Bidirectional relationship between the biofilm of Porphyromonas gingivalis and the amyloid-beta peptide

ABSTRACT

Periodontitis and Porphyromonas gingivalis infections are significant risk factors for the onset of Alzheimer’s disease (AD). Despite the reliance of P. gingivalis on its biofilm for its survival and virulence, the impact of the extracellular matrix on AD’s neuropathological hallmarks has never been examined. In this study, we report a bidirectional relationship between the amyloid-beta (Aβ) peptide, which plays a central role in AD, and the biofilm of P. gingivalis. Using multiple fluorescent markers for biofilm components, we observed that Aβ_1-40 inhibited biofilm formation while Aβ_1-42 increased extracellular matrix production. Also, using thioflavin T staining and atomic force microscopy, we observed co-aggregation of the biofilm and monomeric Aβ_1-40, resulting in faster aggregation and significant changes in aggregate structure. Our findings propose mechanistic explanations for the role of P. gingivalis as a risk factor for AD and offer potential mechanisms for microbial involvement in AD etiology.

IMPORTANCE

While the etiology of Alzheimer’s disease has been studied extensively for the past 50 years, its exact causes remain unknown. Our current understanding is that the accumulation of multiple genetic and environmental risk factors would lead to the onset of the disease. Porphyromonas gingivalis is a bacterium that produces biofilm and elicits periodontitis, a chronic infection of the gums that constitutes a risk factor for Alzheimer’s disease. While studies have looked at the effects of P. gingivalis in triggering Alzheimer’s symptoms in animal models, none have explored the impact of the biofilm, which is essential in this bacterium. Our study seeks to bridge that gap by demonstrating a bidirectional relationship between P. gingivalis biofilm and amyloid beta, one of the brain lesions involved in Alzheimer’s disease. By understanding the risk factors involved in Alzheimer’s disease and their impact, we aim to provide valuable insights on prevention and treatment.

INTRODUCTION

The oral biofilm is a complex microbial community that contributes to the onset of multiple diseases, including periodontitis. Periodontitis is a chronic and inflammatory condition of the periodontium characterized by a bacterial-driven degradation of the gum epithelium and the underlying alveolar bone tissue (1). The onset of periodontitis is usually associated with the proliferation of bacteria from the red complex—Treponema denticola, Tannerella forsythia, and Porphyromonas gingivalis—within the gingival biofilm (2, 3). P. gingivalis specifically contributes to the establishment of the oral biofilm by suppressing the host’s immune response and releasing nutrients through periodontal tissue breakdown (4, 5). It also produces gingipains, cysteine proteases targeting lysine-Xaa (Kgp) or arginine-Xaa (RgpA, RgpB) bonds that contribute to intracellular invasion and degradation of antimicrobial peptides (6–10).

Being strictly anaerobic, P. gingivalis depends on its biofilm to limit O₂ exposure. This lifestyle allows for its survival and the secretion of virulence factors. Although P. gingivalis biofilm formation is poorly characterized, it relies on the production of two co-occurring fimbriae, the major fimbria FimA and the minor fimbria Mfa1 (11–13). This bacterium also produces capsular polysaccharides that promote interspecies aggregation and extracellular DNA for building its extracellular matrix, but genes encoding these processes are unknown (14, 15). P. gingivalis biofilm production also correlates with gingipain secretion, thus contributing to epithelial tissue breakdown, cellular invasion, and release into the bloodstream (16, 17). The progression of multiple diseases such as atherosclerosis (18), rheumatoid arthritis (reviewed in reference 19), and adverse pregnancy outcomes (reviewed in reference 20) is influenced by the propagation of this pathogen. Periodontitis and P. gingivalis infections are also confirmed risk factors for Alzheimer’s disease (AD) (21).

AD is an incurable neurodegenerative disease characterized by the accumulation of aggregated amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles composed of hyperphosphorylated Tau proteins. The occurrence of these lesions triggers neuroinflammation and neuronal cell death, leading to cognitive decline in older adults (22). The toxicity of Aβ is linked to amyloid aggregation into oligomers, which form pores in neuronal cell membranes (23, 24), causing mitochondrial dysfunction (25) and triggering pathogenic inflammation in the central nervous system (CNS) (26). Aβ is mainly secreted in two forms: Aβ_1-40 represents ~90% of the overall Aβ pool but exhibits low toxicity and aggregation; Aβ_1-42 is highly aggregative, neurotoxic, and overrepresented in Aβ plaques (27). Outside the CNS, where it is most observed, Aβ is also produced by other cell types, such as skeletal muscle cells, hepatic cells, platelets, and macrophages (28, 29).

The involvement of microbial infection in AD etiology has attracted increasing interest in the last decade (30). Associations between AD and diverse infectious agents revealed that Aβ acts as an antimicrobial peptide against viral, fungal, and bacterial pathogens (31–35). Indeed, in response to different infections, Aβ_1-42 is produced and accumulates in the CNS (reviewed in reference 32), hinting toward a mechanism in which infections would contribute to AD etiology. Of note, AD development occurs 20–30 years before symptoms appear, which indicates the involvement of a chronic infection rather than an acute event (36).

P. gingivalis is one of the most studied pathogens related to AD, as many of its biomolecules, including nucleic acids, lipopolysaccharides, and gingipains, have been observed in various regions of AD brains (reviewed in reference 37). P. gingivalis has also been isolated from the cerebrospinal fluid of patients (38, 39). In mouse models, repeated oral infections with P. gingivalis resulted in bacterial translocation to the brain, increased Aβ_1-42 secretion, and AD-like neurodegeneration (40, 41). The interaction between Aβ and P. gingivalis also occurs outside the CNS. Notably, Aβ_40/42 was detected in the gingival crevicular fluid of patients with periodontitis, where it aggregated within the gingival biofilm on the gums (42, 43).

Although P. gingivalis is considered a pathogen of interest in AD, the impact of its biofilm on Aβ has not yet been characterized. This multicellular structure is important, as bacterial biofilms have been recovered from Aβ plaques (44–46). A better understanding of the interaction between these two components will provide significant insights into how P. gingivalis could be a risk factor for AD and how it can persist despite Aβ’s antimicrobial activity. In this study, we co-cultivated P. gingivalis under biofilm-inducing conditions alongside Aβ_1-40 and Aβ_1-42 (Aβ_40/42) and observed that the interaction between Aβ and P. gingivalis biofilm varies according to the peptide subtype.

RESULTS

Aβ influences P. gingivalis biofilm formation

Previous reports have identified Aβ_40/42 as an antimicrobial peptide against multiple bacterial species, such as Escherichia coli, Enterococcus faecalis, and Staphylococcus epidermidis (31). To determine if Aβ_40/42 would impact P. gingivalis strain 33277 viability or biofilm formation, P. gingivalis was co-incubated for 24 h with various concentrations of Aβ_40/42 under biofilm-inducing conditions. These Aβ concentrations were chosen to reflect a microenvironment in which bacteria are not abundant but Aβ_40/42 is, such as in the inflamed part of the brain. Similar concentrations were also used in previous studies (31, 35). After the co-incubation, we quantified biofilm formation using a crystal violet assay. Surprisingly, the two Aβ peptides had different impacts on biofilm formation. High concentrations of Aβ_1-40 lowered biofilm production at 25 (55% decrease) and 12.5 μg/mL (34% decrease) (Fig. 1). Meanwhile, incubation with Aβ_1-42 had the opposite effect, resulting in a dose-dependent, significant increase in biofilm formation, peaking between 12.5 (56% increase) and 25 μg/mL (46% increase) (Fig. 1). In parallel, we examined whether Aβ_40/42 affected P. gingivalis viability in planktonic cultures using LIVE/DEAD assays followed by flow cytometry analysis and colony-forming unit (CFU) quantification. Interestingly, the highest concentration of Aβ_1-40 or Aβ_1-42 did not affect P. gingivalis (Fig. S1).

Fig 1.

Influence of Aβ_40/42 on P. gingivalis biofilm growth. Biofilm production of P. gingivalis in the presence of varying concentrations of Aβ_1-40 (left) or Aβ_1-42 (right) in μg/mL, as measured by crystal violet staining after 24 h. This figure contains three technical replicates and is representative of three biological replicates. Statistical analysis was performed using an ANOVA with a Dunnett’s multiple comparison test; * (P ≤ 0.05), ** (P ≤ 0.005), and **** (P ≤ 0.0001) indicate a significant difference from the control (0 μg/mL). Error bars represent the standard deviation (SD).

Since crystal violet is a non-specific dye, the impact of Aβ_40/42 on biofilm formation could be due to changes in the amount of extracellular matrix or bacteria within the biofilm. To discriminate between these two possibilities, we used differential fluorescence staining to quantify the abundance of each component. We used the DNA-binding fluorescent molecule 4′,6-diamidino-2-phenylindole (DAPI) to mark the cells. Thioflavin T (ThT) was used as a general protein marker, as a proxy for proteins within the extracellular matrix (47). Despite being quite specific to amyloid fibers, ThT was shown to be fluorescent in the P. gingivalis biofilm and in cell-free biofilm fragments (Fig. S2). Finally, the matrix exopolysaccharides were labeled using fluorophore-bound lectin concanavalin A (ConA) (48). These markers were used on P. gingivalis biofilms cultivated with 25 μg/mL of Aβ_1-40 or Aβ_1-42, and fluorescence was quantified to determine whether cell, protein, or exopolysaccharide levels varied during biofilm formation. For Aβ_1-40, we observed a significant decrease in the fluorescence intensity of each marker compared to the control with no Aβ (Fig. 2A). Indeed, direct observation of the biofilm by confocal imaging (Fig. 2B) confirmed that in the presence of Aβ_1-40, the biofilm of P. gingivalis was very sparse and organized in small aggregates.

Fig 2.

Influence of Aβ_40/42 on P. gingivalis biofilm composition and thickness. (A) Fluorescence intensity fold change of DAPI, ThT, and ConA staining on P. gingivalis biofilm cultivated with 25 μg/mL Aβ_40/42 for 24 h. Values for the control were pooled from the individual assays on Aβ_1-40 and Aβ_1-42 and normalized against the mean. Statistical analysis was performed using Brown-Forsyth and Welch ANOVA with a Dunnett’s T3 multiple comparison test for DAPI and ConA and Kruskal-Wallis with a Dunn’s multiple comparisons test for ThT, * (P ≤ 0.05), ** (P ≤ 0.005), and **** (P ≤ 0.0001) indicate a significant difference from the control. Error bars represent SD. (B) Cross-sections of P. gingivalis biofilm cultivated with 25 μg/mL Aβ_40/42 for 24 h and visualized with DAPI, ThT, and ConA. Scale bar = 10 μm. Accompanied by the merge of the three channels in a front view. A total of at least 25 images were taken (all biological replicates together). Panel A was generated from a single biological replicate and is representative of all replicates. Scale bar = 50 μm.

Meanwhile, biofilms of P. gingivalis formed with Aβ_1-42 exhibited a notable increase for each marker compared to the control, the degree of which varied among markers. While the rise in intensity associated with DAPI (~1.25-fold) was significant, it was much lower than the fluorescence increases associated with ThT (~4.5-fold) and ConA (~4.2-fold). This result suggests that the effect of Aβ_1-42 on the biofilm was due to a strong stimulation of the production and secretion of the extracellular matrix (Fig. 2A). Of note, the sharp increase in the ThT fluorescence intensity in the presence of Aβ_1-42, which surpasses the increase observed with ConA, could be partly due to ThT binding to the aggregated Aβ within the biofilm. Confocal imaging of biofilm cross-sections showed a thicker community when the biofilm was formed in the presence of Aβ_1-42 (Fig. 2B), resulting in a higher signal in all channels and a visibly increased biomass.

Aβ aggregates within the P. gingivalis biofilm

Previous studies identified biofilm components in the brain of AD patients, interwoven with Aβ plaques (44, 45). We hypothesized that, similarly, Aβ aggregates could be embedded in the biofilm of P. gingivalis. Therefore, we imaged biofilms of P. gingivalis formed in the presence of 5 μg/mL of Aβ_40/42. This concentration had only a small effect on biofilm formation (see Fig. S3), which was important because our goal was to determine whether Aβ_40/42 could be embedded in the biofilm. Matrix components were stained as described in Fig. 2, and Aβ_40/42 was detected using the MOAB-2/6C3 monoclonal antibody coupled to the Alexa Fluor 555 fluorophore. Interestingly, confocal imaging revealed that Aβ aggregates were present as inclusions in the extracellular matrix of P. gingivalis after 24 h. Aβ_1-42 was more abundant within the P. gingivalis biofilm than Aβ_1-40, which was present only in a few instances (Fig. 3A). Quantification of the Alexa Fluor 555 in the biofilm confirmed that the accumulation of Aβ_1-42 was significantly higher than Aβ_1-40 (Fig. 3B). We then assessed if Aβ_1-42 aggregation was more closely associated with cells (DAPI) or the extracellular matrix (ConA). Mander’s co-localization correlation analysis showed that the signal for Aβ_1-42 co-localized significantly more with the exopolysaccharides (ConA) channel than with the DAPI labeled cells (Fig. 3C).

Fig 3.

Presence of Aβ_40/42 within the biofilm of P. gingivalis. (A) Confocal imaging of Aβ_1-40 or Aβ_1-42 (yellow; 6C3 antibody) within the biofilm of P. gingivalis after 24 h. Cells are in blue (DAPI) and exopolysaccharides are in magenta (ConA). (B) Quantification of the fluorescence of Aβ_1-40 or Aβ_1-42 aggregated within the biofilm of P. gingivalis. Statistical analysis was performed using the Kruskal-Wallis test with a Dunn’s multiple comparisons test; * (P ≤ 0.05) and **** (P ≤ 0.0001) indicate a significant difference from the control. (C) Mander’s colocalization correlation of Aβ_1-42 with DAPI (cells) and ConA (biofilm). Statistical analysis was performed using the Mann-Whitney test. *** (P ≤ 0.001). At least 25 images per condition are included in the analysis, covering three biological replicates.

P. gingivalis biofilm influences Aβ aggregation

Since Aβ aggregates were visible within the biofilm of P. gingivalis, we hypothesized that some biofilm components could interact with Aβ peptide and influence its aggregation rate. We first separated the extracellular biofilm matrix from the bacterial cells to produce nanometric biofilm fragments (hereafter, seeds). These seeds were then incubated with monomeric Aβ_40/42 in a 1:20 ratio in the presence of ThT, which binds to β-fold structures formed during amyloid aggregation. This binding leads to increased ThT fluorescence, enabling real-time observation of Aβ aggregation. Real-time fluorescence curves were then analyzed by assessing the aggregation constant (k), the aggregation half-time, and the length of the lag phase. For Aβ_1-40, we observed a significant decrease in lag phase when the peptide was incubated with seeds, as evidenced by the resulting aggregation curve (Fig. 4A). We also observed a non-significant, but still sizable, decrease in half-time. Interestingly, incubation of monomeric Aβ_1-40 with seeds also reduced the peptide’s aggregation constant by threefold. These results indicate that although the presence of seeds reduced the time necessary for fibrillation of Aβ_1-40, the actual aggregation rate was slower. Inversely, incubation with seeds had no impact on the aggregation onset or rate for Aβ_1-42 (Fig. 4B).

Fig 4.

Aggregation kinetics of monomeric Aβ_1-40 (A) and Aβ_1-42 (B) incubated with biofilm seeds from P. gingivalis. Half-time (left), aggregation constant (K, middle), and lag phase (right) were extracted from individual curves. Statistical analysis was performed with Student’s t-test; * (P ≤ 0.05), **** (P ≤ 0.0001). Error bars represent SD. Curves are the average of three technical replicates and are representative of three biological replicates.

We then used atomic force microscopy (AFM) to assess whether the increase in Aβ_1-40 aggregation in the presence of seeds altered the overall structure of fibrils. Briefly, a 100 μg/mL solution of Aβ40/42 was incubated with 5 μg proteins/mL of biofilm seeds for 3 h for Aβ_1-40 or 1 h for Aβ_1-42 before being placed on a clean mica surface. As shown in Fig. 5, Aβ_1-40 alone formed lengthy, complex networks of interconnected fibrils (Fig. 5A). However, in the presence of seeds, Aβ_1-40 formed tight and isolated bundles of thick fibrils. This seemingly higher aggregative state might explain the decrease in the lag phase necessary for Aβ aggregation observed in Fig. 4A. For Aβ_1-42, the aggregation pattern between the peptide alone and with seeds showed no significant difference, consistent with results from the ThT aggregation kinetics assays (Fig. 5B).

Fig 5.

Aggregation of Aβ_1-40 (A) or Aβ_1-42 (B) incubated alone or with biofilm seeds from P. gingivalis at 37°C for 3 h (Aβ_1-40) and 1 h (Aβ_1-42) and visualized through AFM using height sensors. Images represent 12 technical replicates across three biological replicates.

Gingipains can break down Aβ

P. gingivalis produces gingipains, large-spectrum proteases able to break down antimicrobial peptides (49). Since P. gingivalis biofilm was resistant to Aβ_1-42 antibacterial properties, gingipains, which are abundant in the biofilm, could be involved in limiting its toxicity. We therefore assessed the proteolytic activity of gingipains on Aβ_40/42. We first produced gingipain-rich stationary phase supernatants from a 48 h culture of P. gingivalis 33277, of the deletion mutants ΔrgpAΔrgpB (KDP112), Δkgp (KDP129), and of the triple mutant ΔrgpAΔrgpBΔkgp (KDP128). All supernatants were incubated with 5 μg/mL of Aβ_40/42 for 16 h and then spotted onto PVDF membranes for dot blot assays. As shown in Fig. 6A, both Aβ_1-40 and Aβ_1-42 were degraded when incubated with supernatants from P. gingivalis 33277, demonstrating that the bacterial supernatant can break down the peptide. Exposure to the supernatant of ΔrgpAΔrgpBΔkgp did not affect the peptide, suggesting that gingipains are responsible for Aβ_40/42 degradation. Interestingly, the supernatant produced by the ΔrgpAΔrgpB strain also did not break down Aβ_40/42, whereas the supernatant from Δkgp did (Fig. 6A). Densitometry analysis (Fig. 6B) revealed a more pronounced degradation of Aβ₁₋₄₀ by the ΔrgpAΔrgpB mutant compared to the ΔrgpA∆rgpB∆kgp mutant, which could result from variability in the assay or from the upregulation of kgp or another protease in the double arginine-specific gingipains mutant. Interestingly, gingipains could only digest monomeric Aβ_40/42, while fully aggregated fibrils were unaffected (Fig. 6B). Aβ fibrils are notoriously complex to break down, requiring a multi-step process that includes various proteases (50). In our case, gingipains alone were insufficient to fully degrade pre-assembled Aβ complexes.

Fig 6.

Degradation of Aβ_40/42 by gingipains from P. gingivalis. (A) Monomeric Aβ_1-40 or Aβ_1-42 incubated with supernatant from P. gingivalis WT ATCC 33277, Δkgp, ΔrgpAΔrgpB, and ΔrgpAΔrgpBΔkgp. (B) Densitometry analysis of A. Statistical analysis was performed using ANOVA with a Dunnett’s multiple comparison test; * (P ≤ 0.05) and *** (P ≤ 0.001) represent a significant difference compared to ΔrgpAΔrgpBΔkgp. Error bars represent SD. (C) Monomeric and pre-aggregated (24 h at 37°C) Aβ_1-40 or Aβ_1-42 incubated with supernatant from P. gingivalis. Results are representative of three biological replicates. Positive controls represent Aβ without P. gingivalis supernatant.

DISCUSSION

While the link between AD and P. gingivalis has been extensively investigated over the past 10 years, no study has examined the specific impact of the biofilm on the AD hallmark, Aβ (21, 39, 41, 51–57). Using a simplified model, we observed a bidirectional relationship specific to each peptide. Indeed, both Aβ_40/42 impacted P. gingivalis biofilm production differently, but the biofilm only influenced Aβ_1-40 aggregation.

We first determined that Aβ_1-40 and Aβ_1-42 had different effects on P. gingivalis. Biofilm production was decreased when exposed to increasing concentrations of Aβ_1-40, while Aβ_1-42 increased the abundance of the extracellular matrix. These results are surprising considering that Aβ_1-42 is more toxic than Aβ_1-40 (58). Importantly, Aβ_1-42 did not exhibit antimicrobial activity against P. gingivalis, since it stimulated biofilm formation and did not affect the viability of planktonic cells. This lack of antagonism might be due to the abundance of proteinases secreted by P. gingivalis, as discussed later. Although Aβ_1-42 was not cross-seeded by the biofilm seeds, its presence still enhanced biofilm production in a dose-dependent manner (Fig. 1 and 2). One hypothesis is that aggregated Aβ_1-42 clumps could promote bacterial aggregation, thereby stimulating increased matrix secretion. Indeed, the bacterial clumping effect of Aβ has been described in other bacteria (59), most notably in Salmonella typhimurium (60).

In contrast to Aβ_1-42, high concentrations of Aβ_1-40 reduced biofilm formation. These observations are not unlike those made on E. coli, for which the presence of Aβ_1-42 decreased biofilm production (61, 62). Interestingly, this bacterium relies on the presence of the functional amyloid protein CsgA as part of its extracellular matrix. CsgA can cross-seed Aβ_1-42 and form unproductive heterogeneous polymers, leading to a disruption of the biofilm (61). While there are currently no known functional amyloid proteins in P. gingivalis biofilm, aggregation kinetic assays (Fig. 4) and AFM imaging (Fig. 5) showed that the Aβ_1-40 aggregation pattern differed in the presence of biofilm seeds. These results suggest the existence of a co-aggregation phenomenon between Aβ_1-40 and a component of the biofilm matrix. This co-aggregation appears unproductive, as it limits biofilm formation by preventing matrix secretion and assembly (Fig. 2), similar to what was observed with E. coli (61).

Aggregation kinetics assays (Fig. 4) and AFM imaging (Fig. 5) with Aβ_1-42 showed no difference when incubated with P. gingivalis biofilm. This result could stem from faster Aβ_1-42 self-assembly kinetics compared to its potential interaction with a biofilm component. Indeed, Aβ_1-42 has a high aggregation/oligomerization potential and might favor homogeneous aggregation rather than cross-interactions (reviewed in reference 63), thereby not interfering with P. gingivalis biofilm matrix polymerization (Fig. 2).

Aβ_40/42 inclusions within the biofilm appeared unrelated to co-aggregation capacity, as we observed both Aβ_1-42 and Aβ_1-40 embedded within the matrix. These inclusions seemed to result from Aβ_40/42 aggregates trapped in the extracellular matrix following deposition (64), which would also explain the co-localization with exopolysaccharides. Only a small number of Aβ_1-40 inclusions were observed compared to Aβ_1-42, which might be due to the slower aggregation rate of Aβ_1-40 and the presence of gingipains produced by P. gingivalis. Indeed, gingipains can degrade monomeric, but not pre-aggregated Aβ (Fig. 6), since the hydrophobic structures between β-sheets of amyloid oligomers make them resistant to enzymatic breakdown (65). Thus, we hypothesize that there are fewer Aβ_1-40 inclusions embedded in the biofilm because Aβ_1-40 exists as monomers and low-weight oligomers for a longer time than Aβ_1-42, providing more chance for degradation by gingipains.

Proteolysis of antimicrobial peptides, including human peptides, is a key strategy of P. gingivalis to evade the host’s immune response (66, 67, 68). Interestingly, we observed that deletion of arginine-specific gingipains (RgpA/RgpB) but not of the lysine-specific gingipain (Kgp) negated Aβ degradation, despite lysine residues being present in both Aβ subtypes. These two types of gingipains exhibit differences in activity and inhibitory conditions, which may explain why only RgpA/RgpB appeared to degrade Aβ_40/42 under our conditions (69, 70). Further experiments are required to determine if it is also the case in situ.

Aβ_1-42 differs from Aβ_1-40 only by the addition of an isoleucine and an alanine in the C-terminal, which increases Aβ_1-42 overall aggregation rate into protofibrils and fibrils compared to Aβ_1-40 (71, 72). These properties are likely sufficient to explain the difference observed in our study. When co-inoculated with P. gingivalis, Aβ_1-42 auto-aggregates quickly into large, stable oligomers and fibrils, which reduce the likelihood of interacting with biofilm components and being degraded by the gingipains. These oligomers and fibrils would then integrate into the developing biofilm, promoting cell clumping and increasing overall matrix biomass. In contrast, Aβ_1-40 remains in an equilibrium of monomers and low-complexity oligomers for a significant period. This period enables interaction between the biofilm matrix components and Aβ_1-40, leading to alterations to their normal structure. Indeed, Aβ_1-40 fibrils formed unusual bundles rather than long single fibers, and the biofilm formed dispersed clumps rather than covering most of the available surface.

P. gingivalis biofilm components were identified in Aβ plaques isolated from AD patients, suggesting that a co-aggregation phenomenon with Aβ_1-40 and/or an integration of Aβ_1-42 aggregates in the matrix could occur within the brain (44, 45). While the mechanisms underlying biofilm presence in the CNS are still poorly understood, outer membrane vesicles of P. gingivalis are found in the brains of AD patients and contain important biofilm components, such as FimA (53, 73–76). Modulation of Aβ aggregation through physical interaction with viral or bacterial proteins is a key factor that may explain how microorganisms would contribute to AD development (61, 77, 78). P. gingivalis biofilms are also routinely observed on teeth (79), and consequently, our observations demonstrate a potential interaction between P. gingivalis and Aβ outside of the CNS. Aggregates of Aβ were observed on the tooth surface and embedded within the oral biofilm of patients with AD (43), findings that are consistent with our observations. These non-CNS interactions are important, since peripheral infections of P. gingivalis were also linked to AD-like dementia in mice (41, 52).

The P. gingivalis extracellular matrix component that interacts with Aβ_1-40 and alters its aggregation dynamics has yet to be identified. Also, FimA subtypes, capsular polysaccharides, and hemagglutinin expression vary between strains, which may influence biofilm effects on Aβ_40/42 (80, 81). Nonetheless, by shedding light on the interaction between Aβ_40/42 and P. gingivalis, our study offers a new perspective on this bacterium’s potential role in the onset of AD. Although the exact etiology remains unknown, a better understanding of the mechanisms underlying major risk factors, such as periodontitis, can offer valuable insights into AD prevention and treatment strategies.

MATERIALS AND METHODS

Aβ preparation

Aβ_1-40 and Aβ_1-42 (Genscript, NJ, USA) were prepared as previously described (82). Briefly, 1 mg of lyophilized Aβ_40/42 was dissolved in a solution of NH₄OH 10% (wt/vol) to 0.5 mg/mL. The peptides were incubated for 10 min at room temperature before being sonicated for 5 min and aliquoted in microcentrifuge tubes. The aliquots were then lyophilized overnight and stored at −80°C. While lyophilization should remove NH₄OH, we also verified that it did not influence biofilm formation at the maximum working concentration (Fig. S4).

Strain and media

Porphyromonas gingivalis ATCC 33277, KDP112, KDP128, and KDP129 were generously provided by Daniel Grenier (Université Laval, Québec). Strains KDP112 (∆rgpA ∆rgpB), KDP129 (∆kgp), and KDP128 (∆rgpA ∆rgpB ∆kgp) are gingipain deletion mutants in the P. gingivalis ATCC 33277 genetic background (83, 84). Cultures were routinely maintained in Tryptic Soy broth supplemented with hemin and vitamin K (TSBHK; 17 g/L casein peptone, 2.5 g/L K₂HPO₄, 2.5 g/L glucose, 5 g/L NaCl, 3 g/L soy peptone, 5 μg/mL hemin, and 1 μg/mL vitamin K) in a type-B vinyl COY anaerobic chamber with the following gas mix: 80% N₂:10% CO₂:10% H₂, in static conditions. For biofilm-inducing conditions, P. gingivalis was cultured statically in TSBHK supplemented with Tryptone 1% (wt/vol) (TSBHKT) (85).

Crystal violet assay

Crystal violet assays were used to assess biofilm production under different concentrations of Aβ_40/42 (86). First, 36 h cultures of P. gingivalis were centrifuged at 3,200 × g for 20 min and resuspended in TSBHKT. Aβ aliquots were resuspended in 60 mM NaOH and diluted to the proper concentration in the same medium. Biofilm cultures were then performed in polystyrene 48-well plates containing 200 μL of TSBHKT inoculated with P. gingivalis at OD₆₀₀ = 0.005 (5.625 × 10⁶ CFU/mL) and incubated for 24 h at 37°C. Of note, this concentration of P. gingivalis was selected after optimization for the most robust biofilm formation in our conditions. The remaining biofilm was washed with phosphate-buffered saline (PBS; 0.2 g/L KCl, 1.42 g/L Na₂HPO₄, and 0.24 g/L KH₂PO₄, 0.8 g/L NaCl, pH 7.4) before being covered with 200 μL of 0.01% (wt/vol) crystal violet for 20 min at room temperature. Each well was then washed with sterile deionized water to remove excess dye, resuspended in 33% (vol/vol) acetic acid, and quantified at OD₅₉₀.

Imaging of biofilm components

For confocal imaging of biofilm with Aβ_40/42, P. gingivalis was inoculated at OD₆₀₀ = 0.005 in 200 μL TSBHKT + 25 μg/mL Aβ in flat clear-bottom microscopy 96-well plates (Ibidi, Gräfelfing, Germany) for 24 h at 37°C. Supernatants from the cultures were discarded, and the remaining biofilms were washed with PBS. The biofilms were then fixed for 7 min in 200 μL of 4% (vol/vol) paraformaldehyde and then blocked with 200 μL of PBS + 2% (wt/vol) bovine serum albumin for 1 h at room temperature. For the staining of biofilm components under high Aβ concentrations (Fig. 2), we used Concanavalin A-Alexa647 (ConA) (1 h at room temperature, 50 μM; Thermo Fisher, USA), ThT (30 min at room temperature, 100 μM; Millipore Sigma, USA), and DAPI (30 min at room temperature, 1 μg/mL; Millipore Sigma, MA, USA). Pictures of the biofilms were taken using an Olympus FV3000 (Olympus, JP) confocal microscope at 20× magnification (PlanApo objective [20×/0.75 NA {numerical aperture}]) with the following laser settings: 405 nm (DAPI), 445 nm (ThT), and 640 nm (ConA). Laser intensity and sensor sensitivity were the same for all conditions. Image analysis used at least 25 images per condition, spread over three biological replicates. To observe Aβ aggregation within the biofilm (Fig. 3), we used Concanavalin A-Alexa647 (1 h at room temperature, 50 μM, Thermo Fisher, USA), 6C3 anti-amyloid beta peptide monoclonal antibody (1 h at room temperature, 1:1000, Millipore Sigma, MO, USA), Goat anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Antibody, Alexa Fluor 555 (1 h at room temperature, 2 μg/mL, Thermo Fisher, USA), and DAPI (30 min at room temperature, 1 μg/mL, Thermo Fisher, USA). The images were produced with the same confocal microscope at 40× magnification (PlanApo objective [40×/0.95 NA]) with the following laser settings: 405 nm (DAPI), 561 nm (AlexaFluor 555), and 640 nm (ConA), and the analysis was performed using at least 25 images over three biological replicates. Laser intensity and sensor sensitivity were the same for all conditions.

Microscopy analysis

For the fluorescence intensity measurements, Z-stack confocal images were initially preprocessed using Fiji. For each image, Z-sum intensity projection was applied, followed by a rolling ball background subtraction. Subsequently, whole-image intensity measurements were obtained using CellProfiler image analysis software. For the colocalization analysis, Fiji was used to perform maximum intensity projection on Z-stack images. Pixel colocalization was then measured on projection images using the Measure Colocalization module of CellProfiler 4.2.6 (87). Mander’s coefficient was used to measure the correlation between different fluorescence channels (88).

Biofilm seeds preparation

Biofilm fragment preparation was performed as described elsewhere (77). Briefly, multiple wells in a 96-well plate were inoculated with P. gingivalis 33277 in 200 μL of TSBHKT at OD₆₀₀ = 0.005. The biofilm was allowed to form under static conditions at 37°C for 24 h. The biofilm was then scooped in sterile PBS and vortexed at low intensity for 10 min with 25 μm glass beads to detach the cells from the extracellular matrix. It was then spun down at 3,200 × g for 10 min to remove most of the cells. The supernatant was then collected and quantified using Pierce BCA Protein Assay Kit (Thermo Scientific, MA, USA). Notably, proteomic analysis of this extracellular biofilm material confirmed the presence of all major and minor fimbrial subunits. CFU quantification revealed that for the same amount of proteinaceous material, there are 10³ fewer cells in this extracellular biofilm preparation than in the original biofilm (Fig. S5). This preparation was thereby named “seeds” and consists of a suspension of extracellular matrix components in PBS.

Aggregation kinetics assays with ThT

For aggregation kinetics assays with ThT, Aβ aliquots were resuspended in 10 μL of 60 mM NaOH and incubated for 5 min at room temperature. They were then diluted to 10 μg/mL in PBS containing 30 μM ThT and 200 μL were distributed in black 96-well polystyrene plates (Corning, NY, USA) in the presence of 500 ng protein/mL of biofilm seeds. The assay wells were surrounded by two layers of wells filled with water to prevent evaporation. Plates were read every 5 min using a TECAN SPARK plate reader at 440 ± 20 nm excitation and 485 ± 20 nm emission, with constant agitation at 37°C. For each assay, a negative control containing only biofilm seeds and ThT was included to account for fluorescence from the seeds. These values remained flat throughout the assay and were subtracted from the fluorescence intensity measured in the experimental wells (Fig. S6). The resulting curves were analyzed to assess kinetic values as previously reported elsewhere (89). Briefly, the aggregation kinetics results were fitted to a sigmoidal curve (equation 1), where k is the apparent aggregation constant and t_1/2 is the time to reach half-maximal fluorescence.

$${\displaystyle {\displaystyle Y=Y_0+\frac{Y_{\mathrm{m}\mathrm{a}\mathrm{x}}-Y_0}{1+e^{-\left(t-t_{1/2}\right)k}}}}$$ (1)

From this equation, it is also possible to measure the lag phase using equation 2.

$${\displaystyle {\displaystyle \text{Lag}=t_{1/2}-\frac{2}{k}}}$$ (2)

AFM

Experiments leading to AFM were performed in the same way as aggregation kinetics assays with ThT. Briefly, 100 μg/mL solutions of Aβ_40/42 were incubated in PB buffer (0.2 g/L KCl, 1.42 g/L Na₂HPO₄, and 0.24 g/L KH₂PO₄, pH 7.4) with 5 μg protein/mL of biofilm fragments. Aβ_40/42 samples were incubated in static conditions at 37°C for 3 h for Aβ_1-40 and 1 h for Aβ_1-42 before being adsorbed in a humid atmosphere on a clean mica surface (Electron Microscopy Sciences, PA, USA) for 30 min. After adsorption, mica slides were washed twice with ddH₂O and dried under a nitrogen stream. AFM was performed using a Veeco Dimension Icon microscope (Bruker, USA) using ScanAsyst air probes (Bruker, resonance frequency 70 kHz, spring constant 0.4 N/m, tip nominal radius 2 nm). For each condition, 15 images were captured over three biological replicates for an area size of 10 μm × 10 μm.

Gingipain assays

P. gingivalis WT and the gingipain mutants were statically grown in TSBHK for 48 h and adjusted to OD₆₀₀ = 1. Cells were then removed by centrifugation at 3,200 × g for 20 min. Ten microliters of P. gingivalis supernatant was then mixed with 190 μL of a 5 μg/mL Aβ_40/42 solution in PBS. Samples were incubated at 37°C for 16 h before being analyzed by dot blotting. Twenty microliters of sample was spotted onto a PVDF membrane and immunoblotted using MOAB-2 6C3 anti-amyloid beta peptide primary antibody (1 h at room temperature, 1:2,500, Sigma, MO, USA) and Peroxidase AffiniPure Goat Anti-Mouse IgG (H+L) (1 h at room temperature, 1:5,000; Jackson ImmunoResearch, PA, USA). Membranes were revealed using Clarity Max ECL Western Blotting Substrates (Bio-Rad, USA) and imaged through a Bio-Rad ChemiDoc using chemiluminescence. To observe the difference between non-aggregated and aggregated Aβ_40/42, a sample of each Aβ subtype was initially incubated in PBS at 37°C for 24 h. This sample was compared to a fresh aliquot of Aβ and analyzed using the method described above. Densitometry analysis for each sample was performed using the integrated intensity values provided in ImageJ. Briefly, identical areas were overlaid on the dot blot images, and integrated intensity was measured for each dot.

Statistical analysis

Statistical analyses were performed in GraphPad Prism 10. Comparisons were done using Student’s t-test, one-way ANOVA, Mann-Whitney or Kruskal-Wallis tests, all with 95% confidence intervals. Normality was assessed using Shapiro-Wilk’s normality test, and each result has been replicated in at least three independent biological replicates.

SUPPLEMENTAL MATERIAL

The following material is available online at https://doi.org/10.1128/spectrum.01981-25.

Supplemental figures. spectrum.01981-25-s0001.pdf.

Figures S1 to S6.

ASM does not own the copyrights to Supplemental Material that may be linked to, or accessed through, an article. The authors have granted ASM a non-exclusive, world-wide license to publish the Supplemental Material files. Please contact the corresponding author directly for reuse.