex) at Shanghai Applied Protein Technology Co., Ltd. For HILIC separation, the samples were analyzed using a 2.1 mm×100 mm ACQUIY UPLC BEH 1.7 µm column (Waters Corporation). In both ESI positive and negative modes, the mobile phase consisted of A: 25 mmol/L ammonium acetate and 25 mmol/L ammonium hydroxide in water, and B: acetonitrile. For RPLC separation, a 2.1 mm×100 mm ACQUIY UPLC HSS T3 1.8 µm column (Waters Corporation) was utilized. In ESI positive mode, the mobile phase comprised A: water with 0.1% formic acid and B: acetonitrile with 0.1% formic acid. In ESI negative mode, the mobile phase consisted of A: 0.5 mmol/L ammonium fluoride in water and B: acetonitrile. For MS/MS analysis, the ESI source conditions were set as follows: Ion Source Gas1 (Gas1) as 60, Ion Source Gas2 (Gas2) as 60, curtain gas (CUR) as 30, source temperature: 600 ℃, and IonSpray Voltage Floating (ISVF)±5 500 V.

1.8.3 Data analysis

The raw MS data (wiff.scan files) were converted to MzXML files using ProteoWizard MS Convert v3.0.6458 before importing into freely available XCMS software. After normalizing total peak intensity, the processed data were uploaded into SIMCA-P (v14.1), where they underwent multivariate data analysis, including Pareto-scaled principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA). Metabolites with variable importance for the projection (VIP) value>1 were further analyzed for significance, with a threshold of P<0.05 was considered statistically significant.

1.8.4 Bioinformatic analysis

The metabolites were matched against the online Kyoto encyclopedia of genes and genomes (KEGG) database (http://geneontology.org/). KEGG pathway enrichment analyses were conducted using Fisher’s exact test, with pathways yielding a P-value less than 0.05 considered significant. The relative expression data of the analyzed metabolites were utilized to perform hierarchical clustering analysis using Cluster 3.0 (http://bonsai.hgc.jp/~ mdehoon/software/cluster/software.htm).

1.9 Evaluation of the effects of exogenous metabolites on biofilm formation and adhesion of LR-1

Based on the metabolomic analysis results, this experiment selected 8 metabolites related to bacterial biofilm formation and adhesion. These include l-histine, l-proline, l-arginine, l-serine (Solarbio), Rhamnose, N-acetyl-d-lactosamine, NADH (Shandong Sparkjade Biotechnology Co., Ltd.), and d-mannose-6-phosphate (Rhawn). Solutions of these metabolites were prepared at a concentration of 50 mg/mL, and the pH was adjusted to neutral.

The CV staining method was used to assess the impact of the aforementioned 8 metabolites on the biofilm formation of LR-1. Briefly, the bacterial suspension was adjusted to an OD₆₀₀ of 0.1 and inoculated into 96-well cell culture plates with 100 μL per well. Subsequently, 100 μL of the metabolites solution diluted with MRS broth was added, resulting in a final concentration of 100 mg/mL. After incubation at 37 ℃ for 48 h, the biofilms were detected as aforementioned in section 1.6.

The adhesion experiment set up two treatment methods: one involved culturing LR-1 with exogenous metabolites before extracting the bacterial cells and co-culturing them with HT-29 cells, referred to as the met-LR-1-post-LR-1 group. The other method involved simultaneous co-culturing of exogenous metabolites, LR-1, and HT-29 cells, referred to as the met-LR-1-HT-29 group. The specific procedure for the met-LR-1-post-LR-1 group was as follows: 8 exogenous metabolites were added to fresh LR-1 bacterial suspension to achieve a final concentration of 10 mg/mL, with a bacterial concentration of 10⁸ CFU/mL. After incubating at 37 ℃ for 9 h, the bacteria were collected by centrifugation, and the bacterial suspension was adjusted to a concentration of 10⁸ CFU/mL before co-culturing with HT-29 cells in 24-well plates, maintaining a bacteria to cell ratio of 10⁷:2.5×10⁵. For the met-LR-1-HT-29 group, the procedure involved simultaneous co-culturing of bacteria, cells, and exogenous metabolites, with the final concentration of metabolites also set at 10 mg/mL and a bacteria to cell ratio of 10⁷:2.5×10⁵. The co-culturing time was 1.5 h, after which the adhesion rate was calculated, following the same method as described in section 1.7.

1.10 Statistical analysis

Significant differences were determined using analysis of variance (ANOVA) in R (v4.1.1). Data are presented as mean±standard deviation (SD). P-values less than 0.05 were considered significant, with *** representing P<0.001, ** representing P<0.01, * representing P<0.05, and ns indicating no significance. Each experiment was conducted in triplicate, with each test involving at least three separate measurements. In the case of untargeted metabolomics analysis, six samples were analyzed. The relationships between significantly different metabolites and the phenotype of strains were calculated using the Pearson correlation coefficient with the OmicShare tools, a free online platform for data analysis (http://www.omicshare.com/tools). Cytoscape (v3.8.2) was employed to visualize the interaction networks among the significantly different metabolites and the phenotype of the strains.

2 Results and Discussion

2.1 The successful construction of the recombinant strain rbk-pMG76e-LR-1 with overexpression of the rbk gene

The PCR identification results of strains containing the recombinant plasmids rbk-pMG76e and pMG76e are shown in Figure 1A-1B. The results indicate that the plasmids rbk-pMG76e and pMG76e were successfully introduced into LR-1 bacterial cells. Furthermore, the qRT-PCR results indicated that, as shown in Figure 1C, the introduction of plasmid pMG76e did not affect the expression of the rbk gene. In contrast, the introduction of the recombinant plasmid rbk-pMG76e significantly increased the expression of the rbk gene in LR-1, with an enhancement of 359.81 folds (P<0.001). The ribokinase enzyme activity assay similarly indicated that the introduction of the pMG76e plasmid did not affect the ribokinase activity of the LR-1 bacterial cells. However, the introduction of the recombinant plasmid rbk-pMG76e resulted in a 1.33 folds increase in ribokinase activity in the bacterial cells (Figure 1D, P<0.01). The growth experiments, as shown in Figure 1E, showed that the introduction of both pMG76e and rbk-pMG76e did not significantly affect the growth of LR-1.

Figure 1  The rbk gene was successfully overexpressed in LR-1. PCR validation of the rbk-pMG76e-LR-1 (A) and pMG76e-LR-1 (B) recombinant strains. Detection of the rbk gene transcriptional levels (C), ribokinase activity (D) and growth curves (E) in LR-1 (wild-type), pMG76e-LR-1, and rbk-pMG76e-LR-1 strains. The data obtained from three separate experiments are presented as mean±SD. ***: P<0.001; **: P<0.01; ns: No significant.

The rbk gene encodes ribokinase and is involved in the phosphorylation metabolic process of ribose^[6,14]. When ribose is present in the external environment, the rbk gene responds accordingly^[6]. This study demonstrates that the expression level of the intracellular rbk gene and the corresponding enzyme activity can be enhanced through the introduction of an exogenous recombinant plasmid. Additionally, although the introduction of plasmids pMG76e and rbk-pMG76e did not affect the maximum growth concentration of LR-1, it slightly influenced the early growth rate of the cells. This may be attributed to damage caused during the preparation of competent cells or the electroporation process, which could affect intracellular metabolism. However, these effects are likely to be mitigated as bacterial growth progresses.

2.2 The overexpression of the rbk gene enhanced the biofilm formation and adhesion capabilities of the LR-1 strain

The biofilm formation results are illustrated in Figure 2A-2D. The introduction of pMG76e did not affect the biofilm formation of LR-1. However, the overexpression of the rbk gene significantly enhanced the biofilm formation ability of LR-1. Under normal culture conditions, the biofilm formation of rbk-pMG76e-LR-1 increased to approximately 1.55 folds (Figure 2A). The enhancement of biofilm formation was even more pronounced under stress conditions. Under stress conditions of pH 4.0, 0.2% bile salt, and high salt, the overexpression of rbk increased the biofilm formation of the LR-1 strain to about 1.88, 2.34 and 1.62 folds, respectively. Additionally, the introduction of the pMG76e plasmid did not affect the adhesion ability of the LR-1 strain, while the introduction of the rbk-pMG76e plasmid increased the strain’s adhesion to HT-29 cells to approximately 3.58 folds (Figure 2E).

Figure 2  The overexpression of the rbk gene enhanced the biofilm formation and adhesion abilities of the LR-1 strain. The biofilm formation of LR-1, pMG76e-LR-1, and rbk-pMG76e-LR-1 in MRS (A), MRS with pH 4.0 (B), MRS with 0.2% (W/V) bile salt (C), and MRS with 8.0% (W/V) NaCl (D). The adhesion of the three strains to HT-29 cells (E). The data obtained from three separate experiments are presented as mean±SD. **: P<0.01; *: P<0.05; ns: No significant.

Bacteria in a biofilm state possess a stronger ability to resist adverse external environments^[4,6,14]. Therefore, developing biofilm-forming probiotics is currently one of the important research directions for next-generation probiotic formulations^[15-16]. This study suggests that the rbk gene can serve as a key target for enhancing the expression level to improve the biofilm formation ability of Lactobacillus. Additionally, the formation of biofilms by bacteria is a response mechanism to adverse external environments^[3]. The results of this study indicate that enhancing the expression of the rbk gene can effectively increase the biofilm formation ability of Lactobacillus under common stress environments experienced probiotics. Furthermore, adhesion ability is one of the most critical indicators for evaluating the health benefits of probiotics, which is often positively correlated with biofilm formation ability^[3]. This study demonstrates that the rbk gene can be a target for enhancing the adhesion ability of Lactobacillus. Although research on the relationship between the rbk gene and bacterial physiological phenotypes, especially probiotics, is still lacking, this study highlights rbk as a potential target for enhancing the probiotic effects of Lactobacillus, representing a significant addition to related research.

2.3 The overexpression of the rbk gene upregulated the expression of tuf, luxS and rpoN genes in the LR-1 strain

Our previous research has identified the tuf, luxS and rpoN genes as three genes closely related to biofilm formation in Lactobacillus^[6,13]. In this study, the effect of rbk gene overexpression on the expression levels of these three genes is shown in Figure 3. The results indicate that the introduction of the pMG76e plasmid had no significant impact on the expression levels of tuf, luxS and rpoN in the LR-1 strain. However, the introduction of the rbk-pMG76e recombinant plasmid significantly increased the expression levels of the aforementioned three genes. Overexpression of the rbk gene led to an approximate upregulation of the expression levels of tuf, luxS, and rpoN to about 70.30, 96.94 and 45.61 folds, respectively.

Figure 3  The overexpression of rbk in LR-1 upregulates the expression of tuf, luxS, and rpoN genes. The data obtained from three separate experiments are presented as mean±SD. ***: P<0.001; **: P<0.01; ns: No significant.

The tuf, luxS and rpoN genes are three genes that we previously identified through high-throughput screening and preliminary validation to have a significant positive correlation with biofilm formation in Lactobacillus^[6]. The tuf gene encodes the elongation factor EF-Tu, which is a protein responsible for peptide chain elongation and protein folding, and it is also associated with stress resistance^[17]. Additionally, EF-Tu has been found to be an adhesion-related factor in Lactobacillus acidophilus, Lactobacillus plantarum, and Lactobacillus johnsonii^[18-19]. The luxS gene encodes the LuxS protein, which is involved in methionine metabolism. In this process, LuxS converts S-adenosylhomocysteine (SAH) into S-ribosylhomocysteine (SRH) while generating a byproduct^[20]. This byproduct is the signaling molecule AI-2, which in involved in QS of both Gram-positive and Gram-negative bacteria^[20]. QS participates in various social behaviors of bacteria, including Lactobacillus, such as biofilm formation and adhesion^[20]. Therefore, the expression level of luxS can influence the biofilm formation and adhesion abilities of the LR-1 strain. The rpoN gene encodes the σ54 factor, which is involved in various physiological processes, including carbon source metabolism, detoxification system control, and extracellular alginate production^[21]. In Vibrio fischeri, the σ54 factor regulates the expression of the syp gene cluster, which is associated with polysaccharide production, biofilm formation, and adhesion^[22]. Additionally, σ54 has also been found to regulate biofilm formation and adhesion in Bacillus cereus, Enterococcus faecalis, and Escherichia coli K12^[23-25]. In conclusion, tuf, luxS and rpoN are all multifunctional moonlighting genes that have been associated with biofilm formation and other critical physiological behaviors in various strains. Moreover, our previous research has confirmed that they are key genes regulating biofilm formation and other phenotypes in Lactobacillus. In this study, the overexpression of the rbk gene significantly enhanced their expression levels. These results suggest that the rbk gene may positively regulate biofilm formation and adhesion abilities of the LR-1 strain by upregulating the expression of these key moonlighting genes. However, the hierarchical relationships between the rbk gene and these genes, both upstream and downstream, are not clearly established and require further research for in-depth analysis.

2.4 The effect of rbk overexpression on the metabolic profile of the LR-1 strain

This study employed PCA, PLS-DA, and OPLS-DA to conduct multivariate statistical analysis on the metabolites of rbk-pMG76e-LR-1 and pMG76e-LR-1, with the results shown in Figure 4A-4C. PCA is a straightforward non-parametric technique that projects complex metabolic data into a lower-dimensional space, allowing for the identification of potential relationships and uncovering intricate internal data structures^[26]. As illustrated in Figure 4A, the PCA results revealed a distinct variation between the two groups. The sum of the components (1 and 2) accounted for 71.60% of the total variance in the positive mode and 74.40% in the negative mode, respectively. PLS-DA is a well-established linear classification method that is effective for analyzing complex metabolic data sets^[27]. In the positive mode, the R² (X), R² (Y), and Q² values were 0.71, 0.99, 0.99, respectively, while in the negative mode, they were 0.74, 0.99, and 0.99 (Figure 4B). In contrast to PCA and PLS-DA, OPLS-DA can differentiate between predictive and non-predictive (orthogonal) changes^[28]. The R² (X), R² (Y), and Q² values of the OPLS-DA model were 0.71, 0.99, and 0.98 in the positive mode, and 0.74, 0.99, and 0.99 in the negative mode, as shown in Figure 4C. All three methods can be used for integrative analysis of metabolomic profiles of Lactobacillus samples. Lee and colleagues applied PCA and PLS-DA to analyze samples of Lactobacillus sakei at different growth stages based on their metabolites^[29]. Similarly, Tomita and others employed PCA and OPLS-DA to clearly distinguish the metabolic profile of vegetable juice samples fermented by various Lactobacillus strains^[30]. In this study, based on the differential metabolite data, all three analytical methods were able to distinguish between rbk-pMG76e-LR-1 and pMG76e-LR-1 samples, indicating that rbk overexpression significantly affected the metabolic profile LR-1.

Figure 4  The PCA (A), PLS-DA (B) and OPLS-DA (C) analysis of the metabolites from rbk-pMG76e-LR-1 and pMG76e-LR-1. POS: Positive ion model; NEG: Negative ion model.

The differential metabolites of the rbk-pMG76e-LR-1 and pMG76e-LR-1 samples are shown in Figure 5A-5B for positive and negative ion modes, respectively. In the positive ion mode, a total of 83 differential metabolites were detected, while in the negative ion mode, 78 differential metabolites were identified. Some substance fragments were detected in both ion modes, resulting in a total of 145 unique differential metabolites across both groups. Among them, the top five significantly upregulated differential metabolites due to rbk gene introduction were d-ribulose-5-phosphate (49.99 folds), l-rhamnose (28.66 folds), N-acetyl-d-lactosamine (26.19 folds), glutathione (GSH) (16.42 folds), and UDP-N-acetylmuraminate (16.21 folds). Conversely, the top five significantly downregulated differential metabolites were d-arabinono-1,4-lactone (0.06 folds), diaminopimelic acid (0.11 folds), l-gulonic-γ-lactone (0.12 folds), N₆-methyl-l-lysine (0.18 folds), and acetyl carnitine (0.20 folds) (Figure 5C).

Figure 5  The differential metabolites of the rbk-pMG76e-LR-1 and pMG76e-LR-1 samples. The heatmap analysis of significantly differential metabolites in rbk-pMG76e-LR-1 and pMG76e-LR-1 in the positive ion model (A) and in the negative ion model (B). The fold changes of the differential metabolites in rbk-pMG76e-LR-1 compared to pMG76e-LR-1 (C). POS: Positive ion model; NEG: Negative ion model.

This study further predicted the correlation between differential metabolites and phenotypes, with results shown in Figure 6. The predictive analysis indicates that a total of 112 differential metabolites exhibited strong correlations with the phenotypes assessed in this study (P<0.01, absolute value of the coefficient index>0.9), with 77 being positively correlated and 35 negatively correlated. Among these, the phenotype of biofilm formation was positively correlated with 42 differential metabolites and negatively correlated with 27 metabolites. The adhesion phenotype was positively correlated with 6 differential metabolites and negatively with 1 metabolite. The impact of rbk gene introduction on metabolites will be further analyzed and discussed in the following sections from a metabolic pathway perspective.

Figure 6  The Pearson correlation network diagram between differential metabolites and biofilm formation as well as adhesion is presented. The absolute value of correlation coefficient>0.9, P<0.01. Red circles represent differential metabolites that have a positive correlation with biofilm formation and adhesion, while green circles represent differential metabolites that are negatively correlated with these phenotypes. Blue circles indicate the phenotypes of biofilm formation and adhesion capacity. The larger the circle, the more associated substances it contains. Red lines indicate positive correlations, while green lines indicate negative correlations.

2.4.1 Central carbon metabolism changes

Among the 145 differential metabolites, 18 substances (12.41%) belong to the central carbon metabolism pathway, as shown in Figure 7. The analysis indicates that the introduction of the rbk gene leads to the downregulation of three substances: d-xylulose-5P, glycerone-P, and phosphoenolpyruvate, which were reduced to 0.79, 0.88 and 0.81 folds, respectively, while the remaining 15 substances were all upregulated. These differential metabolites are distributed across four carbon metabolic pathway: the Embden-Meyerhof-Parnas (EMP) pathway, the Entner-Doudoroff (ED) pathway, the hexose monophosphate (HMP) pathway, and the tricarboxylic acid (TCA) cycle^[31-33].

Figure 7  Changes in metabolites in the central carbon metabolism pathway following rbk gene introduction are highlighted. Metabolites with increased abundance are marked in red, while those with decreased abundance are marked in green. P: Phosphate; PRPP: 5-phospho-alpha-d-ribose 1-diphosphate.

In the EMP pathway, the introduction of the rbk gene results in the upregulation of α-d-glucose (2.05 folds), α-d-glucose-6P (3.80 folds), β-d-fructose-1,6P2 (2.43 folds), and glyceraldehyde-3P (3.28 folds). Additionally, these four substances are located upstream of the EMP pathway^[32], suggesting that rbk overexpression may enhance the strain LR-1’s ability to utilize the EMP pathway to convert glucose into glyceraldehyde-3P. In the ED pathway, 2-dehydro-3-deoxy-d-gluconate (4.33 folds) and glyceraldehyde-3P (3.28 folds) were found to be upregulated. Microorganism can convert glucose into pyruvate via the ED pathway in just four steps^[33]. These results indicate that rbk overexpressing strains can utilize the ED pathway, rather than the EMP pathway to convert glyceraldehyde-3P into pyruvate. Previous studies have shown that Campylobacter coli B13117 can enhance its environmental tolerance by altering its metabolism to utilize the ED pathway more extensively for the conversion of glucose into glucose-6P and fructose-6P^[33]. Furthermore, in the EMP pathway, the levels of d-mannose and d-glucose were upregulated in the rbk overexpressing strains. These two monomers are important precursor substances for the synthesis of extracellular polysaccharides. Their upregulation may accelerate the efficiency of extracellular polysaccharide synthesis (EPS), which is crucial for biofilm formation and adhesion capacity^[34-36].

In the HMP pathway, rbk overexpression led to a significant upregulation of d-ribulose-5P (49.99 folds), the most prominently upregulated metabolite among all the substances^[32]. The rbk gene is responsible for converting d-ribose to d-ribose-5P, which can then be transformed into d-ribulose-5P^[8,37]. Our results indicate that rbk overexpression enhances the strain LR-1’s ability to convert α-d-glucose-6P into d-ribulose-5P via the HMP pathway. Studies have shown that Lactiplantibacillus can enhance its environmental tolerance by altering its metabolic pathways^[38]. In this study, the overexpression of the rbk gene affects the central carbon metabolism pathway of LR-1, which may play a role in the alteration of the strain’s biofilm formation and adhesion capacity.

2.4.2 Amino acid metabolism changes

In the context of the 145 differential metabolites induced by rbk overexpression, 15 of these metabolites (10.34%) were identified to be located in the amino acid metabolism pathway, as shown in Figure 8. Among them, four amino acids were downregulated: phenylalanine decreased to 0.65 folds, l-leucine decreased to 0.79 folds, serine decreased to 0.25 folds, and threonine decreased to 0.62 folds. Conversely, 11 amino acids were upregulated: l-alanine increased to 1.26 folds, l-aspartate increased to 1.70 folds, l-histidine increased to 2.18 folds, S-adenosyl-l-methionine increased to 2.74 folds, proline increased to 4.04 folds, arginine increased to 3.31 folds, l-valine increased to 1.08 folds, tryptophan increased to 1.98 folds, S-adenosyl-4-aminobutanoate increased to 1.78 folds, acetyl-CoA increased to 2.53 folds, and succinate increased to 5.59 folds.

Figure 8  Changes in metabolites in the amino acid metabolism pathway following rbk gene introduction are highlighted. Metabolites with increased abundance are marked in red, while those with decreased abundance are marked in green. P: Phosphate.

The results indicate that the majority of amino acid levels increased in the rbk-pMG76e-LR-1 recombinant strain, suggesting that the overexpression of the rbk gene enhances amino acid metabolism. Given that amino acids are important biochemical precursors, the increased activity of amino acid metabolism may lead to significant changes in physiological phenotypes. For instance, previous studies have shown that L. plantarum can resist acid stress by upregulating the abundance of aspartate and arginine^[39]. In this study, both of these amino acids were significantly upregulated, which may explain why the rbk overexpressing strain exhibits a stronger biofilm formation in acidic conditions. Furthermore, other studies have found that arginine and proline significantly influence the adhesion ability of L. plantarum ATCC 14917^[40]. The upregulation of these two amino acids in this study may be related to the enhanced adhesion capacity of the rbk overexpressing strain. However, the specific relationships among them still require further investigation.

2.4.3 Energy metabolism changes

Figure 9 shows that out of the 145 different metabolites, 14 (9.66%) are associated with the energy metabolism pathway. In the rbk overexpressing strain, the levels of NADH, NAD⁺, succinate, and ADP increased to 6.02, 2.55, 5.59 and 2.19 folds, respectively, during oxidative phosphorylaiton. During methane metabolism, d-ribulose-5P increased dramatically (49.99 folds), while d-glyceraldehyde-3P (3.28 folds), d-fructose-1,6P2 (2.43 folds), and acetyl-CoA (2.53 folds) also showed significantly increases. However, glycerone-P (0.88 folds), l-serine (0.25 folds), and phosphoenolpyruvate (0.81 folds) decreased in the rbk-pMG76e-LR-1 strain. In the context of sulfur metabolism, only l-serine, PAP, and succinate were detected, with values of 0.25, 1.15 and 5.59 folds, respectively.

Figure 9  Changes in metabolites in the energy metabolism pathway following rbk gene introduction are highlighted. Metabolites with increased abundance are marked in red, while those with decreased abundance are marked in green. P: Phosphate; PAP: Adenosine 3′,5′-diphosphate.

The total NAD(H) plays a crucial role in whole-cell biochemical redox transformations^[37]. The rbk-pMG76e-LR-1 strain exhibited increases in both NAD(H) and its related products, including succinate and acetyl-CoA. Succinate participates in the conversion of fumarate to succinate, generating NAD⁺, while acetyl-CoA is involved in the conversion of pyruvate to acetyl-CoA, producing NADH. This suggests that the elevated levels of NAD(H) may stimulate related biochemical redox reactions, leading to the production of additional reaction products. Furthermore, rbk-pMG76e-LR-1 exhibited higher ADP content. The release of energy from ATP by breaking phosphate bonds, while simultaneously producing ADP, indicates that rbk overexpression results in enhanced energy metabolism and increased energy production.

These results suggest that energy metabolism is likely more active in the rbk-pMG76e-LR-1 strain. The biofilm formation is process is known to be energy-consuming, as the synthesis of the biofilm matrix requires significant metabolic resources^[41]. Therefore, the increased energy metabolism observed in rbk-pMG76e-LR-1 may enhance biofilm formation and improve environmental tolerance. Additionally, studies have shown that L. plantarum FS5-5 can withstand salt stress by boosting energy metabolism^[42].

2.4.4 Nucleotide metabolism changes

Figure 10 illustrates that out of the 145 different metabolites, 21 (14.48%) are linked to the nucleotide metabolism pathway. In this study, most metabolites associated with nucleotide metabolism exhibited higher abundance in the rbk-pMG76e-LR-1 strain. During purine metabolism, several metabolites increased significantly, including ADP-ribose (3.12 folds), GMP (2.56 folds), hypoxanthine (1.59 folds), AMP (1.23 folds), adenosine (4.13 folds), adenine (2.30 folds), and ADP (2.19 folds). In contrast, levels of FAD (0.39 folds), dGTP (0.79 folds), dAMP (0.44 folds), and deoxyadenosine (0.27 folds) decreased in rbk-pMG76e-LR-1. Previous research has indicated that the synthesis of purine nucleotide is positively correlated with biofilm formation^[9,42]. Therefore, it can be hypothesized that the increase in purine metabolites may contribute to enhanced biofilm formation in the rbk-pMG76e-LR-1 strain.

Figure 10  Changes in metabolites in the nucleotide metabolism pathway following rbk gene introduction are highlighted. Metabolites with increased abundance are marked in red, while those with decreased abundance are marked in green.

In terms of pyrimidine metabolism, metabolites such as uracil, UMP, cytosine, UDP, cytidine, and CMP increased to 1.41, 2.17, 1.08, 2.39, 6.83 and 1.27 folds, respectively, in the rbk-pMG76e-LR-1 recombinant strain. However, dihydrouracil, thymine, dTMP, and dTDP showed decreases of 0.36, 0.20, 0.41 and 0.68 folds, respectively. Notably, uracil has been reported to influence all three known QS pathways in Pseudomonas aeruginosa, and mutations related to uracil can disrupt biofilm formation by this strain^[41]. Thus, it is speculated that the increased level of uracil may promote biofilm development in rbk-pMG76e-LR-1.

2.4.5 Changes in other metabolites

Some metabolites were not clearly categorized within the previously mentioned pathways but are closely linked to biofilm formation and stress resistance. For instance, l-rhamnose increased to 28.66 folds in the rbk-pMG76e-LR-1 recombinant strain. This metabolite is considered crucial for the growth of Streptococcus mutans, and disruption in its biosynthesis can heighten the strain’s susceptibility to acid and oxidative stress^[43]. Additionally, other studies have indicated that l-rhamnose biosynthesis can positively stimulate biofilm formation in Listeria monocytogenes and Flavobacterium columnare^[44-45]. Therefore, it is hypothesized that the increased l-rhamnose levels in rbk-pMG76e-LR-1 promote both biofilm formation and stress resistance.

Moreover, several substances with potential health benefits were found to be elevated in the overexpressed rbk strain. Levels of γ-amino butyric acid (GABA), glutathione (GSH), and S-adenosyl methionine (SAM) increased to 1.78, 16.42 and 2.74 folds, respectively, in rbk-pMG76e-LR-1. GSH and SAM are recognized for their liver-protective properties, helping to prevent and treat various liver injuries and diseases^[46]. Additionally, GABA plays a vital role in the resistance of LAB to acidic and bile salt environments^[47-48]. The increases in these metabolites suggest that the overexpressed rbk strain enhances stress resistance and holds potential for improved health benefits.

2.5 Metabolites enhance the biofilm formation and adhesion ability of LR-1 strain

The influence of 8 metabolites on the biofilm formation ability of LR-1 strain is shown in Figure 11A. The biofilm formation ability of LR-1 strain treated with metabolites was slightly improved. l-proline, rhamnose and NADH significantly enhanced the biofilm formation ability of LR-1. l-proline increased by 1.27 folds, rhamnose increased by 1.39 folds, and NADH increased by 1.25 folds. However, other metabolites had no significant impact on its biofilm formation.

Figure 11  Effect of exogenously added metabolites on biofilm formation (A) and adhesion ability (B) of LR-1 strain. The data obtained from three separate experiments are presented as mean±SD. ****: P<0.000 1; ***: P<0.001; **: P<0.01; *: P<0.05; ns: No significant.

The LR-1 strains treated by two treatment methods were used for adhesion to HT-29 cells, and the results are shown in Figure11B. Compared with the control group, various metabolites all increased the adhesion ability of LR-1 to a certain extent, and the adhesion rate of bacteria in the met-LR-1-HT-29 group to HT-29 cells was higher than that of bacteria in the met-LR-1-post-LR-1 group. In the adhesion test of the met-LR-1-post-LR-1 group, d-mannose-6-phosphate significantly increased the adhesion ability of LR-1 (by about 1.30 folds), and other metabolites had no significant impact on the adhesion ability of LR-1. However, in the adhesion test of the met-LR-1-HT-29 group, l-proline, l-arginine, rhamnose, N-acetyl-d-lactosamine, d-mannose-6-phosphate, and NADH significantly increased the adhesion ability of LR-1. Proline increased by 1.40 folds, arginine increased by 1.33 folds, rhamnose increased by 1.41 folds, N-acetyl-d-lactosamine increased by 1.38 folds, d-mannose-6-phosphate increased by 1.44 folds, and NADH increased by 1.52 folds.

The results showed that proline and arginine could significantly enhance the adhesion ability of LR-1, which was consistent with the finding of Wan et al. that arginine and proline would significantly affect the adhesion ability of Lactobacillus plantarum ATCC 14917^[40]. And the adhesiveness of bacteria is an important factor in biofilm formation. As the adhesion ability of bacteria increases, their ability to form biofilms also increases. Some studies have shown that amino acids can participate in the metabolic pathways of lactic acid bacteria, promote the synthesis of adhesion-related substances (such as extracellular polysaccharide EPS and S-layer protein), thereby improving the adhesion ability of lactic acid bacteria^[49], and regulate the quorum-sensing system of lactic acid bacteria through signal transduction pathways, thereby affecting the adhesion behavior of lactic acid bacteria^[50]. Rhamnose, N-acetyl-d-lactosamine, and d-mannose-6-phosphate, as products in the carbon metabolism process, are important precursor substances for the synthesis of EPS. Exogenous addition may accelerate the synthesis efficiency of EPS, thereby affecting biofilm formation and adhesion ability. NADH is a key reductant in energy metabolism. By participating in processes such as glycolysis and oxidative phosphorylation, it provides energy for biofilm formation and maintenance^[51]. A high-level NADH/NAD⁺ ratio may create a more suitable intracellular environment for biofilm formation. Under such conditions, cells may be more inclined to express genes related to biofilm formation, such as genes encoding cell-surface proteins and polysaccharide synthases^[52]. These increased gene expressions may enhance the adhesion ability of lactic acid bacteria. These results may explain the reasons for the significant up-regulation of arginine, proline, rhamnose, N-acetyl-d-lactosamine, d-mannose-6-phosphate, and NADH contents and the improvement of biofilm formation and adhesion ability after the over-expression of the rbk gene in this study.

3 Conclusion

This study demonstrates that the overexpression of the rbk gene enhances the biofilm formation and adhesion capabilities of L. paraplantarum LR-1 while also upregulating the transcriptional levels of the tuf, luxS, and rpoN genes. Additionally, untargeted metabolomic analysis reveals that this overexpression leads to significant changes in 145 metabolites of L. paraplantarum LR-1, with 112 of these metabolites showing a strong correlation with biofilm formation and adhesion. Furthermore, the abundance of most metabolites related to central carbon, amino acid, energy, and nucleotide metabolism is higher in the rbk-pMG76e-LR-1 strain. These findings suggest that the overexpression of the rbk gene enhances the activity of these metabolic pathways. In addition, it was verified by exogenous addition of metabolites that some of the metabolites could significantly increase the biofilm formation and adhesion ability of LR-1 strain, which also indicates on the side that the overexpression of the rbk gene would have an effect on its biofilm formation and adhesion ability. Overall, this study indicates that the rbk gene plays a crucial role in metabolic regulation, significantly promoting the biofilm formation and adhesion abilities of Lactobacillus strains.