The Human Salivary Antimicrobial Peptide Profile according to the Oral Microbiota in Health, Periodontitis and Smoking

Abstract

Antimicrobial peptides (AMPs) are a diverse family of peptides that defend the mucosal surfaces of the oral cavity and other locations. Many AMPs have multiple functions and properties that influence aspects of innate defense and colonization by microorganisms. The human oral cavity is home to the second-most diverse microbiome, and the health of the mouth is influenced by the presence of these bacteria as well as by extrinsic factors such as periodontitis and smoking. This study hypothesized that the AMP profile is different in the presence of extrinsic factors and that this would also be reflected in the bacteria present. The AMP profile was analyzed by quantitative selected-reaction-monitoring mass spectrometry analysis and 40 bacterial species were quantified by DNA-DNA hybridization in saliva donated by 41 individuals. Periodontal status was assessed through dental examination and smoking status through medical charting. Periodontal health (in nonsmokers) was associated with a higher abundance of ribonuclease 7, protachykinin 1, β-defensin 128, lipocalin 1, bactericidal permeability-increasing protein fold-containing family B member 3, and bone-marrow proteoglycan. Nonsmoking periodontal disease was associated with an abundance of neutrophil defensin 1 and cathelicidin. However, 7 AMPs were overabundant in periodontal disease in smokers: adrenomedullin, eosinophil peroxidase, 3 different histones, myeloperoxidase, and neutrophil defensin 1. There were no differentially abundant AMPs in smokers versus nonsmokers with periodontal health. Correlation network inference of healthy nonsmokers, healthy smokers, nonsmoking periodontitis, or smoking periodontitis donors demonstrated very different networks growing in complexity with increasing numbers of stressors. The study highlights the importance of the interaction between the oral cavity and its resident microbiota and how this may be influenced by periodontal disease and smoking.

Keywords: Antimicrobial peptides; Inflammation; Periodontitis; Saliva.

Fig. 1

Visualization of all peptide signatures for all samples. Peptide data were log₁₀-transformed, as shown on the scale bar for colors. Imputation is used for missing value estimation. Missing data squares are represented in white. Both rows and columns are clustered using Manhattan distance and average linkage (63 rows and 41 columns).

Fig. 2

Visualization of all bacterial signatures for all samples. Bacterial data were log₁₀-transformed, as shown on the scale bar for colors. Imputation is used for missing value estimation. Missing data squares are represented in white. Both rows and columns are clustered using Manhattan distance and average linkage (40 rows and 41 columns).

Fig. 3

Clustering of AMP abundance based on correlation to bacterial abundance. Purple represents positive correlation and green represents negative correlation.

Fig. 4

Network analysis of significantly correlated (Spearman correlation: r > 0.75, p < 0.05) peptides and bacteria. Network graphs drawn with Gephi using Fruchterman-Reingold layout and no overlap. Size of node is proportional to the average quantity detected in the condition relative to overall average. Node colors denote bacterium (brown) or peptide (blue). Color of edges represents positive (red) or negative (green) correlation. Perio, periodontitis.