23 research outputs found
Integrated Analysis of Clinical and Microbiome Risk Factors Associated with the Development of Oral Candidiasis during Cancer Chemotherapy.
Oral candidiasis is a common side effect of cancer chemotherapy. To better understand predisposing factors, we followed forty-five subjects who received 5-fluorouracil- or doxorubicin-based treatment, during one chemotherapy cycle. Subjects were evaluated at baseline, prior to the first infusion, and at three additional visits within a two-week window. We assessed the demographic, medical and oral health parameters, neutrophil surveillance, and characterized the salivary bacteriome and mycobiome communities through amplicon high throughput sequencing. Twenty percent of all subjects developed oral candidiasis. Using multivariate statistics, we identified smoking, amount of dental plaque, low bacteriome and mycobiome alpha-diversity, and the proportions of specific bacterial and fungal taxa as baseline predictors of oral candidiasis development during the treatment cycle. All subjects who developed oral candidiasis had baseline microbiome communities dominated by Candida and enriched in aciduric bacteria. Longitudinally, oral candidiasis was associated with a decrease in salivary flow prior to lesion development, and occurred simultaneously or before oral mucositis. Candidiasis was also longitudinally associated with a decrease in peripheral neutrophils but increased the neutrophil killing capacity of Candida albicans. Oral candidiasis was not found to be associated with mycobiome structure shifts during the cycle but was the result of an increase in Candida load, with C. albicans and Candida dubliniensis being the most abundant species comprising the salivary mycobiome of the affected subjects. In conclusion, we identified a set of clinical and microbiome baseline factors associated with susceptibility to oral candidiasis, which might be useful tools in identifying at risk individuals, prior to chemotherapy
Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis.
BACKGROUND: Gastrointestinal mucosal injury (mucositis), commonly affecting the oral cavity, is a clinically significant yet incompletely understood complication of cancer chemotherapy. Although antineoplastic cytotoxicity constitutes the primary injury trigger, the interaction of oral microbial commensals with mucosal tissues could modify the response. It is not clear, however, whether chemotherapy and its associated treatments affect oral microbial communities disrupting the homeostatic balance between resident microorganisms and the adjacent mucosa and if such alterations are associated with mucositis. To gain knowledge on the pathophysiology of oral mucositis, 49 subjects receiving 5-fluorouracil (5-FU) or doxorubicin-based chemotherapy were evaluated longitudinally during one cycle, assessing clinical outcomes, bacterial and fungal oral microbiome changes, and epithelial transcriptome responses. As a control for microbiome stability, 30 non-cancer subjects were longitudinally assessed. Through complementary in vitro assays, we also evaluated the antibacterial potential of 5-FU on oral microorganisms and the interaction of commensals with oral epithelial tissues.
RESULTS: Oral mucositis severity was associated with 5-FU, increased salivary flow, and higher oral granulocyte counts. The oral bacteriome was disrupted during chemotherapy and while antibiotic and acid inhibitor intake contributed to these changes, bacteriome disruptions were also correlated with antineoplastics and independently and strongly associated with oral mucositis severity. Mucositis-associated bacteriome shifts included depletion of common health-associated commensals from the genera Streptococcus, Actinomyces, Gemella, Granulicatella, and Veillonella and enrichment of Gram-negative bacteria such as Fusobacterium nucleatum and Prevotella oris. Shifts could not be explained by a direct antibacterial effect of 5-FU, but rather resembled the inflammation-associated dysbiotic shifts seen in other oral conditions. Epithelial transcriptional responses during chemotherapy included upregulation of genes involved in innate immunity and apoptosis. Using a multilayer epithelial construct, we show mucositis-associated dysbiotic shifts may contribute to aggravate mucosal damage since the mucositis-depleted Streptococcus salivarius was tolerated as a commensal, while the mucositis-enriched F. nucleatum displayed pro-inflammatory and pro-apoptotic capacity.
CONCLUSIONS: Altogether, our work reveals that chemotherapy-induced oral mucositis is associated with bacterial dysbiosis and demonstrates the potential for dysbiotic shifts to aggravate antineoplastic-induced epithelial injury. These findings suggest that control of oral bacterial dysbiosis could represent a novel preventive approach to ameliorate oral mucositis
ORIGINAL ARTICLE Influence of DNA extraction on oral microbial profiles obtained via 16S rRNA gene sequencing
Background and objective: The advent of next-generation sequencing has significantly facilitated character-ization of the oral microbiome. Despite great efforts in streamlining the processes of sequencing and data curation, upstream steps required for amplicon library generation could still influence 16S rRNA gene-based microbial profiles. Among upstream processes, DNA extraction is a critical step that could represent a great source of bias. Accounting for bias introduced by extraction procedures is important when comparing studies that use different methods. Identifying the method that best portrays communities is also desirable. Accordingly, the aim of this study was to evaluate bias introduced by different DNA extraction procedures on oral microbiome profiles. Design: Four DNA extraction methods were tested on mock communities consisting of seven representative oral bacteria. Additionally, supragingival plaque samples were collected from seven individuals and divided equally to test two commonly used DNA extraction procedures. Amplicon libraries of the 16S rRNA gene were generated and sequenced via 454-pyrosequencing. Results: Evaluation of mock communities revealed that DNA yield and bacterial species representation varied with DNA extraction methods. Despite producing the lowest yield of DNA, a method that included bead beating was the only protocol capable of detecting all seven species in the mock community. Comparison o
Correction: Microbiome Profiles in Periodontitis in Relation to Host and Disease Characteristics.
Periodontitis is an inflammatory condition that affects the supporting tissues surrounding teeth. The occurrence of periodontitis is associated with shifts in the structure of the communities that inhabit the gingival sulcus. Although great inter-subject variability in the subgingival microbiome has been observed in subjects with periodontitis, it is unclear whether distinct community types exist and if differences in microbial signatures correlate with host characteristics or with the variable clinical presentations of periodontitis. Therefore, in this study we explored the existence of different community types in periodontitis and their relationship with host demographic, medical and disease-related clinical characteristics. Clustering analyses of microbial abundance profiles suggested two types of communities (A and B) existed in the 34 subjects with periodontitis evaluated. Type B communities harbored greater proportions of certain periodontitis-associated taxa, including species historically associated with the disease, such as Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola, and taxa recently linked to periodontitis. In contrast, subjects with type A communities had increased proportions of different periodontitis-associated species, and were also enriched for health-associated species and core taxa (those equally prevalent in health and periodontitis). Periodontitis subgingival clusters were not associated with demographic, medical or disease-specific clinical parameters other than periodontitis extent (proportion of sites affected), which positively correlated with the total proportion of cluster B signature taxa. In conclusion, two types of microbial communities were detected in subjects with periodontitis. Host demographics and underlying medical conditions did not correlate with these profiles, which instead appeared to be related to periodontitis extent, with type B communities present in more widespread disease cases. The two identified periodontitis profiles may represent distinct dysbiotic processes potentially requiring community-tailored therapeutic interventions
Influence of DNA extraction on oral microbial profiles obtained via 16S rRNA gene sequencing
Using High Throughput Sequencing to Explore the Biodiversity in Oral Bacterial Communities
High throughput sequencing of 16S ribosomal RNA gene amplicons is a cost-effective method for characterization of oral bacterial communities. However, before undertaking large-scale studies, it is necessary to understand the technique-associated limitations and intrinsic variability of the oral ecosystem. In this work we evaluated bias in species representation using an in vitro-assembled mock community of oral bacteria. We then characterized the bacterial communities in saliva and buccal mucosa of five healthy subjects to investigate the power of high throughput sequencing in revealing their diversity and biogeography patterns. Mock community analysis showed primer and DNA isolation biases and an overestimation of diversity that was reduced after eliminating singleton operational taxonomic units (OTUs). Sequencing of salivary and mucosal communities found a total of 455 OTUs (0.3% dissimilarity) with only 78 of these present in all subjects. We demonstrate that this variability was partly the result of incomplete richness coverage even at great sequencing depths, and so comparing communities by their structure was more effective than comparisons based solely on membership. With respect to oral biogeography, we found inter-subject variability in community structure was lower than site differences between salivary and mucosal communities within subjects. These differences were evident at very low sequencing depths and were mostly caused by the abundance of Streptococcus mitis and Gemella haemolysans in mucosa. In summary, we present an experimental and data analysis framework that will facilitate design and interpretation of pyrosequencing-based studies. Despite challenges associated with this technique, we demonstrate its power for evaluation of oral diversity and biogeography patterns