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.

Virtual Healthcare Simulation: Implementation, Distractions, and Preferences.

INTRODUCTION: Social distancing guidelines related to COVID-19 resulted in many simulation centers temporarily closing or adopting virtual simulation-based education (SBE). This mixed methods study aimed to evaluate our center's readiness to implement virtual SBE, the preferred method of delivery (virtual vs. nonvirtual), and any reported distractions. METHODS: Educators and simulation operations specialists (SOSs) used by our simulation center completed a survey focused on our center's implementation readiness for virtual SBE at 3 time points over a 3-week period. Three virtual simulation-based styles were developed: observer, vignette, and hybrid. All styles combined the use of Zoom and LearningSpace. Upon the completion of each session, learners, facilitators, and SOSs completed a survey focused on the preferred method of simulation delivery (virtual vs. nonvirtual) as well as any reported distractions during sessions. RESULTS: While some important lessons were learned, simulation team survey scores suggested an overall agreement in the center's preparedness during the 3-week implementation period. Most learners, facilitators, and SOSs preferred a nonvirtual delivery due to the "hands-on" component. Learners participating in the vignette style, however, significantly preferred virtual SBE due to "learning environment comfort" such as reduced anxiety, "better discussion," and "convenience." Reported distractions focused on "challenges with technology," "interruptions at home," "program logistics," and the "remote atmosphere." CONCLUSIONS: Most learners, facilitators, and SOSs preferred nonvirtual SBE; however, virtual SBE may prove beneficial for learners participating in the vignette style or particularly those experiencing anxiety. Future distractions may be mitigated for the simulation team and learners with proper preparedness.

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.

Oral Microbiome and Cancer Therapy-Induced Oral Mucositis.

Characterization of the role of oral microbiome in cancer therapy-induced oral mucositis (CTOM) is critical in preventing the clinically deleterious effects on patients' health that are associated with CTOM. Funding initiatives related to the National Institutes of Health human microbiome project have resulted in groundbreaking advancements in biology and medicine during the last decade. These advancements have shown that a human being is in fact a superorganism made of human cells and associated symbiotic or commensal microbiota. In this review, we describe the state of science as it relates to fundamental knowledge on oral microbiome and its role in CTOM. We also discuss how state-of-the-art technologies and systems biology tools may be used to help tackle the difficult challenges ahead to develop effective treatments or preventive therapies for oral mucositis. We make a clear distinction between disease processes pertaining to the oral microbiome, which includes opportunistic pathogens that may be defined as pathobionts, and those infectious disease processes initiated by exogenous pathogens. We also explored the extent to which knowledge from the gastrointestinal tract in disease and intestinal mucositis could help us better understand CTOM pathobiology. Finally, we propose a model in which the oral microbiome participates in the current five-step CTOM pathobiology model. With the advent of more sophisticated metagenomics technologies and methods of analysis, much hope lies ahead to implement an effective holistic approach to treat cancer patients affected by CTOM.

Concordance of HOMIM and HOMINGS technologies in the microbiome analysis of clinical samples.

BACKGROUND: Over 700 bacterial species reside in human oral cavity, many of which are associated with local or distant site infections. Extensive characterization of the oral microbiome depends on the technologies used to determine the presence and proportions of specific bacterial species in various oral sites. OBJECTIVE: The objective of this study was to compare the microbial composition of dental plaque at baseline using Human Oral Microbe Identification Microarray (HOMIM) and Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS) technologies, which are based on 16S rRNA. METHODS: Dental plaque samples were collected from 96 patients at baseline prior to a dental procedure involving manipulation of gingival tissues. The samples were surveyed for 293 and 597 oral bacterial species via HOMIM and HOMINGS, respectively, based on 16S rRNA gene sequences. We determined the concordance between the two technologies for common species. Genus level analysis was performed using HOMINGS-specific genus identification capabilities. RESULTS: HOMINGS detected twice the number of species in the same dental plaque samples compared to HOMIM. For the species detected by both HOMIM and HOMINGS, there was no difference in relative proportions of overall bacterial composition at the species, genus or phylum levels. Additionally, there was no difference in relative proportion for total species per patient between the two technologies. CONCLUSION: HOMINGS significantly expanded oral bacterial species identification compared to HOMIM. The genus and species probes, combined in HOMINGS, provided a more comprehensive representation of oral bacterial community, critical for future characterization of oral microbes in distant site infections.

Human annulus cells regulate PAPP-A and IGFBP-4 expression, and thereby insulin-like growth factor bioavailability, in response to proinflammatory cytokine exposure in vitro.

Pregnancy-associated plasma protein-A (PAPP-A) is a metalloproteinase which cleaves IGF binding protein (BP)-4 in the extracellular matrix, making IGF available to nearby cells. We have shown that PAPP-A is present in the human intervertebral disc, and is significantly upregulated in more degenerated discs where increased proinflammatory cytokine levels are present. We hypothesized that increased proinflammatory cytokines present in the degenerating disc might be related to PAPP-A expression. Experiments exposed human annulus cells to IL-1-ß or TNF-α to test this hypothesis. Treated cells showed significantly increased PAPP-A in conditioned media versus controls (p < 0.001). PAPP-A production following exposure to IL-1ß was significantly greater in cells derived from more degenerated versus healthier discs (p = 0.05). PAPP-A gene expression (microarray analysis) was significantly upregulated in IL-1ß- or TNF-α-exposed cells (p = 0.01-0.004). Quantitative RT-PCR confirmed significant upregulation of IGFBP-4 in IL-1ß- or TNF-α-exposed cells. Data have potential relevance to future cell-based biologic therapies for disc degeneration.