Metaproteomics analysis of microbial diversity of human saliva and tongue dorsum in young healthy individuals

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study

BACKGROUND

Our previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer.

METHODS

We employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins.

RESULTS

We measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort.

CONCLUSIONS

We characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer. Video Abstract.

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

Beyond the Bottle: Exploring Health-Promoting Compounds in Wine and Wine-Related Products-Extraction, Detection, Quantification, Aroma Properties, and Terroir Effects

Health-promoting compounds in wine and wine-related products are important due to their potential benefits to human health. Through an extensive literature review, this study explores the presence of these compounds in wine and wine-related products, examining their relationship with terroir and their impact on the aromatic and flavor properties that are perceived orally: sunlight exposure, rainfall patterns, and soil composition impact grapevines' synthesis and accumulation of health-promoting compounds. Enzymes, pH, and the oral microbiome are crucial in sensory evaluation and perception of health promotion. Moreover, their analysis of health-promoting compounds in wine and wine-related products relies on considerations such as the specific target compound, selectivity, sensitivity, and the complexity of the matrix.

Salivary Chemical Barrier Proteins in Oral Squamous Cell Carcinoma-Alterations in the Defense Mechanism of the Oral Cavity

Oral squamous cell carcinoma (OSCC) is one of the most frequent types of head and neck cancer. Despite the genetic and environmental risk factors, OSCC is also associated with microbial infections and/or dysbiosis. The secreted saliva serves as the chemical barrier of the oral cavity and, since OSCC can alter the protein composition of saliva, our aim was to analyze the effect of OSCC on the salivary chemical barrier proteins. Publicly available datasets regarding the analysis of salivary proteins from patients with OSCC and controls were collected and examined in order to identify differentially expressed chemical barrier proteins. Network analysis and gene ontology (GO) classification of the differentially expressed chemical barrier proteins were performed as well. One hundred and twenty-seven proteins showing different expression pattern between the OSCC and control groups were found. Protein-protein interaction networks of up- and down-regulated proteins were constructed and analyzed. The main hub proteins (IL-6, IL-1B, IL-8, TNF, APOA1, APOA2, APOB, APOC3, APOE, and HP) were identified and the enriched GO terms were examined. Our study highlighted the importance of the chemical barrier of saliva in the development of OSCC.

Oral microbiome homogeneity across diverse human groups from southern Africa: first results from southwestern Angola and Zimbabwe

BACKGROUND

While the human oral microbiome is known to play an important role in systemic health, its average composition and diversity patterns are still poorly understood. To gain better insights into the general composition of the microbiome on a global scale, the characterization of microbiomes from a broad range of populations, including non-industrialized societies, is needed. Here, we used the portion of non-human reads obtained through an expanded exome capture sequencing approach to characterize the saliva microbiomes of 52 individuals from eight ethnolinguistically diverse southern African populations from Angola (Kuvale, Kwepe, Himba, Tjimba, Kwisi, Twa, !Xun) and Zimbabwe (Tshwa), including foragers, food-producers, and peripatetic groups (low-status communities who provide services to their dominant neighbors).

RESULTS

Our results indicate that neither host genetics nor livelihood seem to influence the oral microbiome profile, with Neisseria, Streptococcus, Prevotella, Rothia, and Porphyromonas being the five most frequent genera in southern African groups, in line with what has been shown for other human populations. However, we found that some Tshwa and Twa individuals display an enrichment of pathogenic genera from the Enterobacteriaceae family (i.e. Enterobacter, Citrobacter, Salmonella) of the Proteobacteria phylum, probably reflecting deficient sanitation and poor health conditions associated with social marginalization.

CONCLUSIONS

Taken together, our results suggest that socio-economic status, rather than ethnolinguistic affiliation or subsistence mode, is a key factor in shaping the salivary microbial profiles of human populations in southern Africa.

Characterization of tongue dorsum microbiome in wine tasters

Taste plays a paramount role in food and beverage choice, with recent studies pointing to a potential influence of the microorganisms from the tongue dorsum - particularly bacteria - on flavor perception. Thus, the association between tongue dorsum biofilm and taste is a fundamental prerequisite for a better understanding of the role played by these bacteria in wine tasting. To study this impact, we have analyzed the microbiomes from 58 samples of the tongue dorsum surface from professional wine tasters and 30 samples from non professional wine tasters. The microbiome of each sample was characterized through metagenome sequencing of the 16S rRNA gene for taxonomic discrimination of bacteria. A total of 497 taxa were identified in the tongue dorsum, and significant differences in diversity were observed between the wine taster and the control group. The comparison of bacterial diversity between samples collected before and after wine tasting along with the presence of new bacterial taxa indicates a direct effect of wine on the microbiome of frequent wine tasters, particularly in those tasting sparkling wines.

Impact of different oral treatments on the composition of the supragingival plaque microbiome

Background

Dental plaque consists of a diverse microbial community embedded in a complex structure of exopolysaccharides. Dental biofilms form a natural barrier against pathogens but lead to oral diseases in a dysbiotic state.

Objective

Using a metaproteome approach combined with a standard plaque-regrowth study, this pilot study examined the impact of different concentrations of lactoperoxidase (LPO) on early plaque formation, and active biological processes.

Design

Sixteen orally healthy subjects received four local treatments as a randomized single-blind study based on a cross-over design. Two lozenges containing components of the LPO-system in different concentrations were compared to a placebo and Listerine®. The newly formed dental plaque was analyzed by mass spectrometry (nLC-MS/MS). 

Results

On average 1,916 metaproteins per sample were identified, which could be assigned to 116 genera and 1,316 protein functions. Listerine® reduced the number of metaproteins and their relative abundance, confirming the plaque inhibiting effect. The LPO-lozenges triggered mainly higher metaprotein abundances of early and secondary colonizers as well as bacteria associated with dental health but also periodontitis. Functional information indicated plaque biofilm growth.

Conclusion

In conclusion, the mechanisms on plaque biofilm formation of Listerine® and the LPO-system containing lozenges are different. In contrast to Listerine®, the lozenges led to a higher bacterial diversity.

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer

The human oral microbiome correlates with numerous diseases, including lung cancer. Identifying the functional changes by metaproteomics helps understand the disease-related dysbiosis, yet characterizing low-abundant bacteria is challenging. Here, we developed a free-flow isoelectric focusing electrophoresis-mass spectrometry- (FFIEF-MS-) based metaproteomics strategy to reduce host interferences and enrich low-abundant bacteria for in-depth interpretation of the oral microbiome. With our method, the number of interfering peptides decreased by 52.87%, whereas the bacterial peptides and species increased by 94.97% and 44.90%, respectively, compared to the conventional metaproteomics approach. We identified 3647 bacterial proteins, which is the most comprehensive oral metaproteomics study to date. Lung cancer-associated bacteria were validated among an independent cohort. The imbalanced Fusobacterium nucleatum and Prevotella histicola and their dysregulated functions in inhibiting immune response and maintaining cell redox homeostasis were revealed. The FFIEF-MS may serve as a valuable strategy to study the mechanisms between human diseases and microbiomes with broader applications.

Oral-Gut Microbiome Analysis in Patients With Metabolic-Associated Fatty Liver Disease Having Different Tongue Image Feature

Objective

The objective of this study was to identify the biological correlation between the tongue coating color and oral and gut micro-characteristics in metabolic-associated fatty liver disease (MAFLD) patients.

Method

The characteristics of the tongue coating were examined using an automatic tongue diagnosis system. Tongue coating and stool samples were collected from 38 MAFLD patients, and 16S rDNA full-length assembly sequencing technology (16S-FAST) was used for bioinformatic analysis.

Results

Twenty-two and 16 subjects were included in two distinct clusters according to the white/yellow color of the tongue coating, which was assessed by the L*a*b* values of the image. Upon analyzing the microorganisms in the tongue coating, 66 and 62 pathognomonic bacterial genera were found in the White and Yellow Coating Groups, respectively. The abundance of Stomatobaculumis positively correlated with the a* values of the tongue coating in the White Coating Group, while Fusobacterium, Leptotrichia, and Tannerella abundance was significantly correlated with the b* values in the Yellow Coating Group. Function prediction mainly showed the involvement of protein families related to BRITE hierarchies and metabolism. The MHR (MONO%/high-density lipoprotein cholesterol) of the Yellow Coating Group was higher than that of the White Coating Group.

Conclusion

In MAFLD patients, lower a* values and higher b* values are indicators of a yellow tongue coating. There were also significant differences in the flora of different tongue coatings, with corresponding changes in the intestinal flora, indicating a correlation between carbohydrate metabolism disorders and inflammation in the oral microbiome.

Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies

Constant improvements in mass spectrometry technologies and laboratory workflows have enabled the proteomics investigation of biological samples of growing complexity. Microbiomes represent such complex samples for which metaproteomics analyses are becoming increasingly popular. Metaproteomics experimental procedures create large amounts of data from which biologically relevant signal must be efficiently extracted to draw meaningful conclusions. Such a data processing requires appropriate bioinformatics tools specifically developed for, or capable of handling metaproteomics data. In this chapter, we outline current and novel tools that can perform the most commonly used steps in the analysis of cutting-edge metaproteomics data, such as peptide and protein identification and quantification, as well as data normalization, imputation, mining, and visualization. We also provide details about the experimental setups in which these tools should be used.

Metagenome-genome-wide association studies reveal human genetic impact on the oral microbiome

The oral microbiota contains billions of microbial cells, which could contribute to diseases in many body sites. Challenged by eating, drinking, and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1915 individuals, for both the tongue dorsum (n = 2017) and saliva (n = 1915). We identified five genetic loci associated with oral microbiota at study-wide significance (p < 3.16 × 10-11). Four of the five associations were well replicated in an independent cohort of 1439 individuals: rs1196764 at APPL2 with Prevotella jejuni, Oribacterium uSGB 3339 and Solobacterium uSGB 315; rs3775944 at the serum uric acid transporter SLC2A9 with Oribacterium uSGB 1215, Oribacterium uSGB 489 and Lachnoanaerobaculum umeaense; rs4911713 near OR11H1 with species F0422 uSGB 392; and rs36186689 at LOC105371703 with Eggerthia. Further analyses confirmed 84% (386/455 for tongue dorsum) and 85% (391/466 for saliva) of host genome-microbiome associations including six genome-wide significant associations mutually validated between the two niches. As many of the oral microbiome-associated genetic variants lie near miRNA genes, we tentatively validated the potential of host miRNAs to modulate the growth of specific oral bacteria. Human genetics accounted for at least 10% of oral microbiome compositions between individuals. Machine learning models showed that polygenetic risk scores dominated over oral microbiome in predicting risk of dental diseases such as dental calculus and gingival bleeding. These findings indicate that human genetic differences are one explanation for a stable or recurrent oral microbiome in each individual.

Metaproteomics associated with severe early childhood caries highlights the differences in salivary proteins

OBJECTIVE

To investigate the salivary metaproteomic characteristics of the children with and without severe early childhood caries (S-ECC).

DESIGN

In this study, we collected unstimulated saliva samples from 34 children (age 3-4 years) with caries free (NC, dmfs (= index of decayed, missing due to caries, or filled tooth surfaces) = 0, n = 23) and with S-ECC (dmfs≥10, n = 11). Salivary proteins were extracted and reduced, and then a Liquid Chromatography/Mass Spectrometry system was used to identify proteins.

RESULTS

Nearly 3000 proteins were identified in this study, and about 3.5 % of the proteins originated from human while 86 % were derived from microbes. The salivary protein types in the NC group were statistically greater than those in the S-ECC group (P <0.05). Specifically, the salivary protein types derived from microbes in the NC group were significantly greater than those in the S-ECC group. Three proteins, human lactoferrin, penicillin-binding protein 1C [Burkholderia ubonensis], human alpha-defensin 1 (F28a mutant), were decreased statistically in the NC group compared to the S-ECC group (P < 0.05). Only one protein, 50S ribosomal protein L17 secreted by Haemophilus haemolyticus, was significantly increased in the NC group compared to the S-ECC group. Salivary IgA was the top highest protein in the NC group whereas human lysozyme was the top highest protein in the S-ECC group.

CONCLUSIONS

The differential proteins recognized in this study may be conducive for finding a caries biomarker. Understanding the metaproteomic characteristics can help us to control the caries from human origin and microbial origin.

Microbial characteristics across different tongue coating types in a healthy population

Background The physical appearance of tongue coatings is vital for traditional Chinese medicine (TCM) to diagnose health and disease status. The microbiota of different tongue coatings could also influence coating formation and be further associated with specific diseases. Previous studies have focused on bacteria from different tongue coatings in the context of specific diseases, but the normal variations in healthy individuals remain unknown.Aim: We examined the tongue microbiota by metagenomics in 94 healthy individuals classified into eight different tongue types.Results: The overall composition of the tongue coating microbiome is not drastically different among different coating types, similar to the findings of previous studies in healthy populations. Further analysis revealed microbiota characteristics of each coating type, and many of the key bacteria are reported to be implicated in diseases. Moreover, further inclusion of diabetic patients revealed disease-specific enrichment of Capnocytophaga, even though the same tongue coatings were studied.Conclusions: This work revealed the characteristic compositions of distinctive tongue coatings in a healthy population, which serves as a basis for understanding the tongue coating formation mechanism and provides a valuable reference to further investigate disease-specific tongue coating bacterial markers.

Molecular Screening and Analysis Reveal Novel Oral Site-Specific Locations for the Cariogenic Pathogen Scardovia wiggsiae

Introduction: Scardovia wiggsiae (SW) is a newly identified cariogenic pathogen associated with severe early childhood caries and oral disease. New studies have confirmed the presence of this organism among clinical samples from both pediatric and adult patients. However, the recent discovery of this organism has left researchers with only limited information available regarding the prevalence of this organism—and virtually no information regarding oral site-specific locations. Based upon this lack of information, the overall objective of this study was to perform an oral site-specific analysis of SW prevalence from clinical samples. Methods: Using an approved human subjects protocol, samples (n = 60) from an existing saliva and site-specific biorepository were identified and screened for SW presence using quantitative polymerase chain reaction (qPCR). These data were summarized and subsequently analyzed for correlations with demographic (age, sex, race or ethnicity) or clinical (body mass index or BMI, primary/mixed/permanent dentition, orthodontic brackets) variables. Results: These data revealed that average DNA concentrations from all sample sites (saliva, dorsum of tongue, gingival crevicular fluid (GCF), biofilm of upper buccal molar, and biofilm of lower lingual incisor) ranged between 13.74 and 14.69 μg/μL, with an overall average of 14.30 μg/μL ± 1.12 (standard error or SE). qPCR screening revealed a total of n = 34/60 or 56.7% of patient samples harboring SW. A total of n = 71/170 specific oral sites harbored this organism, with the majority of the SW-positive participant samples harboring SW at more than one oral site, n = 22/34 or 64.7%, including non-traditional sites such as GCF and the dorsum of the tongue. Weak correlations were found between specific SW outcomes in GCF and type of dentition (permanent; R = 0.2444), as well as SW outcomes in saliva with age (R = 0.228) and presence of orthodontic brackets (R = 0.2118). Conclusions: This study may be among the first to provide oral site-specific analysis to reveal the prevalence and location of Scardovia among clinical patient samples. Moreover, these data also provide some of the first evidence to suggest this organism may be present not only in traditional supragingival tooth-associated biofilm sites, but also in non-traditional oral sites including the dorsum of the tongue and the gingival crevice. Based upon these results, these data may represent a significant advance in our understanding of the potential sites and locations that harbor this organism and may help contribute to our understanding of the prevalence, distribution and potential for the development of oral disease among clinic patients.

Microbial Screening Reveals Oral Site-Specific Locations of the Periodontal Pathogen Selenomonas noxia

INTRODUCTION

Selenomonas noxia (SN) is an important periodontal pathogen, associated with gingivitis and periodontitis. Many studies have found associations between SN and indicators of poor health outcomes, such as smoking, low socioeconomic status and obesity. However, less is known about the prevalence of this organism and more specifically about other oral site-specific locations that may harbor this organism.

METHODS

Using an existing patient repository (n = 47) of DNA isolated from saliva and other oral sites (n = 235), including the dorsum of the tongue, lower lingual incisor, upper buccal molar and gingival crevicular fluid (GCF), molecular screening for SN was performed. Screening results were analyzed for associations between demographic variables (age, sex, race/ethnicity) and clinical information (body mass index or BMI, presence of orthodontic brackets, primary/mixed/permanent dentition).

RESULTS

qPCR screening revealed a total of n = 62/235 sites or 26.3% harboring SN with saliva and GCF (either alone or in combination with one or more sites) most often observed (Saliva, n = 23/27 or 85.18%, GCF, n = 14/27 or 51%). Analysis of site-specific data revealed most positive results were found among saliva and GCF alone or in combination, with fewer positive results observed among the tongue (33.3%), lower lingual incisor (29.6%), and upper buccal molar (25.9%). No significant associations were found between demographic or clinical variables and presence of SN at any site.

CONCLUSIONS

These results may be among the first to describe site-specific locations of S. noxia among various additional oral biofilm sites. These data may represent a significant advancement in our understanding of the sites and locations that harbor this organism, which may be important for our understanding of the prevalence and distribution of these organisms among patients of different ages undergoing different types of oral treatments, such as orthodontic treatment or therapy.

Bottom-Up Community Proteome Analysis of Saliva Samples and Tongue Swabs by Data-Dependent Acquisition Nano LC-MS/MS Mass Spectrometry

Analysis using mass spectrometry enables the characterization of metaproteomes in their native environments and overcomes the limitation of proteomics of pure cultures. Metaproteomics is a promising approach to link functions of currently actively expressed genes to the phylogenetic composition of the microbiome in their habitat. In this chapter, we describe the preparation of saliva samples and tongue swabs for nLC-MS/MS measurements and their bioinformatic analysis based on the Trans-Proteomic Pipeline and Prophane to study the oral microbiome .

Cyanobacterial blooms in wastewater treatment facilities: Significance and emerging monitoring strategies

Municipal wastewater treatment facilities (WWTFs) are prone to the proliferation of cyanobacterial species which thrive in stable, nutrient-rich environments. Dense cyanobacterial blooms frequently disrupt treatment processes and the supply of recycled water due to their production of extracellular polymeric substances, which hinder microfiltration, and toxins, which pose a health risk to end-users. A variety of methods are employed by water utilities for the identification and monitoring of cyanobacteria and their toxins in WWTFs, including microscopy, flow cytometry, ELISA, chemoanalytical methods, and more recently, molecular methods. Here we review the literature on the occurrence and significance of cyanobacterial blooms in WWTFs and discuss the pros and cons of the various strategies for monitoring these potentially hazardous events. Particular focus is directed towards next-generation metagenomic sequencing technologies for the development of site-specific cyanobacterial bloom management strategies. Long-term multi-omic observations will enable the identification of indicator species and the development of site-specific bloom dynamics models for the mitigation and management of cyanobacterial blooms in WWTFs. While emerging metagenomic tools could potentially provide deep insight into the diversity and flux of problematic cyanobacterial species in these systems, they should be considered a complement to, rather than a replacement of, quantitative chemoanalytical approaches.

Omics and interspecies interaction

Interspecies interactions are key determinants in biofilm behavior, ecology, and architecture. The cellular responses of microorganisms to each other at transcriptional, proteomic, and metabolomic levels ultimately determine the characteristics of biofilm and the corresponding implications for health and disease. Advances in omics technologies have revolutionized our understanding of microbial community composition and their activities as a whole. Large-scale analyses of the complex interaction between the many microbial species residing within a biofilm, however, are currently still hampered by technical and bioinformatics challenges. Thus, studies of interspecies interactions have largely focused on the transcriptional and proteomic changes that occur during the contact of a few prominent species, such as Porphyromonas gingivalis, Streptococcus mutans, Candida albicans, and a few others, with selected partner species. Expansion of available tools is necessary to grow the revealing, albeit limited, insight these studies have provided into a profound understanding of the nature of individual microbial responses to the presence of others. This will allow us to answer important questions including: Which intermicrobial interactions orchestrate the myriad of cooperative, synergistic, antagonistic, manipulative, and other types of relationships and activities in the complex biofilm environment, and what are the implications for oral health and disease?

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane

Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.g., due to the higher complexity of the samples and the larger reference databases demanding specific computing pipelines. Corresponding data analyses usually consist of numerous manual steps that must be closely synchronized. With MetaProteomeAnalyzer and Prophane, we have established two open-source software solutions specifically developed and optimized for metaproteomics. Among other features, peptide-spectrum matching is improved by combining different search engines and, compared to similar tools, metaproteome annotation benefits from the most comprehensive set of available databases (such as NCBI, UniProt, EggNOG, PFAM, and CAZy). The workflow described in this protocol combines both tools and leads the user through the entire data analysis process, including protein database creation, database search, protein grouping and annotation, and results visualization. To the best of our knowledge, this protocol presents the most comprehensive, detailed and flexible guide to metaproteomics data analysis to date. While beginners are provided with robust, easy-to-use, state-of-the-art data analysis in a reasonable time (a few hours, depending on, among other factors, the protein database size and the number of identified peptides and inferred proteins), advanced users benefit from the flexibility and adaptability of the workflow.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.

Rapid diagnosis of periodontitis, a feasibility study using MALDI-TOF mass spectrometry

AIM

The aim of the present study was to assess the feasibility and diagnostic contribution of protein profiling using MALDI-TOF mass spectrometry applied to saliva, gingival crevicular fluid (GCF) and dental plaque from periodontitis and healthy subjects. We hypothesized that rapid routine and blinded MALDI-TOF analysis could accurately classify these three types of samples according to periodontal state.

MATERIALS AND METHODS

Unstimulated saliva, GCF and dental plaque, collected from periodontitis subjects and healthy controls, were analyzed by MALDI-TOF MS. Based on the differentially expressed peaks between the two groups, diagnostic decision trees were built for each sample.

RESULTS

Among 141 patients (67 periodontitis and 74 healthy controls), the decision trees diagnosed periodontitis with a sensitivity = 70.3% (± 0.211) and a specificity = 77.8% (± 0.165) for saliva, a sensitivity = 79.6% (± 0.188) and a specificity = 75.7% (± 0.195) for GCF, and a sensitivity = 72.1% (± 0.202) and a specificity = 72.2% (± 0.195) for dental plaque. The sensitivity and specificity of the tests were improved to 100% (CI 95% = [0.91;1]) and 100% (CI 95% = [0.92;1]), respectively, when two samples were tested.

CONCLUSION

We developed, for the first time, diagnostic tests based on protein profiles of saliva, GCF and dental plaque between periodontitis patients and healthy subjects. When at least 2 of these samples were tested, the best results were obtained.

Technical Considerations and Protocol Optimization for Neonatal Salivary Biomarker Discovery and Analysis

Non-invasive techniques to monitor and diagnose neonates, particularly those born prematurely, are a long-sought out goal of Newborn Medicine. In recent years, technical advances, combined with increased assay sensitivity, have permitted the high-throughput analysis of multiple biomarkers simultaneously from a single sample source. Multiplexed transcriptomic and proteomic platforms, along with more comprehensive assays such as RNASeq, allow for interrogation of ongoing physiology and pathology in unprecedented ways. In the fragile neonatal population, saliva is an ideal biofluid to assess clinical status serially and offers many advantages over more invasively obtained blood samples. Importantly, saliva samples are amenable to analysis on emerging proteomic and transcriptomic platforms, even at quantitatively limited volumes. However, biomarker targets are often degraded in human saliva, and as a mixed source biofluid containing both human and microbial targets, saliva presents unique challenges for the investigator. Here, we provide insight into technical considerations and protocol optimizations developed in our laboratory to quantify and discover neonatal salivary biomarkers with improved reproducibility and reliability. We will detail insights learned from years of experimentation on neonatal saliva within our laboratory ranging from salivary collection techniques to processing to downstream analyses, highlighting the need for consistency in approach and a global understanding of both the potential benefits and limitations of neonatal salivary biomarker analyses. Importantly, we will highlight the need for robust and stringent research in this population to provide the field with standardized approaches and workflows to impact neonatal care successfully.