Saliva Microbiome Research Articles

Dental Biofilm and Saliva Microbiome and Its Interplay with Pediatric Allergies.

Little is known about the interplay and contribution of oral microorganisms to allergic diseases, especially in children. The aim of the clinical study was to associate saliva and dental biofilm microbiome with allergic disease, in particular with allergic asthma. In a single-center study, allergic/asthmatic children (n = 15; AA-Chd; age 10.7 ± 2.9), atopic/allergic children (n = 16; AT/AL-Chd; 11.3 ± 2.9), and healthy controls (n = 15; CON-Chd; age 9.9 ± 2.2) were recruited. After removing adhering biofilms from teeth and collecting saliva, microbiome was analyzed by using a 16s-rRNA gene-based next-generation sequencing in these two mediums. Microbiome structure differed significantly between saliva and dental biofilms (β-diversity). Within the groups, the dental biofilm microbiome of AA-Chd and AT/AL-Chd showed a similar microbial fingerprint characterized by only a small number of taxa that were enriched or depleted (4) compared to the CON-Chd, while both diseased groups showed a stronger microbial shift compared to CON-Chd, revealing 14 taxa in AA-Chd and 15 taxa in AT/AL-Chd that were different. This could be the first note to the contribution of dental biofilm and its metabolic activity to allergic health or disease.

Oral Microbiome in Relation to Periodontitis Severity and Systemic Inflammation.

Systemic inflammation induced by periodontitis is suggested to be the link between periodontitis and cardiovascular disease. The aim of this work was to explore the oral microbiome in periodontitis in relation to disease severity and systemic inflammation. The saliva and subgingival microbiome from periodontal pocket samples of patients with severe (n = 12) and mild periodontitis (n = 13) were analyzed using metagenomic shotgun sequencing. The taxa and pathways abundances were quantified. The diversity was assessed and the abundances to phenotype associations were performed using ANCOM and linear regression. A panel of inflammatory markers was measured in blood and was associated with taxa abundance. The microbial diversity and species richness did not differ between severe and mild periodontitis in either saliva or periodontal pockets. However, there were significant differences in the microbial composition between severe and mild periodontitis in the subgingival microbiome (i.e., pocket samples) and, in a lower grade, in saliva, and this is positively associated with systemic inflammatory markers. The “red complex” and “cluster B” abundances in periodontal pockets were strongly associated with inflammatory markers interleukin-6 and the white blood cell count. Our data suggest that systemic inflammation in severe periodontitis may be driven by the oral microbiome and may support the indirect (inflammatory) mechanism for the association between periodontitis and cardiovascular disease.

Evaluation of the Effect of Storage Methods on Fecal, Saliva, and Skin Microbiome Composition.

As the number of human microbiome studies expand, it is increasingly important to identify cost-effective, practical preservatives that allow for room temperature sample storage. Here, we reanalyzed 16S rRNA gene amplicon sequencing data from a large sample storage study published in 2016 and performed shotgun metagenomic sequencing on remnant DNA from this experiment. Both results support the initial findings that 95% ethanol, a nontoxic, cost-effective preservative, is effective at preserving samples at room temperature for weeks. We expanded on this analysis by collecting a new set of fecal, saliva, and skin samples to determine the optimal ratio of 95% ethanol to sample. We identified optimal collection protocols for fecal samples (storing a fecal swab in 95% ethanol) and saliva samples (storing unstimulated saliva in 95% ethanol at a ratio of 1:2). Storing skin swabs in 95% ethanol reduced microbial biomass and disrupted community composition, highlighting the difficulties of low biomass sample preservation. The results from this study identify practical solutions for large-scale analyses of fecal and oral microbial communities.IMPORTANCE Expanding our knowledge of microbial communities across diverse environments includes collecting samples in places far from the laboratory. Identifying cost-effective preservatives that will enable room temperature storage of microbial communities for sequencing analysis is crucial to enabling microbiome analyses across diverse populations. Here, we validate findings that 95% ethanol efficiently preserves microbial composition at room temperature for weeks. We also identified the optimal ratio of 95% ethanol to sample for stool and saliva to preserve both microbial load and composition. These results provide rationale for an accessible, nontoxic, cost-effective solution that will enable crowdsourcing microbiome studies, such as The Microsetta Initiative, and lower the barrier for collecting diverse samples.

Meta-omics analysis indicates the saliva microbiome and its proteins associated with the prognosis of oral cancer patients

Saliva is a biofluid that maintains the health of oral tissues and the homeostasis of oral microbiota. Studies have demonstrated that Oral squamous cell carcinoma (OSCC) patients have different salivary microbiota than healthy individuals. However, the relationship between these microbial differences and clinicopathological outcomes is still far from conclusive. Herein, we investigate the capability of using metagenomic and metaproteomic saliva profiles to distinguish between Control (C), OSCC without active lesion (L0), and OSCC with active lesion (L1) patients. The results show that there are significantly distinct taxonomies and functional changes in L1 patients compared to C and L0 patients, suggesting compositional modulation of the oral microbiome, as the relative abundances of Centipeda, Veillonella, and Gemella suggested by metagenomics are correlated with tumor size, clinical stage, and active lesion. Metagenomics results also demonstrated that poor overall patient survival is associated with a higher relative abundance of Stenophotromonas, Staphylococcus, Centipeda, Selenomonas, Alloscordovia, and Acitenobacter. Finally, compositional and functional differences in the saliva content by metaproteomics analysis can distinguish healthy individuals from OSCC patients. In summary, our study suggests that oral microbiota and their protein abundance have potential diagnosis and prognosis value for oral cancer patients. Further studies are necessary to understand the role of uniquely detected metaproteins in the microbiota of healthy and OSCC patients as well as the crosstalk between saliva host proteins and the oral microbiome present in OSCC.

Dysbiosis of the Saliva Microbiome in Patients With Polycystic Ovary Syndrome.

Significant differences in salivary microbiota communities between polycystic ovary syndrome (PCOS) patients and healthy controls have been reported, and interestingly, some salivary microbiota exhibit diurnal oscillation in healthy people. However, whether the diurnal oscillation of salivary microbiota is present in PCOS patients is unknown. In this study, we describe the differences in the saliva microbiome between the PCOS group and the control group at different time points over 24 h. 16S rRNA gene amplicon sequencing was performed on salivary and fecal samples from 10 PCOS patients and 10 healthy controls, and salivary samples were collected at 6-h intervals over 24 h (Zeitgeber (ZT)0, ZT6, ZT12, and ZT18). Among the salivary samples, those from the PCOS group showed significant differences from those of the control group at each time point. Differences were evident in taxa level and metabolic pathways. Interestingly, we found that PCOS disrupted the diurnal rhythm of the salivary microbiota abundance, as determined in the group of healthy women. In addition, no similar changes were found in PCOS patients and controls between the oral and fecal microbiota, including differential microbiota at the phylum level. In this study, significant differences in the composition of the salivary microbiota between PCOS and healthy women were detected at different time points. We also showed that the diurnal rhythm of relative abundance of the salivary microbiota was disrupted in patients with PCOS, which might be related to development of oral-related diseases and systematic metabolic disorders.

Comparison of Microbiome in Stimulated Saliva in Edentulous and Dentate Subjects.

Measurement of saliva microbes is promoted as a way to detect oral and systemic disease, yet there is a multitude of factors that affect the oral microbiome. The salivary microbiome is influenced by biofilm of shedding (epithelial) and non-shedding (tooth) surfaces. Methods for study of the salivary microbiome are by no means standardized, and differences in sample collection, storage, and processing can all affect results to some degree. Here we describe one method of saliva collection that has been validated for reproducibility. Standard 16S rRNA gene analysis is done using the Human Oral Microbiome Database library which results in analysis that is straightforward. Everything about this procedure except the library synthesis and DNA sequencing itself can easily be done in-house. To gauge the ability of salivary microbial analytics to distinguish between edentulous and dentate oral conditions, differences in the saliva microbiome of subjects with and without teeth were examined. Fifty-two dentate and 49 edentulous subjects provided stimulated saliva samples. 16S rRNA gene sequencing, QIIME-based data processing, and statistical analysis were done using several different analytical approaches to detect differences in the salivary microbiome between the two groups. Bacteria diversity was lower in the edentulous group. Remarkably, all 31 of the most significant differences in taxa were deficits that occurred in the edentulous group. As one might expect, many of these taxa are attributed to dental plaque and gingival sulcus-associated bacteria verifying that the measurement of 16S rRNA genes in the bacteria of the saliva can be used to reproducibly measure expected differences in the oral microbiome that occur with edentulism or other conditions and diseases.

The predictive power of saliva electrolytes exceeds that of saliva microbiomes in diagnosing early childhood caries

ABSTRACT Early childhood caries (ECC) is one of the most prevalent chronic diseases affecting children worldwide, and thus its etiology, diagnosis, and prognosis are of particular clinical significance. This study aims to test the ability of salivary microbiome and electrolytes in diagnosing ECC, and their interplays within the same population. We here simultaneously profiled salivary microbiome and biochemical components of 331 children (166 caries-free (H group) and 165 caries-active children (C group)) aged 4-6 years. We identified both salivary microbial and biochemical dysbiosis associated with ECC. Remarkably, K+, Cl-, NH4 +, Na+, SO4 2-, Ca2+, Mg2+, and Br- were enriched while pH and NO3 - were depleted in ECC. Moreover, the dmft index (ECC severity) positively correlated with Cl-, NH4 +, Ca2+, Mg2+, Br-, while negatively with pH and NO3 -. Furthermore, machine-learning classification models were constructed based on these biomarkers from saliva microbiota, or electrolytes (and pH). Unexpectedly, the electrolyte-based classifier (AUROC = 0.94) outperformed microbiome-based (AUROC = 0.70) one and the composite-based one (with both microbial and biochemical data; AUC = 0.89) in predicting ECC. Collectively, these findings indicate ECC-associated alterations and interplays in the oral microbiota, electrolytes and pH, underscoring the necessity of developing diagnostic models with predictors from salivary electrolytes.

Oral microbiome and pancreatic cancer.

BACKGROUNDMicrobiota profiles differ between patients with pancreatic cancer and healthy people, and understanding these differences may help in early detection of pancreatic cancer. Saliva sampling is an easy and cost-effective way to determine microbiota profiles compared to fecal and tissue sample collection.AIMTo investigate the saliva microbiome distribution in patients with pancreatic adenocarcinoma (PDAC) and the role of oral microbiota profiles in detection and risk prediction of pancreatic cancer.METHODSWe conducted a prospective study of patients with pancreatic cancer (n = 41) and healthy individuals (n = 69). Bacterial taxa were identified by 16S ribosomal ribonucleic acid gene sequencing, and a linear discriminant analysis effect size algorithm was used to identify differences in taxa. Operational taxonomic unit values of all selected taxa were converted into a normalized Z-score, and logistic regressions were used to calculate risk prediction of pancreatic cancer.RESULTSCompared with the healthy control group, carriage of Streptococcus and Leptotrichina (z-score) was associated with a higher risk of PDAC [odds ratio (OR) = 5.344, 95% confidence interval (CI): 1.282-22.282, P = 0.021 and OR = 6.886, 95%CI: 1.423-33.337, P = 0.016, respectively]. Veillonella and Neisseria (z-score) were considered a protective microbe that decreased the risk of PDAC (OR = 0.187, 95%CI: 0.055-0.631, P = 0.007 and OR = 0.309, 95%CI: 0.100-0.952, P = 0.041, respectively). Among the patients with PDAC, patients reporting bloating have a higher abundance of Porphyromonas (P = 0.039), Fusobacterium (P = 0.024), and Alloprevotella (P = 0.041); while patients reporting jaundice had a higher amount of Prevotella (P = 0.008); patients reporting dark brown urine had a higher amount of Veillonella (P = 0.035). Patients reporting diarrhea had a lower amount of Neisseria and Campylobacter (P = 0.024 and P = 0.034), and patients reporting vomiting had decreased Alloprevotella (P = 0.036).CONCLUSIONSaliva microbiome was able to distinguish patients with pancreatic cancer and healthy individuals. Leptotrichia may be specific for patients living in Sichuan Province, southwest China. Symptomatic patients had different bacteria profiles than asymptomatic patients. Combined symptom and microbiome evaluation may help in the early detection of pancreatic cancer.

Impact of Streptococcus salivarius K12 on Nasopharyngeal and Saliva Microbiome: A Randomized Controlled Trial.

Probiotic lactobacilli have been ineffective in preventing acute otitis media. In contrast to lactobacilli, alpha-hemolytic streptococci belong to the core microbiome of nasopharynx. We investigated the effects of Streptococcus salivarius K12 probiotic on the saliva and nasopharyngeal microbiome in 121 children attending daycare. Children were randomly allocated to receive oral K12 product for 1 month or no treatment. We obtained saliva and nasopharyngeal samples at study entry, at 1 and 2 months. The next-generation sequencing of the bacterial 16S gene was performed. After the intervention, the diversity of saliva or nasopharyngeal microbiome did not differ between groups. The proportion of children with any otopathogen did not differ between the groups. At 1 month, the abundance of otopathogens in nasopharynx was lower in K12 group compared with that in control children (34% vs. 55%, P = 0.037). When we compared each otopathogen separately, Moraxella was the only group lower in the treatment group. We could not verify the reduction of Moraxella when an alternative Human Oral Microbiome Database taxonomy database was used. In children receiving K12 product, the mean abundance of S. salivarius was greater in saliva after the intervention (0.9% vs. 2.0%, P = 0.009). The use of S. salivarius K12 probiotic appeared to be safe because it did not disrupt the normal microbiome in young children. Even though a short-term colonization of S. salivarius was observed in the saliva, the impact of S. salivarius K12 probiotic on the otopathogens in nasopharyngeal microbiome remained uncertain.

Comparative analysis of oral microbiome from Zang and Han populations living at different altitudes

ObjectivesThe aim of this study was to obtain greater insight into the environmental and genetic factors affecting the oral microbiome. DesignTo this end, we investigated the oral microbiome composition in Han and Zang populations living at different altitudes. The saliva microbiome in 115 individuals from Zang and Han populations living at different altitudes was analyzed using the 16 s rRNA gene sequencing method on the Illumina MiSeq platform. The dominant species in the oral microbiome were verified by quantitative real-time polymerase chain reaction (qPCR) analysis. ResultsThe Han population, living at an altitude of 500 m, had higher microbiome diversity than the Zang population living at altitudes of 3000–4000 m. People living at 3000 m had a higher relative abundance of Leptothrix genus, but people living at 500 m had a higher relative abundance of Capnocytophaga genus according to Lefse difference analysis (P < 0.05). Compared to the Zang population, the Han population had higher relative abundances of Porphyromonas and Treponema genus organisms, especially Porphyromonas (P < 0.001). qPCR analysis confirmed that people living at high altitudes had the highest relative abundance of Porphyromonas gingivalis (P < 0.01). ConclusionsThis study showed that both genetics and the environment had significant influences on the oral microbiome composition. The study proposed a meaningful research direction to explore the relationship between different ethnic and altitude groups and oral diseases, such as periodontal diseases.

Trick or Treating in Forensics-The Challenge of the Saliva Microbiome: A Narrative Review.

The oral microbiome harbours microbial community signatures that differ among individuals, highlighting that it could be highly individualizing and potentially unique to each individual. Therefore, the oral microbial traces collected in crime scenes could produce investigative leads. This narrative review will describe the current state-of-the-art of how the salivary microbiome could be exploited as a genetic signature to make inferences in the forensic field. This review has been performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines. Even if further studies are needed to relate the variation in the oral microbiome to specific factors, in order to understand how the salivary microbiome is influenced by an individual’s lifestyle, by reviewing the studies published so far, it is clear that the oral microbial analysis could become a useful forensic tool. Even if promising, caution is required in interpreting the results and an effort to direct research towards studies that fill the current knowledge gaps is certainly useful.

The Link between Oral and Gut Microbiota in Inflammatory Bowel Disease and a Synopsis of Potential Salivary Biomarkers

The objective of this review is to provide recent evidence for the oral–gut axis connection and to discuss gastrointestinal (GI) immune response, inflammatory bowel disease (IBD) pathogenesis, and potential salivary biomarkers for determining GI health. IBD affects an estimated 1.3% of the US adult population. While genetic predisposition and environment play a role, abnormal immune activity and microbiota dysbiosis within the gastrointestinal tract are also linked in IBD pathogenesis. It has been inferred that a reduced overall richness of bacterial species as well as colonization of opportunistic bacteria induce systemic inflammation in the GI tract. Currently, there is supporting evidence that both oral and gut microbiota may be related to the development of IBD. Despite this, there are currently no curative therapies for IBD, and diagnosis requires samples of blood, stool, and invasive diagnostic imaging techniques. Considering the relative ease of collection, emerging evidence of association with non-oral diseases may imply that saliva microbiome research may have the potential for gut diagnostic or prognostic value. This review demonstrates a link between saliva and intestinal profiles in IBD patients, suggesting that saliva sampling has the potential to serve as a non-invasive biomarker for gut diseases such as IBD in the oral–gut axis.

Association between the microbiomes of tonsil and saliva samples isolated from pediatric patients subjected to tonsillectomy for the treatment of tonsillar hyperplasia

Oral microbes have the capacity to spread throughout the gastrointestinal system and are strongly associated with multiple diseases. Given that tonsils are located between the oral cavity and the laryngopharynx at the gateway of the alimentary and respiratory tracts, tonsillar tissue may also be affected by microbiota from both the oral cavity (saliva) and the alimentary tract. Here, we analyzed the distribution and association of the microbial communities in the saliva and tonsils of Korean children subjected to tonsillectomy because of tonsil hyperplasia (n = 29). The microbiome profiles of saliva and tonsils were established via 16S rRNA gene sequencing. Based on the alpha diversity indices, the microbial communities of the two groups showed high similarities. According to Spearman’s ranking correlation analysis, the distribution of Treponema, the causative bacterium of periodontitis, in saliva and tonsils was found to have a significant positive correlation. Two representative microbes, Prevotella in saliva and Alloprevotella in tonsils, were negatively correlated, while Treponema 2 showed a strong positive correlation between saliva and tonsils. Taken together, strong similarities in the microbial communities of the tonsils and saliva are evident in terms of diversity and composition. The saliva microbiome is expected to significantly affect the tonsil microbiome. Furthermore, we suggest that our study creates an opportunity for tonsillar microbiome research to facilitate the development of novel microbiome-based therapeutic strategies.

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children.

Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD.

A longitudinal study of the development of the saliva microbiome in infants 2 days to 5 years compared to the microbiome in adolescents

Understanding oral microbiota programming attracts increasing interest due to its importance for oral health and potential associations with systemic diseases. Here the oral microbiota was longitudinally characterized in children from 2 days (n = 206) to 5 years of age and in young adults (n = 175) by sequencing of the v3-v4 region of the 16S rRNA gene from saliva extracted DNA. Alpha diversity increased by age, with 2-day- and 3-month-old infants in one sub-group, and 18-month- and 3-year-old children in another. Firmicutes decreased up to 3 years of age, whereas Proteobacteria, Actinobacteria, Bacteroidetes and Fusobacteria abundances increased. Abiotrophia, Actinomyces, Capnocytophaga, Corynebacterium, Fusobacterium, Kingella, Leptotrichia, Neisseria and Porphyromonas appeared from 18-months of age. This was paralleled by expansions in the core microbiome that continued up to adulthood. The age-related microbiota transformation was paralleled by functional alterations, e.g., changed metabolic pathways that reflected e.g., breastfeeding and increasing proportions of anaerobic species. Oral microbiotas differed by feeding mode and weakly by mode of delivery, but not gender, pacifier use or cleaning method or probiotic intake. The study shows that the saliva microbiota is diverse 2 days after birth and under transformation up to 5 years of age and beyond, with fluctuations possibly reflecting age-related environmental influences.

&lt;i&gt;In silico&lt;/i&gt;&amp;nbsp;Approach Toward the Identification of Unique Peptides from Viral Protein Infection: Application to COVID-19

We describe a method for rapid in silico selection of diagnostic peptides from newly described viral pathogens and applied this approach to SARS-CoV-2/COVID-19. This approach is multi-tiered, beginning with compiling the theoretical protein sequences from genomic derived data. In the case of SARS-CoV-2 we begin with 496 peptides that would be produced by proteolytic digestion of the viral proteins. To eliminate peptides that would cause cross-reactivity and false positives we remove peptides from consideration that have sequence homology or similar chemical characteristics using a progressively larger database of background peptides. Using this pipeline, we can remove 47 peptides from consideration as diagnostic due to the presence of peptides derived from the human proteome. To address the complexity of the human microbiome, we describe a method to create a database of all proteins of relevant abundance in the saliva microbiome. By utilizing a protein-based approach to the microbiome we can more accurately identify peptides that will be problematic in COVID-19 studies which removes 12 peptides from consideration. To identify diagnostic peptides, another 7 peptides are flagged for removal following comparison to the proteome backgrounds of viral and bacterial pathogens of similar clinical presentation. By aligning the protein sequences of SARS-CoV-2 field isolates deposited to date we can identify peptides for removal due to their presence in highly variable regions that may lead to false negatives as the pathogen evolves. We provide maps of these regions and highlight 3 peptides that should be avoided as potential diagnostic or vaccine targets. Finally, we leverage publicly deposited proteomics data from human cells infected with SARS-CoV-2, as well as a second study with the closely related MERS-CoV to identify the two proteins of highest abundance in human infections. The resulting final list contains the 24 peptides most unique and diagnostic of SARS-CoV-2 infections. These peptides represent the best targets for the development of antibodies are clinical diagnostics. To demonstrate one application of this we model peptide fragmentation using a deep learning tool to rapidly generate targeted LCMS assays and data processing method for detecting CoVID-19 infected patient samples. Funding: No external funding was utilized in or toward this study. Conflict of Interest: The authors declare no competing interests.

Saliva Microbiome Changes in Patients With Periodontitis With and Without Chronic Obstructive Pulmonary Disease.

Objective: The oral microbiota plays a key part in the initial colonization by pathogens and the chronic inflammatory reaction of the host. We measured variations in the salivary microbiota and evaluated their potential associations with periodontitis and chronic obstructive pulmonary disease (COPD).Methods: We investigated the salivary microbiota of patients with COPD and periodontitis (n = 21) compared with that in patients with periodontitis alone (n = 36) and with healthy controls (HCs; n = 14), using pyrosequencing of polymerase chain reaction-amplified 16s rRNA genes.Results: Bacterial richness and diversity were significantly higher in patients suffering from COPD, and the bacterial family Lachnospiraceae was observed frequently only among patients with COPD and periodontitis. Veillonella, Rothia, Actinomyces, and Fusobacterium were the core bacterial genera that showed significant differences among patients with coincident COPD and periodontitis, patients with periodontitis alone, and HCs (p < 0.05). Veillonella, Rothia, and Actinomyces were observed much more frequently in patients with COPD and periodontitis, compared with that in HCs. All tested populations were divided into subgroups based on sex, smoking, or periodontitis index. In the subgroup with a bleeding index >2, Rothia was significantly different in periodontitis with and without COPD groups compared with HCs. In the subgroup with a plaque index >2.5, Rothia and Veillonella showed significant differences in periodontitis with and without COPD groups compared with HCs.Conclusion: Variations in salivary microbiota may be associated with COPD and periodontitis.

Dysbiosis of saliva microbiome in patients with oral lichen planus

BackgroundOral microbiota is not only important for maintaining oral health but also plays a role in various oral diseases. However, studies regarding microbiome changes in oral lichen planus (OLP) are very limited. To the best of our knowledge, there has been only two studies investigating salivary microbiome changes in OLP. Therefore, the purpose of this study was to identify the characteristic microbial profile in the saliva of OLP patients, with or without erosive lesions, and compare that with recurrent aphthous ulcer (RAU), a common oral immunological disorder that also shows multiple erosive/ulcerative lesions. Whole saliva samples were collected from 20 patients with OLP (erosive E, n = 10 and non-erosive NE, n = 10), 10 patients with RAU (U) and 10 healthy controls (C). DNA was extracted from the saliva samples, and the 16S rDNA gene V4 hypervariable region was analyzed using Illumina sequencing.ResultsWe obtained 4949 operational taxonomic units (OTUs) from the V4 region in all saliva samples. Community composition analysis showed a clear decreased relative abundance of genera Streptococcus and Sphingomonas in saliva from RAU patients when compared to the other three groups. Relative abundance of Lautropia and Gemella were higher in E group, whereas relative abundance of Haemophilus and Neisseria were higher in NE group when compared to C group. Abiotrophia and Oribacterium were higher in OLP (combining E and NE groups), while Eikenella and Aggregatibacter were lower when compared to C group. There was statistically significance in α-diversity between E and RAU groups(p < 0.05). Significant differences in β-diversity were detected in bacteria between E and C; NE and C; as well as E and NE groups. The LDA effect size algorithm identified the g_Haemophilus might be the potential biomarker in NE group.ConclusionsWe found that salivary microbiome in erosive OLP was significantly different from that found in RAU; and these changes may be related to the underlying disease process rather than presence of ulcerative/erosive lesions clinically. In addition, our findings in bacterial relative abundance in OLP were significantly different from the previously reported findings, which points to the need for further research in salivary microbiome of OLP.

Lower airway bacterial microbiome may influence recurrence after resection of early-stage non–small cell lung cancer

ObjectiveThe lower airway bacterial microbiome influences carcinogenesis and response to immunotherapy in non–small cell lung cancer (NSCLC). We investigated the association of this microbiome with recurrence in early NSCLC. MethodsMicrobiomes of presurgery bronchoalveolar lavage (BAL) and saliva, and resected stage I NSCLC tumor and adjacent lung tissues of 48 patients were examined by 16S gene sequencing. Tumor gene expression was measured by RNA sequencing. ResultsSpatial relationships of the different biospecimen types was reflected in their microbiomes, with microbiomes of BAL intermediate to those of saliva and lung tissue. BAL and saliva microbiomes were less dissimilar in patients with high α-amylase levels in BAL, indicating oral aspiration as a source of lower airway microbiota. BAL microbiomes of patients with recurrence within 32 months of surgery differed from those without recurrence during ≥32 months of follow-up (n = 18 each), despite no difference for age, sex, smoking history, and tumor histology and grade. The recurrence-associated BAL microbiome signature was present in 16 of the 18 recurrence cases but in only two of the others. Signature presence was associated with shorter recurrence-free survival (log-rank test P < .001; hazard ratio = 14.5), and greater expression in tumors of genes for cell proliferation and epithelial mesenchymal transition. Immune cellular composition of the tumor microenvironment was not different between patients with and without the signature. ConclusionsPresurgery composition of lower airway microbiome may be associated with recurrence of early NSCLC. This association may reflect an influence of the microbiome on tumor biology.

Response of the human gut and saliva microbiome to urbanization in Cameroon

Urban populations from highly industrialized countries are characterized by a lower gut bacterial diversity as well as by changes in composition compared to rural populations from less industrialized countries. To unveil the mechanisms and factors leading to this diversity loss, it is necessary to identify the factors associated with urbanization-induced shifts at a smaller geographical scale, especially in less industrialized countries. To do so, we investigated potential associations between a variety of dietary, medical, parasitological and socio-cultural factors and the gut and saliva microbiomes of 147 individuals from three populations along an urbanization gradient in Cameroon. We found that the presence of Entamoeba sp., a commensal gut protozoan, followed by stool consistency, were major determinants of the gut microbiome diversity and composition. Interestingly, urban individuals have retained most of their gut eukaryotic and bacterial diversity despite significant changes in diet compared to the rural areas, suggesting that the loss of bacterial microbiome diversity observed in industrialized areas is likely associated with medication. Finally, we observed a weak positive correlation between the gut and the saliva microbiome diversity and composition, even though the saliva microbiome is mainly shaped by habitat-related factors.