Introduction: The dental biofilm matrix is an important determinant of virulence for caries development and comprises a variety of extracellular polymeric substances that contribute to biofilm stability. Enzymes that break down matrix components may be a promising approach to caries control, and in light of the compositional complexity of the dental biofilm matrix, treatment with multiple enzymes may enhance the reduction of biofilm formation compared to single enzyme therapy. The present study investigated the effect of the three matrix-degrading enzymes mutanase, beta-glucanase, and DNase, applied separately or in combinations, on biofilm prevention and removal in a saliva-derived in vitro-grown model. Methods: Biofilms were treated during growth to assess biofilm prevention or after 24 h of growth to assess biofilm removal by the enzymes. Biofilms were quantified by crystal violet staining and impedance-based real-time cell analysis, and the biofilm structure was visualized by confocal microscopy and staining of extracellular DNA (eDNA) and polysaccharides. Results: The in vitro model was dominated by Streptococcus spp., as determined by 16S rRNA gene amplicon sequencing. All tested enzymes and combinations had a significant effect on biofilm prevention, with reductions of >90% for mutanase and all combinations including mutanase. Combined application of DNase and beta-glucanase resulted in an additive effect (81.0% ± 1.3% SD vs. 36.9% ± 21.9% SD and 48.2% ± 14.9% SD). For biofilm removal, significant reductions of up to 73.2% ± 5.5% SD were achieved for combinations including mutanase, whereas treatment with DNase had no effect. Glucans, but not eDNA decreased in abundance upon treatment with all three enzymes. Conclusion: Multi-enzyme treatment is a promising approach to dental biofilm control that needs to be validated in more diverse biofilms.

Current therapeutic strategies for caries control include mechanical biofilm removal, the topical application of fluoride, and the use of antimicrobial agents, such as chlorhexidine, xylitol, metal ions, and essential oils [1‒3]. The effect of antimicrobial agents is stronger on planktonic cells than on bacterial biofilms [4], and their continuous application in the oral cavity has been shown to eradicate part of the commensal microbiota, with detrimental effects on the human nitrate cycle and, potentially, blood pressure regulation [5, 6]. Consequently, there is an increasing interest in non-biocidal approaches for the reduction of dental biofilms and associated diseases.

The majority of studies on biofilm-related disease in the mouth has focused on the bacterial colonizers of dental biofilms. However, recent work has increased our understanding of the importance of the surrounding extracellular matrix for biofilm virulence [7, 8]. The biofilm matrix comprises of different extracellular polymeric substances (EPSs) that contribute to mechanical stability, resistance against antimicrobial agents, and nutrient storage for the embedded microorganisms [9‒11]. Extracellular polysaccharides, such as the glucans dextran and mutan, are highly abundant in streptococcal biofilms and were shown to be important for bacterial attachment, biofilm stability, and the formation of acidic pockets that favor enamel demineralization [7, 10, 12‒14]. Extracellular DNA (eDNA) is present in most biofilms and has been shown to be crucial for biofilm stability during early stages of biofilm formation [15, 16].

The use of enzymes to degrade components of the extracellular matrix is a non-biocidal therapeutic approach that seeks to destabilize the biofilm and thereby facilitate its removal [17]. Studies from the 1960s and 1970s showed that treatment with dextranase could disintegrate in vitro-grown single-species Streptococcus biofilms [18] and reduce the amount of Streptococcus mutans in gnotobiotic hamsters and rats [19, 20]. For the combined application of dextranase and mutanase, an additive effect on the reduction of plaque formation was observed [19]. More recently, convincing effects on the reduction of in vitro-grown streptococcal and cross-kingdom biofilms were observed when dextranase and mutanase were used in combination [21‒23]. Likewise, treatment with glucanase or DNase was shown to prevent streptococcal biofilm formation in vitro [24‒26]. Additionally, DNase reduced the formation of dental biofilms in situ during early stages of growth [27].

Taken together, these data demonstrate that biofilm removal can be achieved with enzymes that target different structural components of the extracellular matrix, and that the combined application of different matrix-degrading enzymes may enhance the treatment effect. However, in most of the above-cited studies, treatment was performed on biofilms consisting of one or few species, and to date, no studies have tested the effect of combinations of glucanases and DNases on biofilm formation. Therefore, the aim of this study was to investigate the effect of three matrix-degrading enzymes (mutanase, beta-glucanase, and DNase) on biofilm prevention and removal using a saliva-based in vitro-grown biofilm model. The biofilm model was evaluated using 16S rRNA gene amplicon sequencing and biofilm formation was quantified by crystal violet (CV) staining, confocal laser scanning microscopy (CLSM), and real-time cell analysis (RTCA).

Saliva Collection and Preparation

The study protocol was approved by the Central Jutland Regional Committee on Health Research Ethics (1-10-72-193-20). Stimulated saliva was collected from 10 healthy participants after written informed consent was obtained. The participants did not show any clinical signs of active caries or periodontal disease and had not been treated with antibiotics for 3 months prior to the study. Before the saliva collection, the participants did not eat or drink for a minimum of 1 h. Saliva production was stimulated by paraffin chewing (Merck, Darmstadt, Germany), after which the saliva was collected on ice, pooled and divided into two identical batches. One batch was aliquoted, frozen at −80°C in a mix with glycerol (50%) and phosphate-buffered saline (PBS; ratio 1:1:1), and used as the inoculum for biofilm growth. The other batch was sterile filtered as described previously [28]. In brief, the pooled saliva was mixed with sterile, demineralized water (1:1) and dithiothreitol (2.5 mmol; Merck), and then centrifuged at 4,800 g for 10 min (Centrifuge 5804, Eppendorf, Hamburg, Germany). The supernatant was sterilized by ultrafiltration with 0.45 μm prefilters and 0.2 μm filters (Merck), aliquoted and frozen at −20°C until use.

Biofilm Growth

Unless stated otherwise, biofilms were grown in round-bottom 96-well-plates (Nunclon Delta Surface, Thermo Fisher Scientific, Waltham, MA, USA) from salivary inocula mixed with brain-heart infusion (BHI) broth (Thermo Fisher Scientific) containing 5% sucrose and sterile saliva (ratio 1:8:1). The biofilms were incubated aerobically for 24 h at 37°C with light shaking (50 rpm).

16S rRNA Gene Amplicon Sequencing

The bacterial composition of the salivary inocula and the biofilms was determined by 16S rRNA gene amplicon sequencing. DNA was extracted using the NucleoSpin Soil kit (Machery Nagel, Düren, Germany) following the manufacturer’s protocol. The V3-V4 region of the 16S rRNA gene was amplified in a two-step polymerase chain reaction (PCR) process, as described in Rikvold et al. [29], and sequenced using the 300 bp paired-end mode on the MiSeq (Illumina, San Diego, CA, USA). ZymoBIOMICS™ Microbial Community Standard (Cat. No. D6300) and ZymoBIOMICS™ Microbial Community DNA Standard (Cat. No. D6306) were introduced during the DNA extraction and PCR amplification, respectively, as positive controls (Zymo Research, Irvine, CA, USA). Four samples with PCR grade water were introduced during the DNA extraction as negative controls. An amplicon sequence variant (ASV) table was generated using the UPARSE pipeline [30] according to the method described in Rikvold et al. [29]. The mean number of sequences per sample was 431,556.3 (min: 289,233 and max: 586,236) and the ASV table was down-sampled to 289,000 sequences per sample. The relative abundances of the taxonomical groups were converted to percentages.

Enzyme Preparation, Safety, and Treatment

The enzymes mutanase, beta-glucanase, and DNase were provided by Novozymes A/S (Kgs. Lyngby, Denmark). Enzymes were safety tested alone and in combination for genotoxicity and irritation of oral epithelial tissues and used at a final concentration of 62 μg/mL. Stock enzymes were aliquoted, frozen at −20°C and only thawed once prior to experimental use. Enzymatic treatment was performed either during biofilm growth (prevention assay) or after biofilms were established (removal assay), using single enzymes or combinations of mutanase, beta-glucanase, and DNase, diluted in phosphate-citrate buffer (pH 6.0; Spectrum Chemical, New Brunswick, NJ, USA) to the final concentration. For the prevention assay, the enzymes were added to the growth media. For the removal assay, the spent medium was removed, and the enzyme solutions were added for 30 min at 37°C with light shaking at 50 rpm. Treatment with pure phosphate-citrate buffer served as negative control. After enzyme treatment, biofilms were washed with phosphate-citrate buffer and shaken for 5 s (BioTek PowerWave X52, Holm & Halby, Brøndby, Denmark). Then the wells were emptied by inverting the plate over a funnel. The washing procedure was repeated three times.

Biofilm Quantification by CV Staining

The biofilms were dried for 30 min at 37°C and stained with 200 μL of CV solution (Sigma-Aldrich, St. Louis, MO, USA) for 10 min at room temperature. Unbound stain was removed by rinsing with demineralized water, after which the plates were emptied and dried for 30 min at 37°C. Then 200 μL of acetic acid (33%) was added for 30 min at room temperature to extract the CV stain from the biofilms. 50 µL liquid from each well was transferred to and diluted in 150 μL acetic acid (33%). Absorbance was measured with a plate reader (BioTek PowerWave X52) in flat bottom 96-well plates (Nunclon Delta Surface, Thermo Fisher Scientific) at 590 nm. Experiments were performed in technical quadruplicates and at least in biological triplicates.

Enzymatic Treatment of Planktonic Cultures

To test if enzymatic treatment had an antibacterial effect on oral bacteria, the strains Actinomyces naeslundii AK 6, Nesseria subflava DSM 17610, Lacticaseibacillus rhamnosus DSM 20021, Streptococcus mutans DSM 20523, Streptococcus mitis SK 24, and Streptococcus salivarius SK 56 were grown in planktonic culture. Strains were cultivated on blood agar plates (5% horse blood; SSI, Copenhagen, Denmark) for 48 h and thereafter grown in BHI broth for 20–24 h (pre-culture). Equal amounts of the pre-cultures were transferred to fresh BHI broth and grown until stationary phase, in the absence and presence of 62 μg/mL of mutanase, beta-glucanase, and DNase. Growth conditions are listed in online suppl. Table S1 (for all online suppl. material, see https://doi.org/10.1159/000535980). Absorbance was measured at 600 nm (Ultrospec 10 Cell Density Meter, Harvard Bioscience, Holliston, MA, USA) after 1 h, 4 h, and 24 h. Experiments were performed in quadruplicates.

Real-Time Cell Analysis

RTCA continuously monitors the adhesion of bacterial cells to well plates by converting electric impedance measurements into a dimensionless cell index [31, 32]. Biofilms were grown in RTCA E-plates (16 well; Agilent Technologies, Santa Clara, CA, USA) in the presence and absence of 62 μg/mL mutanase or a combination of mutanase, beta-glucanase, and DNase (prevention assay). In negative control wells, the salivary inoculum was replaced with sterile saliva. The biofilms were incubated according to the supplier’s protocol [33], and the cell index was monitored continuously (xCELLigence RTCA SP, Agilent Technologies, Santa Clara, CA, USA) for 24 h at 37°C. Then the biofilms were washed with phosphate-citrate buffer, shaken for 5 s (Vortex V-1 plus; Biosan, Riga, Latvia), and the wells were emptied by inverting the plate over a funnel. The washing procedure was repeated three times. Thereafter, fresh growth medium was added and the cellular index was again measured for 20 min. Finally, the biofilm biovolumes were quantified by CV staining as described above. The experiment was carried out in technical quadruplicates and biological triplicates.

Quantification of Biofilm Matrix Components by CLSM

Biofilms were grown in 8-well plates for microscopy (Ibidi, Gräfelfing, Germany) in the presence of fluorescently labeled dextran (2 μm; Dextran, Alexa Fluor™ 647; Thermo Fisher Scientific). During growth, the dextran was incorporated into the biofilm matrix polysaccharides [34]. After growth, the biofilms were treated with a combination of mutanase, beta-glucanase, and DNase (removal assay) and washed three times in phosphate-citrate buffer. eDNA in the biofilms was stained with TOTO™-1 (2 μm; Thermo Fisher Scientific). Microbial cells were counterstained SYTO™ 41 (10 μm; Thermo Fisher Scientific). Biofilms were imaged using an inverted CLSM (Zeiss LSM 700, Carl Zeiss AG, Oberkochen, Germany) equipped with a ×63 oil immersion objective (1.4 NA; alpha Plan-Apochromat, Zeiss). Excitation/detection settings were as follows: SYTO™ 41–405 nm/300–518 nm; TOTO™-1 – 488 nm/509–800 nm; Alexa Fluor™ 647–639 nm/300–800 nm. To avoid bleed-through, different fluorophores were excited and detected sequentially. The image size was 512 × 512 pixels (101.61 μm × 101.61 μm), acquired with a pixel dwell time of 1.58 µs and a line average of 1. The pinhole was set to 1.38 (Alexa Fluor™ 647), 1.79 (TOTO™-1) and 2.12 (SYTO™ 41) Airy Units, yielding an optical slice of 1.1 μm. In each biofilm, z-stacks with three equidistant slices were acquired in six predefined fields of view with a step size of 1,000 μm in between. Experiments were carried out in biological quadruplicates.

Digital image analysis was performed using the software daime [35]. The areas covered by matrix polysaccharides, eDNA, and microbial cells were determined by threshold-based segmentation of the red, green and blue channel images, respectively. For each z-stack, biovolumes were estimated according to the Cavalieri principle by multiplying the areas covered by matrix polysaccharides, eDNA, and microbial cells with the interslice distance [36].

Statistical Analysis

The effect of enzymatic treatment on biofilm biovolumes (determined by CV staining) and cell indices (determined by RCTA) was analyzed by one-way ANOVA with Dunnett’s correction for multiple comparisons. Paired t tests were used to assess the effect of enzyme treatment on planktonic bacterial growth and differences in the abundance of biofilm matrix components (determined by CLSM). The threshold for statistical significance was set to α = 0.05. All calculations were performed using GraphPad Prism (V9.5.0 for Windows, GraphPad Software, San Diego, CA, USA).

The salivary inoculum employed for biofilm growth comprised a range of common oral bacterial genera (mean relative abundance ±SD), such as Streptococcus spp. (19.9% ± 0.6%), Veilonella spp. (15.1% ± 0.8%), Haemophilus spp. (13.1% ± 0.4%), Prevotella spp. (9.7% ± 0.2%), Neisseria spp. (8.4% ± 0.3%), and Fusobacterium spp. (8.2% ± 0.5%) (Fig. 1, online suppl. Table S2). After 24 h of aerobic incubation in a medium rich in sucrose, the relative abundance of Streptococcus spp. increased considerably to 95.9% ± 0.73%, whereas the fraction of all other bacteria decreased. The most abundant streptococcal ASV identified in the saliva samples belonged to the S. oralis/mitis group, whereas S. salivarius was most abundant in the biofilms (online suppl. Table S2). An average of 560.0 ASVs (±24.9 SD) was observed in the saliva samples, with Streptococcus accounting for an average of 57.7 (±4.2 SD) ASVs. The overall number of ASVs was reduced to an average of 198.9 (±18.3 SD) in the biofilm samples, whereas the number of streptococcal ASVs remained similar with 49.5 (±5.3 SD). Shannon indices were 3.9 (±0.04 SD) and 0.9 (±0.1 SD) for saliva and biofilm samples, respectively (online suppl. Table S2).

Fig. 1.

Bacterial composition. The relative abundance of bacterial genera in the salivary inoculum and in biofilms grown for 24 h in the presence of sucrose was determined by 16S rRNA gene amplicon sequencing. Biofilms were dominated by Streptococcus spp.

Fig. 1.

Bacterial composition. The relative abundance of bacterial genera in the salivary inoculum and in biofilms grown for 24 h in the presence of sucrose was determined by 16S rRNA gene amplicon sequencing. Biofilms were dominated by Streptococcus spp.

Close modal

When enzymes were added during biofilm growth (prevention assay), biofilm formation was reduced by up to 96.8% (±1.3% SD; p < 0.0001), compared to control treatment (Fig. 2). All tested enzymes and enzyme combinations showed a significant effect on biofilm prevention (p < 0.05), with mutanase being the most effective single enzyme. The treatment effect did not differ significantly between combinations that included mutanase (online suppl. Table S3). DNase and beta-glucanase had less pronounced effects, with average reductions of 36.9% (±21.9% SD; p = 0.0011) and 48.2% (±14.9% SD; p < 0.0001), respectively. When these two enzymes were used in combination, the treatment effect was enhanced, resulting in 81.0% (±1.3% SD) biofilm prevention (p = 0.0002).

Fig. 2.

Effect of enzymatic treatment on the prevention of biofilm growth. Mutanase, beta-glucanase, DNase, or combinations of the enzymes were added to the medium during biofilm growth. After 24 h, the amount of biofilm formed was quantified by crystal violet (CV) staining and compared to control treatment with buffer only (dashed line). All single enzymes and enzyme combinations reduced the amount of biofilm formed significantly, with mutanase being the most effective single enzyme. **p < 0.01; ****p < 0.0001. Error bars = SD.

Fig. 2.

Effect of enzymatic treatment on the prevention of biofilm growth. Mutanase, beta-glucanase, DNase, or combinations of the enzymes were added to the medium during biofilm growth. After 24 h, the amount of biofilm formed was quantified by crystal violet (CV) staining and compared to control treatment with buffer only (dashed line). All single enzymes and enzyme combinations reduced the amount of biofilm formed significantly, with mutanase being the most effective single enzyme. **p < 0.01; ****p < 0.0001. Error bars = SD.

Close modal

The observed inhibition of biofilm formation cannot be ascribed to an antibacterial effect of the enzymes. Planktonic growth of different oral bacteria, including S. mutans, S. mitis, and S. salivarius, was not inhibited by the addition of mutanase, beta-glucanase, and DNase (online suppl. Fig. S1). Furthermore, RTCA showed almost identical cell indices during a 24-h incubation period for control biofilms and biofilms grown in the presence of mutanase (24 h: p = 0.91) or all three enzymes (24 h: p = 0.73; Fig. 3a). After a washing step, the cell indices were significantly lower for biofilms treated with mutanase or all three enzymes (p < 0.05) compared to control treatment, which illustrates that the mechanical stability of the enzyme-treated biofilms was reduced (Fig. 3b). The reduction in biofilm biovolumes was confirmed by subsequent CV staining (online suppl. Fig. S2).

Fig. 3.

Real-time cell analysis (RTCA) of biofilm formation. Biofilm growth was monitored for 24 h in the presence of mutanase, a combination of enzymes (mutanase, beta-glucanase, and DNase) or in the absence of enzymes (control). a After 24 h of growth, cell indices were not significantly different between treatment groups. Thereafter, biofilms were washed (arrow) and RTCA was continued for another 20 min. After washing, cell indices for biofilms treated with mutanase and the enzyme combination were significantly lower than for the control. b Mean cell indices compared to control treatment (dashed line) before and after washing. M, mutanase; MGD, mutanase, beta-glucanase, and DNase; *p < 0.05. Error bars = SD.

Fig. 3.

Real-time cell analysis (RTCA) of biofilm formation. Biofilm growth was monitored for 24 h in the presence of mutanase, a combination of enzymes (mutanase, beta-glucanase, and DNase) or in the absence of enzymes (control). a After 24 h of growth, cell indices were not significantly different between treatment groups. Thereafter, biofilms were washed (arrow) and RTCA was continued for another 20 min. After washing, cell indices for biofilms treated with mutanase and the enzyme combination were significantly lower than for the control. b Mean cell indices compared to control treatment (dashed line) before and after washing. M, mutanase; MGD, mutanase, beta-glucanase, and DNase; *p < 0.05. Error bars = SD.

Close modal

Enzyme treatment removed up to 73.2% (±5.5% SD) of established biofilms compared to control treatment (Fig. 4). Again, mutanase was the most effective single enzyme (p < 0.0001), and there were no statistically significant differences between treatments that included mutanase (online suppl. Table S4). Beta-glucanase, but not DNase significantly reduced the amount of biofilm, with average reductions of 25.6% (±17.4% SD; p < 0.0001) and 11.0% (±16.7% SD; p = 0.12), respectively. In contrast to treatment during growth, the combined application of DNase and beta-glucanase did not result in increased biofilm removal (22.0% ± 10.2% SD), compared to treatment with beta-glucanase alone (p = 0.99).

Fig. 4.

Effect of enzymatic treatment on biofilm removal. Treatment with mutanase, beta-glucanase, DNase, or combinations of the enzymes was performed for 30 min after 24 h of biofilm growth. The amount of biofilm formed was quantified by CV staining and compared to control treatment with buffer only (dashed line). Treatment with mutanase, beta-glucanase, and enzyme combinations reduced the amount of biofilm significantly, with mutanase being the most effective single enzyme. ns, not significant; ***p < 0.001; ****p < 0.0001. Error bars = SD.

Fig. 4.

Effect of enzymatic treatment on biofilm removal. Treatment with mutanase, beta-glucanase, DNase, or combinations of the enzymes was performed for 30 min after 24 h of biofilm growth. The amount of biofilm formed was quantified by CV staining and compared to control treatment with buffer only (dashed line). Treatment with mutanase, beta-glucanase, and enzyme combinations reduced the amount of biofilm significantly, with mutanase being the most effective single enzyme. ns, not significant; ***p < 0.001; ****p < 0.0001. Error bars = SD.

Close modal

Biofilm morphology and the abundance of biofilm matrix components were assessed by CLSM. The biofilms were dominated by cocci and displayed thick bacterial clusters, as well as areas with low cell density. The average biofilm thickness was 15.67 μm (±5.4 μm SD). Glucans, as visualized by fluorescently labeled dextran (Alexa Fluor™ 647), were highly abundant in the biofilm matrix (70.3% ± 36.9% SD of the bacterial biovolume), whereas eDNA, visualized by TOTO™-1, only constituted a minor component (10.3% ± 9.7% SD of the bacterial biovolume; Fig. 5a, b). Enzymatic treatment with a combination of mutanase, beta-glucanase, and DNase significantly reduced the relative amount of glucans in the biofilms (p = 0.02; Fig. 5b, c). Changes observed in the biovolumes of microbial cells and eDNA were not significant.

Fig. 5.

Confocal microscopy imaging of biofilm matrix components. a Biofilms were dominated by cocci (blue) and comprised large amounts of matrix glucans (red) that were equally distributed across the biofilms. eDNA (green) only constituted a minor component of the biofilms. b Treatment with a combination of mutanase, beta-glucanase, and DNase reduced the amount of matrix polysaccharides. No effect on the abundance of eDNA was observed. Bars = 20 μm. c Compared to control treatment (dashed line), the amount of matrix polysaccharides was significantly reduced in enzyme-treated biofilms but not the amount of microbial cells or eDNA. ns, not significant; *p < 0.05. Error bars = SD.

Fig. 5.

Confocal microscopy imaging of biofilm matrix components. a Biofilms were dominated by cocci (blue) and comprised large amounts of matrix glucans (red) that were equally distributed across the biofilms. eDNA (green) only constituted a minor component of the biofilms. b Treatment with a combination of mutanase, beta-glucanase, and DNase reduced the amount of matrix polysaccharides. No effect on the abundance of eDNA was observed. Bars = 20 μm. c Compared to control treatment (dashed line), the amount of matrix polysaccharides was significantly reduced in enzyme-treated biofilms but not the amount of microbial cells or eDNA. ns, not significant; *p < 0.05. Error bars = SD.

Close modal

The present study demonstrated strong effects of the three matrix-degrading enzymes mutanase, beta-glucanase, and DNase on biofilm prevention and removal in a saliva-derived biofilm model dominated by Streptococcus spp. The enzymes were most effective when added to the medium during biofilm growth, resulting in >90% reduction in biofilm formation (Fig. 2). The treatment effect cannot be ascribed to an antibacterial action of the enzymes, as demonstrated by the undisturbed growth of planktonic cultures and identical RTCA results in the presence of the enzymes (online suppl. Fig. S1, 3). Instead, it is conceivable that the enzymes destabilized biofilms by cleaving important matrix components, resulting in disruption of biofilms when exposed to mechanical shear during the subsequent washing procedure.

Mutanase predominantly hydrolyzes water-insoluble α-(1→3)-linked glucans [23, 24] and it was proved to be the most effective single enzyme for biofilm control. It almost fully prevented biofilm formation and also removed about 60% of the biofilm when applied after growth. These results are in line with previous studies that observed highly significant reductions of streptococcal biofilms grown in vitro [22, 36, 37] and in gnotobiotic rats [19] upon treatment with mutanase.

Treatment with beta-glucanase or DNase resulted in lower but still significant effects on biofilm formation. When added to the medium, both enzymes had additive effects on prevention (Fig. 2). In contrast, DNase did not enhance the effect of beta-glucanase, nor did it remove significant amounts of biofilm on its own when applied after biofilm growth (Fig. 4). These findings are in accordance with the literature, which has consistently shown that the effect of DNase is restricted to early stages of biofilm formation [15, 16, 27, 38]. In addition, TOTO™-1 staining showed that only small amounts of eDNA were integrated into the matrix structure (Fig. 5). The significant effects of beta-glucanase treatment on biofilm prevention and removal suggest that the matrix harbored polysaccharides comprising β-glucosidic bonds, which have generally received less attention in dental biofilm research [10]. When applied after growth, the addition of beta-glucanase and/or DNase enhanced the effect of mutanase to some extent, but without reaching statistical significance.

This is the first study to investigate the effect of combined treatment with an alpha-glucanase (mutanase), a beta-glucanase, and a nuclease (DNase) on a dental biofilm model. Previous studies have shown additive effects for combinations of mutanase and dextranase or mutanase, dextranase, and lipase on biofilm reduction [19, 21, 24]. Hence, the concept of multi-enzyme treatment to simultaneously target several key components of the biofilm matrix seems promising. However, in the biofilm model employed in the present work, none of the tested enzyme combinations exceeded the treatment effect of mutanase.

The biofilm model employed in the present study was dominated by Streptococcus spp. (Fig. 1), with S. salivarius being the most prevalent organism. When exposed to sucrose, different strains of S. salivarius have been reported to produce water-insoluble polysaccharides, such as glucans rich in α-(1→3) glycosidic bonds [39‒41]. The low genetic diversity of the model may have resulted in a homogenous matrix composition that facilitated the overwhelming effect of, especially, mutanase. It remains to be determined if similar treatment effects can be achieved in biofilms with a greater microbial diversity at the genus level and a resulting greater matrix diversity. Future research should therefore investigate the combined application of mutanase, beta-glucanase, and DNase on more diverse biofilm models. In the present study, enzymatic treatment was performed either during the entire biofilm growth phase or for 30 min after biofilm growth. Continuous treatment represents a proof-of-concept scenario that cannot be extrapolated to a clinical context, whereas an exposure time of 30 min may be achieved in vivo, depending on the mode of application and enzyme substantivity. The effect of even shorter and, potentially, more frequent enzyme exposures should be investigated in future studies to mimic a more realistic treatment regimen.

In conclusion, within the limits of this in vitro study, enzyme treatment with mutanase or with combinations of mutanase, beta-glucanase, and DNase is a promising approach for non-biocidal biofilm control. The effectiveness of multi-enzyme treatment for the prevention of biofilm build-up and, ultimately, caries prevention remains to be elucidated in clinical trials.

The authors would like to thank Karina Kambourakis Johnsen, Andreas Møllebjerg, and Signe M. Nielsen for excellent assistance during the study. Anette Aakjær Thomsen, Lene Grønkjær, Javier E. Garcia, and Jimmi Overgaard Kristiansen are acknowledged for great technical support.

This study protocol was reviewed and approved by the Central Jutland Regional Committee on Health Research Ethics (1-10-72-193-20). Written informed consent was obtained from all participants included in the study.

Pernille D. Rikvold is an industrial Ph.D. student at Aarhus University, co-funded by Novozymes A/S and the Innovation Fund Denmark (9065-00244B). Lea B. S. Hansen and Manish K. Tiwari are employees at Novozymes A/S. Mette Rose Jørgensen was employee at Novozymes A/S during the investigations. A patent application (WO 2023/110900) filed in the name of Novozymes A/S relates to this work.

The study was funded by the Innovation Fund Denmark (9065-00244B) and Novozymes A/S. The funders had no role in the study design, data collection, and the decision to publish. 16S rRNA gene data analysis was performed by Lea B. S. Hansen. All other data analyses were performed by Aarhus University.

P.D.R.: conceptualization, methodology, data acquisition, formal analysis, investigation, writing – original draft, and visualization. L.B.S.H.: formal analysis, investigation, data curation, and writing – review and editing. M.R.J.: conceptualization, methodology, project administration, supervision, and writing – review and editing. M.K.T.: methodology, investigation, writing – review and editing, and project administration. R.L.M.: conceptualization, resources, writing – review and editing, supervision, project administration, and funding acquisition. S.S.: conceptualization, methodology, formal analysis, investigation, resources, writing – original draft, supervision, project administration, and funding acquisition.

All data generated or analyzed during this study are included in this article and its supplementary material files. Further inquiries can be directed to the corresponding authors.

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