Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

High-throughput proteomic analysis of extracellular vesicles from saliva by chemical probe-based array

Extracellular vesicles (EVs) are cell-released, nucleus-free particles with a double-membrane structure that effectively prevents degradation of internal components by a variety of salivary enzymes. Saliva is an easily accessible biofluid that contains a wealth of valuable information for disease diagnosis and monitoring and especially reflect respiratory and digestive tract diseases. However, the lack of efficient and high-throughput methods for proteomic analysis of salivary biomarkers poses a significant challenge. Herein, we designed a salivary EV amphiphile-dendrimer supramolecular probe (SEASP) array which enables efficient enrichment and in situ detection of EVs protein biomarkers. Detergent Tween-20 washing of SEASP arrays removes high abundance of heteroproteins from saliva well. This array shows good analytical performance in the linear range of 10 μL-150 μL (LOD = 0.4 μg protein, or 10 μL saliva), exhibiting a good recovery (80.0 %). Compared to ultracentrifugation (UC), this procedure provides simple and convenient access to high-purity EVs (1.3 × 109 particles per mg protein) with good physiological status and structure. Coupling with mass spectrometry based proteomic analysis, differentially expressed proteins as selected asthma biomarkers have been screened. Then, we validated the proteomics primary screening results through clinical samples (100 μL each) using the SEASP array. Utilizing the dual antibody fluorescence technology, SEASP enables the simultaneous high-throughput detection of two proteins. Therefore, the EVs marker protein CD81 could be used as an internal standard to normalize the number of EVs, which was stably expressed in EVs. Proteomics and array results suggested that HNRNPU (P = 4.9 * 10-6) and MUC5B (P = 4.7 * 10-11) are promising protein biomarkers for infantile asthma. HNRNPU and MUC5B may be associated with disease onset and subtypes. The SEASP arrays provide a significant advancement in the field of salivary biomarker. The array enables high-throughput in situ protein detection for highly viscous and complex biological samples. It provides a rapid, low-cost, highly specific screening procedure and experimental basis for early disease screening and diagnosis in the field of liquid biopsy.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Description of a 'plankton filtration bias' in sequencing-based bacterial community analysis and of an Arduino microcontroller-based flowmeter device that can help to resolve it

Diversity studies of aquatic picoplankton (bacterioplankton) communities using size-class filtration, DNA extraction, PCR and sequencing of phylogenetic markers, require a robust methodological pipeline, since biases have been demonstrated essentially at all levels, including DNA extraction, primer choice and PCR. Even different filtration volumes of the same plankton sample and, thus, different biomass loading of the filters, can distort the sequencing results. In this study, we designed an Arduino microcontroller-based flowmeter that records the decrease of initial (maximal) flowrate as proxy for increasing biomass loading and clogging of filters during plankton filtration. The device was tested using freshwater plankton of Lake Constance, and total DNA was extracted and an 16S rDNA amplicon was sequenced. We confirmed that different filtration volumes used for the same water sample affect the sequencing results. Differences were visible in alpha and beta diversities and across all taxonomic ranks. Taxa most affected were typical freshwater Actinobacteria and Bacteroidetes, increasing up to 38% and decreasing up to 29% in relative abundance, respectively. In another experiment, a lake water sample was filtered undiluted and three-fold diluted, and each filtration was stopped once the flowrate had reduced to 50% of initial flowrate, hence, at the same degree of filter clogging. The three-fold diluted sample required three-fold filtration volumes, while equivalent amounts of total DNA were extracted and differences across all taxonomic ranks were not statistically significant compared to the undiluted controls. In conclusion, this work confirms a volume/biomass-dependent bacterioplankton filtration bias for sequencing-based community analyses and provides an improved procedure for controlling biomass loading during filtrations and recovery of equivalent amounts of DNA from samples independent of the plankton density. The application of the device can also avoid the distorting of sequencing results as caused by the plankton filtration bias.

Effect of Probiotic Supplements on the Oral Microbiota-A Narrative Review

Data from systematic reviews and meta-analyses show that probiotics positively impact clinical parameters of oral diseases such as gingivitis, dental caries, and periodontitis. However, the working mechanism of probiotics is not fully understood, but is hypothesized to be mediated by direct and indirect interactions with the oral microbiota and the human host. In the present narrative review, we focused on the microbiological effect of probiotic supplements based on data retrieved from randomized clinical trials (RCTs). In addition, we assessed to what extent contemporary molecular methods have been employed in clinical trials in the field of oral probiotics. Multiple RCTs have been performed studying the potential effect of probiotics on gingivitis, dental caries, and periodontitis, as evaluated by microbial endpoints. In general, results are conflicting, with some studies reporting a positive effect, whereas others are not able to record any effect. Major differences in terms of study designs and sample size, as well as delivery route, frequency, and duration of probiotic consumption, hamper comparison across studies. In addition, most RCTs have been performed with a limited sample size using relatively simple methods for microbial identification, such as culturing, qPCR, and DNA-DNA checkerboard, while high-throughput methods such as 16S sequencing have only been employed in a few studies. Currently, state-of-the-art molecular methods such as metagenomics, metatranscriptomics, and metaproteomics have not yet been used in RCTs in the field of probiotics. The present narrative review revealed that the effect of probiotic supplements on the oral microbiota remains largely uncovered. One important reason is that most RCTs are performed without studying the microbiological effect. To facilitate future systematic reviews and meta-analyses, an internationally agreed core outcome set for the reporting of microbial endpoints in clinical trials would be desirable. Such a standardized collection of outcomes would most likely improve the quality of probiotic research in the oral context.

Starch treatment improves the salivary proteome for subject identification purposes

Identification of subjects, including perpetrators, is one of the most crucial goals of forensic science. Saliva is among the most common biological fluids found at crime scenes, containing identifiable components. DNA has been the most prominent identifier to date, but its analysis can be complex due to low DNA yields and issues preserving its integrity at the crime scene. Proteins are emerging as viable candidates for subject identification. Previous work has shown that the salivary proteome of the least-abundant proteins may be helpful for subject identification, but more optimized techniques are needed. Among them is removing the most abundant proteins, such as salivary α-amylase. Starch treatment of saliva samples elicited the removal of this enzyme and that of glycosylated, low-molecular-weight proteins, proteases, and immunoglobulins, resulting in a saliva proteome profile enriched with a subset of proteins, allowing a more reliable and nuanced subject identification.

The enhancement mechanisms of mucin and lactoferrin on α-amylase activity in saliva: Exploring the interactions using QCM-D and molecular docking

α-Amylase activity differs between individuals and is influenced by dietary behavior and salivary constituents, but limited information is available on the relationship between α-amylase activity and saliva components. This study investigated the impact of salivary proteins on α-amylase activity, their various correlations, the effect of mucin (MUC5B and MUC7) and lactoferrin on the enzymatic kinetics of α-amylase, and the mechanisms of these interactions using the quartz crystal microbalance with dissipation (QCM-D) technique and molecular docking. The results showed that α-amylase activity was significantly correlated with the concentrations of MUC5B (R2 = 0.42, p < 0.05), MUC7 (R2 = 0.35, p < 0.05), and lactoferrin (R2 = 0.35, p < 0.05). An in vitro study demonstrated that α-amylase activity could be significantly increased by mucins and lactoferrin by decreasing the Michaelis constant (Km) of α-amylase. Moreover, the results from the QCM-D and molecule docking suggested that mucin and lactoferrin could interact with α-amylase to form stable α-amylase-mucin and α-amylase-lactoferrin complexes through hydrophobic interactions, electrostatic interactions, Van der Waals forces, and hydrogen bonds. In conclusion, these findings indicated that the salivary α-amylase activity depended not only on the α-amylase content, but also could be enhanced by the interactions of mucin/lactoferrin with α-amylase.

Different physicochemical interactions between varietal wines and human saliva: Correspondence with astringency

Astringency corresponds to the sensation of dryness and roughness that is experienced in the oral cavity in association with the interaction between salivary proteins and food polyphenols. In this study, the phenolic composition of seven varietal wines, the intensity of astringency they evoke and the physicochemical reactivity of these wines with whole human saliva were evaluated. Phenolic composition of wines was characterized by spectrophotometry and HPLC chromatography. Intensity of astringency was evaluated by trained sensory panels. Saliva from a single volunteer subject was used to assess wine-saliva interactions. To this end, binary mixtures were produced at different v/v wine/saliva ratios and each of them assayed for the ability of the salivary protein to diffuse on a cellulose membrane (diffusion test) and to remain in solution (precipitation test). Physicochemical reactivities between wine components and the protein fraction of saliva were contrasted against the astringency and the phenolic profile of each varietal wine. The study supports the view that astringency depends on physicochemical interactions between two complex matrices -wine and saliva- and not between some of their particular components.

Salivary proteomic profile of young healthy subjects

Background: The incidence of noncommunicable diseases (NCDs) has been rapidly ramped up worldwide. Hence, there is an urgent need to non-invasively detect NCDs possibly by exploiting saliva as a 'liquid biopsy' to identify biomarkers of the health status. Since, the absence of standardized procedures of collection/analysis and the lack of normal ranges makes the use of saliva still tricky, our purpose was to outline a salivary proteomic profile which features healthy individuals. Methods: We collected saliva samples from 19 young blood donors as reference population and the proteomic profile was investigated through mass-spectrometry. Results: We identified 1,004 proteins of whose 243 proteins were shared by all subjects. By applying a data clustering approach, we found a set of six most representative proteins across all subjects including Coronin-1A, F-actin-capping protein subunit alpha, Immunoglobulin J chain, Prosaposin, 78 kDa glucose-regulated protein and Heat shock 70 kDa protein 1A and 1B. Conclusion: All of these proteins are involved in immune system activation, cellular stress responses, proliferation, and invasion thus suggesting their use as biomarkers in patients with NCDs.

GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.

Elucidating regulatory processes of intense physical activity by multi-omics analysis

BACKGROUND

Physiological and biochemical processes across tissues of the body are regulated in response to the high demands of intense physical activity in several occupations, such as firefighting, law enforcement, military, and sports. A better understanding of such processes can ultimately help improve human performance and prevent illnesses in the work environment.

METHODS

To study regulatory processes in intense physical activity simulating real-life conditions, we performed a multi-omics analysis of three biofluids (blood plasma, urine, and saliva) collected from 11 wildland firefighters before and after a 45 min, intense exercise regimen. Omics profiles post- versus pre-exercise were compared by Student's t-test followed by pathway analysis and comparison between the different omics modalities.

RESULTS

Our multi-omics analysis identified and quantified 3835 proteins, 730 lipids and 182 metabolites combining the 3 different types of samples. The blood plasma analysis revealed signatures of tissue damage and acute repair response accompanied by enhanced carbon metabolism to meet energy demands. The urine analysis showed a strong, concomitant regulation of 6 out of 8 identified proteins from the renin-angiotensin system supporting increased excretion of catabolites, reabsorption of nutrients and maintenance of fluid balance. In saliva, we observed a decrease in 3 pro-inflammatory cytokines and an increase in 8 antimicrobial peptides. A systematic literature review identified 6 papers that support an altered susceptibility to respiratory infection.

CONCLUSION

This study shows simultaneous regulatory signatures in biofluids indicative of homeostatic maintenance during intense physical activity with possible effects on increased infection susceptibility, suggesting that caution against respiratory diseases could benefit workers on highly physical demanding jobs.

Cystatin SN (CST1) as a Novel Salivary Biomarker of Periodontitis

Identification of biomarkers could help in assessing periodontal health status and monitoring treatment outcomes. Therefore, the aim of this cross-sectional study was to identify potential innovative salivary biomarkers for the diagnosis of periodontitis using an untargeted proteomic approach. Forty-five healthy non-smoker participants diagnosed as having periodontally healthy conditions (H), severe periodontitis (P), and healthy but reduced periodontium after active periodontal treatment (T) were consecutively enrolled (15 per each group) in the study. A higher number of spots were identified in the proteome of unstimulated whole saliva collected from H and T subjects compared with P group, mainly within the range of 8-40 kDa. Protein spots of interest were analysed by MALDI-TOF-MS, allowing the identification of cystatin SN (CST1) isoform, as confirmed by Western blot. CST1 was markedly expressed in the H group, while it was absent in most P samples (p < 0.001). Interestingly, a distinct CST1 expression was observed in saliva from T patients. CST1 was negatively correlated with the percentage of pathological sites (p < 0.001) and was effective in discriminating active periodontitis from healthy periodontal status (whether H or T). Therefore, salivary CST1 may be a promising non-invasive biomarker for periodontal disease diagnosis and monitoring.

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.

Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.

Review Insights on Salivary Proteomics Biomarkers in Oral Cancer Detection and Diagnosis

Early detection is crucial for the treatment and prognosis of oral cancer, a potentially lethal condition. Tumor markers are abnormal biological byproducts produced by malignant cells that may be found and analyzed in a variety of bodily fluids, including saliva. Early detection and appropriate treatment can increase cure rates to 80-90% and considerably improve quality of life by reducing the need for costly, incapacitating medicines. Salivary diagnostics has drawn the interest of many researchers and has been proven to be an effective tool for both medication monitoring and the diagnosis of several systemic diseases. Since researchers are now searching for biomarkers in saliva, an accessible bodily fluid, for noninvasive diagnosis of oral cancer, measuring tumor markers in saliva is an interesting alternative to blood testing for early identification, post-treatment monitoring, and monitoring high-risk lesions. New molecular markers for oral cancer detection, treatment, and prognosis have been found as a result of developments in the fields of molecular biology and salivary proteomics. The numerous salivary tumor biomarkers and how they relate to oral cancer and pre-cancer are covered in this article. We are optimistic that salivary protein biomarkers may one day be discovered for the clinical detection of oral cancer because of the rapid advancement of proteomic technology.

The salivary proteome in relation to oral mucositis in autologous hematopoietic stem cell transplantation recipients: a labelled and label-free proteomics approach

BACKGROUND

Oral mucositis is a frequently seen complication in the first weeks after hematopoietic stem cell transplantation recipients which can severely affects patients quality of life. In this study, a labelled and label-free proteomics approach were used to identify differences between the salivary proteomes of autologous hematopoietic stem cell transplantation (ASCT) recipients developing ulcerative oral mucositis (ULC-OM; WHO score ≥ 2) or not (NON-OM).

METHODS

In the TMT-labelled analysis we pooled saliva samples from 5 ULC-OM patients at each of 5 timepoints: baseline, 1, 2, 3 weeks and 3 months after ASCT and compared these with pooled samples from 5 NON-OM patients. For the label-free analysis we analyzed saliva samples from 9 ULC-OM and 10 NON-OM patients at 6 different timepoints (including 12 months after ASCT) with Data-Independent Acquisition (DIA). As spectral library, all samples were grouped (ULC-OM vs NON-OM) and analyzed with Data Dependent Analysis (DDA). PCA plots and a volcano plot were generated in RStudio and differently regulated proteins were analyzed using GO analysis with g:Profiler.

RESULTS

A different clustering of ULC-OM pools was found at baseline, weeks 2 and 3 after ASCT with TMT-labelled analysis. Using label-free analysis, week 1-3 samples clustered distinctly from the other timepoints. Unique and up-regulated proteins in the NON-OM group (DDA analysis) were involved in immune system-related processes, while those proteins in the ULC-OM group were intracellular proteins indicating cell lysis.

CONCLUSIONS

The salivary proteome in ASCT recipients has a tissue protective or tissue-damage signature, that corresponded with the absence or presence of ulcerative oral mucositis, respectively.

TRIAL REGISTRATION

The study is registered in the national trial register (NTR5760; automatically added to the International Clinical Trial Registry Platform).

Feasibility of using a realistic food bolus for semi-dynamic in vitro gastric digestion of hard cheese with pH-stat monitoring of protein hydrolysis

Oral processing of solid foods leads to boluses made of a human saliva and particles distributed in the size range ∼ 0 to 5 mm. However, studies on the release of nutrients from realistic solid food boluses during digestion are scarce because such mechanisms are difficult to investigate in vivo, and in vitro experiments generally recommend to extensively mince solid foods during the oral stage. Similarly, it has previously been shown that the peptic hydrolysis of protein solutions during in vitro gastric digestion can be monitored by acid titration in both static and dynamic pH conditions, but such approach has never been evaluated in the presence of particles of several millimetres in size. The first objective of the study was therefore to test the feasibility of using a realistic food bolus for gastric digestion studies with a pH-stat monitoring of proteolysis, using Emmental cheese as a solid food and with consideration of gastric acidifying kinetics. Degree of hydrolysis (DH) of proteins was monitored from two series of experiments performed in the presence and absence of pepsin. Other DH measurements, estimated from an independent approach based on the amount of free NH₂ groups (OPA method) contained by peptides released in the supernatant (UV absorbance) validated the pH-stat results. A second objective of this work was to test the possible influence of human saliva on gastric proteolysis (in comparison with a water-based bolus). Results showed that saliva slightly delayed initiation of proteolysis, which could be explained by the slightly higher initial pH of the saliva-based bolus, but had no statistical effects on pepsin activity. We conclude that acid titration with a pH-stat system can be a valuable approach to monitor the gastric in vitro proteolysis of realistic solid food boluses in dynamic pH conditions.

A novel strategy for quantification of α2,3- and α2,6-linked sialic acids in sialylated glycoproteins

Sialic acid, a monosaccharide containing nine carbon atoms, is widely distributed in eukaryotic cells. The bound sialic acids are mainly present at the glycan ends of glycoconjugates via α2-3 or α2-6 glycosidic bonds, and alterations in their expression levels and linkage types are associated with the progress of many diseases and tumors. The present study provides a new strategy for quantification of α2,3- and α2,6-linked sialic acids in sialylated glycoproteins. In fact, quantification of α2,3-linked sialic acids were based on the difference of the bound sialic acids in the sample before and after treatment with α2-3 neuraminidase, whereas the α2,6-linked sialic acids were equal to the bound sialic acids in the α2-3 neuraminidase-treated sample. Subsequently, α2,3/6-linked sialic acids in salivary glycoproteins from healthy volunteers and diabetic patients were quantified in accordance with this method. This work provides an accurate method for the quantification of α2,3- and α2,6-linked sialic acids in the sialoglycoproteins, which is more instructive for understanding the biological roles of α2,3/6-linked sialic acid in sialoglycoproteins.

Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome

Dental caries is the most common chronic disease in children that causes negative effects on their health, development, and well-being. Early preventive interventions are key to reduce early childhood caries prevalence. An efficient strategy is to provide risk-based targeted prevention; however, this requires an accurate caries risk predictor, which is still lacking for infants before caries onset. We aimed to develop a caries prediction model based on the salivary microbiome of caries-free 1-y-old children. Using a nested case-control design within a prospective cohort study, we selected 30 children based on their caries status at 1-y follow-up (at 2 y old): 10 children who remained caries-free, 10 who developed noncavitated caries, and 10 who developed cavitated caries. Saliva samples collected at baseline before caries onset were analyzed through 16S rRNA gene sequencing. The results of β diversity analysis showed a significant difference in salivary microbiome composition between children who remained caries-free and those who developed cavitated caries at 2 y old (analysis of similarities, Benjamini-Hochberg corrected, P = 0.042). The relative abundance of Prevotella nanceiensis, Leptotrichia sp. HMT 215, Prevotella melaninogenica, and Campylobacter concisus in children who remained caries-free was significantly higher than in children who developed cavitated caries (Wilcoxon rank sum test, P = 0.024, 0.040, 0.049, and 0.049, respectively). These taxa were also identified as biomarkers for children who remained caries-free (linear discriminant analysis effect size, linear discriminant analysis score = 3.69, 3.74, 3.53, and 3.46). A machine learning model based on these 4 species distinguished between 1-y-old children who did and did not develop cavitated caries at 2 y old, with an accuracy of 80%, sensitivity of 80%, and specificity of 80% (area under the curve, 0.8; 95% CI, 44.4 to 97.5). Our findings suggest that these salivary microbial biomarkers could assist in predicting future caries in caries-free 1-y-old children and, upon validation, are promising for development into an adjunctive tool for caries risk prediction for prevention and monitoring.

Simulated annealing aided genetic algorithm for gene selection from microarray data

In recent times, microarray gene expression datasets have gained significant popularity due to their usefulness to identify different types of cancer directly through bio-markers. These datasets possess a high gene-to-sample ratio and high dimensionality, with only a few genes functioning as bio-markers. Consequently, a significant amount of data is redundant, and it is essential to filter out important genes carefully. In this paper, we propose the Simulated Annealing aided Genetic Algorithm (SAGA), a meta-heuristic approach to identify informative genes from high-dimensional datasets. SAGA utilizes a two-way mutation-based Simulated Annealing (SA) as well as Genetic Algorithm (GA) to ensure a good trade-off between exploitation and exploration of the search space, respectively. The naive version of GA often gets stuck in a local optimum and depends on the initial population, leading to premature convergence. To address this, we have blended a clustering-based population generation with SA to distribute the initial population of GA over the entire feature space. To further enhance the performance, we reduce the initial search space by a score-based filter approach called the Mutually Informed Correlation Coefficient (MICC). The proposed method is evaluated on 6 microarray and 6 omics datasets. Comparison of SAGA with contemporary algorithms has shown that SAGA performs much better than its peers. Our code is available at https://github.com/shyammarjit/SAGA.

Role of Insect and Mammal Glutathione Transferases in Chemoperception

Glutathione transferases (GSTs) are ubiquitous key enzymes with different activities as transferases or isomerases. As key detoxifying enzymes, GSTs are expressed in the chemosensory organs. They fulfill an essential protective role because the chemosensory organs are located in the main entry paths of exogenous compounds within the body. In addition to this protective function, they modulate the perception process by metabolizing exogenous molecules, including tastants and odorants. Chemosensory detection involves the interaction of chemosensory molecules with receptors. GST contributes to signal termination by metabolizing these molecules. By reducing the concentration of chemosensory molecules before receptor binding, GST modulates receptor activation and, therefore, the perception of these molecules. The balance of chemoperception by GSTs has been shown in insects as well as in mammals, although their chemosensory systems are not evolutionarily connected. This review will provide knowledge supporting the involvement of GSTs in chemoperception, describing their localization in these systems as well as their enzymatic capacity toward odorants, sapid molecules, and pheromones in insects and mammals. Their different roles in chemosensory organs will be discussed in light of the evolutionary advantage of the coupling of the detoxification system and chemosensory system through GSTs.

Qualitative and Quantitative Mass Spectrometry in Salivary Metabolomics and Proteomics

The metabolomics and proteomics analysis of saliva, an excellent biofluid that is a rich source of biological compounds, allows for the safe and frequent screening of drugs, their metabolites, and molecular biomarkers of various diseases. One of the most frequently used analytical methods in saliva analysis is liquid chromatography coupled with mass spectrometry (LC-MS) and tandem mass spectrometry. The low ionisation efficiency of some compounds and a complex matrix makes their identification by MS difficult. Furthermore, quantitative analysis by LC-MS frequently cannot be performed without isotopically labelled standards, which usually have to be specially synthesised. This review presented reports on qualitative and quantitative approaches in salivary metabolomics and proteomics. The purpose of this manuscript was to present the challenges, advances, and future prospects of mass spectrometry, both in the analysis of salivary metabolites and proteins. The presented review should appeal to those interested in the recent advances and trends in qualitative and quantitative mass spectrometry in salivary metabolomics and proteomics, which may facilitate a diagnostic accuracy, the evaluation of treatment efficacy, the early diagnosis of disease, and a forensic investigation of some unapproved drugs for any medical or dietary administration.

Top-Down Proteomics Detection of Potential Salivary Biomarkers for Autoimmune Liver Diseases Classification

(1) Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases characterized by chronic hepatic inflammation and progressive liver fibrosis. The possible use of saliva as a diagnostic tool has been explored in several oral and systemic diseases. The use of proteomics for personalized medicine is a rapidly emerging field. (2) Salivary proteomic data of 36 healthy controls (HCs), 36 AIH and 36 PBC patients, obtained by liquid chromatography/mass spectrometry top-down pipeline, were analyzed by multiple Mann-Whitney test, Kendall correlation, Random Forest (RF) analysis and Linear Discriminant Analysis (LDA); (3) Mann-Whitney tests provided indications on the panel of differentially expressed salivary proteins and peptides, namely cystatin A, statherin, histatin 3, histatin 5 and histatin 6, which were elevated in AIH patients with respect to both HCs and PBC patients, while S100A12, S100A9 short, cystatin S1, S2, SN and C showed varied levels in PBC with respect to HCs and/or AIH patients. RF analysis evidenced a panel of salivary proteins/peptides able to classify with good accuracy PBC vs. HCs (83.3%), AIH vs. HCs (79.9%) and PBC vs. AIH (80.2%); (4) RF appears to be an attractive machine-learning tool suited for classification of AIH and PBC based on their different salivary proteomic profiles.

Proteomic Identification of Saliva Proteins as Noninvasive Diagnostic Biomarkers

Many biomedically relevant biomarkers are proteins with characteristic biochemical properties and a relatively restricted subcellular distribution. The comparative and mass spectrometry-based proteomic analysis of body fluids can be particularly instrumental for the targeted identification of novel protein biomarkers with pathological relevance. In this respect, new research efforts in biomarker discovery focus on the systematic mapping of the human saliva proteome, as well as the pathobiochemical identification of disease-related modifications or concentration changes in specific saliva proteins. As a product of exocrine secretion, saliva can be considered an ideal source for the biochemical identification of new disease indicators. Importantly, saliva represents a body fluid that is continuously available for diagnostic and prognostic assessments. This chapter gives an overview of saliva proteomics, including a discussion of the usefulness of both liquid chromatography and two-dimensional gel electrophoresis for efficient protein separation in saliva proteomics.

Proteins in Tumor-Derived Plasma Extracellular Vesicles Indicate Tumor Origin

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor.

Intraglandular mesenchymal stem cell treatment induces changes in the salivary proteome of irradiated patients

BACKGROUND

Hyposalivation and xerostomia (dry mouth), are the leading site-effects to treatment of head and neck cancer. Currently, there are no effective therapies to alleviate radiation-induced hyposalivation. Adipose tissue-derived mesenchymal stem/stromal cells (AT-MSCs) have shown potential for restoring salivary gland function. However, the mode of action is unknown. The purpose of the present study was therefore to characterize the effect of AT-MSC therapy on the salivary proteome in previously irradiated head and neck cancer patients.

METHODS

Whole saliva was collected from patients with radiation-induced salivary gland hypofunction (n = 8) at baseline, and 120 days after AT-MSC treatment, and from healthy controls (n = 10). The salivary proteome was characterized with mass spectrometry based proteomics, and data was compared within the AT-MSC group (baseline versus day 120) and between AT-MSC group and healthy controls. Significance levels between groups were determined by using double-sided t-test, and visualized by means of principal component analysis, volcano plots and cluster analysis.

RESULTS

Here we show that 140 human proteins are significantly differentially expressed in saliva from patients with radiation-induced hypofunction versus healthy controls. AT-MSC treatment induce a significant impact on the salivary proteome, as 99 proteins are differentially expressed at baseline vs. 120 days after treatment. However, AT-MSC treatment does not restore healthy conditions, as 212 proteins are significantly differentially expressed in saliva 120 days after AT-MSCs treatment, as compared to healthy controls.

CONCLUSION

The results indicate an increase in proteins related to tissue regeneration in AT-MSCs treated patients. Our study demonstrates the impact of AT-MSCs on the salivary proteome, thereby providing insight into the potential mode of action of this novel treatment approach.

Salivary inflammatory biomarkers are predictive of mild cognitive impairment and Alzheimer's disease in a feasibility study

Alzheimer's disease (AD) is an insidious disease. Its distinctive pathology forms over a considerable length of time without symptoms. There is a need to detect this disease, before even subtle changes occur in cognition. Hallmark AD biomarkers, tau and amyloid-β, have shown promising results in CSF and blood. However, detecting early changes in these biomarkers and others will involve screening a wide group of healthy, asymptomatic individuals. Saliva is a feasible alternative. Sample collection is economical, non-invasive and saliva is an abundant source of proteins including tau and amyloid-β. This work sought to extend an earlier promising untargeted mass spectrometry study in saliva from individuals with mild cognitive impairment (MCI) or AD with age- and gender-matched cognitively normal from the South Australian Neurodegenerative Disease cohort. Five proteins, with key roles in inflammation, were chosen from this study and measured by ELISA from individuals with AD (n = 16), MCI (n = 15) and cognitively normal (n = 29). The concentrations of Cystatin-C, Interleukin-1 receptor antagonist, Stratifin, Matrix metalloproteinase 9 and Haptoglobin proteins had altered abundance in saliva from AD and MCI, consistent with the earlier study. Receiver operating characteristic analysis showed that combinations of these proteins demonstrated excellent diagnostic accuracy for distinguishing both MCI (area under curve = 0.97) and AD (area under curve = 0.97) from cognitively normal. These results provide evidence for saliva being a valuable source of biomarkers for early detection of cognitive impairment in individuals on the AD continuum and potentially other neurodegenerative diseases.

The interplay between oral microbes and immune responses

Oral microbes play a critical role in maintaining oral homeostasis. Microbial dysbiosis promotes disease pathogenesis through several mechanisms. Recent studies have revealed that microbial imbalance and sustained inflammation are involved in disease progression. The adverse interaction triggered by a host immune response to microorganisms can lead to oral and systemic diseases. Here, we reviewed how oral microbes communicate with hosts during the development of local and distant inflammation. Elucidation of these processes may reveal future directions in this field and the potential targets of novel biological therapies for oral and systemic diseases.

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.

A rapid and non-invasive proteomic analysis using DBS and buccal swab for multiplexed second-tier screening of Pompe disease and Mucopolysaccharidosis type I

PURPOSE

Current newborn screening programs for Pompe disease (PD) and mucopolysaccharidosis type I (MPS I) suffer from a high false positive rate and long turnaround time for clinical follow up. This study aimed to develop a novel proteomics-based assay for rapid and accurate second-tier screening of PD and MPS I. A fast turnaround assay would enable the identification of severe cases who need immediate clinical follow up and treatment.

METHODS

We developed an immunocapture coupled with mass spectrometry-based proteomics (Immuno-SRM) assay to quantify GAA and IDUA proteins in dried blood spots (DBS) and buccal swabs. Sensitivity, linearity, reproducibility, and protein concentration range in healthy control samples were determined. Clinical performance was evaluated in known PD and MPS I patients as well as pseudodeficiency and carrier cases.

RESULTS

Using three 3.2 mm punches (~13.1 μL of blood) of DBS, the assay showed reproducible and sensitive quantification of GAA and IDUA. Both proteins can also be quantified in buccal swabs with high reproducibility and sensitivity. Infantile onset Pompe disease (IOPD) and severe MPS I cases are readily identifiable due to the absence of GAA and IDUA, respectively. In addition, late onset Pompe disease (LOPD) and attenuated MPS I patients showed much reduced levels of the target protein. By contrast, pseudodeficiency and carrier cases exhibited significant higher target protein levels compared to true patients.

CONCLUSION

Direct quantification of endogenous GAA and IDUA peptides in DBS by Immuno-SRM can be used for second-tier screening to rapidly identify severe PD and MPS I patients with a turnaround time of <1 week. Such patients could benefit from immediate clinical follow up and possibly earlier treatment.

Discovery, validation, and diagnostic ability of multiple protein-based biomarkers in saliva and gingival crevicular fluid to distinguish between health and periodontal diseases

Aim

To discover and validate differential protein biomarker expression in saliva and gingival crevicular fluid (GCF) to discriminate objectively between periodontal health and plaque‐induced periodontal disease states.

Materials and Methods

One‐hundred and ninety participants were recruited from two centres (Birmingham and Newcastle upon Tyne, UK) comprising healthy, gingivitis, periodontitis, and edentulous donors. Samples from the Birmingham cohort were analysed by quantitative mass spectrometry proteomics for biomarker discovery. Shortlisted candidate proteins were then verified by enzyme‐linked immunosorbent assay in both cohorts. Leave‐one‐out cross validation logistic regression analysis was used to identify the best performing biomarker panels.

Results

Ninety‐five proteins were identified in both GCF and saliva samples, and 15 candidate proteins were selected based upon differences discovered between the donor groups. The best performing panels to distinguish between: health or gingivitis and periodontitis contained matrix metalloproteinase‐9 (MMP9), S100A8, alpha‐1‐acid glycoprotein (A1AGP), pyruvate kinase, and age (area under the curve [AUC] 0.970); health and gingivitis contained MMP9, S100A8, A1AGP, and pyruvate kinase, but not age (AUC 0.768); and mild to moderate and advanced periodontitis contained MMP9, S100A8, A1AGP, pyruvate kinase, and age (AUC 0.789).

Conclusions

Biomarker panels containing four proteins with and without age as a further parameter can distinguish between periodontal health and disease states.

Integrated N-glycoproteomics Analysis of Human Saliva for Lung Cancer

Aberrant protein N-glycosylation is a cancer hallmark, which has great potential for cancer detection. However, large-scale and in-depth analysis of N-glycosylation remains challenging because of its high heterogeneity, complexity, and low abundance. Human saliva is an attractive diagnostic body fluid, while few efforts explored its N-glycoproteome for lung cancer. Here, we utilized a zwitterionic-hydrophilic interaction chromatography-based strategy to specifically enrich salivary glycopeptides. Through quantitative proteomics analysis, 1492 and 1234 intact N-glycopeptides were confidently identified from pooled saliva samples of 10 subjects in the nonsmall-cell lung cancer group and 10 subjects in the normal control group. Accordingly, 575 and 404 N-glycosites were revealed for the lung cancer group and normal control group. In particular, 154 N-glycosites and 259 site-specific glycoforms were significantly dysregulated in the lung cancer group. Several N-glycosites located at the same glycoprotein and glycans attached to the same N-glycosites were observed with differential expressions, including haptoglobin, Mucin-5B, lactotransferrin, and α-1-acid glycoprotein 1. These N-glycoproteins were mainly related to inflammatory responses, infectious diseases, and cancers. Our study achieved comprehensive characterization of salivary N-glycoproteome, and dysregulated site-specific glycoforms hold promise for noninvasive detection of lung cancer.

Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era

Despite significant healthcare advances in the 21st century, the exact etiology of dental caries remains unsolved. The past two decades have witnessed a tremendous growth in our understanding of dental caries amid the advent of revolutionary omics technologies. Accordingly, a consensus has been reached that dental caries is a community-scale metabolic disorder, and its etiology is beyond a single causative organism. This conclusion was based on a variety of microbiome studies following the flow of information along the central dogma of biology from genomic data to the end products of metabolism. These studies were facilitated by the unprecedented growth of the next- generation sequencing tools and omics techniques, such as metagenomics and metatranscriptomics, to estimate the community composition of oral microbiome and its functional potential. Furthermore, the rapidly evolving proteomics and metabolomics platforms, including nuclear magnetic resonance spectroscopy and/or mass spectrometry coupled with chromatography, have enabled precise quantification of the translational outcomes. Although the majority supports ‘conserved functional changes’ as indicators of dysbiosis, it remains unclear how caries dynamics impact the microbiota functions and vice versa, over the course of disease onset and progression. What compounds the situation is the host-microbiota crosstalk. Genome-wide association studies have been undertaken to elucidate the interaction of host genetic variation with the microbiome. However, these studies are challenged by the complex interaction of host genetics and environmental factors. All these complementary approaches need to be orchestrated to capture the key players in this multifactorial disease. Herein, we critically review the milestones in caries research focusing on the state-of-art singular and integrative omics studies, supplemented with a bibliographic network analysis to address the oral microbiome, the host factors, and their interactions. Additionally, we highlight gaps in the dental literature and shed light on critical future research questions and study designs that could unravel the complexities of dental caries, the most globally widespread disease.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Mass Spectrometry Approaches for SARS-CoV-2 Detection: Harnessing for Application in Food and Environmental Samples

The public health crisis caused by the emergence of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in 2019 has drastically changed our lifestyle in virtually all contexts around the world. SARS-CoV-2 is mainly airborne, transmitted by the salivary droplets produced when infected people cough or sneeze. In addition, diarrhea symptoms and the detection of SARS-CoV-2 in feces suggest a fecal–oral route of contagion. Currently, the high demand for SARS-CoV-2 diagnosis has surpassed the availability of PCR and immunodetection probes and has prompted the development of other diagnostic alternatives. In this context, mass spectrometry (MS) represents a mature, robust alternative platform for detection of SARS-CoV-2 and other human viruses. This possibility has raised great interest worldwide. Therefore, it is time for the global application of MS as a feasible option for detecting SARS-CoV-2, not only in human fluids, but also in other matrices such as foods and wastewater. This review covers the most relevant established methods for MS-based SARS-CoV-2 detection and discusses the future application of these tools in different matrices. Significance: The Coronavirus Disease 2019 (COVID-19) pandemic highlighted the pros and cons of currently available PCR and immunodetection tools. The great concern over the infective potential of SARS-CoV-2 viral particles that can persist for several hours on different surfaces under various conditions further evidenced the need for reliable alternatives and high-throughput methods to meet the needs for mass detection of SARS-CoV-2. In this context, MS-based proteomics emerging from fundamental studies in life science can offer a robust option for SARS-CoV-2 detection in human fluids and other matrices. In addition, the substantial efforts towards detecting SARS-CoV-2 in clinal samples, position MS to support the detection of this virus in different matrices such as the surfaces of the packing food process, frozen foods, and wastewaters. Proteomics and mass spectrometry are, therefore, well positioned to play a role in the epidemiological control of COVID-19 and other future diseases. We are currently witnessing the opportunity to generate technologies to overcome prolonged pandemics for the first time in human history.

Evaluation of the Suitability of Dried Saliva Spots for In-Depth Proteome Analyses for Clinical Applications

Previously, we performed nontargeted proteome analysis using dried blood spots (DBSs) that are widely used in newborn screening for the clinical diagnosis of congenital genetic diseases and immunodeficiency. We have developed an efficient and simple pretreatment method for DBSs that can detect more than 1000 proteins. To complement proteins that are difficult to detect via DBS analysis with less invasive alternative body fluids, we conducted this study to investigate the proteins detected from dried saliva spots (DSSs) using single-shot LC-MS/MS, which is practical in clinical settings. We also clarified whether DSSs have the same advantages as DBSs, and we investigated the influence of saliva collection conditions and the storage environment on their protein profile. As a result, we detected approximately 5000 proteins in DSSs and whole saliva, and we concluded that they were sufficient to complement the proteins lacking in the blood analysis. DSSs could be used as an alternative tool to DBSs for detecting the presence of causative proteins.

Novel impacts of saliva with regard to oral health

The maintenance of balanced oral homeostasis depends on saliva. A readily available and molecularly rich source of biological fluid, saliva fulfills many functions in the oral cavity, including lubrication, pH buffering, and tooth mineralization. Saliva composition and flow can be modulated by different factors, including circadian rhythm, diet, age, drugs, and disease. Recent events have revealed that saliva plays a central role in the dissemination and detection of the SARS-CoV-2 coronavirus. A working knowledge of saliva function and physiology is essential for dental health professionals.

MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19

Background

Methods

Results

Conclusion

An integrated workflow for enhanced taxonomic and functional coverage of the mouse fecal metaproteome

Intestinal microbiota plays a key role in shaping host homeostasis by regulating metabolism, immune responses and behavior. Its dysregulation has been associated with metabolic, immune and neuropsychiatric disorders and is accompanied by changes in bacterial metabolic regulation. Although proteomics is well suited for analysis of individual microbes, metaproteomics of fecal samples is challenging due to the physical structure of the sample, presence of contaminating host proteins and coexistence of hundreds of taxa. Furthermore, there is a lack of consensus regarding preparation of fecal samples, as well as downstream bioinformatic analyses following metaproteomics data acquisition. Here we assess sample preparation and data analysis strategies applied to mouse feces in a typical mass spectrometry-based metaproteomic experiment. We show that subtle changes in sample preparation protocols may influence interpretation of biological findings. Two-step database search strategies led to significant underestimation of false positive protein identifications. Unipept software provided the highest sensitivity and specificity in taxonomic annotation of the identified peptides of unknown origin. Comparison of matching metaproteome and metagenome data revealed a positive correlation between protein and gene abundances. Notably, nearly all functional categories of detected protein groups were differentially abundant in the metaproteome compared to what would be expected from the metagenome, highlighting the need to perform metaproteomics when studying complex microbiome samples.

Salivary anti-nuclear antibody (ANA) mirrors serum ANA in systemic lupus erythematosus

OBJECTIVES

To assay salivary anti-nuclear antibody (ANA) and its isotypes in patients with systemic lupus erythematosus (SLE) and to investigate relevant clinical associations.

METHODS

Saliva samples were collected from SLE patients and assayed for salivary ANA using immunofluorescence (IF). Isotypes of salivary ANA, including IgG-ANA, IgA-ANA, and IgM-ANA, were quantified using enzyme-linked immunosorbent assay. The correlations between clinical parameters and levels of salivary ANA and isotypes were evaluated.

RESULTS

Salivary ANA IF intensities were significantly higher in SLE patients than in healthy controls, irrespective of SLE patient disease activity, and strongly correlated with serum ANA titers. Salivary ANA was detected in 67.14% of SLE patients and 10.00% of healthy controls (p < 0.001). Among ANA-positive samples, 80.85% exhibited a nuclear ANA pattern, and 42.55% exhibited a cytoplasmic ANA pattern. Salivary IgG-ANA, IgA-ANA, and IgM-ANA levels, as assayed by ELISA, were significantly increased in both active and less active SLE patients compared with healthy controls, and levels of each isotype were significantly correlated with serum ANA titer. Salivary IgM-ANA levels correlated with the physician global assessment (PGA), SLE disease activity index (SLEDAI), and negatively with serum C3 and C4. Salivary IgG-ANA also correlated with erythrocyte sedimentation rate (ESR), SLEDAI, and negatively with serum C3.

CONCLUSION

Salivary ANA levels correlate with serum ANA titer, and salivary IgM-ANA and IgG-ANA correlate variably with PGA, SLEDAI, ESR and complement levels. These findings underscore the potential of using salivary ANA and ANA isotypes as surrogates for serum ANA, particularly for future point-of-care applications since saliva is easier to obtain than blood.

Recent advances in mass-spectrometry based proteomics software, tools and databases

The field of proteomics immensely depends on data generation and data analysis which are thoroughly supported by software and databases. There has been a massive advancement in mass spectrometry-based proteomics over the last 10 years which has compelled the scientific community to upgrade or develop algorithms, tools, and repository databases in the field of proteomics. Several standalone software, and comprehensive databases have aided the establishment of integrated omics pipeline and meta-analysis workflow which has contributed to understand the disease pathobiology, biomarker discovery and predicting new therapeutic modalities. For shotgun proteomics where Data Dependent Acquisition is performed, several user-friendly software are developed that can analyse the pre-processed data to provide mechanistic insights of the disease. Likewise, in Data Independent Acquisition, pipelines are emerged which can accomplish the task from building the spectral library to identify the therapeutic targets. Furthermore, in the age of big data analysis the implications of machine learning and cloud computing are appending robustness, rapidness and in-depth proteomics data analysis. The current review talks about the recent advancement, and development of software, tools, and database in the field of mass-spectrometry based proteomics.

Salivary Proteome Profile of Women during Fertile Phase of Menstrual Cycle as Characterized by Mass Spectrometry

Objectives:

Ovulation is such a critical physiological process that its noninvasive detection based on salivary constituents has several advantages in humans. Hence, the present study is proposed to identify the ovulatory-specific proteins in saliva in order to detect ovulation phase.

Materials and Methods:

Samples were collected from women volunteers. The procedure adopted was approved by the Institutional Human Ethical Committee (DM/2014/101/38), Bharathidasan University. The saliva samples were collected from thirty healthy female volunteers, with a prior written consent. One-way analysis of variance was used to calculate protein concentration and band intensity using SPSS 16 software (SPSS Inc., Cary, NC, USA). The salivary protein expression pattern during different phases of menstrual cycle was analyzed using gel-based high resolution-liquid chromatography-mass spectrometry/mass spectrometry and matrix-assisted laser desorption ionization-time of flight/time of flight. Further, bioinformatics tools were adopted to annotate the proteins identified at various phases of menstrual cycle.

Results:

As many as 530 proteins showed up in the saliva during ovulatory phase, whereas there were only 251 proteins identified during postovulatory phase. The functional annotation of salivary proteins revealed that the proteins got assigned to the class of “extracellular proteins” which are concerned with regulatory functions. The 16 unique and/or differentially expressed protein spots appeared during ovulatory phase, among which Cystatin-S, Prolactin-inducible protein, Cystatin-A, Cystatin-SN, BPI fold-containing family A member 2, Alpha-tubulin N-acetyltransferase 1, Carbonic anhydrase-6, Protein LEG1 homolog, Hemoglobin subunit beta, and Pancreatic alpha-amylase were identified.

Conclusion:

Total salivary proteome profile has been listed with respect to various phases of menstrual cycle. Among the protein listed, Cystatin-S offers a biomarker protein and/or indicator of ovulatory phase. However, extensive validation is required before arriving to a candidate bio-marker protein.

Viral Inactivation Impacts Microbiome Estimates in a Tissue-Specific Manner

The global emergence of novel pathogenic viruses presents an important challenge for research, as high biosafety levels are required to process samples. While inactivation of infectious agents facilitates the use of less stringent safety conditions, its effect on other biological entities of interest present in the sample is generally unknown. Here, we analyzed the effect of five inactivation methods (heat, ethanol, formaldehyde, psoralen, and TRIzol) on microbiome composition and diversity in samples collected from four different body sites (gut, nasal, oral, and skin) and compared them against untreated samples from the same tissues. We performed 16S rRNA gene sequencing and estimated abundance and diversity of bacterial taxa present in all samples. Nasal and skin samples were the most affected by inactivation, with ethanol and TRIzol inducing the largest changes in composition, and heat, formaldehyde, TRIzol, and psoralen inducing the largest changes in diversity. Oral and stool microbiomes were more robust to inactivation, with no significant changes in diversity and only moderate changes in composition. Firmicutes was the taxonomic group least affected by inactivation, while Bacteroidetes had a notable enrichment in nasal samples and moderate enrichment in fecal and oral samples. Actinobacteria were more notably depleted in fecal and skin samples, and Proteobacteria exhibited a more variable behavior depending on sample type and inactivation method. Overall, our results demonstrate that inactivation methods can alter the microbiome in a tissue-specific manner and that careful consideration should be given to the choice of method based on the sample type under study. IMPORTANCE Understanding how viral infections impact and are modulated by the microbiome is an important problem in basic research but is also of high clinical relevance under the current pandemic. To facilitate the study of interactions between microbial communities and pathogenic viruses under safe conditions, the infectious agent is generally inactivated prior to processing samples. The effect of this inactivation process in the microbiome is, however, unknown. Further, it is unclear whether biases introduced by inactivation methods are dependent on the sample type under study. Estimating the magnitude and nature of the changes induced by different methods in samples collected from various body sites thus provides important information for current and future studies that require inactivation of pathogenic agents.

Using Cartesian Doubt To Build a Sequencing-Based View of Microbiology

The technological leap of DNA sequencing generated a tension between modern metagenomics and historical microbiology. We are forcibly harmonizing the output of a modern tool with centuries of experimental knowledge derived from culture-based microbiology. As a thought experiment, we borrow the notion of Cartesian doubt from philosopher Rene Descartes, who used doubt to build a philosophical framework from his incorrigible statement that "I think therefore I am." We aim to cast away preconceived notions and conceptualize microorganisms through the lens of metagenomic sequencing alone. Specifically, we propose funding and building analysis and engineering methods that neither search for nor rely on the assumption of independent genomes bound by lipid barriers containing discrete functional roles and taxonomies. We propose that a view of microbial communities based in sequencing will engender novel insights into metagenomic structure and may capture functional biology not reflected within the current paradigm.

Functional Diversity within Gut Microbiomes: Implications for Conserving Biodiversity

Conservation research has historically been conducted at the macro level, focusing on animals and plants and their role in the wider ecosystem. However, there is a growing appreciation of the importance of microbial communities in conservation. Most microbiome research in conservation thus far has used amplicon sequencing methods to assess the taxonomic composition of microbial communities and inferred functional capabilities from these data. However, as manipulation of the microbiome as a conservation tool becomes more and more feasible, there is a growing need to understand the direct functional consequences of shifts in microbiome composition. This review outlines the latest advances in microbiome research from a functional perspective and how these data can be used to inform conservation strategies. This review will also consider some of the challenges faced when studying the microbiomes of wild animals and how they can be overcome by careful study design and sampling methods. Environmental changes brought about by climate change or direct human actions have the potential to alter the taxonomic composition of microbiomes in wild populations. Understanding how taxonomic shifts affect the function of microbial communities is important for identifying species most threatened by potential disruption to their microbiome. Preservation or even restoration of these functions has the potential to be a powerful tool in conservation biology and a shift towards functional characterisation of gut microbiome diversity will be an important first step.

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

Oral enzymatic detoxification system: Insights obtained from proteome analysis to understand its potential impact on aroma metabolization

The oral cavity is an entry path into the body, enabling the intake of nutrients but also leading to the ingestion of harmful substances. Thus, saliva and oral tissues contain enzyme systems that enable the early neutralization of xenobiotics as soon as they enter the body. Based on recently published oral proteomic data from several research groups, this review identifies and compiles the primary detoxification enzymes (also known as xenobiotic-metabolizing enzymes) present in saliva and the oral epithelium. The functions and the metabolic activity of these enzymes are presented. Then, the activity of these enzymes in saliva, which is an extracellular fluid, is discussed with regard to the salivary parameters. The next part of the review presents research evidencing oral metabolization of aroma compounds and the putative involved enzymes. The last part discusses the potential role of these enzymatic reactions on the perception of aroma compounds in light of recent pieces of evidence of in vivo oral metabolization of aroma compounds affecting their release in mouth and their perception. Thus, this review highlights different enzymes appearing as relevant to explain aroma metabolism in the oral cavity. It also points out that further works are needed to unravel the effect of the oral enzymatic detoxification system on the perception of food flavor in the context of the consumption of complex food matrices, while considering the impact of food oral processing. Thus, it constitutes a basis to explore these biochemical mechanisms and their impact on flavor perception.

Stimulated saliva composition in patients with cancer of the head and neck region

BACKGROUND

To analyse over time changes in stimulated whole saliva regarding total protein, Immunoglobulin A (IgA), and mucin type O-glycans (mostly MUC5B and MUC7) in head and neck cancer patients.

METHODS

29 dentate patients (20 men and 9 women, 59 ± 8 years) treated with curative radiation therapy and chemotherapy for cancer of the head and neck region were included. The stimulated whole salivary secretion rate was determined and saliva collected at four time-points: at pretreatment, and at 6 months, 1 and 2 years post treatment. The total protein concentration was determined spectrophotometrically by using Bicinchoninic Acid assay and Immunoglobulin A (IgA) by using ELISA technique. Glycosylation pattern of salivary mucins was determined in samples collected pre- and post treatment by using LC/MS electrospray and mucin content quantified using SDS-AgPAGE gels and PAS staining.

RESULTS

Compared with pretreatment, the total protein concentration was increased already at 6 months post treatment (p < 0.01), and continued to increase up to 2 years post treatment (p < 0.001). During that period no significant changes in IgA concentration was detected. At pretreatment, the output/min of both total protein and IgA was significantly higher than at all time-points post treatment. Saliva from the cancer patients showed a low abundance/no detectable MUC7, while the MUC5B level remained, compared to saliva from a healthy control. The glycomic analysis showed that the percentage of core 2 O-glycans was increased as core 1, 3 and 4 O-glycans were decreased. The level of sialylation was higher at 6 months post treatment, while sulfation was lower.

CONCLUSION

A decreased output per minute of proteins at decreased salivary secretion rate, as well as reduced sulfation of MUC5B at 6 months post treatment tended to correlate with the patients' experience of sticky saliva and oral dryness. At 2 years post treatment, the decreased amount of IgA combined with a lowered salivary secretion rate indicate a reduced oral defense with increased risk of oral infections.

Taxonomic and Functional Dysregulation in Salivary Microbiomes During Oral Carcinogenesis

Exploring microbial community compositions in humans with healthy versus diseased states is crucial to understand the microbe-host interplay associated with the disease progression. Although the relationship between oral cancer and microbiome was previously established, it remained controversial, and yet the ecological characteristics and their responses to oral carcinogenesis have not been well studied. Here, using the bacterial 16S rRNA gene amplicon sequencing along with the in silico function analysis by PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2), we systematically characterized the compositions and the ecological drivers of saliva microbiome in the cohorts of orally healthy, non-recurrent oral verrucous hyperplasia (a pre-cancer lesion), and oral verrucous hyperplasia–associated oral cancer at taxonomic and function levels, and compared them with the re-analysis of publicly available datasets. Diversity analyses showed that microbiome dysbiosis in saliva was significantly linked to oral health status. As oral health deteriorated, the number of core species declined, and metabolic pathways predicted by PICRUSt2 were dysregulated. Partitioned beta-diversity revealed an extremely high species turnover but low function turnover. Functional beta-diversity in saliva microbiome shifted from turnover to nestedness during oral carcinogenesis, which was not observed at taxonomic levels. Correspondingly, the quantitative analysis of stochasticity ratios showed that drivers of microbial composition and functional gene content of saliva microbiomes were primarily governed by the stochastic processes, yet the driver of functional gene content shifted toward deterministic processes as oral cancer developed. Re-analysis of publicly accessible datasets supported not only the distinctive family taxa of Veillonellaceae and Actinomycetaceae present in normal cohorts but also that Flavobacteriaceae and Peptostreptococcaceae as well as the dysregulated metabolic pathways of nucleotides, amino acids, fatty acids, and cell structure were related to oral cancer. Using predicted functional profiles to elucidate the correlations to the oral health status shows superior performance than using taxonomic data among different studies. These findings advance our understanding of the oral ecosystem in relation to oral carcinogenesis and provide a new direction to the development of microbiome-based tools to study the interplay of the oral microbiome, metabolites, and host health.