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. 2015 Dec 19;3:69.
doi: 10.1186/s40168-015-0136-z.

Protein Relative Abundance Patterns Associated With Sucrose-Induced Dysbiosis Are Conserved Across Taxonomically Diverse Oral Microcosm Biofilm Models of Dental Caries

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Free PMC article

Protein Relative Abundance Patterns Associated With Sucrose-Induced Dysbiosis Are Conserved Across Taxonomically Diverse Oral Microcosm Biofilm Models of Dental Caries

Joel D Rudney et al. Microbiome. .
Free PMC article

Abstract

Background: The etiology of dental caries is multifactorial, but frequent consumption of free sugars, notably sucrose, appears to be a major factor driving the supragingival microbiota in the direction of dysbiosis. Recent 16S rRNA-based studies indicated that caries-associated communities were less diverse than healthy supragingival plaque but still displayed considerable taxonomic diversity between individuals. Metagenomic studies likewise have found that healthy oral sites from different people were broadly similar with respect to gene function, even though there was an extensive individual variation in their taxonomic profiles. That pattern may also extend to dysbiotic communities. In that case, shifts in community-wide protein relative abundance might provide better biomarkers of dysbiosis that can be achieved through taxonomy alone.

Results: In this study, we used a paired oral microcosm biofilm model of dental caries to investigate differences in community composition and protein relative abundance in the presence and absence of sucrose. This approach provided large quantities of protein, which facilitated deep metaproteomic analysis. Community composition was evaluated using 16S rRNA sequencing and metaproteomic approaches. Although taxonomic diversity was reduced by sucrose pulsing, considerable inter-subject variation in community composition remained. By contrast, functional analysis using the SEED ontology found that sucrose induced changes in protein relative abundance patterns for pathways involving glycolysis, lactate production, aciduricity, and ammonia/glutamate metabolism that were conserved across taxonomically diverse dysbiotic oral microcosm biofilm communities.

Conclusions: Our findings support the concept of using function-based changes in protein relative abundance as indicators of dysbiosis. Our microcosm model cannot replicate all aspects of the oral environment, but the deep level of metaproteomic analysis it allows makes it suitable for discovering which proteins are most consistently abundant during dysbiosis. It then may be possible to define biomarkers that could be used to detect at-risk tooth surfaces before the development of overt carious lesions.

Figures

Fig. 1
Fig. 1
Mean real-time pH curves for paired NS (green) and WS (red) microcosms from 12 subjects. Readings were taken once every 15 min for 70 h. The error bars represent standard deviations. The blue arrows denote time points at which the WS microcosms were pulsed with sucrose. The purple arrow indicates the approximate time when samples of NS and WS biofilms were collected for protein extraction
Fig. 2
Fig. 2
Principal coordinates plot of results for taxonomic data obtained by HOMINGS analysis. The Bray-Curtis distance metric was used. The point labels include the subject number followed by the type of sample. Plaque inoculums (P) are shown in blue, NS microcosms (NS) are shown in green, and WS microcosms (WS) are shown in red. The blue, green, and red ellipses are arbitrary and provided solely to aid visualization of each group
Fig. 3
Fig. 3
Principal coordinates plot of results for species-level taxonomic assignments by MEGAN5 LCA analysis. The Bray-Curtis distance metric was used. The point labels include the subject number followed by the type of sample. NS microcosms (NS) are shown in green, and WS microcosms (WS) are shown in red. The green and red ellipses are arbitrary and provided solely to aid visualization of each group
Fig. 4
Fig. 4
Principal coordinates plot of results for proteins identified by MEGAN5 SEED analysis. The Bray-Curtis distance metric was used. The point labels include the subject number followed by the type of sample. NS microcosms (NS) are shown in green, and WS microcosms (WS) are shown in red. The green and red ellipses are arbitrary and provided solely to aid visualization of each group
Fig. 5
Fig. 5
Simplified Galaxy-P workflow. In Part 1, RAW files for each NS and WS pair were run in parallel within a single workflow to generate a second-step search database for each pair. In Part 2, the spectra for the NS and WS samples then were searched independently and the search outputs were processed to generate inputs for MEGAN analysis

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