口腔微生物采集

目的：本研究通过比较口腔鳞状细胞癌(OSCC)、口腔潜在恶性病变(OPMD)及对照组的唾液中IL-6、IL-8、MMP-9的浓度差别，筛选出能够用于预测OSCC发生的特异性的唾液分子标记物。方法：将60名受试者分为3个研究组，即OSCC组(n = 20)、OPMD组(n = 20)和健康对照组(n = 20)。所有受试者均提供非刺激性的唾液样本，使用ELISA试剂盒检测IL-6、IL-8、MMP-9的浓度。结果：OSCC组的唾液IL-6、IL-8、MMP-9浓度显著高于对照组(P < 0.05)，OPMD组的唾液IL-6、IL-8、MMP-9浓度高于对照组，且IL-8的浓度具有统计学差异(P < 0.05)。OSCC组的唾液IL-6、IL-8、MMP-9的浓度显著高于OPMD组(P < 0.05)。结论：本研究表明OSCC唾液中的IL-6、IL-8、MMP-9的浓度相比对照组显著增高，且OSCC和OPMD组间唾液IL-6、IL-8、MMP-9的浓度存在统计学差异。唾液IL-6、IL-8、MMP-9在OSCC和OPMD的治疗、癌前预测及随访中是一种有临床参考价值的特异唾液分子标志物。

目的：建立实验小鼠四种常见病原微生物的多重PCR快速检测方法。方法：对四种病原微生物引物浓度、特异性以及DNA模板的敏感性进行测试，优化多重PCR反应条件；对活体实验动物口腔及粪便样本进行优化处理，简化DNA模板的提取方法。结果：四种病原微生物的多重PCR反应在引物浓度0.15 μmol/L和退火温度56℃的反应条件下扩增，灵敏度高(绿脓杆菌的敏感性为100 pg，金黄色葡萄球菌的敏感性为1 pg，肺炎克雷伯杆菌的敏感性为10 pg，嗜肺巴斯德杆菌的敏感性为1 pg)且特异性好，与实验动物常见的致病菌无交叉反应。活体实验动物口腔及粪便样本经培养煮沸1 min后即能快速获取检测模板。结论：该方法灵敏特异、简便快速，可为活体实验动物大规模筛查和检测四种病原微生物提供借鉴。

目的：分析近年儿童猩红热的临床特征。方法：对113例有发热皮疹等临床表现并经咽拭子培养A组β型溶血性链球菌阳性的儿童猩红热确诊病例的临床特征进行回顾性分析。结果：113例患儿中男70例，女43例，4~7岁年龄段儿童占77.9%；90例有发热，占79.6%；全部患儿均有皮疹，典型充血性鸡皮样粟粒疹73例(64.6%)，口腔黏膜明显充血83例(73.4%)，口周苍白圈14例(12.4%)，巴氏线20例(17.7%)；皮疹以躯干部位最为常见，占91.2%；首诊临床诊断为“猩红热”14例；全部患儿均未出现严重并发症表现。结论：学龄前期及学龄期儿童是猩红热的高发人群，临床症状趋于轻症化、不典型化，临床缺少快速实验室诊断方法，易延误早期临床诊治。除典型皮疹外，口腔黏膜明显充血可能是猩红热的早期表现之一，可进一步深入研究。

目的：压舌板作为一种常规的医疗诊疗检查器具，广泛应用于口腔护理操作、五官科常规检查、窒息抢救、发音治疗、某些手术的辅助治疗等操作；方法：从压舌板的改进及压舌板在临床中的应用两个方面进行综述，为新型压舌板的研发及临床使用提供新思路，同时对压舌板的应用前景进行了展望。

The oral microbiome, studied by sampling the saliva or by oral rinse, has been long thought to have diagnostic capacity for head and neck cancers (HNC). However, previous reports on the HNC oral microbiome provide inconsistent results. The aim of this study is to consolidate these datasets and determine the oral microbial composition between HNC patients to healthy and premalignant individuals. We analyzed 16 published head and neck cancer (HNC) short-read 16S rRNA sequencing datasets, specifically targeting the V3V4, V4 and V4V5 regions. These datasets included saliva and oral rinse samples from donors with HNC, as well as from healthy and premalignant donors. Differences in diversities and microbial abundance were determined. HNC saliva displayed lower alpha diversity than healthy donors. In contrast, the opposite trend was observed for oral rinse samples. Beta diversity scores were largely similar across different patient types. Similar oral phyla were detected for all samples, but proportions were largely dependent on sample type (i.e., saliva or oral rinse) and primer set utilized for 16S rRNA sequencing. Neisseria, Leptotrichia and Megasphaera were elevated in healthy saliva, while Mycoplasma was elevated in HNC saliva. Oral rinse and saliva displayed similar enrichment for Fusobacterium, while Veillonella, Alloprevotella, and Campylobacter showed conflicting results. The sparse partial least squares discriminant analysis model performed effectively in discriminating HNC from healthy or premalignant patients using V3V4 saliva (AUC = 0.888) and V3V4 oral rinse (AUC = 0.928), while poor discriminative capacity was observed for V4 saliva (AUC = 0.688). In conclusion, our meta-analysis highlighted the limitations of 16S rRNA sequencing, particularly due to variations across study batches, primer sets (i.e., V3V4, V4), and sample types. Hence, caution should be exercised when interpreting 16S rRNA sequencing results across studies, especially when different primer sets and sample types are used.

No abstract available

Saliva is a readily accessible and inexpensive biological specimen that enables investigation of the oral microbiome, which can serve as a biomarker of oral and systemic health. There are two routine approaches to collect saliva, stimulated and unstimulated; however, there is no consensus on how sampling method influences oral microbiome metrics. In this study, we analyzed paired saliva samples (unstimulated and stimulated) from 88 individuals, aged 7–18 years. Using 16S rRNA gene sequencing, we investigated the differences in bacterial microbiome composition between sample types and determined how sampling method affects the distribution of taxa associated with untreated dental caries and gingivitis. Our analyses indicated significant differences in microbiome composition between the sample types. Both sampling methods were able to detect significant differences in microbiome composition between healthy subjects and subjects with untreated caries. However, only stimulated saliva revealed a significant association between microbiome diversity and composition in individuals with diagnosed gingivitis. Furthermore, taxa previously associated with dental caries and gingivitis were preferentially enriched in individuals with each respective disease only in stimulated saliva. Our study suggests that stimulated saliva provides a more nuanced readout of microbiome composition and taxa distribution associated with untreated dental caries and gingivitis compared to unstimulated saliva.

The exploration of oral microbiome has been increasing due to its relatedness with various systemic diseases, but standardization of saliva sampling for microbiome analysis has not been established, contributing to the lack of data comparability. Here, we evaluated the factors that influence the microbiome data. Saliva samples were collected by the two collection methods (passive drooling and mouthwash) using three saliva-preservation methods (OMNIgene, DNA/RNA shield, and simple collection). A total of 18 samples were sequenced by both Illumina short-read and Nanopore long-read next-generation sequencing (NGS). The component of the oral microbiome in each sample was compared with alpha and beta diversity and the taxonomic abundances, to find out the effects of factors on oral microbiome data. The alpha diversity indices of the mouthwash sample were significantly higher than that of the drooling group with both short-read and long-read NGS, while no significant differences in microbial diversities were found between the three saliva-preservation methods. Our study shows mouthwash and simple collection are not inferior to other sample collection and saliva-preservation methods, respectively. This result is promising since the convenience and cost-effectiveness of mouthwash and simple collection can simplify the saliva sample preparation, which would greatly help clinical operators and lab workers.

Recent research suggests that dysbiosis of the oral microbial community is associated with head and neck cancer (HNC). It remains unclear whether this dysbiosis causes chemo-radiotherapy (CRT)-related complications. However, to address this question, it is essential to determine the most representative oral site for microbiome sampling. In this study, our purpose was to determine the optimal site for oral sample collection and whether the presence of HNC is associated with altered oral microbiome from this site. In 21 newly diagnosed HNC patients and 27 healthy controls, microbiome samples were collected from saliva, swabs from buccal mucosa, tongue, hard palate, faucial pillars and all mucosal sites combined. Microbial DNA was extracted and underwent 16S rRNA amplicon gene sequencing. In healthy controls, analysis of observed taxonomic units detected differences in alpha- and beta-diversity between sampling sites. Saliva was found to have the highest intra-community microbial diversity and lowest within-subject (temporal) and between-subject variance. Feature intersection showed that most species were shared between all sites, with saliva demonstrating the most unique species as well as highest overlap with other sites. In HNC patients, saliva was found to have the highest diversity but differences between sites were not statistically significant. Across all sites, HNC patients had lower alpha diversity than healthy controls. Beta-diversity analysis showed HNC patients’ microbiome to be compositionally distinct from healthy controls. This pattern was confirmed when the salivary microbiome was considered alone. HNC patients exhibited reduced diversity of the oral microbiome. Salivary samples demonstrate temporal stability, have the richest diversity and are sufficient to detect perturbation due to presence of HNC. Hence, they can be used as representative oral samples for microbiome studies in HNC patients.

Abstract There are multiple habitats in the oral cavity with bacteria, fungi, viruses, and protozoa residing in, which together constitute the oral micro‐ecosystem. These microflorae in the oral cavity primarily include saliva, supragingival dental plaque, subgingival dental plaque, submucosal plaque around implants, plaque in root canals, and plaque on the mucosal surface. The interest and knowledge of the microbiome have dynamically increased with the advancement of technology. Therefore, a reliable, feasible, and practical sampling strategy for the oral microbiome is required for the investigation. This paper introduced the sampling strategy of oral microorganisms, consisting of sample collection, transport, processing, and storage. The materials and devices involved in this study are all commonly used in clinical practice or laboratory. The feasibility and reliability of the sampling methods described in this paper have been verified by multiple studies.

When collecting oral and fecal samples for large epidemiological microbiome studies, optimal storage conditions such as immediate freezing, are not always feasible. It is fundamental to study the impact of temporary room temperature (RT) storage and shipping on the microbiome diversity obtained in different types of samples. We performed a pilot study aimed at validating the sampling protocol based on the viability of the 16S rRNA gene sequencing in microbiome samples. Fecal and oral samples from five participants were collected and preserved in different conditions: a) 70% ethanol; b) in a FIT tube for stool samples; and c) in a chlorhexidine solution for oral wash samples. Four aliquots were prepared per sample, which were stored at RT, and frozen at days 0, 5, 10 and 15, respectively. In terms of alpha diversity, the maximum average decrease in 5 days was 0.3%, 1.6% and 1.7% for oral, stool in ethanol and stool in FIT, respectively. Furthermore, the relative abundances of the most important phyla and orders remained stable over the two weeks. The stability of fecal and oral samples for microbiome studies preserved at RT with 70% ethanol, chlorhexidine and in FIT tubes was verified for a 15-day window, with no substantial changes in terms of alpha diversity and relative abundances.

Oral biofilm and its molecular analysis provide a basis for investigating various dental research and clinical questions. Knowledge of biofilm composition leads to a better understanding of cariogenic and periopathogenic mechanisms. Microbial changes taking place in the oral cavity during childhood are of interest for several reasons. The evolution of the child oral microbiota and shifts in its composition need to be analyzed further to understand and possibly prevent the onset of disease. At the same time, advanced knowledge of the natural composition of oral biofilm is needed. Early stages of caries-free permanent dentition with healthy gums provide a widely unaffected subgingival habitat that can serve as an in situ baseline for studying features of oral health and disease. Analysis of children's oral biofilm during different stages in life is thus an important theme in the field. Modern molecular analysis methods can provide comprehensive information about the bacterial diversity of such biofilms. To enable microbiota data comparison, it is important to standardize each step in the procedure for molecular data generation. This procedure spans from clinical sampling, Next Generation Sequencing (NGS), bioinformatic data processing, to taxonomic interpretation. One of the most critical factors here is biofilm sampling. Sampling in children is even more challenging in particular due to limited space in subgingival areas. We thus focus on the use of paper points for subgingival sampling. This article provides a detailed protocol for oral biofilm sampling of the subgingival sulcus, the mucosa, and saliva in children.

Periodontitis is caused by pathogenic subgingival microbial biofilm development and dysbiotic interactions between host and hosted microbes. A thorough characterization of the subgingival biofilms by deep amplicon sequencing of 121 individual periodontitis pockets of nine patients and whole metagenomic analysis of the saliva microbial community of the same subjects were carried out. Two biofilm sampling methods yielded similar microbial compositions. Taxonomic mapping of all biofilms revealed three distinct microbial clusters. Two clinical diagnostic parameters, probing pocket depth (PPD) and clinical attachment level (CAL), correlated with the cluster mapping. The dysbiotic microbiomes were less diverse than the apparently healthy ones of the same subjects. The most abundant periodontal pathogens were also present in the saliva, although in different representations. The single abundant species Tannerella forsythia was found in the diseased pockets in about 16–17-fold in excess relative to the clinically healthy sulcus, making it suitable as an indicator of periodontitis biofilms. The discrete microbial communities indicate strong selection by the host immune system and allow the design of targeted antibiotic treatment selective against the main periodontal pathogen(s) in the individual patients.

Dental plaque is composed of hundreds of bacterial taxonomic units and represents one of the most diverse and stable microbial ecosystems associated with the human body. Taxonomic composition and functional capacity of mature plaque is gradually shaped during several stages of community assembly via processes such as co-aggregation, competition for space and resources, and by bacterially produced reactive agents. Knowledge on the dynamics of assembly within complex communities is very limited and derives mainly from studies composed of a limited number of bacterial species. To fill current knowledge gaps, we applied parallel metagenomic and metatranscriptomic analyses during assembly and maturation of an in vitro oral biofilm. This model system has previously demonstrated remarkable reproducibility in taxonomic composition across replicate samples during maturation. Time course analysis of the biofilm maturation was performed by parallel sampling every 2–3 h for 24 h for both DNA and RNA. Metagenomic analyses revealed that community taxonomy changed most dramatically between three and six hours of growth when pH dropped from 6.5 to 5.5. By applying comparative metatranscriptome analysis we could identify major shifts in overall community activities between six and nine hours of growth when pH dropped below 5.5, as 29,015 genes were significantly up- or down- expressed. Several of the differentially expressed genes showed unique activities for individual bacterial genomes and were associated with pyruvate and lactate metabolism, two-component signaling pathways, production of antibacterial molecules, iron sequestration, pH neutralization, protein hydrolysis, and surface attachment. Our analysis also revealed several mechanisms responsible for the niche expansion of the cariogenic pathogen Lactobacillus fermentum. It is highly regarded that acidic conditions in dental plaque cause a net loss of enamel from teeth. Here, as pH drops below 5.5 pH to 4.7, we observe blooms of cariogenic lactobacilli, and a transition point of many bacterial gene expression activities within the community. To our knowledge, this represents the first study of the assembly and maturation of a complex oral bacterial biofilm community that addresses gene level functional responses over time.

Maintenance of astronaut health during spaceflight will require monitoring and potentially modulating their microbiomes. However, documenting microbial shifts during spaceflight has been difficult due to mission constraints that lead to limited sampling and profiling. Here we executed a six-month longitudinal study to quantify the high-resolution human microbiome response to three days in orbit for four individuals. Using paired metagenomics and metatranscriptomics alongside single-nuclei immune cell profiling, we characterized time-dependent, multikingdom microbiome changes across 750 samples and 10 body sites before, during and after spaceflight at eight timepoints. We found that most alterations were transient across body sites; for example, viruses increased in skin sites mostly during flight. However, longer-term shifts were observed in the oral microbiome, including increased plaque-associated bacteria (for example, Fusobacteriota), which correlated with immune cell gene expression. Further, microbial genes associated with phage activity, toxin–antitoxin systems and stress response were enriched across multiple body sites. In total, this study reveals in-depth characterization of microbiome and immune response shifts experienced by astronauts during short-term spaceflight and the associated changes to the living environment, which can help guide future missions, spacecraft design and space habitat planning. Longitudinal multi-omics reveals shifts to the human microbiome across multiple body sites and the associated immune responses during short-term spaceflight.

The aim was to evaluate susceptibility of oropharyngeal contamination with various bronchoscopic sampling techniques. 67 patients with obstructive lung disease and 58 control subjects underwent bronchoscopy with small-volume lavage (SVL) through the working channel, protected bronchoalveolar lavage (PBAL) and bilateral protected specimen brush (PSB) sampling. Subjects also provided an oral wash (OW) sample, and negative control samples were gathered for each bronchoscopy procedure. DNA encoding bacterial 16S ribosomal RNA was sequenced and bioinformatically processed to cluster into operational taxonomic units (OTU), assign taxonomy and obtain measures of diversity. The proportion of Proteobacteria increased, whereas Firmicutes diminished in the order OW, SVL, PBAL, PSB (p<0.01). The alpha-diversity decreased in the same order (p<0.01). Also, beta-diversity varied by sampling method (p<0.01), and visualisation of principal coordinates analyses indicated that differences in diversity were smaller between OW and SVL and OW and PBAL samples than for OW and the PSB samples. The order of sampling (left versus right first) did not influence alpha- or beta-diversity for PSB samples. Studies of the airway microbiota need to address the potential for oropharyngeal contamination, and protected sampling might represent an acceptable measure to minimise this problem. Protected bronchoscopic sampling is most suitable for identification of a distinct airway microbiome http://ow.ly/qIIy30eqB9M

AIMS The microbial profiles of peri-implantitis and periodontitis (PT) are inconclusive. The controversies mainly arise from the differences in sampling sites, targeted gene fragment, and microbiome analysis techniques. The objective of this study was to explore the microbiomes of peri-implantitis (PI), control implants (CI), PT and control teeth (CT), and the microbial change of PI after nonsurgical treatment (PIAT). METHODS Twenty-two patients diagnosed with both PT and peri-implantitis were recruited. Clinical periodontal parameters and radiographic bone levels were recorded. In each patient, the subgingival and submucosal plaque samples were collected from sites with PI, CI, PT, CT, and PIAT. Microbiome diversity was analyzed by high-throughput amplicon sequencing using full-length of 16S rRNA gene by next generation sequencing. RESULTS The 16S rRNA gene sequencing analysis revealed 512 OTUs in oral microbiome and 377 OTUs reached strain levels. The PI and PT groups possessed their own unique core microbiome. Treponema denticola was predominant in PI with probing depth of 8-10 mm. Interestingly, Thermovirga lienii DSM 17291 and Dialister invisus DSM 15470 were found to associate with PI. Nonsurgical treatment for peri-implantitis did not significantly alter the microbiome, except Rothia aeria. CONCLUSION Our study suggests Treponemas species may play a pivotal role in peri-implantitis. Nonsurgical treatment did not exert a major influence on the peri-implantitis microbiome in short-term follow-up. PT and peri-implantitis possess the unique microbiome profiles, and different therapeutic strategies may be suggested in the future.

Molecular characterization of the oral microbiome is a crucial first step in experiments which aim to understand the complex dynamics of the oral microbiome or the interplay with host health and disease. Third-generation Oxford Nanopore Technology (ONT) offers advanced long-read sequencing capabilities, which hold promise for improved molecular characterization by distinguishing closely related microbial species within oral ecosystems in health and disease states. However, the performance of ONT sequencing of oral samples requires validation, and the consistency of this approach across different analytical and sampling conditions is not well understood. This study evaluates various factors that may influence the ONT sequencing outputs of saliva microbiota and compares results with those from Illumina MiSeq’s v3v4 amplicon sequencing. Our analysis includes assessments of various stages in the workflow, including different collection and extraction methods, such as robot-extracted saliva DNA used in population-based biobanks, the effects of limited DNA quantities, different bioinformatics pipelines, and different 16S rRNA gene databases. The results demonstrate that ONT provides superior resolution in identifying oral species and subspecies compared to Illumina MiSeq, though the choice of bioinformatics strategy significantly affects the outcomes. Additionally, we confirm the suitability of biobank saliva DNA for large-scale cohort studies, which facilitates the mapping of oral bacterial phylotypes associated with disease states, including less prevalent conditions. Overall, our findings confirm a markedly improved resolution of oral microbiomes by ONT and offer an evidence base to guide the conduct of experiments using this method.

Human microbial communities are characterized by their taxonomic, metagenomic and metabolic diversity, which varies by distinct body sites and influences human physiology. However, when and how microbial communities within each body niche acquire unique taxonomical and functional signatures in early life remains underexplored. We thus sought to determine the taxonomic composition and potential metabolic function of the neonatal and early infant microbiota across multiple body sites and assess the effect of the mode of delivery and its potential confounders or modifiers. A cohort of pregnant women in their early third trimester (n = 81) were prospectively enrolled for longitudinal sampling through 6 weeks after delivery, and a second matched cross-sectional cohort (n = 81) was additionally recruited for sampling once at the time of delivery. Samples across multiple body sites, including stool, oral gingiva, nares, skin and vagina were collected for each maternal–infant dyad. Whole-genome shotgun sequencing and sequencing analysis of the gene encoding the 16S rRNA were performed to interrogate the composition and function of the neonatal and maternal microbiota. We found that the neonatal microbiota and its associated functional pathways were relatively homogeneous across all body sites at delivery, with the notable exception of the neonatal meconium. However, by 6 weeks after delivery, the infant microbiota structure and function had substantially expanded and diversified, with the body site serving as the primary determinant of the composition of the bacterial community and its functional capacity. Although minor variations in the neonatal (immediately at birth) microbiota community structure were associated with the cesarean mode of delivery in some body sites (oral gingiva, nares and skin; R2 = 0.038), this was not true for neonatal stool (meconium; Mann–Whitney P > 0.05), and there was no observable difference in community function regardless of delivery mode. For infants at 6 weeks of age, the microbiota structure and function had expanded and diversified with demonstrable body site specificity (P < 0.001, R2 = 0.189) but without discernable differences in community structure or function between infants delivered vaginally or by cesarean surgery (P = 0.057, R2 = 0.007). We conclude that within the first 6 weeks of life, the infant microbiota undergoes substantial reorganization, which is primarily driven by body site and not by mode of delivery.

No abstract available

The oral microbiome is linked to oral and systemic health, but its fluctuation under frequent daily activities remains elusive. Here, we sampled saliva at 10- to 60-min intervals to track the high-resolution microbiome dynamics during the course of human activities. This dense time series data showed that eating activity markedly perturbed the salivary microbiota, with tongue-specific Campylobacter concisus and Oribacterium sinus and dental plaque-specific Lautropia mirabilis, Rothia aeria, and Neisseria oralis increased after every meal in a temporal order. The observation was reproducible in multiple subjects and across an 11-mo period. The microbiome composition showed significant diurnal oscillation patterns at different taxonomy levels with Prevotella/Alloprevotella increased at night and Bergeyella HMT 206/Haemophilus slowly increased during the daytime. We also identified microbial co-occurring patterns in saliva that are associated with the intricate biogeography of the oral microbiome. Microbial source tracking analysis showed that the contributions of distinct oral niches to the salivary microbiome were dynamically affected by daily activities, reflecting the role of saliva in exchanging microbes with other oral sites. Collectively, our study provides insights into the temporal microbiome variation in saliva and highlights the need to consider daily activities and diurnal factors in design of oral microbiome studies.

Background The rumen bacterial communities are changing dynamically throughout the first year of calf’s life including the weaning period as a critical event. Rumen microbiome analysis is often limited to invasive rumen sampling procedures but the oral cavity of ruminants is expected to harbour rumen microbes due to regurgitation activity. The present study used buccal swab samples to define the rumen core microbiome and characterize the shifts in rumen and oral microbial communities occurring as result of calf’s age as well as time of weaning. Results Buccal swab samples of 59 calves were collected along the first 140 days of life and compared to stomach tubing sample of the rumen at day 140. Animals were randomly divided into two weaning groups. Microbiota of saliva and rumen content was analysed by 16S rRNA gene amplicon sequencing. Our study showed that most rumen-specific bacterial taxa were equally observed in rumen samples as well as in the buccal swabs, though relative abundance varied. The occurrence of rumen-specific OTUs in buccal swab samples increased approximately 1.7 times from day 70 to day 140, indicating the gradual development of rumen as calf aged. The rumen-specific bacterial taxa diversity increased, and inter-animal variations decreased with age. Early weaning (7 weeks of age) rapidly increased the rumen microbial diversity from pre- to post-weaned state. Rumen microbiota of early-weaned calves seemed to have a suppressed growth of starch- and carbohydrate-utilizing bacteria and increased fibre degraders. Whereas, in late-weaned calves (17 weeks of age) no impact of dietary modifications on rumen microbiota composition was observed after weaning. Oral-specific bacterial community composition was significantly affected by calf’s age and time of weaning. Conclusions The present study showed the significant impact of calf’s age and weaning on the establishment of rumen- and oral-specific bacterial communities utilizing buccal swab samples. The results emphasize the possibility of using buccal swab samples as a replacement of complex stomach tube method for large-scale predictive studies on ruminants. For in-depth rumen microbiome studies, the time of sampling should be carefully considered using an active phase of regurgitation.

Saliva is a fascinating biological fluid which has all the features of a perfect diagnostic tool. In fact, its collection is rapid, simple, and noninvasive. Thanks to several transport mechanisms and its intimate contact with crevicular fluid, saliva contains hundreds of proteins deriving from plasma. Advances in analytical techniques have opened a new era—called “salivaomics”—that investigates the salivary proteome, transcriptome, microRNAs, metabolome, and microbiome. In recent years, researchers have tried to find salivary biomarkers for oral and systemic diseases with various protocols and technologies. The review aspires to provide an overall perspective of salivary biomarkers concerning oral diseases such as lichen planus, oral cancer, blistering diseases, and psoriasis. Saliva has proved to be a promising substrate for the early detection of oral diseases and the evaluation of therapeutic response. However, the wide variation in sampling, processing, and measuring of salivary elements still represents a limit for the application in clinical practice.

The low bacterial load in samples acquired from the lungs, have made studies on the airway microbiome vulnerable to contamination from bacterial DNA introduced during sampling and laboratory processing. We have examined the impact of laboratory contamination on samples collected from the lower airways by protected (through a sterile catheter) bronchoscopy and explored various in silico approaches to dealing with the contamination post-sequencing. Our analyses included quantitative PCR and targeted amplicon sequencing of the bacterial 16S rRNA gene. The mean bacterial load varied by sample type for the 23 study subjects (oral wash>1st fraction of protected bronchoalveolar lavage>protected specimen brush>2nd fraction of protected bronchoalveolar lavage; p < 0.001). By comparison to a dilution series of know bacterial composition and load, an estimated 10–50% of the bacterial community profiles for lower airway samples could be traced back to contaminating bacterial DNA introduced from the laboratory. We determined the main source of laboratory contaminants to be the DNA extraction kit (FastDNA Spin Kit). The removal of contaminants identified using tools within the Decontam R package appeared to provide a balance between keeping and removing taxa found in both negative controls and study samples. The influence of laboratory contamination will vary across airway microbiome studies. By reporting estimates of contaminant levels and taking use of contaminant identification tools (e.g. the Decontam R package) based on statistical models that limit the subjectivity of the researcher, the accuracy of inter-study comparisons can be improved.

Saliva diagnostics have become increasingly popular due to their non-invasive nature and patient-friendly collection process. Various collection methods are available, yet these are not always well standardized for either quantitative or qualitative analysis. In line, the objective of this study was to evaluate if measured levels of various biomarkers in the saliva of healthy individuals were affected by three distinct saliva collection methods: 1) unstimulated saliva, 2) chew stimulated saliva, and 3) oral rinse. Saliva samples from 30 healthy individuals were obtained by the three collection methods. Then, the levels of various salivary biomarkers such as proteins and ions were determined. It was found that levels of various biomarkers obtained from unstimulated saliva were comparable to those in chew stimulated saliva. The levels of potassium, sodium, and amylase activity differed significantly among the three collection methods. Levels of all biomarkers measured using the oral rinse method significantly differed from those obtained from unstimulated and chew-stimulated saliva. In conclusion, both unstimulated and chew-stimulated saliva provided comparable levels for a diverse group of biomarkers. However, the results obtained from the oral rinse method significantly differed from those of unstimulated and chew-stimulated saliva, due to the diluted nature of the saliva extract.

Background: Saliva has been studied as a better indicator of disorders and diseases than blood. Specifically, the salivary glucose level is considered to be an indicator of diabetes mellitus (DM). However, saliva collection methods can affect the salivary glucose level, thereby affecting the correlation between salivary glucose and blood glucose. Therefore, this study aims to identify an ideal saliva collection method and to use this method to determine the population and individual correlations between salivary glucose and blood glucose levels in DM patients and healthy controls. Finally, an analysis of the stability of the individual correlations is conducted. Methods: This study included 40 age-matched DM patients and 40 healthy controls. In the fasting state, saliva was collected using six saliva collection methods, venous blood was collected simultaneously from each study participant, and both samples were analyzed at the same time using glucose oxidase peroxidase. A total of 20 DM patients and 20 healthy controls were arbitrarily selected from the above participants for one week of daily testing. The correlations between salivary glucose and blood glucose before and after breakfast were analyzed. Finally, 10 DM patients and 10 healthy controls were arbitrarily selected for one month of daily testing to analyze the stability of individual correlations. Results: Salivary glucose levels were higher in DM patients than healthy controls for the six saliva collection methods. Compared with unstimulated saliva, stimulated saliva had decreased glucose level and increased salivary flow. In addition, unstimulated parotid salivary glucose was most correlated with blood glucose level (R2 = 0.9153), and the ROC curve area was 0.9316, which could accurately distinguish DM patients. Finally, it was found that the correlations between salivary glucose and blood glucose in different DM patients were quite different. The average correlation before breakfast was 0.83, and the average correlation after breakfast was 0.77. The coefficient of variation of the correlation coefficient before breakfast within 1 month was less than 5%. Conclusion: Unstimulated parotid salivary glucose level is the highest and is most correlated with blood glucose level, which can be accurately used to distinguish DM patients. Meanwhile, the correlation between salivary glucose and blood glucose was found to be relatively high and stable before breakfast. In general, the unstimulated parotid salivary glucose before breakfast presents an ideal saliva collecting method with which to replace blood-glucose use to detect DM, which provides a reference for the prediction of DM.

Background Although increasing attention is being paid to cortisol and the sulfated form of dehydroepiandrosterone (DHEA-S) as stress biomarkers, the feasibility of saliva collection of such biomarkers has yet to be investigated among dementia care dyads (persons with dementia [PWD] and family caregivers) living in a home setting. We explored the feasibility and acceptability of in-home saliva collection for cortisol and DHEA-S as stress biomarkers among dementia care dyads. Methods Dementia care dyads were recruited from a memory evaluation center. After pre-evaluation and education sessions, participants collected their saliva 3 times a day, 5 days a week, for 8 consecutive weeks. We calculated frequency counts and percentages to assess enrollment rate, retention rate, the completion rate of saliva collection, and valid samples of cortisol and DHEA-S. Independent samples t-tests were performed to compare mean differences in the total number of collected samples and valid samples between PWD and family caregivers at each time point of saliva collection. Results A total of 46 dyads were referred to this study; 32 dyads (69.6%) agreed to participate, and 26 started collecting saliva. Twenty-four dyads (75%) completed 8 weeks of saliva collection. There were no significant differences (p > 0.05) in the number of collected samples and valid samples between PWD and caregiver participants. Conclusion This study supports the feasibility of in-home saliva collection for stress biomarker assay and the need for further investigation into self-administered collection of stress biomarkers with a particular focus on dementia care dyads living at home.

SARS-CoV-2 outbreak led to unprecedented innovative scientific research to preclude the virus dissemination and limit its impact on life expectancy. Waiting for the collective immunity by vaccination, mass-testing, and isolation of positive cases remain essential. The development of a diagnosis method requiring a simple and non-invasive sampling with a quick and low-cost approach is on demand. We hypothesized that the combination of saliva specimens with MALDI-TOF MS profiling analyses could be the winning duo. Before characterizing MS saliva signatures associated with SARS-CoV-2 infection, optimization and standardization of sample collection, preparation and storage up to MS analyses appeared compulsory. In this view, successive experiments were performed on saliva from healthy healthcare workers. Specimen sampling with a roll cotton of Salivette® devices appeared the most appropriate collection mode. Saliva protein precipitation with organic buffers did not improved MS spectra profiles compared to a direct loading of samples mixed with acetonitrile/formic acid buffer onto MS plate. The assessment of sample storage conditions and duration revealed that saliva should be stored on ice until MS analysis, which should occur on the day of sampling. Kinetic collection of saliva highlighted reproducibility of saliva MS profiles over four successive days and also at two-week intervals. The intra-individual stability of saliva MS profiles should be a key factor in the future investigation for biomarkers associated with SARS-CoV-2 infection. However, the singularity of MS profiles between individuals will require the development of sophisticated bio-statistical analyses such as machine learning approaches. MALDI-TOF MS profiling of saliva could be a promising PCR-free tool for SARS-CoV-2 screening.

AIM This study aims to test the feasibility and effectiveness of a novel pacifier-based saliva collection method on children and infants in comparison to an oral swab-based saliva collection method. MATERIALS AND METHODS This study was performed during spring 2018 in a clinical non-sponsored setting at Queen Silvia Children's Hospital pediatric emergency ward. Saliva collection was performed by comparing oral swab (Salimetrics® SalivaBio's Children's Swab) with a pacifier-based saliva collection method (Salivac®). All participating children used both saliva collection systems. The amount of saliva collected in 2 minutes was measured. The amount of time needed for the healthcare professional was recorded. Parental preference was evaluated by a questionnaire. RESULTS No statistically significant difference was observed in collected saliva (174 µL for pacifier-based saliva collection and 158 µL for oral swab). The healthcare professional spent significantly less (p < 0.001) mean time with the pacifier-based saliva collection method than with the oral swab (31 vs 150 sec). A total of 48 out of the 52 caretakers preferred the pacifier-based saliva collection method compared to the oral swab. CONCLUSION The novel pacifier-based saliva collection method proved to be a feasible, appreciated, and effective way of collecting saliva that simplifies the saliva collection method among children and infants. CLINICAL SIGNIFICANCE The pacifier-based saliva collection method simplifies saliva testing. The closed vacutainer system minimizes the risk of saliva contamination and opens up for novel home testing strategies.

Salivary pepsin is a promising marker for the non-invasive diagnosis of laryngopharyngeal reflux (LPR). For reliable results regarding pepsin in saliva, it is critical to standardize the collection, storage, and pre-processing methods. In this study, we optimized the saliva collection protocols, including storage conditions, i.e., solution, temperature, and time, and the pre-processing filter for pepsin. Moreover, we prepared a simple immunochromatographic strip for the rapid detection of pepsin and evaluated its sensing performance. As a result, we selected a polypropylene (PP) filter as the pre-processing filter for salivary pepsin in low resource settings, such as those where point of care testing (POCT) is conducted. This filter showed a similar efficiency to the centrifuge (standard method). Finally, we detected the pepsin using gold nanoparticles conjugated with monoclonal pepsin antibody. Under optimized conditions, the lower limit of detection for pepsin test strips was determined as 0.01 μg/mL. Furthermore, we successfully detected the salivary pepsin in real saliva samples of LPR patients, which were pre-processed by the PP filter. Therefore, we expect that our saliva collection protocol and pepsin immunochromatographic strip can be utilized as useful tools for a non-invasive diagnosis/screening of LPR in POCT.

Saliva represents an ideal matrix for diagnostic biomarker development as it is readily available and requires no invasive collection procedures. However, salivary RNA is labile and rapidly degrades. Previous attempts to isolate RNA from saliva have yielded poor quality and low concentrations. Here we compare collection and processing methods and propose an approach for future studies. The effects of RNA stabilisers, storage temperatures, length of storage and fasting windows were investigated on pooled saliva samples from healthy volunteers. Isolated RNA was assessed for concentration and quality. Bacterial growth was investigated through RT-PCR using bacterial and human primers. Optimal conditions were implemented and quality controlled in a clinical setting. The addition of RNAlater increased mean RNA yield from 4912 ng/μl to 15,473 ng and RNA Integrity Number (RIN) from 4.5 to 7.0. No significant changes to RNA yield were observed for storage at room temperature beyond 1 day or at -80 °C. Bacterial growth did not occur in samples stored at ambient temperature for up to a week. There was a trend towards higher RNA concentration when saliva was collected after overnight fasting but no effect on RIN. In the clinic, RNA yields of 6307 ng and RINs of 3.9 were achieved, improving on previous reports. The method we describe here is a robust, clinically feasible saliva collection method using preservative that gives high concentrations and improved RINs compared to saliva collected without preservative.

Different collection methods may influence the ability to detect and quantify biomarker levels in saliva, particularly in the expression of DNA/RNA methylation regulators of several inflammations and tissue turnover markers. This pilot study recruited five participants and unstimulated saliva were collected by either spitting or drooling, and the relative preference for each method was evaluated using a visual analogue scale. Subsequently, total RNA, gDNA and proteins were isolated using the Trizol method. Thereafter, a systematic evaluation was carried out on the potential effects of different saliva collection methods on periodontium-associated genes, DNA/RNA epigenetic factors and periodontium-related DNA methylation levels. The quantity and quality of DNA and RNA were comparable from different collection methods. Periodontium-related genes, DNA/RNA methylation epigenetic factors and periodontium-associated DNA methylation could be detected in the saliva sample, with a similar expression for both methods. The methylation of tumour necrosis factor-alpha gene promoter from drooling method showed a significant positive correlation (TNF α, r = 0.9) with clinical parameter (bleeding on probing-BOP). In conclusion, the method of saliva collection has a minimal impact on detecting periodontium-related genetic and epigenetic regulators in saliva. The pilot data shows that TNF α methylation may be correlated with clinical parameters.

With the democratization of genetic testing, researchers, clinicians, and educators must consider the varying degree of field conditions when collecting samples for genetic analyses. For genotyping or sequencing studies, study designers have multiple options from which to choose, including cheek swabs and saliva sampling. One significant benefit of saliva collection is that it can be done remotely, in the privacy of one’s home. This same benefit adds a risk of compliance. Therefore, our goal with this study was to see if the quality and quantity of the saliva collection by a saliva DNA collection kit would be affected by not following the manufacturer’s directions, i.e., drinking or eating right before collection. We asked five participants to collect saliva samples according to the manufacturer’s guidance and also after consuming five food items or beverages. We evaluated DNA quantity and quality post-purification using spectroscopy, electrophoresis, and polymerase chain reaction genotyping. Consistent with our hypothesis, we did not see a difference in quantity or quality of the isolated DNA. From our results, we conclude that the manufacturer’s instructions serve as an ideal guideline, but the collection devices are robust enough to permit flexibility in sampling at home or in the field.

No abstract available

We aimed to investigate the impact of saliva collection and processing methods on AST, CK and LDH. Saliva was collected from 17 healthy participants by a passive drool. Each saliva sample was distributed into 3 aliquots: not treated, centrifuged, and passed through cotton. Centrifugation improved the precision of assays and produced lower values of AST and CK. The use of cotton resulted in decreased levels of LDH. This data stress the importance of the standardization of sample processing to measure enzymes in saliva.

Background There is an urgent need to expand testing for SARS-CoV-2 and other respiratory pathogens as the global community struggles to control the COVID-19 pandemic. Current diagnostic methods can be affected by supply chain bottlenecks and require the assistance of medical professionals, impeding the implementation of large-scale testing. Self-collection of saliva may solve these problems, as it can be completed without specialized training and uses generic materials. Methods We observed 30 individuals who self-collected saliva using four different collection devices and analyzed their feedback. Two of these devices, a funnel and bulb pipette, were used to evaluate at-home saliva collection by 60 individuals. SARS-CoV-2-spiked saliva samples were subjected to temperature cycles designed to simulate the conditions the samples might be exposed to during the summer and winter seasons and sensitivity of detection was evaluated. Results All devices enabled the safe, unsupervised self-collection of saliva. The quantity and quality of the samples received were acceptable for SARS-CoV-2 diagnostic testing, as determined by human RNase P detection. There was no significant difference in SARS-CoV-2 nucleocapsid gene (N1) detection between the freshly spiked samples and those incubated with the summer and winter profiles. Conclusion We demonstrate inexpensive, generic, buffer free collection devices suitable for unsupervised and home saliva self-collection.

The oral microbiome has been connected with lung health and may be of significance in the progression of SARS-CoV-2 infection. Saliva-based SARS-CoV-2 tests provide the opportunity to leverage stored samples for assessing the oral microbiome. However, these collection kits have not been tested for their accuracy in measuring the oral microbiome. Saliva is highly enriched with human DNA and reducing it prior to shotgun sequencing may increase the depth of bacterial reads. We examined both the effect of saliva collection method and sequence processing on measurement of microbiome depth and diversity by 16S rRNA gene amplicon and shotgun metagenomics. We collected 56 samples from 22 subjects. Each subject provided saliva samples with and without preservative, and a subset provided a second set of samples the following day. 16S rRNA gene (V4) sequencing was performed on all samples, and shotgun metagenomics was performed on a subset of samples collected with preservative with and without human DNA depletion before sequencing. We observed that the beta diversity distances within subjects over time was smaller than between unrelated subjects, and distances within subjects were smaller in samples collected with preservative. Samples collected with preservative had higher alpha diversity measuring both richness and evenness. Human DNA depletion before extraction and shotgun sequencing yielded higher total and relative reads mapping to bacterial sequences. We conclude that collecting saliva with preservative may provide more consistent measures of the oral microbiome and depleting human DNA increases yield of bacterial sequences.

No abstract available

This study aims to evaluate the effect of the presence of food and the material used in a panel of biomarkers in saliva of horses. For the food effect study, clean saliva was incubated with a known amount of food consisting of oats, hay or grass. Significant changes were observed when saliva was incubated with oats for total protein (P = .050) and phosphorus (P = .008), with grass for total protein (P = .037), salivary alpha-amylase (sAA, P = .018), total esterase (TEA, P = .018), butyrilcholinesterase (BChE, P = .037), adenosine deaminase (ADA, P = .037), and total bilirubin (P = .018), and with hay for sAA (P = .018), phosphorus (P = .037), γ-glutamyl transferase (gGT, P = .004), and creatine kinase (CK, P = .016). For the material-based collection study, saliva using a sponge and a cotton role at the same time were collected and compared. Lower values were obtained in clean saliva collected with cotton role compared to sponge for sAA (P = .030), TEA (P = .034), BChE (P = .003), gGT (P = .002) and cortisol (P < .001) In conclusion, the presence of food and the material used for its collection, can influence the results obtained when analytes are measured in saliva of horses.

Maintaining a salivary metabolic profile upon sample collection and preparation is determinant in metabolomics. Nuclear magnetic resonance (NMR) spectroscopy was used to identify metabolite changes during short-term storage, at room temperature (RT)/4 °C/−20 °C, and after sample preparation, at RT/4 °C (mimicking typical clinical/laboratory settings). Interestingly, significant metabolic inter-individual and inter-day variability were noted, probably determining sample stability to some extent. After collection, no changes were noted at −20 °C (at least for 4 weeks). RT storage induced decreases in methylated macromolecules (6 h); lactate (8 h); alanine (12 h); galactose, hypoxanthine, pyruvate (24 h); sarcosine, betaine, choline, N-acetyl-glycoproteins (48 h), while acetate increased (48 h). Less, but different, changes were observed at 4 °C, suggesting different oral and microbial status at different temperatures (with a possible contribution from inter-individual and inter-day variability), and identifying galactose, hypoxanthine, and possibly, choline esters, as potential general stability indicators. After preparation, addition of NaN3 did not impact significantly on saliva stabilization, neither at RT nor at 4 °C, although its absence was accompanied by slight increases in fucose (6.5 h) and proline (8 h) at RT, and in xylose (24 h) at 4 °C. The putative metabolic origins of the above variations are discussed, with basis on the salivary microbiome. In summary, after collection, saliva can be stored at RT/4 °C for up to 6 h and at −20 °C for at least 4 weeks. Upon preparation for NMR analysis, samples are highly stable at 25 °C up to 8 h and at 4 °C up to 48 h, with NaN3 addition preventing possible early changes in fucose, proline (6–8 h), and xylose (24 h) levels.

No abstract available

No abstract available

Saliva has attracted attention as a diagnostic fluid due to the association of oral microbiota with systemic diseases. However, the lack of standardised methods for saliva collection has led to the slow uptake of saliva in microbiome research. The aim of this study was to systematically evaluate the potential effects on salivary microbiome profiles using different methods of saliva collection, storage and gDNA extraction. Three types of saliva fractions were collected from healthy individuals with or without the gDNA stabilising buffer. Subsequently, three types of gDNA extraction methods were evaluated to determine the gDNA extraction efficiencies from saliva samples. The purity of total bacterial gDNA was evaluated using the ratio of human β-globin to bacterial 16S rRNA PCR while 16S rRNA gene amplicon sequencing was carried out to identify the bacterial profiles present in these samples. The quantity and quality of extracted gDNA were similar among all three gDNA extraction methods and there were no statistically significant differences in the bacterial profiles among different saliva fractions at the genus-level of taxonomic classification. In conclusion, saliva sampling, processing and gDNA preparation do not have major influence on microbiome profiles.

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

The human oral cavity harbors one of the most diverse microbial communities with different oral microenvironments allowing the colonization of unique microbial species. This study aimed to determine which of two commonly used sampling sites (dental plaque vs. oral swab) would provide a better prediction model for caries-free vs. severe early childhood caries (S-ECC) using next generation sequencing and machine learning (ML). In this cross-sectional study, a total of 80 children (40 S-ECC and 40 caries-free) < 72 months of age were recruited. Supragingival plaque and oral swab samples were used for the amplicon sequencing of the V4-16S rRNA and ITS1 rRNA genes. The results showed significant differences in alpha and beta diversity between dental plaque and oral swab bacterial and fungal microbiomes. Differential abundance analyses showed that, among others, the cariogenic species Streptococcus mutans was enriched in the dental plaque, compared to oral swabs, of children with S-ECC. The fungal species Candida dubliniensis and C. tropicalis were more abundant in the oral swab samples of children with S-ECC compared to caries-free controls. They were also among the top 20 most important features for the classification of S-ECC vs. caries-free in oral swabs and for the classification of dental plaque vs. oral swab in the S-ECC group. ML approaches revealed the possibility of classifying samples according to both caries status and sampling sites. The tested site of sample collection did not change the predictability of the disease. However, the species considered to be important for the classification of disease in each sampling site were slightly different. Being able to determine the origin of the samples could be very useful during the design of oral microbiome studies. This study provides important insights into the differences between the dental plaque and oral swab bacteriome and mycobiome of children with S-ECC and those caries-free.

No abstract available

No abstract available

No abstract available

No abstract available

No abstract available

Periodontal disease is one of the most commonly diagnosed oral diseases in dogs and can result from undisturbed dental plaque. Dental prophylaxis is a routinely practiced veterinary procedure, but its effects on both the plaque and oral microbiota is not fully understood. The objectives of this study were to evaluate the impact of dental prophylaxis on the composition of the supragingival plaque and composite oral microbiota in clinically healthy dogs and to determine if composite sampling could be used in lieu of sampling the plaque microbiota directly. Thirty dogs received a dental prophylaxis. Supragingival plaque and composite oral samples were collected just prior to, and one week after dental prophylaxis. A subsample of 10 dogs was followed, and additional samples were collected two and five weeks post-prophylaxis. The V4 region of the 16S rRNA gene was used for Illumina MiSeq next-generation sequencing. Results demonstrate that decreases in Treponema as well as increases in Moraxella and Neisseria distinguished the plaque pre- and one week post-prophylaxis timepoints (all P<0.05). Within the oral microbiota, the initially dominant Psychrobacter (20% relative abundance) disappeared one week later (P<0.0001), and Pseudomonas became the dominant taxon one week after treatment (80% relative abundance, P<0.0001). A rapid transition back towards the pre-dental prophylaxis microbiota by five weeks post-treatment was seen for both niches, suggesting the canine oral microbiota is resilient. Direct comparison of the two environments yielded striking differences, with complete separation of groups. Firmicutes (40%) and Spirochaetes (22%) predominated in the plaque while Proteobacteria (58%) was predominant in the oral microbiota. Greater richness was also seen in the plaque microbiota. This study reveals that prophylaxis had a profound impact on both the plaque and oral microbiota, and the longitudinal results help elucidate the pathophysiology of periodontal disease. The results suggest that oral swabs are a poor proxy for plaque samples and highlight the need to study specific oral niches.

No abstract available

The oral cavity is the portal of entry for many microorganisms that affect swine, and the swine oral fluid has been used as a specimen for the diagnosis of several infectious diseases. The oral microbiota has been shown to play important roles in humans, such as protection against non-indigenous bacteria. In swine, studies that have investigated the microbial composition of the oral cavity of pigs are scarce. This study aimed to characterize the oral fluid microbiota of weaned pigs from five commercial farms in Brazil and compare it to their respective fecal and environmental microbiotas. Bacterial compositions were determined by 16S rRNA gene sequencing and analyzed in R Studio. Oral fluid samples were significantly less diverse (alpha diversity) than pen floor and fecal samples (P < 0.01). Alpha diversity changed among farms in oral fluid and pen floor samples, but no differences were observed in fecal samples. Permutational ANOVA revealed that beta diversity was significantly different among sample types (P = 0.001) and farms (P = 0.001), with separation of sample types (feces, pen floor, and oral fluid) on the principal coordinates analysis. Most counts obtained from oral fluid samples were classified as Firmicutes (80.4%) and Proteobacteria (7.7%). The genera Streptococcus, members of the Pasteurellaceae family, and Veillonella were differentially abundant in oral fluid samples when compared to fecal samples, in which Streptococcus was identified as a core genus that was strongly correlated (SparCC) with other taxa. Firmicutes and Bacteroidota were the most relatively abundant phyla identified in fecal and pen floor samples, and Prevotella_9 was the most classified genus. No differentially abundant taxa were identified when comparing fecal samples and pen floor samples. We concluded that under the conditions of our study, the oral fluid microbiota of weaned piglets is different (beta diversity) and less diverse (alpha diversity) than the fecal and environmental microbiotas. Several differentially abundant taxa were identified in the oral fluid samples, and some have been described as important colonizers of the oral cavity in human microbiome studies. Further understanding of the relationship between the oral fluid microbiota and swine is necessary and would create opportunities for the development of innovative solutions that target the microbiota to improve swine health and production.

Objective Tube feeders are prone to membranous substance formation on the palate, and those with membranous substances have a risk of fever, with the probable involvement of their oral bacteria. However, the palatal microbiota of those with membranous substances has not been elucidated. Therefore, we evaluated the differences in palatal microbiota between tube-fed individuals with and without membranous substances to clarify the microbiota. Materials and methods This study included 19 participants aged 65 years who required tube feeding. The participants’ characteristics were collected from nursing records and oral examinations. If membranous materials were found on the palate, a specimen was collected. Membranous substances were defined as keratotic degeneration observed under a microscope. Additionally, we performed a comprehensive microbiome analysis by extracting DNA from the samples and performing 16 S rRNA gene sequencing. Finally, we compared the participant demographics and oral microbiota between patients with and without membranous substances. Results A total of 11 participants had membranous substances associated with “mouth dryness” (p < 0.001) and “constant mouth opening” (p = 0.020). Palatal microbiota differed between those with and without membranous substances. Among the bacteria with a relative abundance greater than 1.0%, the abundance of Streptococcus (p = 0.007), Fusobacterium (p = 0.041), Streptococcus agalactiae (p = 0.009), and Fusobacterium nucleatum subsp. vincentii (p = 0.026) was significantly higher in the membranous substance group than in the non-membranous substance group. Conclusions The palatal microbiota of individuals undergoing tube feeding differed depending on the presence or absence of membranous substances. Membrane substance formation associated with dry mouth purportedly alters the palatal microbiota. Streptococcus, Fusobacterium, S. agalactiae, and F. nucleatum subsp. vincentii were more abundant in the oral microbiota of patients with membranous substances. Thus, preventing this formation may help in controlling the growth of these microbes.

OBJECTIVE This retrospective surveillance study aimed to follow periodontitis-associated bacterial profiles and to identify time-dependent changes in antibiotic susceptibility patterns. MATERIALS AND METHODS From 2008 to 2015 bacterial specimen from deep periodontal pockets were collected from a total of 7804 German adults diagnosed with periodontitis. Presence of selected bacteria was confirmed by anaerobic culture and nucleic acid amplification. Antimicrobial susceptibility of clinical isolates was tested by disk diffusion with antibiotics used for treatment of periodontitis and oral infections. Prevalences of periodontal pathogens were calculated and temporal evolution of antimicrobial susceptibility towards amoxicillin, amoxicillin/clavulanic acid, metronidazole, doxycycline, clindamycin, azithromycin, ciprofloxacin, and ampicillin was analyzed with logistic regression. RESULTS The prevalence of patients harboring bacteria was 95.9% Fusobacterium nucleatum, 88.0% Tannerella forsythia, 76.5% Treponema denticola, 76.4%, Campylobacter rectus, 76.0% Eikenella corrodens, 75.0% Capnocytophaga spp., 68.2% Porphyromonas gingivalis, 57.7% Peptostreptococcus micros, 43.1% Prevotella intermedia, 30.4% Eubacterium nodatum and 21.5% Aggregatibacter actinomycetemcomitans. In 63.5 % of patients one or more isolates were not susceptible to at least one of the antibiotics tested. The data further revealed a trend towards decreasing susceptibility profiles (p < 0.05) with antibiotic non-susceptibilities in 37% of patients in 2008 and in 70% in 2015. CONCLUSIONS The present study confirmed a high prevalence of periodontal pathogens in the subgingival microbiota of German periodontitis patients. The data revealed an incremental increase in isolates displaying resistance to some antibiotics but no relevant change in susceptibility to amoxicillin and metronidazole.

Oral taxa are often found in the chronic obstructive pulmonary disease (COPD) lung microbiota, but it is not clear if this is due to a physiologic process such as aspiration or experimental contamination at the time of specimen collection. Microbiota samples were obtained from nine subjects with mild or moderate COPD by swabbing lung tissue and upper airway sites during lung lobectomy. Lung specimens were not contaminated with upper airway taxa since they were obtained surgically. The microbiota were analyzed with 16S rRNA gene qPCR and 16S rRNA gene hypervariable region 3 (V3) sequencing. Data analyses were performed using QIIME, SourceTracker, and R. Streptococcus was the most common genus in the oral, bronchial, and lung tissue samples, and multiple other taxa were present in both the upper and lower airways. Each subject’s own bronchial and lung tissue microbiota were more similar to each other than were the bronchial and lung tissue microbiota of two different subjects (permutation test, p = 0.0139), indicating more within-subject similarity than between-subject similarity at these two lung sites. Principal coordinate analysis of all subject samples revealed clustering by anatomic sampling site (PERMANOVA, p = 0.001), but not by subject. SourceTracker analysis found that the sources of the lung tissue microbiota were 21.1% (mean) oral microbiota, 8.7% nasal microbiota, and 70.1% unknown. An analysis using the neutral theory of community ecology revealed that the lung tissue microbiota closely reflects the bronchial, oral, and nasal microbiota (immigration parameter estimates 0.69, 0.62, and 0.74, respectively), with some evidence of ecologic drift occurring in the lung tissue. This is the first study to evaluate the mild-moderate COPD lung tissue microbiota without potential for upper airway contamination of the lung samples. In our small study of subjects with COPD, we found oral and nasal bacteria in the lung tissue microbiota, confirming that aspiration is a source of the COPD lung microbiota.

Background People with COPD have been reported to bear a distinct airway microbiota from healthy individuals based on bronchoalveolar lavage (BAL) and sputum samples. Unfortunately, the collection of these samples involves relatively invasive procedures and is resource-demanding, limiting its regular use. Non-invasive samples from the upper airways could constitute an interesting alternative, but its relationship with COPD is still underexplored. We examined the merits of saliva to identify the typical profile of COPD oral bacteria and test its association with the disease. Methods Outpatients with COPD and age-sex matched healthy controls were recruited and characterised based on clinical parameters and 16S rRNA profiling of oral bacteria. A clustering analysis based on patients’ oral bacteria beta-diversity and logistic regressions were performed to evaluate the association between oral bacteria composition and COPD. Results 128 individuals participated (70 patients and 58 controls). Differential abundance analyses showed differences in patients comparable to the ones previously observed in samples from the lower respiratory tract, i.e ., an increase in Proteobacteria (particularly Haemophilus ) and loss of microbiota diversity. An unsupervised clustering analysis separated patients in two groups based on microbiota composition differing significantly in the frequency of patients hospitalized due to severe acute exacerbation of COPD (AECOPD) and in the frequency of GOLD D patients. Furthermore, a low frequency of Prevotella was associated with a significantly higher risk of recent severe AECOPD and of being GOLD D. Conclusion Salivary bacteria showed an association with COPD, particularly with severe exacerbations, supporting the use of this non-invasive specimen for future studies of heterogeneous respiratory diseases like COPD.

Aim The aim of this study was to investigate whether the compositionality of the lower airway microbiota predicts later exacerbation risk in persons with COPD in a cohort study. Materials and methods We collected lower airways microbiota samples by bronchoalveolar lavage and protected specimen brushes, and oral wash samples from 122 participants with COPD. Bacterial DNA was extracted from all samples, before we sequenced the V3-V4 region of the 16S RNA gene. The frequency of moderate and severe COPD exacerbations was surveyed in telephone interviews and in a follow-up visit. Compositional taxonomy and α and β diversity were compared between participants with and without later exacerbations. Results The four most abundant phyla were Firmicutes, Bacteroidetes, Proteobacteria and Fusobacteria in both groups, and the four most abundant genera were Streptococcus, Veillonella, Prevotella and Gemella. The relative abundances of different taxa showed a large variation between samples and individuals, and no statistically significant difference of either compositional taxonomy, or α or β diversity could be found between participants with and without COPD exacerbations within follow-up. Conclusion The findings from the current study indicate that individual differences in the lower airway microbiota in persons with COPD far outweigh group differences between frequent and nonfrequent COPD exacerbators, and that the compositionality of the microbiota is so complex as to present large challenges for use as a biomarker of later exacerbations. Contrary to previous reports, in this study there were no significant associations between the lung microbiota in stable COPD and COPD exacerbation frequency https://bit.ly/2ZVcNdG

BackgroundThe emergence of multi-drug resistant pathogens is an urgent health-related problem, and the appropriate use of antibiotics is imperative. It is often difficult to identify the causative bacteria in patients with aspiration pneumonia because tracheal aspirate contains contaminants of oral bacteria. We investigated the dynamics of microbiota in mechanically ventilated patients with aspiration pneumonia to develop a treatment strategy.MethodsTwenty-two intubated patients with aspiration pneumonia were recruited. Saliva and tracheal aspirate of the subjects were collected at three time points: (A) within 2 h after intubation, (B) just before administration of antibiotics, and (C) 48-72 h after administration of antibiotics. The microbiota in each specimen was analyzed by using the 16S rRNA gene clone library sequencing method. Bacterial floras of the samples were analyzed by principal component analysis.ResultsPrincipal component analysis based on the composition of genus revealed that although the changes of microbiota in the saliva from (A) to (B) were not clear, the composition of anaerobes in the tracheal aspirate (B) was lower than (A). In fact, the reduction of anaerobes, not in the saliva but in the tracheal aspirate from (A) to (B), was confirmed by incident rate ratios estimated by a multilevel Poisson regression model (p < 0.001). The extent of decrease in anaerobes was fully dependent on the time difference between the sampling of tracheal aspirate (A) and (B)—in particular, over 3 h of mechanical ventilation. This indicates that the alterations of microbiota (involving the reduction of anaerobes in the lower respiratory tract) occurred during mechanical ventilation prior to the administration of antibiotics. After the administration of antibiotics, Enterobacter spp., Corynebacterium spp., Pseudomonas aeruginosa, Klebsiella pneumoniae, Staphylococcus aureus, and Granulicatera adiacens were predominantly detected in the tracheal aspirate (C).ConclusionThe microbiota of the lower respiratory tract changes dynamically during mechanical ventilation and during the administration of antibiotics in intubated patients with aspiration pneumonia. Antibiotics should be selected on the premise that dynamic changes in microbiota (involved in the reduction of anaerobes) may occur during the mechanical ventilation in these patients.

Abstract Background The lower respiratory tract microbiota of the horse is different in states of health and disease, but the bacterial and fungal composition of the healthy respiratory tract of the horse has not been studied in detail. Hypothesis The respiratory tract environment contains distinct niche microbiotas, which decrease in species richness at more distal sampling locations. Objective Characterize the bacterial and fungal microbiotas along the upper and lower respiratory tract of the horse. Animals Healthy Argentinian Thoroughbred horses (n = 11) from the same client‐owned herd. Methods Prospective cross‐sectional study. Eleven upper and lower respiratory tract anatomical locations (bilateral nasal, bilateral deep nasal, nasopharynx, floor of mouth, oropharynx, arytenoids, proximal and distal trachea, guttural pouch) were sampled using a combination of swabs, protected specimen brushes, and saline washes. Total DNA was extracted from each sample and negative control, and the 16S rRNA gene (V4) and ITS2 region were sequenced. Community composition, alpha‐diversity, and beta‐diversity were compared among sampling locations. Results Fungal species richness and diversity were highest in the nostrils. More spatial heterogeneity was found in bacterial composition than in fungal communities. The pharyngeal microbiota was most similar to the distal tracheal bacterial and fungal microbiota in healthy horses and therefore may serve as the primary source of bacteria and fungi to the lower respiratory tract. Conclusions and Clinical Importance The pharynx is an important location that should be targeted in respiratory microbiota research in horses. Future studies that investigate whether biomarkers of respiratory disease can be reliably detected in nasopharyngeal swab samples are warranted.

The quali-quantitative characterization of the oral microbiota is crucial for an exhaustive knowledge of the oral ecology and the modifications of the microbial composition that occur during periodontal pathologies. In this study, we designed and validated a new phylogenetic DNA-microarray (OralArray) to quickly and reliably characterize the most representative bacterial groups that colonize the oral cavity. The OralArray is based on the Ligation Detection Reaction technology associated to Universal Arrays (LDR-UA), and includes 22 probe sets targeted to bacteria belonging to the phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Spirochaete. The tool is characterized by high specificity, sensitivity and reproducibility. The OralArray was successfully tested and validated on different oral samples (saliva, lingual plaque, supragingival plaque, and healing cap) collected from 10 healthy subjects. For each specimen, a microbial signature was obtained, and our results established the presence of an oral microbial profile specific for each subject. Moreover, the tool was applied to evaluate the efficacy of a disinfectant treatment on the healing caps before their usage. The OralArray is, thus, suitable to study the microbiota associated with various oral sites and to monitor changes arising from therapeutic treatments.

Saliva is a promising specimen for the detection of viruses that cause upper respiratory infections including severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) due to its cost‐effectiveness and noninvasive collection. However, together with intrinsic enzymes and oral microbiota, children's unique dietary habits may introduce substances that interfere with diagnostic testing. To determine whether children's dietary choices impact SARS‐CoV‐2 molecular detection in saliva, we performed a diagnostic study that simulates testing of real‐life specimens provided from healthy children (n = 5) who self‐collected saliva at home before and at 0, 20, and 60 min after eating 20 foods they selected. Each of 72 specimens was split into two volumes and spiked with SARS‐CoV‐2‐negative or SARS‐CoV‐2‐positive clinical standards before side‐by‐side testing by reverse‐transcription polymerase chain reaction matrix‐assisted laser desorption ionization time‐of‐flight (RT‐PCR/MALDI‐TOF) assay. Detection of internal extraction control and SARS‐CoV‐2 nucleic acids was reduced in replicates of saliva collected at 0 min after eating 11 of 20 foods. Interference resolved at 20 and 60 min after eating all foods except hot dogs in one participant. This represented a significant improvement in the detection of nucleic acids compared to saliva collected at 0 min after eating (p = 0.0005). We demonstrate successful detection of viral nucleic acids in saliva self‐collected by children before and after eating a variety of foods. Fasting is not required before saliva collection for SARS‐CoV‐2 testing by RT‐PCR/MALDI‐TOF, but waiting for 20 min after eating is sufficient for accurate testing. These findings should be considered for SARS‐CoV‐2 testing and broader viral diagnostics in saliva specimens.

Dental caries and periodontal diseases are associated with a shift from symbiotic microbiota to dysbiosis. The aim of our study was to develop a rapid, sensitive, and economical method for the identification and quantification of selected cariogenic and periodontal oral bacteria. Original protocols were designed for three real-time multiplex PCR assays to detect and quantify the ratio of 10 bacterial species associated with dental caries (“cariogenic” complex) or periodontal diseases (red complex, orange complex, and Aggregatibacter actinomycetemcomitans). A total number of 60 samples from 30 children aged 2–6 years with severe early childhood caries and gingivitis were tested. In multiplex assays, the quantification of total bacterial (TB) content for cariogenic bacteria and red complex to eliminate differences in quantities caused by specimen collection was included. The mean counts for the TB load and that of ten evaluated specimens corresponded to previously published results. We found a significant difference between the microbial compositions obtained from the area of control and the affected teeth (p < 0.05). Based on this comprehensive microbiological examination, the risk of dental caries or periodontal inflammation may be determined. The test could also be used as a tool for behavioral intervention and thus prevention of the above-mentioned diseases.

Objective Little is known concerning the stability of the lower airway microbiome. We have compared the microbiota identified by repeated bronchoscopy in healthy subjects and patients with ostructive lung diseaseases (OLD). Methods 21 healthy controls and 41 patients with OLD completed two bronchoscopies. In addition to negative controls (NCS) and oral wash (OW) samples, we gathered protected bronchoalveolar lavage in two fractions (PBAL1 and PBAL2) and protected specimen brushes (PSB). After DNA extraction, we amplified the V3V4 region of the 16S rRNA gene, and performed paired-end sequencing (Illumina MiSeq). Initial bioinformatic processing was carried out in the QIIME-2 pipeline, identifying amplicon sequence variants (ASVs) with the DADA2 algorithm. Potentially contaminating ASVs were identified and removed using the decontam package in R and the sequenced NCS. Results A final table of 551 ASVs consisted of 19 × 10 6 sequences. Alpha diversity was lower in the second exam for OW samples, and borderline lower for PBAL1, with larger differences in subjects not having received intercurrent antibiotics. Permutational tests of beta diversity indicated that within-individual changes were significantly lower than between-individual changes. A non-parametric trend test showed that differences in composition between the two exams (beta diversity) were largest in the PSBs, and that these differences followed a pattern of PSB > PBAL2 > PBAL1 > OW. Time between procedures was not associated with increased diversity. Conclusion The airways microbiota varied between examinations. However, there is compositional microbiota stability within a person, beyond that of chance, supporting the notion of a transient airways microbiota with a possibly more stable individual core microbiome.

Background This study aimed to characterize the bacterial microbiota in the oral cavity (OC), throat, trachea, and distal alveoli of patients with primary malignant tracheal tumors (PMTT), including squamous cell carcinoma (SCC) and salivary gland carcinoma patients (SGC), for comparison with a matched non-malignant tracheal tumor (NMTT) group. Methods Patients with pathological diagnosis of PMTT and NMTT were included in this study. Saliva, throat swab (TS), trachea protected specimen brush (PSB), and bronchoalveolar lavage fluid (BALF) samples were collected for 16S rRNA gene sequencing. The composition, diversity, and distribution of the microbiota were compared among biogeographic sampling sites and patient groups. The relationship between the genera-level taxon abundance and tracheal tumor types was also investigated to screen for candidate biomarkers. Findings The most represented phyla in the four sites were Bacteroidetes, Firmicutes, Proteobacteria, and Fusobacteria. In SCC patients, the relative abundance of Bacteroidetes and Firmicutes gradually decreased with increasing depth into the respiratory tract, while the relative abundance of Proteobacteria gradually increased. Bacterial communities at the four biogeographic sites formed two distinct clusters, with OC and TS samples comprising one cluster and PSB and BALF samples comprising the other group. Principal coordinate analysis showed that trachea microbiota in SCC patients were distinct from that of SGC or NMTT patients. In the trachea, AUCs generated by Prevotella and Alloprevotella showed that the abundance of these genera could distinguish SCC patients from both NMTT and SGC patients. Interpretation The structure of respiratory tract microbiota in PMTT patients is related to tumor type. Certain bacteria could potentially serve as markers of SCC, although verification with large-sample studies is necessary.

Diabetes with its highly prevalence has become a major contributor to the burden of health care costs worldwide. Recent unequivocal evidence has revealed a bidirectional link between oral health and diabetes. In this study, the effects of the Oral Health Promotion Program (OHPP) on oral hygiene, oral health-related quality of life and glycated haemoglobin (HbA1c) levels in diabetic elderly were examined. Moreover, microbial changes in the saliva microbiota community were also emphatically investigated. A quasi-experiment was conducted in regionally representative communities to assess oral health and oral microbiota of the elderly diabetic participants. The participants in the intervention group (n = 26) received OHPP including three phases of cognition, intensification and consolidation during the program, when those in the control group (n = 26) received routine oral care. Clinical parameters were recorded at two different time points as before the study (T0), and 3 months after intervention onset (T1). Oral health was measured via the oral health impact profile (OHIP-14) questionnaire, dental plaque index, HbA1c and mastery of oral health knowledge, and sequencing of the 16S rRNA gene from saliva samples was used to analyze the oral microbiota. The average age of the final sample was 71.77 years (SD = 6.06), 53.8% (28/52) of whom were male. A reduction in the plaque index and improvements in oral health-related quality of life and mastery of oral health knowledge were observed in the intervention group. Meanwhile, the α-diversity of the microbiota increased in both groups, but more significant in the intervention group. PCoA analyses showed significant differences in microbial community structure in both groups, and LEfSe analyses revealed a decrease of g_Streptococcus and g_Rothia after the implementation of OHPP and a decrease of g_Streptococcusa, g_Porphyromonas, g_Gemella after the routine oral care. There was no statistically significant difference in the HbA1c level between two groups. OHPP superiorly contributes to the improvement of oral health and oral microbiota in elderly diabetic patients. The overarching goal is to introduce attention to the importance of good oral health as a crucial point in preventing and managing diabetes mellitus and thereby make it a meaningful contribution to public health and geriatric care. This study was retrospectively registered in Chinese Clinical Trial on October 9, 2022 (ID ChiCTR2200064453).

A total of 5 small Indian mongoose ( Herpestes auropunctatus (Hodgson, 1836)) specimens were captured to obtain oral swabs with all specimens being released after sampling. DNA extraction from oral swabs was done using the QIAamp DNA Microbiome and the 16S rRNA gene was amplified targeting variable region V1 to V8 (1350 bp). Next-generation sequen c ing (NGS) of PCR products was performed from Macrogen, Korea. A KORONA plot was constructed to visualize relative abundance of the top 10 bacterial taxa. The following bacterial phyla were identified; Proteobacteria (58.0%), Bacteroidetes (20.0%), Firmicutes (12.0%), Fusobacteria (7.0%), and Patescibacteria (2.0%). The dominant bacterial classes included Gammaproteobacteria (57.0%), Bacteroidia (20.0%), Bacilli (4.0%), and Alphaproteobacteria (0.8%). The prevalent bacter i al orders were Pseudomonadales (19.0%), Bacteroidales (10.0%), Flavobacteriales (9.0%), and Clostridiales (7.0%), with Fusobacteriales and Betaproteobacteriales each at 5.0%, and Lactobacillales, Absconditabacteriales, and Saccharimonadales at 4.0%, 1.0%, and 0.1%, respectively. The identified families and their relative abundances were Pasteurellaceae (29.0%), Weeksellaceae (5.0%), Neisseriaceae (4.0%), Peptostreptococcaceae (3.0%), with Erysipelotrichaceae, Leptotrichiaceae, and Enterobacteriaceae each at 2.0%, and Cardiobacteriaceae and Burkholderiaceae at 1.0% each. Other families included Xa n thomonadaceae (0.8%), Carnobacteriaceae (0.5%), and Streptococcaceae (0.2%). The genera identify ed were Pasteurella , Paracoccus , Escherichia , Shigella , Moraxella , Stenotrophomonas , Neisseria , Conchiformibius , Bergeyella , Capnocytoph a ga , Fusobacterium , Oceanivirga , Streptococcus , Bacillus , and Defluviitaleaceae. The identification of genera such as Pa s teurella , Neisseria , Eschrichia and Shigella warrants further investigation into their potential role as reservoirs of zoonotic pathogens especially given the mongoose's invasive nature, close contact with human and animal populations.

OBJECTIVE Aim: To study the susceptibility of isolates obtained from the oral cavities of individuals with inflammatory periodontal diseases and maxillofacial pathology to bacteriophages. PATIENTS AND METHODS Materials and Methods: Biological specimens were obtained from the Dental Medical Center and University Clinic of O.O. Bogomolets National Medical University and the National Specialized Children's Hospital OKHMATDYT. Biomaterial was collected from the wound surface using a sterile FLmedical transport system (Italy). Clinical isolates used in the studies included Escherichia coli, Klebsiella spp., Pseudomonas spp., and Staphylococcus aureus. We assessed the susceptibility of microorganisms to bacteriophages by administering 0.01 ml of bacteriophage culture to a bacterial culture. A suspension (inoculum) was prepared from a 24-hour culture of microorganisms in sterile saline and then Mueller Hinton agar was inoculated with it. The results were recorded 24 hours post-incubation in a thermostat at 37°C. The study used bacteriophages from the bacterial test cultures Klebsiella pneumoniae DSM30104, Staphylococcus aureus DSM 799, Escherichia coli DSM 1103, and Pseudomonas aeruginosa DSM 50071, provided by NeoProBioCare Ukraine Ltd. RESULTS Results: The susceptibility rates of isolates to phages were 40% for Klebsiella spp, 73.3% for S. aureus, 50.0% for E. coli, and 20.0% for Pseudomonas spp. Prior research confirms the effectiveness of bacteriophages in oral diseases. This method may be beneficial in controlling opportunistic microorganisms and maintaining the oral microbiota balance. CONCLUSION Conclusions: The application of bacteriophages for inflammatory oral diseases appears promising and warrants further research. Clinical trials and additional scientific investigations are necessary to confirm its safety and effectiveness.

Medication-related osteonecrosis of the jaw (MRONJ) can cause significant pain and loss of aesthetics and function if not treated properly. However, diagnosis still relies on detailed intraoral examinations and imaging. Prognosis varies even among patients with similar stages or conditions of MRONJ, emphasizing the need for a deeper understanding of its complex mechanisms. Thus, this study aimed to identify the oral microbiota of patients with MRONJ. This single-center prospective cohort study included patients with confirmed MRONJ who visited the Department of Oral and Maxillofacial Surgery at Yonsei University Dental Hospital between 2021 and 2022. Oral swab samples were collected from the affected and unaffected sides of each patient. The composition and enumeration of the microbial communities were analyzed, and the diversity was compared to verify ecological changes in the groups using a next-generation sequencing-based 16S metagenomic analysis. A statistical analysis was performed using Wilcoxon signed-rank test with SPSS version 22, and values of P less than 0.05 were considered statistically significant. The final study sample included 12 patients. The mean age was 82.67 ± 5.73 (range, 72–90) years. Changes in microbial composition were observed at different taxonomic levels (phylum, genus, and species). The identified microorganisms were commonly associated with periodontitis, gingival disease, and endodontic infection, suggesting a multifactorial etiology of MRONJ. Although this study is based on a small number of cases, it shows that MRONJ is not caused by a specific microorganism but can rather be caused by a variety of factors. By addressing these findings in large-scale studies, the significance of oral microbiome in pathogenesis can be further elucidated and can facilitate the development of effective therapeutic interventions for patients with MRONJ.

Elevated stress negatively impacts health, increasing the risk of cardiovascular diseases, weak immunity, anxiety, and cognitive decline. Current lab-based methods lack real-time stress measurement, while saliva diagnostics offers a convenient and non-invasive alternative. This work proposes repurposing dental floss as a thread-analytical saliva diagnostic device. This method uses flossing to collect and transport saliva to a flexible electrochemical sensor via capillary microfluidics, where cortisol, a stress biomarker, is measured. By integrating an electropolymerized molecularly imprinted polymer specific to cortisol (cort-eMIP) on a porous-laser-engraved-graphene (PLEG) working electrode, the saliva-floss platform shows a detection range of 0.10-10000 pg mL-1 (R2 = 0.9916) with a detection limit of 0.023 pg mL-1 for cortisol (in buffer medium). The saliva-sensing dental floss provides results within 5 minutes. The thread-based microfluidic design minimizes interference and ensures consistent repeatability when testing artificial and actual human saliva samples, yielding 98.64 to 102.4 percent recoveries with a relative standard deviation of 5.01%, demonstrating high accuracy and precision. Validated using human saliva samples in a stress study, it showed a high correlation (r= 0.9910) with conventional ELISA assays. Combined with a wireless readout, this saliva floss offers a convenient way to monitor daily stress levels and can be extended to detect other critical salivary biomarkers.

In diagnostic testing, establishing an indeterminate class is an effective way to identify samples that cannot be accurately classified. However, such approaches also make testing less efficient and must be balanced against overall assay performance. We address this problem by reformulating data classification in terms of a constrained optimization problem that (i) minimizes the probability of labeling samples as indeterminate while (ii) ensuring that the remaining ones are classified with an average target accuracy X. We show that the solution to this problem is expressed in terms of a bathtub principle that holds out those samples with the lowest local accuracy up to an X-dependent threshold. To illustrate the usefulness of this analysis, we apply it to a multiplex, saliva-based SARS-CoV-2 antibody assay and demonstrate up to a 30 % reduction in the number of indeterminate samples relative to more traditional approaches.

Two species with similar resource requirements respond in a characteristic way to variations in their habitat -- their abundances rise and fall in concert. We use this idea to learn how bacterial populations in the microbiota respond to habitat conditions that vary from person-to-person across the human population. Our mathematical framework shows that habitat fluctuations are sufficient for explaining intra-bodysite correlations in relative species abundances from the Human Microbiome Project. We explicitly show that the relative abundances of phylogenetically related species are positively correlated and can be predicted from taxonomic relationships. We identify a small set of functional pathways related to metabolism and maintenance of the cell wall that form the basis of a common resource sharing niche space of the human microbiota.

The oral microbiome likely plays key roles in human health. Yet, population-representative characterizations are lacking. To characterize the composition, diversity, and correlates of the oral microbiome in US adults. This cross-sectional study analyzed data from the population-representative National Health and Nutrition Examination Survey (NHANES) from 2009 to 2012. Microbiome data were made publicly available in 2024. NHANES participants were aged 18 to 69 years and provided oral rinse samples in 1 of 2 consecutive NHANES cycles (2009-2010 and 2011-2012). Demographic, socioeconomic, behavioral, anthropometric, metabolic, and clinical characteristics. Oral microbiome measures, characterized through 16S ribosomal RNA gene sequencing, included α diversity (observed amplicon sequence variants [ASVs], Faith phylogenetic diversity, Shannon-Weiner Index, and Simpson Index); β diversity (unweighted UniFrac, weighted UniFrac, and Bray-Curtis dissimilarity); and prevalence and relative abundance at phylum level through genus level. Analyses accounted for the NHANES complex sample design. This study included 8237 US adults aged 18 to 69 years, representing 202 314 000 individuals (102 813 000 men [50.8%]; mean [SD] age, 42.3 [14.4] years; 9.3% self-reported as Mexican American, 12.1% as non-Hispanic Black, 64.7% as non-Hispanic White, 5.9% as other Hispanic, and 8.1% as other non-Hispanic individuals). The oral microbiome encompassed 37 bacterial phyla, 99 classes, 212 orders, 446 families, and 1219 genera. Five phyla (Firmicutes, Actinobacteria, Bacteroidetes, Proteobacteria, and Fusobacteria) and 6 genera (Veillonella, Streptococcus, Prevotella 7, Rothia, Actinomyces, and Gemella) were present in nearly all US adults (weighted prevalence, >99%). These genera were the most abundant, accounting for 65.7% of total abundance. Observed ASVs showed a quadratic pattern with age (peak at 30 years), were similar by sex, significantly lower among non-Hispanic White individuals, and increased with greater body mass index (BMI), alcohol use, and periodontal disease severity. All covariates together accounted for a modest proportion of oral microbiome variability as measured by β diversity: R2 = 8.7% (95% CI, 8.4%-9.1%) for unweighted UniFrac, R2 = 7.2% (95% CI, 6.6%-7.7%) for weighted UniFrac, and R2 = 6.3% (95% CI, 3.1%-6.7%) for Bray-Curtis matrices. By contrast, relative abundance of a few genera explained a high percentage of variability in β diversity for weighted UniFrac: Aggregatibacter (R2 = 22.4%; 95% CI, 22.1%-22.8%), Lactococcus (R2 = 21.6%; 95% CI, 20.9%-22.3%), and Haemophilus (R2 = 18.4%; 95% CI, 18.1%-18.8%). Prevalence and relative abundance of numerous genera were associated with age, race and ethnicity, smoking, BMI categories, alcohol use, and periodontal disease severity. This cross-sectional study of the oral microbiome in US adults showed that a few genera were universally present and a different set of genera explained a high percentage of oral microbiome diversity across the population. This comprehensive characterization provides a contemporary reference standard for future studies.

The purpose of this scoping review was to examine the oral microbiome composition in preterm infants, sampling and collection methods, as well as exposures associated with oral microbiome composition and health implications. We conducted a scoping review of the literature using the Arskey and O'Malley framework. We identified a total of 13 articles which met our inclusion criteria and purpose of this scoping review. Articles included in this review compared the oral microbiome in preterm infants to term infants, examined alterations to the oral microbiome over time, compared the oral microbiome to different body site microbiomes, and explored associations with clinically relevant covariates and outcomes. Exposures associated with the diversity and composition of the oral microbiome in preterm infants included delivery mode, oral feeding, oropharyngeal care, skin-to-skin care, and antibiotics. Day of life and birth weight were also associated with oral microbiome composition. The oral microbiome may be associated with the composition of the tracheal and gut microbiomes, likely due to their proximity. Alpha and beta diversity findings varied across studies as well as the relative abundance of taxa. This is likely due to the different sampling techniques and timing of collection, as well as the wide range of infant clinical characteristics. Multiple factors may influence the composition of the oral microbiome in preterm infants. However, given the heterogeneity of sampling techniques and results within this review, the evidence is not conclusive on the development as well as short- and long-term implications of the oral microbiome in preterm infants and needs to be explored in future research studies. KEY POINTS: · Day of life is a critical factor in oral microbiome development in preterm infants.. · The oral microbiome may be associated with tracheal and gut microbiome colonization.. · Future research should examine sampling methodology for examining the oral microbiome.. · Future research should explore associations with the oral microbiome and adverse health outcomes..

Cancer therapy-induced oral mucositis is a frequent major oncological problem, secondary to cytotoxicity of chemo-radiation treatment. Oral mucositis commonly occurs 7-10 days after initiation of therapy; it is a dose-limiting side effect causing significant pain, eating difficulty, need for parenteral nutrition and a rise of infections. The pathobiology derives from complex interactions between the epithelial component, inflammation, and the oral microbiome. Our longitudinal study analysed the dynamics of the oral microbiome (bacteria and fungi) in nineteen patients undergoing chemo-radiation therapy for oral and oropharyngeal squamous cell carcinoma as compared to healthy volunteers. The microbiome was characterized in multiple oral sample types using rRNA and ITS sequence amplicons and followed the treatment regimens. Microbial taxonomic diversity and relative abundance may be correlated with disease state, type of treatment and responses. Identification of microbial-host interactions could lead to further therapeutic interventions of mucositis to re-establish normal flora and promote patients' health. Data presented here could enhance, complement and diversify other studies that link microbiomes to oral disease, prophylactics, treatments, and outcome.

The human oral microbiome has primarily been studied in clinical settings and for medical purposes. More recently, oral microbial research has been incorporated into other areas of study. In forensics, research has aimed to exploit the variation in composition of the oral microbiome to answer forensic relevant topics, such as human identification and geographical provenience. Several studies have focused on the use of microbiome for continental, national, or ethnic origin evaluations. However, it is not clear how the microbiome varies between similar ethnic populations across different regions in a country. We report here a comparison of the oral microbiomes of individuals living in two regions of Italy - Lombardy and Piedmont. Oral samples were obtained by swabbing the donors' oral mucosa, and the V4 region of the 16S rRNA gene was sequenced from the extracted microbial DNA. Additionally, we compared the oral and the skin microbiome from a subset of these individuals, to provide an understanding of which anatomical region may provide more robust results that can be useful for forensic human identification. Initial analysis of the oral microbiota revealed the presence of a core oral microbiome, consisting of nine taxa shared across all oral samples, as well as unique donor characterising taxa in 31 out of 50 samples. We also identified a trend between the abundance of Proteobacteria and Bacteroidota and the smoking habits, and of Spirochaetota and Synergistota and the age of the enrolled participants. Whilst no significant differences were observed in the oral microbial diversity of individuals from Lombardy or Piedmont, we identified two bacterial families - Corynebacteriaceae and Actinomycetaceae - that showed abundance trends between the two regions. Comparative analysis of the skin and oral microbiota showed significant differences in the alpha (p = 0.0011) and beta (Pr(>F)= 9.999e-05) diversities. Analysis of skin and oral samples from the same donor further revealed that the skin microbiome contained more unique donor characterising taxa than the oral one. Overall, this study demonstrates that whilst the oral microbiome of individuals from the same country and of similar ethnicity are largely similar, there may be donor characterising taxa that might be useful for identification purposes. Furthermore, the bacterial signatures associated with certain lifestyles could provide useful information for investigative purposes. Finally, additional studies are required, the skin microbiome may be a better discriminant for human identification than the oral one.

HIV-associated periodontal diseases (PD) could serve as a source of chronic inflammation. Here, we sought to characterize the oral microbial signatures of HIV+ and HIV- individuals at different levels of PD severity.This cross-sectional study included both HIV+ and HIV- patients with varying degrees of PD. Two tooth, 2 cheek, and 1 saliva samples were obtained for microbiome analysis. Mothur/SILVADB were used to classify sequences. R/Bioconductor (Vegan, PhyloSeq, and DESeq2) was employed to assess overall microbiome structure differences and differential abundance of bacterial genera between groups. Polychromatic flow cytometry was used to assess immune activation in CD4 and CD8 cell populations.Around 250 cheek, tooth, and saliva samples from 50 participants (40 HIV+ and 10 HIV-) were included. Severity of PD was classified clinically as None/Mild (N), Moderate (M), and Severe (S) with 18 (36%), 16 (32%), and 16 (32%) participants in each category, respectively. Globally, ordination analysis demonstrated clustering by anatomic site (R2 = 0.25, P < 0.001). HIV status and PD severity showed a statistically significant impact on microbiome composition but only accounted for a combined 2% of variation. HIV+ samples were enriched in genera Abiotrophia, Neisseria, Kingella, and unclassified Neisseriaceae and depleted in Leptotrichia and Selenomonas. The Neisseria genus was consistently enriched in HIV+ participants regardless of sampling site and PD level. Immune markers were altered in HIV+ participants but did not show association with the oral microbiome.HIV-associated changes in oral microbiome result in subtle microbial signatures along different stages of PD that are common in independent oral anatomic sites.

The human microbiome project (HMP) promoted further understanding of human oral microbes. However, research on the human oral microbiota has not made as much progress as research on the gut microbiota. Currently, the causal relationship between the oral microbiota and oral diseases remains unclear, and little is known about the link between the oral microbiota and human systemic diseases. To further understand the contribution of the oral microbiota in oral diseases and systemic diseases, a Human Oral Microbiome Database (HOMD) was established in the US. The HOMD includes 619 taxa in 13 phyla, and most of the microorganisms are from American populations. Due to individual differences in the microbiome, the HOMD does not reflect the Chinese oral microbial status. Herein, we established a new oral microbiome database-the Oral Microbiome Bank of China (OMBC, http://www.sklod.org/ombc ). Currently, the OMBC includes information on 289 bacterial strains and 720 clinical samples from the Chinese population, along with lab and clinical information. The OMBC is the first curated description of a Chinese-associated microbiome; it provides tools for use in investigating the role of the oral microbiome in health and diseases, and will give the community abundant data and strain information for future oral microbial studies.

The relationship between the oral microbiome and oral squamous cell carcinoma (OSCC) has been extensively investigated. Nonetheless, most previous studies were single-center, resulting in the absence of systematic evaluations. To address this gap, we performed a comprehensive meta-analysis on 1,255 samples from OSCC-related 16S rRNA gene data sets, representing a diverse range of OSCC phenotypes. It is recognized that the progression of cancer is related to the alterations in the microbiome among different phenotypes. Our findings revealed distinct microbiome characteristics among different sample types, with Biopsy (Bios) and Swab samples exhibiting significant differences between phenotypes. In Bios samples, the microbiomes of the Cancer group and the normal tissue adjacent to the tumor (NAT) group display a higher similarity, while both differ from the microbiome of the Fibroepithelial polyp (FEP) group. Moreover, the identified differential genera and pathways corresponded with these observations. We developed a diagnostic model using the random forest algorithm on Swab samples, achieving an area under the receiver operating characteristic curve (AUC) of 0.918. Importantly, this model exhibited considerable effectiveness (AUC = 0.849) when applied to another sequencing platform. Taken together, our study provides a comprehensive overview of the oral microbiome during various OSCC progression stages, potentially enhancing early detection and treatment.IMPORTANCEThis study answers key questions regarding the universal microbial characteristics and comprehensive oral microbiome dynamics during oral squamous cell carcinoma (OSCC) progression. By integrating multiple data sets, we examine the following critical aspects: (1) Do different sample types harbor distinct microbial communities within the oral cavity? (2) Which sample types offer greater potential for investigating OSCC progression? (3) How are the oral microbiomes of the Cancer group, normal tissue adjacent to the tumor group, and Fibroepithelial polyp group related, and what is their potential association with OSCC development? (4) Can a diagnostic model based on microbial signatures effectively distinguish between Cancer and Health groups using Swab samples?

The aim of this study is to compare the efficacy of two methods for collecting saliva samples from infants under 2 years of age for cariogenic streptococci (CS) count. Two collection methods were applied in 11 infants. In Method (A), saliva samples were collected by swabbing the inner cheek mucosa and floor of the mouth in figure of eight motions with a sterile cotton swab until it was soaked. In method (B), saliva samples were collected by aspiration of 1 ml of saliva with a sterile plastic syringe on the floor of the mouth, after stimulation with glove. The samples were cultured in modified Gold's broth (MSMG), and on trypticase, yeast extract, sucrose, cystine and bacitracin culture medium (TYSCB). In method (A), the swab with the sample was unloaded in situ on TYSCB and placed in PBS medium for transport. Then, 100 μl of the eluate was seeded in MSMG. In method (B) 100 μl were seeded in TYSCB and 100 μl in MSMG. Both culture media were incubatedundercapnophilicconditions for 48 hours at 37 °C. Colony forming units (CFU/ml) were counted by calibrated operators (kappa = 0.75). The presence of cariogenic streptococci (CS) (Streptococcus mutans-Streptococcus sobrinus) was determined by qPCR in the samples collected by both methods. The CFU/ml counts in MSMG differed significantly between methods (p = 0.021). In TYSCB, the recovery of CFU/ml was higher in method (A), without significant difference (p = 0.705). The molecular technique detected presence of CS, with no difference between collection methods. Collecting saliva samples by swabbing proved more effective in terms of recovery of microorganisms, and did not affect the detection of presence of CS by molecular techniques. El objetivo de este estudio es comparar la eficacia de dos métodos de obtención de muestras salivales, en infantes menores de 2 años para el recuento de estreptococos cariogénicos (EC). Se aplicaron dos métodos de recolección en 11 infantes, el método (A), consistió en la recolección de muestras de saliva con hisopos de algodón estériles, realizando movimientos en ocho sobre la mucosa del carrillo y piso de boca, hasta embeber el hisopo. En el método (B) la recolección de las muestras se realizó por aspiración con jeringa plástica estéril en piso de boca hasta obtener 1 ml, luego de estimulación con guante. Las muestras fueron cultivadas en caldo de Gold modificado (MSMG) y medio de cultivo TYSCB (tripticasa, extracto de levadura, sacarosa, cistina y bacitracina). En (A), el hisopo con la muestra fue descargado in situ en TYSCB y colocado en medio de transporte PBS. 100 μl del eluato se sembró en MSMG. En (B) 100 μl fueron sembrados en TYSCB y 100μlen MSMG. Ambosmedios de cultivo fueron incubados en condiciones de capnofilia por 48 hs. a 37°C. El recuento de unidades formadoras de colonias (UFC/ml) se realizó por operadores calibrados (kappa= 0.75). La presencia de EC (Streptococcus mutans - Streptococcus sobrinus) fue determinada por qPCR en las muestras obtenidas por ambos métodos. Los resultados mostraron que los recuentos de UFC/ml en MSMG presentaron diferencias significativas entre ambos métodos (p=0.021) En TYSCB la recuperación de UFC/ml fue mayor en el método (A), sin observarse diferencias significativas (p=0.705). Se detectó la presencia de EC por técnica molecular, sin mostrar diferencias entre los métodos empleados. La recolección de muestra de saliva con hisopo presentó mayor eficacia en términos de recuperación de microorganismos, sin alterar la detección de presencia de EC por técnicas moleculares.

Salivary iodine concentration (SIC) has been demonstrated to apply to iodine nutrition assessment. However, limited research exists on saliva collection and storage methods, which are essential for reliable measurements of SIC. This study aims to investigate the effects of various saliva sample collection and storage methods and to establish standardized protocols. Healthy adults were randomly recruited from the university. This study was designed with 2 components: collection methods and storage conditions. Participants provided 4 saliva samples each under stimulation and mouthwash conditions for the collection method analysis. Regarding storage conditions, a 5-mL saliva sample was collected and divided into 4 portions. One portion underwent analysis within 24 h, whereas the remaining 3 were stored at -80°C, -20°C, and 4°C, respectively. SIC detection was performed after 7, 90, 180, and 365 d of storage. Compared with natural secretion, SIC significantly decreased by 21.44 μg/L [95% confidence interval (CI): -33.74, -9.14] after olfactory stimulation, by 17.74 μg/L (95% CI: 26.06, -9.43) after mechanical stimulation, by 74.37 μg/L (95% CI: -85.31, -63.44) after chewing stimulation, and by 23.90 μg/L (95% CI: -31.00, -16.79) 1 min after rinsing. No significant change was observed after rinsing for 5 and 10 min (P > 0.05). Compared with timely testing, SIC remained stable at -80°C for 365 d (all P > 0.05). However, at -20°C, SIC significantly decreased by 20.8 μg/L (95% CI: -37.7, -3.79) after 180 d, and by 26.9 μg/L (95% CI: -43.9, -9.81) after 365 d. At 4°C, SIC significantly increased by 25.8 μg/L (95% CI: 5.49, 46.2) after 365 d. This study recommends collecting saliva through natural secretion 5 min after rinsing. For long-term storage (≥180 d), samples should be preserved at -80°C. For short-term storage (≤90 d), they may be stored at -80°C, -20°C, or 4°C.

Obtaining DNA samples through saliva samples is becoming more common, and more companies are responding to this demand with saliva collection/DNA extraction kits. The University of Pittsburgh's School of Dental Medicine maintains a DNA bank, which our lab helps direct. While we have always used Oragene (DNAGenotek, Kanata, Canada) kits to collect samples in the past, we recently compared 5 alternative kits/methods in an effort to reduce costs while maintaining quality. The kits/ methods were: Norgen (Norgen Biotek Corp., Thorold, Canada), Stratec (Stratec Biomedical, Birkenfeld, Germany), DNAgard (Biomatrica, San Diego, CA, USA), Oasis (Oasis Diagnostics, Vancouver, WA, USA), and an inhouse protocol for DNA extraction from whole saliva. We compared 7 protocols for extracting DNA from saliva using 5 commercially available kits. We primarily looked at total DNA yield, but also considered cost, ease of sample collection, and complexity of extraction protocol. When compared to the Oragene kits, only Norgen and Startec had comparable DNA yields (30 µg or more). Oasis was the easiest to use in terms of sample collection. When compared to our whole saliva DNA extraction protocol, all kits had higher yields, shorter extraction time, and easier protocols.

Human saliva mirrors the body's health and can be collected non-invasively, does not require specialized skills and is suitable for large population based screening programs. The aims were twofold: to evaluate the suitability of commercially available saliva collection devices for quantifying proteins present in saliva and to provide levels for C-reactive protein (CRP), myoglobin, and immunoglobin E (IgE) in saliva of healthy individuals as a baseline for future studies. Saliva was collected from healthy volunteers (n=17, ages 18-33years). The following collection methods were evaluated: drool; Salimetrics® Oral Swab (SOS); Salivette® Cotton and Synthetic (Sarstedt) and Greiner Bio-One Saliva Collection System (GBO SCS®). We used AlphaLISA® assays to measure CRP, IgE and myoglobin levels in human saliva. Significant (p<0.05) differences in the salivary flow rates were observed based on the method of collection, i.e. salivary flow rates were significantly lower (p<0.05) in unstimulated saliva (i.e. drool and SOS), when compared with mechanically stimulated methods (p<0.05) (Salivette® Cotton and Synthetic) and acid stimulated method (p<0.05) (SCS®). Saliva collected using SOS yielded significantly (p<0.05) lower concentrations of myoglobin and CRP, whilst, saliva collected using the Salivette® Cotton and Synthetic swab yielded significantly (p<0.05) lower myoglobin and IgE concentrations respectively. The results demonstrated significantly relevant differences in analyte levels based on the collection method. Significant differences in the salivary flow rates were also observed depending on the saliva collection method. The data provide preliminary baseline values for salivary CRP, myoglobin, and IgE levels in healthy participants and based on the collection method.

Saliva is frequently used as a diagnostic fluid and several collection devices have been developed. The aim of the present study was to investigate the validity and reliability of two types of Salivette collection kits (non-covered cotton roll and polypropylene covered polyether roll) relative to conventional collection of saliva using paraffin wax chewing stimulation. Whole saliva samples were collected from 16 healthy volunteers. Following a cross-over design saliva was collected in a standardized way. The flow rate was determined and saliva samples were analyzed for pH, buffer capacity, electrolytes and protein/glycoprotein content. We find that Salivette methods do not allow evaluation of flow rate. pH was unaffected but buffer capacity was lower in Salivette collected than in paraffin wax-stimulated saliva. The non-covered cotton rolls reduced the content of Na+, K+, Cl-, as well as glycoprotein markers (hexosamines, fucose, sialic acid), lysozyme, lactoferrin, salivary- and myeloperoxidase but increased the concentrations of Ca2+, PO4(3)- and SCN-. Polypropylene covered polyether rolls affected saliva composition less than the non-covered cotton rolls. Thus, SCN- and sIgA concentrations were higher and lysozyme activity lower in the former (covered roll) saliva than in paraffin wax saliva. The reliability of the Salivette kits was good. We conclude that the Salivette method generates data significantly different from conventional paraffin wax-stimulated saliva such as buffer capacity and several electrolytes and organic components. Care should be taken in interpreting the results when such methods are employed.

In the context of forensic casework, it is imperative to both establish a DNA profile from biological specimens and accurately identify the specific bodily fluid source. To achieve this, DNA methylation markers have been developed for the differentiation of blood, semen, vaginal epithelial secretions, and saliva samples. Saliva, alternatively referred to as oral fluid, is recognized for its heterogeneous cellular composition, characterized by a mixture of epithelial, leukocytic, and bacterial cells. Consequently, our research has revealed variations in methylation percentages that correlate with the method employed for collecting saliva samples. To investigate these concepts, we scrutinized four CpG markers situated within or in proximity to the BCAS4, SLC12A8, SOX2OT, and FAM43A genes. Subsequently, we designed primers based on bioinformatically transformed reference sequences for these markers and rigorously assessed their quality by examining dimer and hairpin formation, melting temperature, and specificity. These loci were identified as saliva markers based on either buccal swabs or spit collection. Yet, there has been minimal or no research conducted to explore the variations in methylation between different collection methods. For this study, buccal, lip, tongue, spit, and nasal swabs were collected from 20 individuals (N = 100). Mock forensic samples, which include chewing gum (N = 10) and cigarettes (N = 10), were also tested. DNA was extracted, bisulfite converted, then amplified using in-house designed assays, and pyrosequenced. The methylation levels were compared to other body fluids (semen, blood, vaginal epithelia, and menstrual blood [N = 32]). A total of 608 pyrosequencing results demonstrated that sampling location and collection method can greatly influence the level of methylation, highlighting the importance of examining multiple collection/deposition methods for body fluids when developing epigenetic markers.

The recovery of steroids, peptides and therapeutic drugs from commercial saliva collection devices was investigated. Saliva, spiked with defined concentrations of the analytes was applied to the Quantisal, three different Salivettes, and the Saliva-Collection-System to investigate effects of volume, exposure time and temperature on the recovery. Additionally, saliva was collected from healthy subjects with the same devices. It was found that glucocorticoids can be measured very well from samples obtained with the synthetic fiber Salivettes and the Quantisal (80-100%). For androgens, the Quantisal and the Saliva-Collection-System reached recoveries >80%. The Quantisal and polyester Salivette achieved best recoveries (>80%) for peptides. The results for the cotton Salivette were extremely poor for melatonin, insulin or IL-8 (<20%). The results from the spike-recovery experiments were confirmed by samples collected from healthy volunteers. For most therapeutic drugs the synthetic fiber Salivettes achieved best recoveries of 100+/-10%. Longer exposure of saliva on the collection devices must be avoided for most of the analytes, due to their limited stability and increased adsorption. In conclusion, no device is suitable for all of the salivary compounds. Strict pre-analytical precautions must be considered (e.g. immediate processing of the sample) to guarantee reliable analytical results.

Saliva is a well-established source of DNA for various applications due to its non-invasive collection and its provision of high-quality DNA. However, its use in wild and free-ranging animal research remains limited due to challenges in collection without direct animal handling. In this study, we developed and evaluated a hands-off saliva collection method designed for free-ranging domestic dogs (FRDs), serving as a model for non-invasive genetic sampling of wildlife. Our method utilized a funnel paired with a commercially available Performagene kit (DNA Genotek, Canada), presented to the dog in the presence of an operator. The dog was free to approach and interact with the apparatus, depositing saliva while trying to reach bait. We compared DNA yield and genotyping success from samples using this hands-off method with those collected via the manufacturer's recommended method. We collected 461 saliva samples from 326 FRDs, performing 750 DNA extractions. Samples collected by hand yielded significantly higher DNA concentrations after the first extraction attempt (mean = 46.3 ng/µL) than those collected using the hands-off method (mean = 32.2 ng/µL). Despite lower DNA concentrations, genotyping success did not significantly differ between methods, demonstrating that the hands-off method can yield DNA suitable for genomic analyses. The hands-off saliva collection method is a viable alternative to invasive sampling, addressing ethical concerns and enabling genomic studies in wild animals. Furthermore, our method mitigates sampling bias toward bold individuals, a common limitation in behavioral and genetic studies of free-ranging animals. With minor adaptations, this method could be applied across various species, including more elusive ones, contributing to conservation genetics and behavioral ecology research.

The human oral cavity is a major point of entry for microorganisms, many of which live and multiply in the mouth. In addition, it provides an accessible site for sampling compared to other parts of the body; however, caution should be taken during oral sampling as many factors contribute to the microbial diversity in a site-dependent manner. The accessibility of the oral cavity and its microbial diversity emphasize the crucial need to avoid cross-contamination during the sampling procedure. In this chapter, we describe various detailed oral sampling procedures. These methods include supragingival dental plaque sampling, subgingival dental plaque sampling, oral mucosal sampling, and endodontic sampling methods for extracted teeth or in the patient's mouth. The proposed protocols provide tips to avoid contamination between different oral sources of bacteria and possible alternatives to the tools used.

No abstract

This study aimed to make a comparison of two sampling strategies of subgingival plaque after combined mechanical-antibiotic periodontal therapy. Thirty patients (18 female) suffering from aggressive (n = 12) or generalised severe chronic (n = 18) periodontitis were included. Aggregatibacter actinomycetemcomitans had been detected subgingivally in all prior to anti-infective therapy (AT) and combined mechanical-antibiotic AT had been rendered. After AT clinical examinations were performed and subgingival plaque was sampled from the same four sites as prior to AT (ASPRE) as well as from the four deepest sites after AT (DEEP). Per patient two pooled samples (ASPRE/DEEP) were generated and analysed for A. actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola using a commercial 16S rRNA test. ASPRE failed to detect A. actinomycetemcomitans, DEEP detected A. actinomycetemcomitans only in two patients (7 %). Only for T. forsythia DEEP (53 %) provided higher detection frequencies than ASPRE (27 %; p = 0.005). Detection frequencies of P. gingivalis and T. denticola ranged from 47 to 53 %. After combined mechanical-antibiotic AT sampling the deepest sites revealed higher detection rates. Combined mechanical-antibiotic AT suppresses A. actinomycetemcomitans to a higher extent than P. gingivalis, T. forsythia and T. denticola.

Dental plaque samples from (i) subjects with no apparent oral disease, (ii) mentally retarded subjects with periodontal disease, and (iii) subjects with active caries were collected in three transport media viz. a dithiothreitol poised balanced mineral salt solution designated as reduced transport fluid (RTF), VMG II, and modified Stuart medium (SBL). The samples were dispersed by sonic treatment, diluted in the respective medium in which they were collected, and cultured on MM10 sucrose agar. The efficiency of the transport media in the survival of dental plaque flora was determined by comparing the quantitative recovery (expressed as percentage of the initial viable count) from the specimens stored for various lengths of time. The data showed a great variation in the recovery of the oral bacterial flora from the plaque samples. VMG II and SBL served better than RTF as storage media for non-disease-associated dental plaque cultured under strict anaerobic conditions. Recoveries of bacteria from periodontal plaque specimens stored in RTF were higher than SBL and VMG II under identical conditions. The organisms present in the carious plaque samples appeared to survive much better in RTF and VMG II than in SBL as determined by conventional anaerobic culturing technique. However, VMG II showed a higher recovery of organisms from these specimens with an increase in the storage period, suggesting multiplication of the plaque flora. RTF did not allow the growth of oral bacterial flora under all experimental conditions. On the basis of the relative performance of these media it is suggested that RTF is a satisfactory medium for the transport of oral bacteria present in the samples.

No abstract

Human dental plaque consists of a wide variety of microorganisms, some of which are believed to cause systemic infections, including abscesses, at various sites in the body. To confirm this hypothesis experimentally, we examined the abscess-forming ability of native dental plaque in mice, the microbial features of the infectious locus produced by the plaque, and the anti-phagocytic property of microbial isolates. Aliquots of a suspension of supragingival dental plaque containing 6 x 10(6) colony-forming unit of bacteria were injected subcutaneously into the dorsa of mice. Abscess formation was induced in 76 of 85 mice using ten different plaque samples. Thirteen microorganisms were isolated from pus samples aspirated from abscess lesions. The microbial composition of pus, examined in 17 of 76 abscesses, was very simple compared to that of the plaque sample that had induced the abscess. The majority of the isolates belonged to the Streptococcus anginosus group, normally a minor component of plaque samples. S. anginosus was the most frequently detected organism and the most prevalent in seven abscesses, and Streptococcus intermedius and Streptococcus constellatus were predominant in one and three abscess samples, respectively. Each isolate of S. anginosus group produced abscesses in mice, and heat-treated supragingival dental plaque influenced the abscess-forming ability of S. anginosus isolate. These isolates possessed a high antiphagocytic capacity against human polymorphonuclear leukocytes. Our results suggest that human supragingival dental plaque itself is a source of the infectious pathogens that cause abscess formation.

The present study was performed in 10 adults in order to evaluate the effect of an antiseptic mouthrinse (Listerine) on the rate of dental plaque formation and gingivitis development during a 2-week period when all efforts towards active mechanical oral hygiene were withdrawn. The study was performed as a crossover study and was carried out during four consecutive 2-week periods. During the first and third periods (preparatory periods) the participants were subjected to repeated professional tooth cleanings in order to establish plaque- and gingivitis-free dentitions. During the second and fourth periods (test and control periods) the participants were not allowed to brush their teeth but rinsed their mouths three times a day with Listerine or a placebo mouthwash. Plaque Index, Gingival Index, gingival fluid flow, and crevicular leukocytes were assessed on d 0, 2, 4, 7, and 14. On d 7 and 14, dental plaque was removed from the right and left jaws respectively and the wet weights determined. The chemotactic activity elaborated by the plaques was studied in Boyden chambers. During the Listerine test period, significantly lower Plaque and Gingival Index values were scored and lower amounts of plaque could be sampled in comparison to the control period.

The prediction of caries risk has been of long-standing interest. Generally, few of the tests involving oral bacteria or their products have become accepted. Presently, the main focus is on counts of lactobacilli (L) and mutans streptococci (MS). Due to their positive numerical association with human caries and the linkage of this association to carbohydrate consumption, counts of L and MS may, potentially, serve not only as a caries risk predictor but also as an indicator of carbohydrate consumption, another caries-risk factor. The value of counts of L and MS as caries-risk predictors has been evaluated by means of studies providing data on test sensitivity, specificity, and predictive values. These and other studies indicate that their use for the prediction of caries risk of individuals is not possible but is more promising for that of the caries risk of groups (e.g., identification of high-caries-risk subjects); further, the prediction of low caries risk may be more reliable than that of high caries risk. The influence of test variables on the test results has been discussed. These include the level of caries increment, subject age, methods of caries evaluation, use of saliva or dental plaque as test sample, sampling frequency, type of bacterial growth medium, and the use of simplified methods rather than conventional laboratory procedures for microbial enumeration. An approach to optimize the use of microbiological caries-risk predictors in different populations as well as their use in conjunction with other caries-risk predictors has been discussed. The latter include the incipient caries lesion or past caries experience and salivary buffering capacity and flow rate. Due to the multifactorial nature of caries etiology, it is expected that multivariate approaches rather than the use of single parameters may improve caries risk prediction for individuals as well as groups of subjects.

Dental plaque is home to a diverse and complex community of bacteria, but has generally been believed to be inhabited by relatively few viruses. We sampled the saliva and dental plaque from 4 healthy human subjects to determine whether plaque was populated by viral communities, and whether there were differences in viral communities specific to subject or sample type. We found that the plaque was inhabited by a community of bacteriophage whose membership was mostly subject-specific. There was a significant proportion of viral homologues shared between plaque and salivary viromes within each subject, suggesting that some oral viruses were present in both sites. We also characterized Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) in oral streptococci, as their profiles provide clues to the viruses that oral bacteria may be able to counteract. While there were some CRISPR spacers specific to each sample type, many more were shared across sites and were highly subject specific. Many CRISPR spacers matched viruses present in plaque, suggesting that the evolution of CRISPR loci may have been specific to plaque-derived viruses. Our findings of subject specificity to both plaque-derived viruses and CRISPR profiles suggest that human viral ecology may be highly personalized.

Recent genomic data have revealed multiple interactions between Neanderthals and modern humans, but there is currently little genetic evidence regarding Neanderthal behaviour, diet, or disease. Here we describe the shotgun-sequencing of ancient DNA from five specimens of Neanderthal calcified dental plaque (calculus) and the characterization of regional differences in Neanderthal ecology. At Spy cave, Belgium, Neanderthal diet was heavily meat based and included woolly rhinoceros and wild sheep (mouflon), characteristic of a steppe environment. In contrast, no meat was detected in the diet of Neanderthals from El Sidrón cave, Spain, and dietary components of mushrooms, pine nuts, and moss reflected forest gathering. Differences in diet were also linked to an overall shift in the oral bacterial community (microbiota) and suggested that meat consumption contributed to substantial variation within Neanderthal microbiota. Evidence for self-medication was detected in an El Sidrón Neanderthal with a dental abscess and a chronic gastrointestinal pathogen (Enterocytozoon bieneusi). Metagenomic data from this individual also contained a nearly complete genome of the archaeal commensal Methanobrevibacter oralis (10.2× depth of coverage)-the oldest draft microbial genome generated to date, at around 48,000 years old. DNA preserved within dental calculus represents a notable source of information about the behaviour and health of ancient hominin specimens, as well as a unique system that is useful for the study of long-term microbial evolution.

Microorganisms colonizing the apical root canal system are conceivably the ones directly involved with the causation and maintenance of apical periodontitis. This article systematically reviews the reports on the microbiome occurring exclusively at the apical root canal of teeth with primary and posttreatment apical periodontitis. The electronic databases PubMed, Embase, Web of Science, Science Direct, and Proquest were searched up to August 2023. Clinical studies using culture and molecular microbiology methods to identify the microbial taxa present exclusively in the apical root canal segment of infected teeth with apical periodontitis were included. Studies were critically assessed using the Joanna Briggs Institute Critical Prevalence Assessment Checklist. From 2277 articles initially detected, 52 were selected for full reading and 21 were eventually included in this review. Of these, molecular methods were used in 19 and culture in 2 studies. Ten studies evaluated primary infections, 8 evaluated posttreatment infections, and 3 included both. Cryopulverization of the apical root specimens was conducted in 11 studies. All studies evaluated the prevalence and diversity of bacteria, and only one also reported on fungi. Overall, the most frequent/abundant bacterial taxa found in the apical canal of primary infections were Pseudoramibacter alactolyticus, Olsenella uli, Fusobacterium species, Streptococcus species, Porphyromonas endodontalis, Prevotella species, Actinomyces species, Parvimonas micra, Treponema denticola, Synergistetes species, and an as-yet uncharacterized taxon. In posttreatment infections, the most prevalent/abundant bacterial taxa included species of Streptococcus, Enterococcus, Fusobacterium, Actinomyces, Pseudoramibacter, Pseudomonas, and Propionibacterium. At the phylum level, Firmicutes was the most represented. The average apical bacterial load ranged from 10 Microbial diversity in the apical part of the root canal system was examined encompassing data from both primary and posttreatment infections. Heterogeneity amongst the studies, especially in sample collection and microbial identification methods, is an important limitation that prevented a meta-analysis. There is a pronounced bacterial diversity in the infected apical canal, with a high interindividual variability. Different microbiome compositions at the species/genus level are observed according to the infection type. PROSPERO CRD42021275886.

A number of cohort studies have collected Scope mouthwash samples by mail, which are being used for microbiota measurements. We evaluated the stability of Scope mouthwash samples at ambient temperature and determined the comparability of Scope mouthwash with saliva collection using the OMNIgene ORAL Kit. Fifty-three healthy volunteers from Mayo Clinic and 50 cohort members from Bangladesh provided oral samples. One aliquot of the OMNIgene ORAL and Scope mouthwash were frozen immediately and one aliquot of the Scope mouthwash remained at ambient temperature for 4 days and was then frozen. DNA was extracted and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using the HiSeq. Intraclass correlation coefficients (ICC) were calculated. The overall stability of the Scope mouthwash samples was relatively high for alpha and beta diversity. For example, the meta-analyzed ICC for the Shannon index was 0.86 (95% confidence interval, 0.76-0.96). Similarly, the ICCs for the relative abundance of the top 25 genera were generally high. The comparability of the two sample types was relatively low when measured using ICCs, but were increased by using a Spearman correlation coefficient (SCC) to compare the rank order of individuals. Overall, the Scope mouthwash samples appear to be stable at ambient temperature, which suggests that oral rinse samples received by the mail can be used for microbial analyses. However, Scope mouthwash samples were distinct compared with OMNIgene ORAL samples. Studies should try to compare oral microbial metrics within one sample collection type.

The oral microbiota plays an important role in buccal health and in diseases such as periodontitis and meningitis. The study of the human oral bacteria has so far focused on subjects from Western societies, while little is known about subjects from isolated communities. This work determined the composition of the oral mucosa microbiota from six Amazon Amerindians, and tested a sample preservation alternative to freezing. Paired oral swabs were taken from six adults of Guahibo ethnicity living in the community of Platanillal, Amazonas State, Venezuela. Replicate swabs were preserved in liquid nitrogen and in Aware Messenger fluid (Calypte). Buccal DNA was extracted, and the V2 region of the 16S rRNA gene was amplified and pyrosequenced. A total of 17 214 oral bacterial sequences were obtained from the six subjects; these were binned into 1034 OTUs from 10 phyla, 30 families and 51 genera. The oral mucosa was highly dominated by four phyla: Firmicutes (mostly the genera Streptococcus and Veillonella), Proteobacteria (mostly Neisseria), Bacterioidetes (Prevotella) and Actinobacteria (Micrococcineae). Although the microbiota were similar at the phylum level, the Amerindians shared only 62 % of the families and 23 % of the genera with non-Amerindians from previous studies, and had a lower richness of genera (51 vs 177 reported in non-Amerindians). The Amerindians carried unidentified members of the phyla Bacteroidetes, Firmicutes and Proteobacteria and their microbiota included soil bacteria Gp1 (Acidobacteriaceae) and Xylanibacter (Prevotellaceae), and the rare genus Phocoenobacter (Pasteurellaceae). Preserving buccal swabs in the Aware Messenger oral fluid collection device substantially altered the bacterial composition in comparison to freezing, and therefore this method cannot be used to preserve samples for the study of microbial communities.

The human microbiome emerges as a promising reservoir for diagnostic markers and therapeutics. Since host-associated microbiomes at various body sites differ and diseases do not occur in isolation, a comprehensive analysis strategy highlighting the full potential of microbiomes should include diverse specimen types and various diseases. To ensure robust data quality and comparability across specimen types and diseases, we employ standardized protocols to generate sequencing data from 1931 prospectively collected specimens, including from saliva, plaque, skin, throat, eye, and stool, with an average sequencing depth of 5.3 gigabases. Collected from 515 patients, these samples yield an average of 3.7 metagenomes per patient. Our results suggest significant microbial variations across diseases and specimen types, including unexpected anatomical sites. We identify 583 unexplored species-level genome bins (SGBs) of which 189 are significantly disease-associated. Of note, the existence of microbial resistance genes in one specimen was indicative of the same resistance genes in other specimens of the same patient. Annotated and previously undescribed SGBs collectively harbor 28,315 potential biosynthetic gene clusters (BGCs), with 1050 significant correlations to diseases. Our combinatorial approach identifies distinct SGBs and BGCs, emphasizing the value of pan-body pan-disease microbiomics as a source for diagnostic and therapeutic strategies.

The human microbiota is postulated to affect cancer risk, but collecting microbiota specimens with prospective follow-up for diseases will take time. Buccal cell samples have been obtained from mouthwash for the study of human genomic DNA in many cohort studies. Here, we evaluate the feasibility of using buccal cell samples to examine associations of human microbiota and disease risk. We obtained buccal cells from mouthwash in 41 healthy participants using a protocol that is widely employed to obtain buccal cells for the study of human DNA. We compared oral microbiota from buccal cells with that from eight other oral sample types collected by following the protocols of the Human Microbiome Project. Microbiota profiles were determined by sequencing 16S rRNA gene V3-V4 region. Compared with each of the eight other oral samples, the buccal cell samples had significantly more observed species (P < 0.002) and higher alpha diversity (Shannon index, P < 0.02). The microbial communities were more similar (smaller beta diversity) among buccal cells samples than in the other samples (P < 0.001 for 12 of 16 weighted and unweighted UniFrac distance comparisons). Buccal cell microbial profiles closely resembled saliva but were distinct from dental plaque and tongue dorsum. Stored buccal cell samples in prospective cohort studies are a promising resource to study associations of oral microbiota with disease. The feasibility of using existing buccal cell collections in large prospective cohorts allows investigations of the role of oral microbiota in chronic disease etiology in large population studies possible today. Cancer Epidemiol Biomarkers Prev; 26(2); 249-53. ©2016 AACR.