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. 2024 Dec 23;12(12):2668.
doi: 10.3390/microorganisms12122668.

The Effect of Oral Care Product Ingredients on Oral Pathogenic Bacteria Transcriptomics Through RNA-Seq

Affiliations

The Effect of Oral Care Product Ingredients on Oral Pathogenic Bacteria Transcriptomics Through RNA-Seq

Ping Hu et al. Microorganisms. .

Abstract

Various ingredients are utilized to inhibit the growth of harmful bacteria associated with cavities, gum disease, and bad breath. However, the precise mechanisms by which these ingredients affect the oral microbiome have not been fully understood at the molecular level. To elucidate the molecular mechanisms, a high-throughput bacterial transcriptomics study was conducted, and the gene expression profiles of six common oral bacteria, including two Gram-positive bacteria (Actinomyces viscosus, Streptococcus mutans) and four Gram-negative bacteria (Porphyromonas gingivalis, Tannerella forsythia, Fusobacterium nucleatum, and Prevotella pallens), were analyzed. The bacteria were exposed to nine common ingredients in toothpaste and mouthwash at different concentrations (stannous fluoride, stannous chloride, arginine bicarbonate, cetylpyridinium chloride, sodium monofluorophosphate, sodium fluoride, potassium nitrate, zinc phosphate, and hydrogen peroxide). Across 78 ingredient-microorganism pairs with 360 treatment-control combinations, significant and reproducible ingredient-based transcriptional response profiles were observed, providing valuable insights into the effects of these ingredients on the oral microbiome at the molecular level. This research shows that oral care product ingredients applied at biologically relevant concentrations manifest differential effects on the transcriptomics of bacterial genes in a variety of oral periodontal pathogenic bacteria. Stannous fluoride, stannous chloride, and cetylpyridinium chloride showed the most robust efficacy in inhibiting the growth or gene expression of various bacteria and pathogenic pathways. Combining multiple ingredients targeting different mechanisms might be more efficient than single ingredients in complex oral microbiomes.

Keywords: RNA-Seq; bacteria; cetylpyridinium chloride; oral care; pathogen; stannous fluoride; transcriptomics; virulence factors.

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Conflict of interest statement

All authors are current employees of Procter & Gamble. The research cited in this document was funded by Procter & Gamble.

Figures

Figure 1
Figure 1
Heatmap of treatment-induced total bacterial RNA yield fold change compared to untreated control indicated that stannous and hydrogen peroxide down-regulated RNA synthesis in all tested oral bacteria.
Figure 2
Figure 2
Heatmap of treatment-induced differential expressed gene ratio (DEGR) showed stannous compounds induced strong gene expression changes in all tested oral bacteria.
Figure 3
Figure 3
Microbial transcriptomics response to oral hygiene product ingredients is used to evaluate and rank material for treatment effect, indicating that stannous is the top treatment for these groups of tested bacteria. (a) Heatmap of log2 fold change of all the 12,546 genes from the six tested bacteria strains. (b) PCA plot of the combined gene expression data from all the 12,546 genes, showing all the tested materials and their relative distance to the control samples. (c) The rank treatment effect of different materials based on the normalized distance to control based on the PCA plot indicated that the stannous compounds are a top treatment for disturbing microbial gene expression, and the color matches the PCA plot.
Figure 4
Figure 4
Treatment-induced transcriptomics changes in genes involved in LPS biosynthesis. (a) Heatmap of log2 fold change of P. gingivalis genes involved in LPS biosynthesis (Lipid A, Core, O-Antigen, or APS biosynthesis) and LPS export compared to no-treatment controls. (b) KEGG pathway mapping of the first four genes of P. gingivalis LPS biosynthesis pathway highlights gene expression changes induced by ArgB, H2O2, SnCl2_L, and SnF2_L, showing that stannous compounds down-regulated LPS biosynthesis. ArgB up-regulated LPS biosynthesis. (c) Bar plot of the log2 fold change of P. gingivalis LpxA gene, the first step for Lipid A biosynthesis, a critical component for LPS biosynthesis. (d) Bar plot of the log2 fold change of P. gingivalis LpxC gene, which is a rate-limiting gene for the LPS biosynthesis pathway. (e) Heat map of log2 fold change of LpxA and LpxC genes from all four tested Gram-negative bacteria. The standard error is shown as an error bar in all bar figures; a single star indicates p-value ≤ 0.05, and double stars indicate fdr-adjusted p-value ≤ 0.05.
Figure 5
Figure 5
Treatment-induced transcriptomics changes in genes involved in P. gingivalis toxin translocation, secretion system, and infection (a) Heatmap of Log2 fold change of P. gingivalis genes involved in toxin translocation, secretion system, and infection (including Type 9 Secretion System (T9SS), PPAD, gingipain, frimbrium, humY-tonB, VIM, quorum sensing gene LuxS, LuxR, NO stress-associated gene cdrH, and infection-associated gene hflX) compared to untreated control from all tested bacteria strains. (b) Bar plot of the log2 fold change of P. gingivalis Type 9 Secretion System gene PorQ encoded by pgi:PG_0602. (c) Bar plot of the log2 fold change of P. gingivalis fimbrium subunit C (fimC) gene encoded by pgi:PG_1881. (d) Bar plot of the log2 fold change of P. gingivalis VimF Glycosyltransferase gene encoded by pgi:PG_0884, a key virulence modulating component. (e) Bar plot of the log2 fold change of P. gingivalis hflX gene encoded by pgi:PG_1886, a key virulence factor for infection and invasion. (f) Bar plot of the log2 fold change of P. gingivalis peptidylarginine deiminase (PPAD) gene encoded by pgi:PG_1424. (g) Bar plot of the log2 fold change of P. gingivalis cdhR gene encoded by pgi:PG_1237, also named luxR as a component of quorum sensing, regulating NO stress resistance. The standard error is shown as an error bar in all bar figures; a single star indicates p-value ≤ 0.05, and double stars indicate fdr-adjusted p-value ≤ 0.05.
Figure 6
Figure 6
Treatment-induced transcriptomic responses of degradative enzymes including proteases, peptidases, and hemolysins. (a) Heatmap of log2 fold change of degradative enzymes, such as proteases, peptidases, and hemolysins, from all the tested bacteria strains compared to the no-treatment controls. (b) Gene number of the degradation enzymes in each bacteria genome and representational ratio towards all the genes encoded in the genome. (c) Bar plot of the log2 fold change of P. gingivalis gingipain A gene encoded by pgi:PG_2024. (d) Bar plot of the log2 fold change of P. gingivalis gingipain B gene encoded by pgi:PG_0506. (e) Bar plot of the log2 fold change of P. gingivalis hemolysin gene encoded by pgi:PG_1875. (f) Bar plot of the log2 fold change of F. nucleatum prtC collagenase gene encoded by PKHDFLHN_00556 [73]. The standard error is shown as an error bar in all bar figures; a single star indicates p-value ≤ 0.05, and double stars indicate fdr-adjusted p-value ≤ 0.05.
Figure 7
Figure 7
Transcriptomic changes in genes that are regulated by major oral care ingredients and involved in biofilm development, adhesion to, and infection of host cells. (a). Genes in biofilm development and survival. (b). Genes in attachment to and initial interaction with host cells, such as gingival keratinocytes. (c). Genes encoding products that directly degrade the cellular structure of gingiva and facilitate bacterial survival and infection. The directions of gene expression changes are based on the results observed with SnF2, SnCl2, and CPC, which had the strongest activity. Blue arrows designate down-regulation, and red arrows designate up-regulation.

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