Human oral mucosa and oral microbiome interactions following supragingival plaque reconstitution in healthy volunteers: a diet-controlled balanced design proof-of-concept model to investigate oral pathologies

Changes in the oral microbiome may contribute to oral pathologies, especially in patients undergoing cancer therapy. Interactions between oral microbiome and oral mucosa may exacerbate inflammation. We determined whether probiotic-controlled plaque formation could impact proximal oral mucosa gene expression profiles in healthy volunteers. A 3-weeks balanced sample collection design from healthy volunteers (HVs) was implemented. At Week-1 plaques samples and labial mucosa brush biopsies were obtained from HVs in the morning (N = 4) and/or in the afternoon (N = 4), and groups were flipped at Week-3. A fruit yogurt and tea diet were given 2-4hrs before sample collection. mRNA gene expression analysis was completed using RNA-Seq and DESeq2. Bacterial taxa relative abundance was determined by 16S HOMINGS. Bacterial diversity changes and metabolic pathway enrichment were determined using PRIMERv7 and LEfSe programs. Alpha- and beta-diversities did not differ morning (AM) vs. afternoon (PM). The most affected KEGG pathway was Toll-like receptor signaling in oral mucosa. Eighteen human genes and nine bacterial genes were differentially expressed in plaque samples. Increased activity for 'caries-free' health-associated calcifying Corynebacterium matruchotii and reduced activity for Aggregatibacter aphrophilus, an opportunistic pathogen, were observed. Microbial diversity was not altered after 8 hours plaque formation in healthy individuals as opposed to gene expression.

Cutaneous Microbiome Profiles Following Chlorhexidine Treatment in a 72-Hour Daily Follow-Up Paired Design: a Pilot Study

Venous catheter-related bloodstream infections represent a significant problem in the United States. Our objective was to determine daily changes in skin microbiome profiles up to 72h postchlorhexidine treatment. Left and right forearm skin swab samples were obtained from 10 healthy volunteers over 72h at 24h intervals. Dorsal surface of left arm was treated with chlorohexidine gluconate (CHG) at initial time point (T = 0), while the right arm remained untreated (control). Swab samples were obtained shortly before (T = 0) and after CHG treatment (T = 24-48-72h). Bacterial DNA extraction, 16S rRNA gene V1-V3 sequencing and taxonomic annotation were performed using ZymoBIOMICS pipeline. PERMANOVA, linear discriminant and bacterial interaction network analyses were performed. A total of 13 total phyla, 273 genera, and 950 total species were detected across all time points, CHG-treated or CHG-untreated. Most abundant species included Cutibacterium acnes, Staphylococcus epidermidis, and Rothia Mucilaginosa. Low biomass-related inconsistent taxa detection was observed. PERMANOVA suggested a marginal difference between CHG-treated and CHG-untreated microbiome profiles (Genera: P(perm) = 0.0531; Species: P(perm) = 0.0450). Bacterial interaction network guided PERMANOVA analyses detected a microbiome change over time, suggesting a consistent CHG treatment-specific change. LEfSe identified Finegoldia magna, Bacillus pumilus, Bacillus thermoamylovorans as the only distinctive species. These species were more abundant and/or present post-CHG treatment in the CHG-treated group. These findings suggest that the skin microbiome was not significantly different 24, 48, or 72h after CHG treatment. Previous culture-based studies have found similar results after 24h. Future studies will be needed to determine the mechanisms of bacterial regrowth after CHG treatment. IMPORTANCE Annually, over 80,000 central line infections occur in the United States. Understanding the pathogenesis of these infections is crucial. Chlorhexidine is the most commonly used skin preparation before line placement. We hypothesized that the use of chlorhexidine and dressings will alter the normal arm skin microbiome over a period of 72h. We used 16S-rRNA gene next generation sequencing (NGS) to determine the forearm skin microbiome of volunteers. The left arm was swabbed with chlorhexidine and the right arm served as control. The skin microbiome returned to normal after 24h. Our NGS results confirm findings of two previous culture-based studies. Relative abundance of Bacillus spp. in the chlorhexidine-treated samples was increased, consistent with one previous study. Based on the results of this pilot study, we will need to measure viable bacteria during a 24h time course following chlorhexidine treatment to understand the source of skin microbiome replenishment.

Haemophilus pittmaniae and Leptotrichia spp. Constitute a Multi-Marker Signature in a Cohort of Human Papillomavirus-Positive Head and Neck Cancer Patients

Objectives

Human papillomavirus (HPV) is a known etiological factor of oropharyngeal head and neck cancer (HNC). HPV positivity and periodontal disease have been associated with higher HNC risk, suggesting a role for oral bacterial species. Our objective was to determine oral microbiome profiles in HNC patients (HPV-positive and HPV-negative) and in healthy controls (HC).

Methods

Saliva samples and swabs of buccal mucosa, supragingival plaque, and tongue were collected from HNC patients (N = 23 patients, n = 92 samples) before cancer therapy. Next-generation sequencing (16S-rRNA gene V3–V4 region) was used to determine bacterial taxa relative abundance (RA). β-Diversities of HNC HPV+ (N = 16 patients, n = 64 samples) and HNC HPV– (N = 7 patients, n = 28 samples) groups were compared using PERMANOVA (pMonte Carlo < 0.05). LEfSe discriminant analysis was performed to identify differentiating taxa (Log LDA > 2.0). RA differences were analyzed by Mann–Whitney U-test (α = 0.05). CombiROC program was used to determine multi-marker bacterial signatures. The Microbial Interaction Network Database (MIND) and LitSuggest online tools were used for complementary analyses.

Results

HNC vs. HC and HNC HPV+ vs. HNC HPV– β-diversities differed significantly (pMonte Carlo < 0.05). Streptococcus was the most abundant genus for HNC and HC groups, while Rothia mucilaginosa and Haemophilus parainfluenzae were the most abundant species in HNC and HC patients, respectively, regardless of antibiotics treatment. LEfSe analysis identified 43 and 44 distinctive species for HNC HPV+ and HNC HPV– groups, respectively. In HNC HPV+ group, 26 periodontal disease-associated species identified by LefSe had a higher average RA compared to HNC HPV– group. The significant species included Alloprevotella tannerae, Fusobacterium periodonticum, Haemophilus pittmaniae, Lachnoanaerobaulum orale, and Leptotrichia spp. (Mann–Whitney U-test, p < 0.05). Of 43 LEfSe-identified species in HPV+ group, 31 had a higher RA compared to HPV– group (Mann–Whitney U-test, p < 0.05). MIND analysis confirmed interactions between Haemophilus and Leptotrichia spp., representing a multi-marker signature per CombiROC analysis [area under the curve (AUC) > 0.9]. LitSuggest correctly classified 15 articles relevant to oral microbiome and HPV status.

Conclusion

Oral microbiome profiles of HNC HPV+ and HNC HPV– patients differed significantly regarding periodontal-associated species. Our results suggest that oral bacterial species (e.g., Leptotrichia spp.), possessing unique niches and invasive properties, coexist with HPV within HPV-induced oral lesions in HNC patients. Further investigation into host–microbe interactions in HPV-positive HNC patients may shed light into cancer development.

Comorbidities and Susceptibility to COVID-19: A Generalized Gene Set Data Mining Approach

The COVID-19 pandemic has led to over 2.26 million deaths for almost 104 million confirmed cases worldwide, as of 4 February 2021 (WHO). Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, and obesity. Although several vaccines have been deployed, there are few alternative anti-viral treatments available in the case of reduced or non-existent vaccine protection. Adopting a long-term holistic approach to cope with the COVID-19 pandemic appears critical with the emergence of novel and more infectious SARS-CoV-2 variants. Our objective was to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational meta-analysis approach. SNP datasets were downloaded from a publicly available genome-wide association studies (GWAS) catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using the program MAGMA. An SNP annotation program was used to analyze MAGMA-identified genes. Differential gene expression was determined for significant genes across 30 general tissue types using the Functional and Annotation Mapping of GWAS online tool GENE2FUNC. COVID-19 comorbidities (n = 22) from six disease categories were found to have significant associated pathways, validated by Q-Q plots (p < 0.05). Protein-protein interactions of significant (p < 0.05) differentially expressed genes were visualized with the STRING program. Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. In conclusion, we were able to identify the pathways potentially affected by or affecting SARS-CoV-2 infection in underlying medical conditions likely to confer susceptibility and/or the severity of COVID-19. Our findings have implications in future COVID-19 experimental research and treatment development.

Oral Microbiome Signatures in Hematological Cancers Reveal Predominance of Actinomyces and Rothia Species

The endogenous microbiome of healthy individuals in oral cavities is diverse, representing over 700 bacterial species. Imbalance in oral and gut microbiome composition and associated gene expression has been linked to different forms of hematological (blood) cancers. Our objective is to compare oral microbiome profiles of patients with blood cancers (BC group: N = 39 patients, n = 124 oral samples) to those of healthy control subjects (HC group: N = 27 subjects, n = 100 oral samples). Saliva samples and swabs of buccal mucosa, supragingival plaque, and tongue were collected from blood cancer patients and healthy controls. Next-generation sequencing (16S-rRNA gene V3-V4 region) was used to determine the relative abundance of bacterial taxa present at the genus and species levels. Differences in oral microbiome beta-diversity were determined using multivariate permutational analysis of variance (PERMANOVA). Linear discriminant analysis (LDA) effect size (LEfSe) analysis was performed to identify differentiating bacterial taxa in pairwise comparisons. The PATRIC_v3.6.7 online tool was used to determine the predominance of potential pathogenicity in the BC group. The oral microbiome beta-diversities of the BC and HC groups differed and corresponded to a reduced alpha-diversity in the BC group. LEfSe analysis showed significant LDA scores for Actinomyces and Rothia spp., differentiating the BC group from the HC group. In silico analysis using PATRIC_v3.6.7 demonstrated that the groups of bacteria possessing traits of "antibiotic resistance", "oral pathogen", and "virulence" was enriched in the BC group. Although 56% of the BC patients received antibiotics within two weeks of the oral bacterial sampling, Actinomyces genus remained the top differentiating feature in the BC group regardless of the administration of antibiotics, while Rothia dentocariosa was detected as the top differentiating feature in the BC patients who did not receive antibiotics, but not in those who received antibiotics. Further investigation is needed to better understand the interactions of certain oral species with the host immune system to better characterize clinically relevant associations with hematological cancers.

Immortalization of Salivary Gland Epithelial Cells of Xerostomic Patients: Establishment and Characterization of Novel Cell Lines

Primary Sjögren’s Syndrome (pSS) is an autoimmune disease mainly affecting salivary and lacrimal glands. Previous pSS studies have relied on primary cell culture models or cancer cell lines with limited relevance to the disease. Our objective was to generate and characterize immortalized salivary gland epithelial cells (iSGECs) derived from labial salivary gland (LSG) biopsies of pSS patients (focus score > 1) and non-Sjögren’s Syndrome (nSS) xerostomic (i.e., sicca) female patients. To characterize iSGECs (n = 3), mRNA expression of specific epithelial and acinar cell markers was quantified by qRT-PCR. Protein expression of characterization markers was determined by immunocytochemistry and Western blot. Secretion of α-amylase by iSGECs was confirmed through colorimetric activity assay. Spheroid formation and associated alterations in expression markers were determined using matrigel-coated cell culture plates. Consistent mRNA and protein expressions of both epithelial and pro-acinar cell markers were observed in all three iSGEC lines. When cultured on matrigel medium, iSGECs formed spheroids, secreted α-amylase after β-adrenergic stimulation, and expressed multiple acinar cell markers at late passages. One iSGEC line retained adequate cell morphology without a loss of SV40Lt expression and proliferation potential after over 100 passages. In conclusion, our established iSGEC lines represent a viable model for salivary research due to their passaging capacity and maintenance of pro-acinar cell characteristics.

Lasting Gammaproteobacteria profile changes characterized hematological cancer patients who developed oral mucositis following conditioning therapy

Background: Oral mucositis (OM) is a common side effect of conditioning therapy implemented before hematopoietic stem cell transplantation (HSCT). The role of oral microbiome in OM is not fully elucidated. Objective: To determine oral microbiome profile changes post-conditioning in HSCT patients who developed moderate OM, or mild to no OM. Design: Patient groups were: Muc0-1 with OM-score = 0-1 (43 paired samples) and Muc2 with WHO OM-score = 2 (36 paired samples). Bacterial DNA was isolated from oral samples (saliva, swabs of buccal mucosa, tongue, and supragingival plaque) at pre-conditioning (T 0 ), post-conditioning mucositis onset (T Muc ), and one-year post-conditioning (T Year ). 16S-rRNA gene next-generation sequencing was used to determine the relative abundance (RA) of >700 oral species. Alpha-diversity, beta-diversity and linear discriminant analyses (LDA) were performed Muc2 versus Muc0-1. Results: Muc2 oral microbiome alpha- and beta-diversity differed between T 0 and T Muc . Muc2 alpha-diversity and Muc0-1 beta-diversity did not differ between T 0 and T Year . T 0 to T Muc LDA scores were significant in Muc2 for Gammaproteobacteria. For Muc2 patients, the average RA decreased for Haemophilus parainfluenza, a species known as mucosal surfaces protector, but increased for Escherichia-Shigella genera. Conclusions: Post-conditioning OM might contribute to long-term oral microbiome changes affecting Gammaproteobacteria, in HSCT patients.