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      The effect of dental material type and masticatory forces on periodontitis-derived subgingival microbiomes

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          Abstract

          Restorative dental materials can frequently extend below the gingival margin, serving as a potential haven for microbial colonization, and altering the local oral microbiome to ignite infection. However, the contribution of dental materials on driving changes of the composition of the subgingival microbiome is under-investigated. This study evaluated the microbiome-modulating properties of three biomaterials, namely resin dental composites (COM), antimicrobial piezoelectric composites (BTO), and hydroxyapatite (HA), using an optimized in vitro subgingival microbiome model derived from patients with periodontal disease. Dental materials were subjected to static or cyclic loading (mastication forces) during biofilm growth. Microbiome composition was assessed by 16S rRNA gene sequencing. Dysbiosis was measured in terms of subgingival microbial dysbiosis index (SMDI). Biomaterials subjected to cyclic masticatory loads were associated with enhanced biofilm viability except on the antibacterial composite. Biomaterials held static were associated with increased biofilm biomass, especially on HA surfaces. Overall, the microbiome richness (Chao index) was similar for all the biomaterials and loading conditions. However, the microbiome diversity (Shannon index) for the HA beams was significantly different than both composites. In addition, beta diversity analysis revealed significant differences between composites and HA biomaterials, and between both loading conditions (static and cyclic). Under static conditions, microbiomes formed over HA surfaces resulted in increased dysbiosis compared to composites through the enrichment of periopathogens, including Porphyromonas gingivalis, Porphyromonas endodontalis, and Fretibacterium spp., and depletion of commensals such as Granulicatella and Streptococcus spp. Interestingly, cyclic loading reversed the dysbiosis of microbiomes formed over HA (depletion of periopathogenes) but increased the dysbiosis of microbiomes formed over composites (enrichment of Porphyromonas gingivalis and Fusobacterim nucleatum). Comparison of species formed on both composites (control and antibacterial) showed some differences. Commercial composites enriched Selenomonas spp. and depleted Campylobacter concisus. Piezoelectric composites effectively controlled the microbiome viability without significantly impacting the species abundance. Findings of this work open new understandings of the effects of different biomaterials on the modulation of oral biofilms and the relationship with oral subgingival infections.

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          QIIME allows analysis of high-throughput community sequencing data.

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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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                Author and article information

                Contributors
                Journal
                Biofilm
                Biofilm
                Biofilm
                Elsevier
                2590-2075
                08 May 2024
                June 2024
                08 May 2024
                : 7
                : 100199
                Affiliations
                [a ]Smart Biomaterials Laboratory, Department of Oral Health Sciences, Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA
                [b ]Oral Microbiome Research Laboratory, Department of Oral Health Sciences, Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA
                [c ]Department of Microbiology, Forsyth Institute, Cambridge, MA, USA
                [d ]Bioengineering Department, College of Engineering, Temple University, Philadelphia, PA, USA
                Author notes
                [* ]Corresponding author. 3223 North Broad Street, AEGD Clinic - Room 2E15, Philadelphia, PA, 19140, USA. sorrego@ 123456temple.edu
                [** ]Corresponding author. alhebshi@ 123456temple.edu
                Article
                S2590-2075(24)00024-8 100199
                10.1016/j.bioflm.2024.100199
                11127099
                38800100
                24435808-3236-40b5-851c-9b95684837c2
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 9 March 2024
                : 19 April 2024
                : 4 May 2024
                Categories
                Article

                biomaterial-microbiome interactions,oral microbiome,periodontitis,microbiota,dysbiosis,dental materials,biomaterials,biofilm,oral infections,piezoelectric,barium titanate,hydroxyapatite,composites,subgingival

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