Factors influencing oral microbiome analysis: from saliva sampling methods to next-generation sequencing platforms

Mixed oral biofilms are controlled by the interspecies interactions of Fusobacterium nucleatum

BACKGROUND

Fusobacterium nucleatum (F. nucleatum) is an integral component of supra- and subgingival biofilms, especially more prevalent in subgingival areas during both periodontal health and disease.

AIMS

In this review, we explore the physical, metabolic, and genetic interactions that influence the role of F. nucleatum in the formation of mixed oral biofilms. The role of F. nucleatum in antibiotic resistance in oral biofilms was discussed and some therapeutic strategies were proposed.

METHODS

PubMed, Scopus, Google Scholar, and the Web of Science were extensively searched for English-language reports.

RESULTS

F. nucleatum-derived proteins such as RadD, Fap2, FomA, and CmpA are involved in direct interactions contributing to biofilm formation, while autoinducer-2 and putrescine are involved in metabolic interactions. Both groups are essential for the formation and persistence of oral biofilms. This study highlights the clinical relevance of targeted interactions of F. nucleatum in supra- and subgingival oral biofilms.

CONCLUSIONS

By focusing on these interactions, researchers and clinicians can develop more effective strategies to prevent biofilm-related disease and reduce the spread of antibiotic resistance. Further research in this area is warranted to explore the potential therapeutic interventions that can be derived from understanding the interactions of F. nucleatum in oral biofilm dynamics.

Assessing peri-implant bacterial community structure: the effect of microbiome sample collection method

BACKGROUND

Oral microbiota comprises polymicrobial communities shaped by mutualistic coevolution with the host, contributing to homeostasis and regulating immune function. Nevertheless, dysbiosis of oral bacterial communities is associated with a number of clinical symptoms that ranges from infections to oral cancer. Peri-implant diseases are biofilm-associated inflammatory conditions affecting the soft and hard tissues around dental implants. Characterization and identification of the biofilm community are essential for the understanding of the pathophysiology of such diseases. For that sampling methods should be representative of the biofilm communities Therefore, there is a need to know the effect of different sampling strategies on the biofilm characterization by next generation sequencing.

METHODS

With the aim of selecting an appropriate microbiome sampling procedure for periimplant biofilms, next generation sequencing was used for characterizing the bacterial communities obtained by three different sampling strategies two months after transepithelial abutment placement: adjacent periodontal crevicular fluid (ToCF), crevicular fluid from transepithelial abutment (TACF) and transepithelial abutment (TA).

RESULTS

Significant differences in multiple alpha diversity indices were detected at both the OTU and the genus level between different sampling procedures. Differentially abundant taxa were detected between sample collection strategies, including peri-implant health and disease related taxa. At the community level significant differences were also detected between TACF and TA and also between TA and ToCF. Moreover, differential network properties and association patterns were identified.

CONCLUSIONS

The selection of sample collection strategy can significantly affect the community composition and structure.

TRIAL REGISTRATION

This research is part of a randomized clinical trial that was designed to assess the effect of transepithelial abutment surface on the biofilm formation. The trial was registered at Trial Registration ClinicalTrials.gov under the number NCT03554876.

The emerging role of the gut microbiota and its application in inflammatory bowel disease

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a complex disorder with an unknown cause. However, the dysbiosis of the gut microbiome has been found to play a role in IBD etiology, including exacerbated immune responses and defective intestinal barrier integrity. The gut microbiome can also be a potential biomarker for several diseases, including IBD. Currently, conventional treatments targeting pro-inflammatory cytokines and pathways in IBD-associated dysbiosis do not yield effective results. Other therapies that directly target the dysbiotic microbiome for effective outcomes are emerging. We review the role of the gut microbiome in health and IBD and its potential as a diagnostic, prognostic, and therapeutic target for IBD. This review also explores emerging therapeutic advancements that target gut microbiome-associated alterations in IBD, such as nanoparticle or encapsulation delivery, fecal microbiota transplantation, nutritional therapies, microbiome/probiotic engineering, phage therapy, mesenchymal stem cells (MSCs), gut proteins, and herbal formulas.

Impact of root canal disinfection on the bacteriome present in primary endodontic infection: A next generation sequencing study

AIM

To investigate the bacteriome present in teeth with primary endodontic infection (PEI) and apical periodontitis (AP) and to determine quantitatively and qualitatively the impact of chemomechanical preparation (CMP) using 2.5% sodium hypochlorite NAOCl on the bacteriome found in PEI with AP using the Illumina MiSeq platform.

METHODOLOGY

Thirty-six paired samples from 18 patients were successfully sequenced and analysed. Samples were collected at two sampling times: before (s1) and after (s2) CMP using 2.5% NaOCl. The DNA was extracted from s1 and s2 samples and quantified using quantitative PCR (qPCR). All 36 samples were sequenced using the Illumina MiSeq platform. Raw V3-V4 amplicon sequencing data were processed with the DADA2 pipeline to generate amplicon sequence variants (ASVs). Alpha diversity metrics representing abundance (Chao1) and diversity and evenness (Shannon, Simpson) were computed. The paired-sample Wilcoxon's test was used to compare alpha diversity metrics and qPCR counts between s1 and s2. The PERMANOVA method (with 999 permutations) was applied to compare community composition between sample types (s1 versus s2) and between patient IDs. ALDEx2 (ANOVA-like differential expression tool for high-throughput sequencing data) to investigate differentially abundant taxa between s1 and s2. A paired-sample Wilcoxon's test was used to compare alpha diversity metrics and qPCR counts between s1 and s2.

RESULTS

The qPCR counts were significantly higher in s1 compared to s2 (p = .0007). The Chao1 index indicated no difference in alpha diversity (p < .7019); whereas Shannon (p = .0056) and Simpson (p = .02685) indexes showed higher values in s2. The PERMANOVA test using Adonis2 showed a significant effect of sample time on community composition (R2 = .0630, p = .012). Patient ID also showed a significant effect on community composition (R2 = .6961, p = .001). At the genus level, Dialister, Mogibacterium, Prevotella, and Olsenella were differentially enriched at s1, while Actinomyces, Stenotrophomonas_unclassified, Enterococcus_unclassified, and Actinomyces_unclassified were differentially enriched in s2.

CONCLUSION

The bacteriome present in teeth with PEI with AP is complex and diverse. CMP using 2.5% NaOCl showed a high quantitatively and qualitatively disinfectant impact on the bacteriome present in PEI with AP.

Saliva assay: a call for methodological standardization

The oral cavity provides an ideal environment for microorganisms, including bacteria, viruses, and fungi, to flourish. Increasing attention has been focused on the connection between the oral microbiome and both oral and systemic diseases, spurring active research into the collection and analysis of specimens for healthcare purposes. Among the various methods for analyzing the oral microbiome, saliva analysis is especially prominent. Saliva samples, which can be collected non-invasively, provide information on the systemic health and oral microbiome composition of an individual. This review was performed to evaluate the current state of the relevant research through an examination of the literature and to suggest an appropriate assay method for investigating the oral microbiome. We analyzed articles published in English in SCI(E) journals after January 1, 2000, ultimately selecting 53 articles for review. Articles were identified through keyword searches in the PubMed, Embase, Cochrane, Web of Science, and CINAHL databases. Three experienced researchers conducted full-text assessments following title and abstract screening to select appropriate papers. Subsequently, they organized and analyzed the desired data. Our review revealed that most studies utilized unstimulated saliva samples for oral microbiome analysis. Of the 53 studies examined, 29 identified relationships between the oral microbiome and various diseases, such as oral disease, Behçet disease, cancer, and oral lichen planus. However, the studies employed diverse methods of collection and analysis, which compromised the reliability and accuracy of the findings. To address the limitations caused by methodological inconsistencies, a standardized saliva assay should be established.

Microbes for lung cancer detection: feasibility and limitations

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

Advances in Electrochemical Biosensors for the Detection of Common Oral Diseases

Limiting and preventing oral diseases remains a major challenge to the health of populations around the world, so finding ways to detect early-stage diseases (e.g., caries, periodontal disease, and oral cancer) and aiding in their prevention has always been an important clinical treatment concept. The development and application of electrochemical detection technology can provide important support for the early detection and non-invasive diagnosis of oral diseases and make up for the shortcomings of traditional diagnostic methods, which are highly sensitive, non-invasive, cost-effective, and less labor-intensive. It detects specific disease markers in body fluids through electrochemical reactions, discovers early warning signals of diseases, and realizes rapid and reliable diagnosis. This paper comprehensively summarizes the development and application of electrochemical biosensors in the detection and diagnosis of common oral diseases in terms of application platforms, sensing types, and disease detection, and discusses the challenges faced by electrochemical biosensors in the detection of oral diseases as well as the great prospects for future applications, in the hope of providing important insights for the future development of electrochemical biosensors for the early detection of oral diseases.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Single-cell RNA-Seq reveals intracellular microbial diversity within immune cells during SARS-CoV-2 infection and recovery

Intracellular microorganisms, like viruses, bacteria, and fungi, pose challenges in detection due to their non-culturable forms. Transcriptomic analysis at cellular level enables exploration of distributions and the impact of these microorganisms on host cells, a domain that remains underexplored because of methodological limitations. Single-cell technology shows promise in addressing this by capturing polyadenine-tailed transcripts, because recent studies confirmed polyadenylation in microbial transcriptomes. We utilized single-cell RNA-seq from PBMCs to probe intracellular microbes in healthy, SARS-CoV-2-positive, and recovered individuals. Among 76 bacterial species detected, 16 showed significant abundance differences. Buchnera aphidicola, Streptomyces clavuligerus, and Ehrlichia canis emerged significantly in memory-B, Naïve-T, and Treg cells. Staphylococcus aureus, Mycoplasma mycoides, Leptospira interrogans, and others displayed elevated levels in SARS-CoV-2-positive patients, suggesting possible disease association. This highlights the strength of single-cell technology in revealing potential microorganism's cell-specific functions. Further research is essential for functional understanding of their cell-specific abundance across physiological states.

Mucosal Microbiome in Patients with Early Bowel Polyps: Inferences from Short-Read and Long-Read 16S rRNA Sequencing

Numerous studies have correlated dysbiosis in stool microbiota with colorectal cancer (CRC); however, fewer studies have investigated the mucosal microbiome in pre-cancerous bowel polyps. The short-read sequencing of variable regions in the 16S rRNA gene has commonly been used to infer bacterial taxonomy, and this has led, in part, to inconsistent findings between studies. Here, we examined mucosal microbiota from patients who presented with one or more polyps, compared to patients with no polyps, at the time of colonoscopy. We evaluated the results obtained using both short-read and PacBio long-read 16S rRNA sequencing. Neither sequencing technology identified significant differences in microbial diversity measures between patients with or without bowel polyps. Differential abundance measures showed that amplicon sequence variants (ASVs) associated with Ruminococcus gnavus and Escherichia coli were elevated in mucosa from polyp patients, while ASVs associated with Parabacteroides merdae, Veillonella nakazawae, and Sutterella wadsworthensis were relatively decreased. Only R. gnavus was consistently identified using both sequencing technologies as being altered between patients with polyps compared to patients without polyps, suggesting differences in technologies and bioinformatics processing impact study findings. Several of the differentially abundant bacteria identified using either sequencing technology are associated with inflammatory bowel diseases despite these patients being excluded from the current study, which suggests that early bowel neoplasia may be associated with a local inflammatory niche.