The epithelial barrier at mucosal sites comprises an important mechanical protective feature of innate immunity, and is intimately involved in communicating signals of infection/tissue damage to inflammatory and immune cells in these local environments. A wide array of antimicrobial factors (AMF) exist at mucosal sites and in secretions that contribute to this innate immunity. A non-human primate model of ligature-induced periodontitis was used to explore characteristics of the antimicrobial factor transcriptome (n = 114 genes) of gingival biopsies in health, initiation and progression of periodontal lesions, and in samples with clinical resolution. Age effects and relationship of AMF to the dominant members of the oral microbiome were also evaluated. AMF could be stratified into 4 groups with high (n = 22), intermediate (n = 29), low (n = 18) and very low (n = 45) expression in healthy adult tissues. A subset of AMF were altered in healthy young, adolescent and aged samples compared with adults (e.g., APP, CCL28, DEFB113, DEFB126, FLG2, PRH1) and were affected across multiple age groups. With disease, a greater number of the AMF genes were affected in the adult and aged samples with skewing toward decreased expression, for example WDC12, PGLYRP3, FLG2, DEFB128, and DEF4A/B, with multiple age groups. Few of the AMF genes showed a >2-fold increase with disease in any age group. Selected AMF exhibited significant positive correlations across the array of AMF that varied in health and disease. In contrast, a rather limited number of the AMF significantly correlated with members of the microbiome; most prominent in healthy samples. These correlated microbes were different in younger and older samples and differed in health, disease and resolution samples. The findings supported effects of age on the expression of AMF genes in healthy gingival tissues showing a relationship to members of the oral microbiome. Furthermore, a dynamic expression of AMF genes was related to the disease process and showed similarities across the age groups, except for low/very low expressed genes that were unaffected in young samples. Targeted assessment of AMF members from this large array may provide insight into differences in disease risk and biomolecules that provide some discernment of early transition to disease.

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Published in Frontiers in Oral Health, v. 3, article 817249.

© 2022 Ebersole, Kirakodu, Nguyen and Gonzalez

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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This work was supported by National Institute of Health grant P20GM103538.

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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/, GSE180588; https://www.ncbi.nlm.nih.gov/, PRJNA516659.

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/froh.2022.817249/full#supplementary-material It is also available for download as the additional file listed at the end of this record.

Supplementary-Figure-1.zip (7847 kB)
Supplementary Figure 1. (A–D) Altered transcript levels expressed as fold-difference from baseline healthy levels to initiation (0.5 months), progression (1 and 3 months) and resolution (5 months) of periodontal lesions in each age group.

Supplementary-Figure-2.zip (1954 kB)
Supplementary Figure 2. Differences in AMF expression levels based upon categorization of bacterial families in the microbiome into high and low levels. Each point denotes the value of an AMF gene level based upon expression in high vs. low family microbiome samples.

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