Background: Bacterial infections have been linked to malignancies due to their ability to induce chronic inflammation. We investigated the association of oral bacteria in oral squamous cell carcinoma (OSCC/tumor) tissues and compared with adjacent non-tumor mucosa sampled 5 cm distant from the same patient (n = 10). By using culture-independent 16S rRNA approaches, denaturing gradient gel electrophoresis (DGGE) and cloning and sequencing, we assessed the total bacterial diversity in these clinical samples. Results: DGGE fingerprints showed variations in the band intensity profiles within non-tumor and tumor tissues of the same patient and among the two groups. The clonal analysis indicated that from a total of 1200 sequences characterized, 80 bacterial species/phylotypes were detected representing six phyla, Firmicutes, Bacteroidetes, Proteobacteria, Fusobacteria, Actinobacteria and uncultivated TM7 in non-tumor and tumor libraries. In combined library, 12 classes, 16 order, 26 families and 40 genera were observed. Bacterial species, Streptococcus sp. oral taxon 058, Peptostreptococcus stomatis, Streptococcus salivarius, Streptococcus gordonii, Gemella haemolysans, Gemella morbillorum, Johnsonella ignava and Streptococcus parasanguinis I were highly associated with tumor site where as Granulicatella adiacens was prevalent at non-tumor site. Streptococcus intermedius was present in 70% of both non-tumor and tumor sites. Conclusions: The underlying changes in the bacterial diversity in the oral mucosal tissues from non-tumor and tumor sites of OSCC subjects indicated a shift in bacterial colonization. These most prevalent or unique bacterial species/phylotypes present in tumor tissues may be associated with OSCC and needs to be further investigated with a larger sample size.

Blockade of the Piezo1 mechanoreceptor decreases myeloid cell suppression of immune responses to cancer and polymicrobial sepsis.

The gut microbiome shapes local and systemic immunity. The liver is presumed to be a protected sterile site. As such, a hepatic microbiome has not been examined. Here, we showed a liver microbiome in mice and humans that is distinct from that of the gut and is enriched in Proteobacteria. It undergoes dynamic alterations with age and is influenced by the environment and host physiology. Fecal microbial transfer experiments revealed that the liver microbiome is populated from the gut in a highly selective manner. Hepatic immunity is dependent on the microbiome, specifically the bacteroidetes species. Targeting bacteroidetes with oral antibiotics reduced hepatic immune cells by approximately 90%, prevented antigen-presenting cell (APC) maturation, and mitigated adaptive immunity. Mechanistically, our findings are consistent with presentation of bacteroidetes-derived glycosphingolipids to NKT cells promoting CCL5 signaling, which drives hepatic leukocyte expansion and activation, among other possible host-microbe interactions. Collectively, we reveal a microbial/glycosphingolipid/NKT/CCL5 axis that underlies hepatic immunity.

There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as Veillonella, Rothia, and Prevotella, are annotated by all databases; however, less common genera, such as Bulleidia and Paludibacter, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies.

Periodontal disease (PerioD) is a chronic inflammatory disease of dysbiotic etiology. Animal models and few human data showed a relationship between oral bacteria and gut dysbiosis. However, the effect of periodontal inflammation and subgingival dysbiosis on the gut is unknown. We hypothesized that periodontal inflammation and its associated subgingival dysbiosis contribute to gut dysbiosis even in subjects free of known gut disorders. We evaluated and compared elderly subjects with Low and High periodontal inflammation (assessed by Periodontal Inflamed Surface Area (PISA)) for stool and subgingival derived bacteria (assayed by 16S rRNA sequencing). The associations between PISA/subgingival dysbiosis and gut dysbiosis and bacteria known to produce short-chain fatty acid (SCFA) were assessed. LEfSe analysis showed that, in Low PISA, species belonging to Lactobacillus, Roseburia, and Ruminococcus taxa and Lactobacillus zeae were enriched, while species belonging to Coprococcus, Clostridiales, and Atopobium were enriched in High PISA. Regression analyses showed that PISA associated with indicators of dysbiosis in the gut mainly reduced abundance of SCFA producing bacteria (Radj = −0.38, p = 0.03). Subgingival bacterial dysbiosis also associated with reduced levels of gut SCFA producing bacteria (Radj = −0.58, p = 0.002). These results suggest that periodontal inflammation and subgingival microbiota contribute to gut bacterial changes.