Background Periodontitis is a chronic inflammatory disease affecting more than 50% of the global population, resulting in irreversible gum damage, alveolar bone loss and ultimately tooth loss. Periodontitis arises from stable, multi-species biofilms whose pathogenicity is driven by emergent ecological interactions persistent to antimicrobial perturbations. Fusobacterium spp. are considered key microbial components that provide scaffolding for this ecological niche, which includes the pathobionts Tannerella forsythia, Prevotella intermedia and Porphyromonas gingivalis.Objectives To examined how oral microbial interactions shape periodontal biofilms and whether selectively targeting Fusobacterium polymorphum by bacteriophages can disrupt this pathogenic community structure.Materials and methods In vitro biofilms were established using (i) F. polymorphum, T. forsythia and P. intermedia on their own, (ii) T. forsythia and P. intermedia in dual-species biofilms with F. polymorphum and (iii) four-species complex biofilms involving F. polymorphum, T. forsythia, P. intermedia and P. gingivalis. The biofilms were then exposed to the F. polymorphum-specific bacteriophage FNU1 to assess the ecological impact of targeted viral predation on a single member of the biofilm community. Biofilm formation, spatial organisation and microbial interactions were visualised by confocal laser scanning microscopy using CellTrace™ proliferation assays and live-dead staining. Community biofilm biomass was quantified using 0.1% crystal violet staining.Results Multi-species biofilms displayed enhanced biomass and increased cell density relative to simpler communities. Disruption of F. polymorphum by bacteriophage FNU1 led to significant reductions in total biofilm biomass and altered cell density in the single-species F. polymorphum biofilm as well as dual- and four-species complex biofilms.Conclusion Our findings support a role for F. polymorphum-specific bacteriophages in destabilising complex biofilms of periodontal pathobionts. They highlight the importance of F. polymorphum in community dynamics in microbial biofilms and that its precision targeting results in ecological perturbation with the potential to reverse dysbiosis in chronic inflammation in periodontitis.

The human microbiome is a foundational and dynamic foundation for several health-related functions and disease processes. Advances in microbiome sequencing have enabled the characterization of microbial communities in several niches. Longitudinal microbiome studies further strive to discover clinically informative microbial community trajectories. However, these data are fraught with dropout events, high noise, and irregular sampling that limit and prevent the use of many available longitudinal analysis tools. To address these challenges, we introduce Bidirectional GRU-ODE-Bayes (BGOB), a deep learning framework developed for longitudinal microbiome interpolation. BGOB combines bidirectional information flow and ODE-based continuous modeling to jointly interpolate and smoothen trends across individual participants, providing uniform, denoised time intervals across patients. BGOB enables vastly improved performance in differential abundance testing and time-to-event analysis, and makes possible longitudinal analyses requiring uniformity, such as lead-lag detection and temporal clustering. After interpolation, previously low-powered datasets are able to broadly recapitulate known microbiology and elucidate interacting microbial communities. We highlight several associations between microbial taxa and disease, including novel species associated with Early Childhood Caries and disruption of key healthy gut microbiota in Inflammatory Bowel Disease. The BGOB package is publicly available at https://github.com/Rachel-Lyu/BGOB\_n\_test ### Competing Interest Statement The authors have declared no competing interest.

INTRODUCTION:Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental caries in young children. Valid and reliable diagnostic or prognostic tools that enable accurate individualised prediction of current or future dental caries are essential for facilitating personalised caries prevention and early intervention. However, no efficacious tools currently exist in early childhood-the optimal period for disease prevention. We aim to develop and validate diagnostic and prognostic prediction tools for dental caries in young children, using a combination of environmental, physical, behavioural and biological early life data. METHODS AND ANALYSIS:Data sources include two prospective studies, with a total sample size of approximately 600 children. These cohorts have collected detailed demographic, antenatal, perinatal and postnatal data from medical records and parent-completed questionnaires and biological samples including a dental plaque swab. Candidate predictor variables will include sociodemographic characteristics, health history, behavioural and microbiological characteristics. The outcome variable will be the presence, incidence or severity of dental caries diagnosed using the International Caries Detection and Assessment System. Statistical and machine learning approaches will be used for selection of predictor variables and model development. Internal validation will be conducted using resampling methods (i.e., bootstrapping) and nested cross-validation. Model performance will be evaluated using standard performance metrics such as accuracy, discrimination and calibration. Where feasible, external validation will be performed in an independent cohort. Model development and reporting will be guided by the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias Assessment Tool (PROBAST) guidelines. ETHICS AND DISSEMINATION:This study has ethical and governance approval from The Royal Children's Hospital Melbourne Human Research Ethics Committee (HREC/111803/RCHM-2024). Results of this study will be published in peer-reviewed journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER:Infant2Child: ACTRN12622000205730-pre-results; MisBair: NCT01906853-post results.

Candida species and Staphylococcus aureus coexist in nosocomial infections. These interkingdom interactions are associated with oral biofilm formation, leading to various oral diseases. This study elucidated the interkingdom interactions of these microorganisms, particularly their aggregation and biofilm formation, in three different media. Candida auris, Candida albicans, Candida lusitaniae, Candida dubliniensis, Candida parapsilosis, Candida glabrata and S. aureus were used in this study. Aggregation assays were conducted to determine planktonic interaction, and biofilm assays were performed to investigate intra- and interkingdom interactions in a static biofilm environment. Most Candida spp. exhibited a high auto-aggregation percentage in brain heart infusion broth supplemented with yeast extract (BHIYE). In addition, co-culture biofilm with S. aureus significantly reduced the total cell counts of Candida spp. compared to mono-culture (p < 0.05). In conclusion, co-aggregation, biofilm biomass and total cell count were species- and growth medium-dependent, and S. aureus interacted antagonistically with Candida spp.

Background:There is no specific cure for periodontitis and treatment is symptomatic, primarily by physical removal of the subgingival plaque biofilm. Current non-surgical periodontal therapy becomes less effective as the periodontal pocket depth increases and as such new adjunctive treatments are required. The development of antibiotic resistance has driven a recent resurgence of interest in bacteriophage therapy. Methods:Here we review the published literature with a focus on the subgingival phageome, key oral pathobionts and the dysbiotic nature of periodontitis leading to the emergence of synergistic, proteolytic and inflammophilic bacterial species in subgingival plaque. We discuss the opportunities available, the barriers and the steps needed to develop bacteriophage therapy as an adjunctive treatment for periodontitis. Results:The oral phageome (or virome) is diverse, featuring abundant bacteriophage, that could target key subgingival bacteria. Yet to date few bacteriophages have been isolated and characterised from oral bacterial species, although many more have been predicted by genomic analyses. Bacteriophage therapy has yet to be tested against chronic diseases that are caused by dysbiosis of the endogenous microbial communities. Conclusion:To be effective as an adjunctive treatment for periodontitis, bacteriophage therapy must cause the collapse of the dysbiotic bacterial community, thereby resolving inflammation and enabling the reestablishment of a health-associated mutualistic subgingival bacterial community. The isolation and characterisation of novel oral bacteriophage is an essential first step in this process.

Background:The targeted manipulation of the microbiome using bacteriophages represents a novel approach for addressing antibiotic resistance and polymicrobial diseases. Objective:To isolate and characterise bacteriophages for key bacteria associated with pathogenic periodontal biofilms. Design:Using standard microbiological and bioinformatics techniques, this study isolated and characterized lytic (FNU2 and FNU3) and temperate (FNU4) bacteriophages specific to Fusobacterium nucleatum, a key bacterium in oral biofilms linked to periodontitis and a range of cancers. Results:Morphological and genomic analyses revealed distinct features, with FNU2 and FNU3 classified as Latrobevirus and FNU4 as an unclassified Caudoviricetes. Comparative bioinformatic analysis revealed various defence and anti-defence systems in bacterial hosts and bacteriophages, highlighting complex interactions. Functional assays demonstrated the efficacy of these bacteriophages in disrupting single-species F. nucleatum biofilms and dual-species biofilms of F. nucleatum and Porphyromonas gingivalis. Conclusion:These findings highlight the potential of F. nucleatum-specific bacteriophages as precise tools for microbiome modulation in chronic diseases such as periodontitis and cancer.

Information generated from longitudinally sampled microbial data has the potential to illuminate important aspects of development and progression for many human conditions and diseases. Identifying microbial biomarkers and their time-varying effects can not only advance our understanding of pathogenetic mechanisms, but also facilitate early diagnosis and guide optimal timing of interventions. However, longitudinal predictive modeling of highly noisy and dynamic microbial data (e.g. metagenomics) poses analytical challenges.To overcome these challenges, we introduce a robust and interpretable machine-learning-based longitudinal microbiome analysis framework, LP-Micro, that encompasses (i) longitudinal microbial feature screening via a polynomial group lasso, (ii) disease outcome prediction implemented via machine learning methods (e.g. XGBoost, deep neural networks), and (iii) interpretable association testing between time points, microbial features, and disease outcomes via permutation feature importance. We demonstrate in simulations that LP-Micro can not only identify incident disease-related microbiome taxa, but also offers improved prediction accuracy compared with existing approaches. Applications of LP-Micro in two longitudinal microbiome studies with clinical outcomes of childhood dental disease and weight loss following bariatric surgery yield consistently high prediction accuracy. Moreover, LP-Micro highlights critical time points and associated microbial changes: oral microbial changes, including Streptococcus mutans, are most informative for predicting childhood dental disease at around 39 months of age, while gut microbial changes shortly after bariatric surgery strongly predict future weight loss. These findings are both informative and aligned with clinical expectations. The tool LP-Micro can be seen at https://github.com/IV012/LPMicro.

BACKGROUND:Social disadvantage leads to dental caries during childhood. AIM:This study investigated whether dental caries occur earlier in children from households experiencing social disadvantage than those not experiencing social disadvantage. DESIGN:The overall risk of, and relative time to, early childhood caries (ECC) according to sociodemographic characteristics in Victoria, Australia, was quantified. Records for 134 463 children in Victoria, Australia, from 2009 to 2019 were analysed. Time ratios (TR) and hazard ratios (HR) of carious lesion(s) in early childhood were estimated. RESULTS:Compared with reference groups, Indigenous children had an adjusted TR of 0.80 (95% CI: 0.78, 0.82), children from households with languages other than English had an adjusted TR of 0.83 (95% CI: 0.82, 0.84), and dependants of concession cardholders had an adjusted TR of 0.81 (95% CI: 0.80, 0.81); therefore, 20%, 17% and 19% reduced times to the first carious lesion, respectively. The estimated HRs were 1.57 (95% CI: 1.49, 1.67) for Indigenous children, 1.46 (95% CI: 1.42, 1.50) for children from households with other languages and 1.57 (CI: 1.53, 1.60) for dependants of concession cardholders. CONCLUSION:Preventive oral health interventions must be targeted early in children from households experiencing social disadvantage to avoid social inequities in ECC.

Information generated from longitudinally-sampled microbial data has the potential to illuminate important aspects of development and progression for many human conditions and diseases. Identifying microbial biomarkers and their time-varying effects can not only advance our understanding of pathogenetic mechanisms, but also facilitate early diagnosis and guide optimal timing of interventions. However, longitudinal predictive modeling of highly noisy and dynamic microbial data (e.g., metagenomics) poses analytical challenges. To overcome these challenges, we introduce a robust and interpretable machine-learning-based longitudinal microbiome analysis framework, LP-Micro, that encompasses: (i) longitudinal microbial feature screening via a polynomial group lasso, (ii) disease outcome prediction implemented via machine learning methods (e.g., XGBoost, deep neural networks), and (iii) interpretable association testing between time points, microbial features, and disease outcomes via permutation feature importance. We demonstrate in simulations that LP-Micro can not only identify incident disease-related microbiome taxa but also offers improved prediction accuracy compared to existing approaches. Applications of LP-Micro in two longitudinal microbiome studies with clinical outcomes of childhood dental disease and weight loss following bariatric surgery yield consistently high prediction accuracy. The identified critical early predictive time points are informative and aligned with clinical expectations.

Periodontitis is a chronic inflammatory disease driven by dysbiosis in subgingival microbial communities leading to increased abundance of a limited number of pathobionts, including Porphyromonas gingivalis and Treponema denticola. Oral health, particularly periodontitis, is a modifiable risk factor for Alzheimer disease (AD) pathogenesis, with components of both these bacteria identified in postmortem brains of persons with AD. Repeated oral inoculation of mice with P. gingivalis results in brain infiltration of bacterial products, increased inflammation, and induction of AD-like biomarkers. P. gingivalis displays synergistic virulence with T. denticola during periodontitis. The aim of the current study was to determine the ability of P. gingivalis and T. denticola, grown in physiologically relevant conditions, individually and in combination, to induce AD-like pathology following chronic oral inoculation of female mice over 12 weeks. P. gingivalis alone significantly increased all 7 brain pathologies examined: neuronal damage, activation of astrocytes and microglia, expression of inflammatory cytokines interleukin 1β (IL-1β) and interleukin 6 and production of amyloid-β plaques and hyperphosphorylated tau, in the hippocampus, cortex and midbrain, compared to control mice. T. denticola alone significantly increased neuronal damage, activation of astrocytes and microglia, and expression of IL-1β, in the hippocampus, cortex and midbrain, compared to control mice. Coinoculation of P. gingivalis with T. denticola significantly increased activation of astrocytes and microglia in the hippocampus, cortex and midbrain, and increased production of hyperphosphorylated tau and IL-1β in the hippocampus only. The host brain response elicited by oral coinoculation was less than that elicited by each bacterium, suggesting coinoculation was less pathogenic.

Periodontitis is a common chronic inflammatory disease, affecting approximately 19% of the global adult population. A relationship between periodontal disease and Alzheimer disease has long been recognized, and recent evidence has been uncovered to link these 2 diseases mechanistically. Periodontitis is caused by dysbiosis in the subgingival plaque microbiome, with a pronounced shift in the oral microbiota from one consisting primarily of Gram-positive aerobic bacteria to one predominated by Gram-negative anaerobes, such as Porphyromonas gingivalis. A common phenomenon shared by all bacteria is the release of membrane vesicles to facilitate biomolecule delivery across long distances. In particular, the vesicles released by P gingivalis and other oral pathogens have been found to transport bacterial components across the blood-brain barrier, initiating the physiologic changes involved in Alzheimer disease. In this review, we summarize recent data that support the relationship between vesicles secreted by periodontal pathogens to Alzheimer disease pathology.

The cause of Alzheimer's disease (AD), and the pathophysiological mechanisms involved, remain major unanswered questions in medical science. Oral bacteria, especially those species associated with chronic periodontitis and particularly Porphyromonas gingivalis, are being linked causally to AD pathophysiology in a subpopulation of susceptible individuals. P. gingivalis produces large amounts of proteolytic enzymes, haem and iron capture proteins, adhesins and internalins that are secreted and attached to the cell surface and concentrated onto outer membrane vesicles (OMVs). These enzymes and adhesive proteins have been shown to cause host tissue damage and stimulate inflammatory responses. The ecological and pathophysiological roles of P. gingivalis OMVs, their ability to disperse widely throughout the host and deliver functional proteins lead to the proposal that they may be the link between a P. gingivalis focal infection in the subgingivae during periodontitis and neurodegeneration in AD. P. gingivalis OMVs can cross the blood brain barrier and may accelerate AD-specific neuropathology by increasing neuroinflammation, plaque/tangle formation and dysregulation of iron homeostasis, thereby inducing ferroptosis leading to neuronal death and neurodegeneration.

Fusobacterium nucleatum is an important oral bacterium that has been linked to the development of chronic diseases such as periodontitis and colorectal cancer. In periodontal disease, F. nucleatum forms the backbone of the polymicrobial biofilm and in colorectal cancer is implicated in aetiology, metastasis and chemotherapy resistance. The control of this bacteria may be important in assisting treatment of these diseases. With increased rates of antibiotic resistance globally, there is need for development of alternatives such as bacteriophages, which may complement existing therapies. Here we describe the morphology, genomics and functional characteristics of FNU1, a novel bacteriophage lytic against F. nucleatum . Transmission electron microscopy revealed FNU1 to be a large Siphoviridae virus with capsid diameter of 88 nm and tail of approximately 310 nm in length. Its genome was 130914 bp, with six tRNAs, and 8% of its ORFs encoding putative defence genes. FNU1 was able to kill cells within and significantly reduce F. nucleatum biofilm mass. The identification and characterisation of this bacteriophage will enable new possibilities for the treatment and prevention of F. nucleatum associated diseases to be explored.

Abstract Background Periodontitis, a chronic disease that progresses over years, is a modifiable risk factor for Alzheimer’s disease (AD). Periodontitis is caused by endogenous oral pathobionts, including Porphyromonas gingivalis (Pg) and Treponema denticola (Td), that have a synergistic relationship resulting in increased virulence. Pg and Td proteins and DNA have been detected in post-mortem brains of AD patients. However it is unclear if these bacteria infect the brain or if the detected bacterial products are on membrane vesicles (MVs); spherical nanostructures released from bacteria. The aims of this work were to determine whether intact bacterial cells were in brains of mice after chronic oral inoculation with these organisms; whether Td enhanced the ability of Pg products to penetrate the brain and whether Td alone induced AD biomarkers Methods C57BL/6 mice were orally inoculated 3 times/week for 12 weeks with either Pg, Td, or Pg + Td cells in a 2:1 ratio, or sham inoculated as a negative control. Mice were culled and their brains dissected, with one hemisphere prepared for immunohistochemistry (IHC) as FFPE tissue and probed with antibodies to amyloid beta (Aβ), phospho-Tau (p-Tau) and the Pg surface protein RgpA. The other hemisphere had the hippocampus removed for transmission electron microscopy (TEM) analysis. Results Pg alone and Pg + Td inoculated mice showed significant increases in alveolar bone loss compared with the uninoculated control. No whole bacterial cells were detected in any of the brains of inoculated mice including those that were IHC positive for RgpA. RgpA immunoactivity was not significantly different in brains of mice that received Pg alone or the Pg+Td combination. Aβ and p-Tau were detected in all mice with an increasing magnitude in uninoculated < Td inoculated ≤ Pg inoculated ≤ Pg+Td inoculated. Conclusion Conclusions: Repeated oral inoculation of mice with Pg alone and Pg + Td resulted in periodontitis, as determined by alveolar bone loss. The lack of whole bacterial cells in the brain argues against a direct infection mechanism of AD initiation by the oral bacteria Pg and Td. Our data are consistent with the observed AD-like pathology in the brain resulting from a focal infection of Pg and/or Td in the mouth mediated by MV penetration of the brain. Disclosures All Authors: No reported disclosures

Despite recent advances in the development of orthopedic devices, implant-related failures that occur as a result of poor osseointegration and nosocomial infection are frequent. In this study, we developed a multiscale titanium (Ti) surface topography that promotes both osteogenic and mechano-bactericidal activity using a simple two-step fabrication approach. The response of MG-63 osteoblast-like cells and antibacterial activity toward Pseudomonas aeruginosa and Staphylococcus aureus bacteria was compared for two distinct micronanoarchitectures of differing surface roughness created by acid etching, using either hydrochloric acid (HCl) or sulfuric acid (H2SO4), followed by hydrothermal treatment, henceforth referred to as either MN-HCl or MN-H2SO4. The MN-HCl surfaces were characterized by an average surface microroughness (Sa) of 0.8 ± 0.1 μm covered by blade-like nanosheets of 10 ± 2.1 nm thickness, whereas the MN-H2SO4 surfaces exhibited a greater Sa value of 5.8 ± 0.6 μm, with a network of nanosheets of 20 ± 2.6 nm thickness. Both micronanostructured surfaces promoted enhanced MG-63 attachment and differentiation; however, cell proliferation was only significantly increased on MN-HCl surfaces. In addition, the MN-HCl surface exhibited increased levels of bactericidal activity, with only 0.6% of the P. aeruginosa cells and approximately 5% S. aureus cells remaining viable after 24 h when compared to control surfaces. Thus, we propose the modulation of surface roughness and architecture on the micro- and nanoscale to achieve efficient manipulation of osteogenic cell response combined with mechanical antibacterial activity. The outcomes of this study provide significant insight into the further development of advanced multifunctional orthopedic implant surfaces.

BACKGROUND:Pre-clinical evidence implicates oral bacteria in the pathogenesis of Alzheimer's disease (AD), while clinical studies show diverse results.OBJECTIVE:To comprehensively assess the association between oral bacteria and AD with clinical evidence.METHODS:Studies investigating the association between oral bacteria and AD were identified through a systematic search of six databases PubMed, Embase, Cochrane Central Library, Scopus, ScienceDirect, and Web of Science. Methodological quality ratings of the included studies were performed. A best evidence synthesis was employed to integrate the results. When applicable, a meta-analysis was conducted using a random-effect model.RESULTS:Of the 16 studies included, ten investigated periodontal pathobionts and six were microbiome-wide association studies. Samples from the brain, serum, and oral cavity were tested. We found over a ten-fold and six-fold increased risk of AD when there were oral bacteria (OR = 10.68 95% CI: 4.48-25.43; p < 0.00001, I2 = 0%) and Porphyromonas gingivalis (OR = 6.84 95% CI: 2.70-17.31; p < 0.0001, I2 = 0%) respectively in the brain. While AD patients exhibited lower alpha diversity of oral microbiota than healthy controls, the findings of bacterial communities were inconsistent among studies. The best evidence synthesis suggested a moderate level of evidence for an overall association between oral bacteria and AD and for oral bacteria being a risk factor for AD.CONCLUSION:Current evidence moderately supports the association between oral bacteria and AD, while the association was strong when oral bacteria were detectable in the brain. Further evidence is needed to clarify the interrelationship between both individual species and bacterial communities and the development of AD.

Abstract The current early childhood caries (ECC) case definition contains a substantial degree of clinical heterogeneity, and to address this, we sought to identify clinical subtypes of the disease. We used tooth surface-level dental caries experience from a discovery and 3 replication community-based cohorts of 3-to-5-year-old children (N=226,471). We identified five disease subtypes with distinct patterns of caries lesion intraoral distribution that largely replicated across cohorts. These subtypes were associated with established caries risk factors (e.g., history of nighttime bottle-feeding), showed familial concordance and microbiome differences, and predicted dental caries experience 7 years after subtype assignment. Notably, classification of children in these subgroups can be achieved by inspecting small sets of easily examinable tooth surfaces with reasonable accuracy. Collectively, our findings provide evidence for generalizable and clinically recognizable subtypes of ECC. Etiology, targeted prevention, and optimal management of these subtypes should be systematically investigated in future studies.

Background Human microbiomes assemble in an ordered, reproducible manner yet there is limited information about early colonisation and development of bacterial communities that constitute the oral microbiome. Aim The aim of this study was to determine the effect of exposure to breastmilk on assembly of the infant oral microbiome during the first 20 months of life. Methods The oral microbiomes of 39 infants, 13 who were never breastfed and 26 who were breastfed for more than 10 months, from the longitudinal VicGeneration birth cohort study, were determined at four ages. In total, 519 bacterial taxa were identified and quantified in saliva by sequencing the V4 region of the bacterial 16S rRNA genes. Results There were significant differences in the development of the oral microbiomes of never breastfed and breastfed infants. Bacterial diversity was significantly higher in never breastfed infants at 2 months, due largely to an increased abundance of Veillonella and species from the Bacteroidetes phylum compared with breastfed infants. Conclusion These differences likely reflect breastmilk playing a prebiotic role in selection of early-colonising, health-associated oral bacteria, such as the Streptococcus mitis group. The microbiomes of both groups became more heterogenous following the introduction of solid foods.