A dynamic range compression and three-dimensional peptide fractionation analysis platform expands proteome coverage and the diagnostic potential of whole saliva

Comparisons of Whole Saliva and Cell Free Saliva by DIA-Based Proteome Profiling

BACKGROUND

Saliva has emerged as a promising diagnostic resource due to its accessibility, noninvasiveness, and repeatability, enabling early disease detection and timely intervention. However, current studies often overlook the distinction between whole saliva (WS) and cell-free saliva (CFS). Objective This study aims to compare the proteomic profiles of WS and CFS.

METHOD AND RESULT

The saliva was detected with and without low-abundance protein enrichment using nanoparticles, employing DIA-MS technology. Our findings reveal a substantial enhancement in the detectability of low-abundance proteins in saliva with utilization of nanoparticles, enabling identification of 12%-15% low-abundance proteins previously undetectable in WS or CFS. In total, 3817 saliva proteins were identified, with 3413 found in WS and 2340 in CFS. More interestingly, we found that it was not the similarity of the samples that did the clustering, but rather it depended more on the different detection methods and sample types. And the predominant functions of the identified proteins in WS were related to oxidative phosphorylation and neurodegenerations, whereas those in CFS were primarily associated with nitrogen and glycosaminoglycan metabolism. And both exhibited functions in immune response and proteasome.

CONCLUSION

This study represents the first comparison of WS and CFS, providing valuable experimental evidence for guiding the selection of research subjects in future saliva omics studies.

E. coli-expressed SECRET AGENT O-GlcNAc modifies threonine 829 of GIGANTEA

The Arabidopsis thaliana glycosyl transferases SPINDLY (SPY) and SECRET AGENT (SEC) modify nuclear and cytosolic proteins with O-linked fucose or O-linked N-acetylglucosamine (O-GlcNAc), respectively. O-fucose and O-GlcNAc modifications can occur at the same sites. SPY interacts physically and genetically with GIGANTEA (GI), suggesting that it could be modified by both enzymes. Previously, we found that, when co-expressed in Escherichia coli, SEC modifies GI; however, the modification site was not determined. By analyzing the overlapping sub-fragments of GI, we identified a region that was modified by SEC in E. coli. Modification was undetectable when threonine 829 (T829) was mutated to alanine, while the T834A and T837A mutations reduced the modification, suggesting that T829 was the primary or the only modification site. Mapping using mass spectrometry detected only the modification of T829. Previous studies have shown that the positions modified by SEC in E. coli are modified in planta, suggesting that T829 is O-GlcNAc modified in planta.

Saliva Based Diagnostic Prediction of Oral Squamous Cell Carcinoma using FTIR Spectroscopy

Oral cancer ranks as the sixth most prevalent form of cancer worldwide, presenting a significant public health concern. According to the World Health Organization (WHO), within a 5-year period following diagnosis, the mortality rate among oral cancer patients of all stages stands at 45%. In this study, a total of 60 patients divided into 2 groups were recruited. Group A included 30 histo-pathologically confirmed OSCC patients and Group B included 30 healthy controls. A standardized procedure was followed to collect saliva samples. FTIR spectroscopy was done for all the saliva samples collected from both Group A and B. An IR Prestige-21 (Shimadzu Corp, Japan) spectrometer was used to record IR spectra in the 40-4000 cm-1 range SVM classifier was applied in the classification of disease state from normal subjects using FTIR data. The peaks were identified at wave no 1180 cm-1, 1230 cm-1, 1340 cm-1, 1360 cm-1, 1420 cm-1, 1460 cm-1, 1500 cm-1, 1540 cm-1, 1560 cm-1, and 1637 cm-1. The observed results of SVM demonstrated the accuracy of 91.66% in the classification of Cancer tissues from the normal subjects with sensitivity of 83.33% while specificity and precision of 100.0%. The development of oral cancer leads to noticeable alterations in the secondary structure of proteins. These findings emphasize the promising use of ATR-FTIR platforms in conjunction with machine learning as a reliable, non-invasive, reagent-free, and highly sensitive method for screening and monitoring individuals with oral cancer.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Proteomic Analysis of Salivary Extracellular Vesicles from COVID-19 Patients Reveals a Specific Anti-COVID-19 Response Protein Signature

Despite the understanding of the coronavirus disease-19 (COVID-19), the role of salivary extracellular vesicles (sEVs) in COVID-19 remains unclear. Exploring the proteomic cargo of sEVs could prove valuable for diagnostic and prognostic purposes in assessing COVID-19. The proteomic cargo of sEVs from COVID-19(+) subjects and their healthy close contacts (HCC) was explored. sEVs were isolated by ultracentrifugation from unstimulated saliva samples, and subsequently characterized through nanoparticle tracking, transmission electron microscopy, and Western blot analyses. The proteomic cargo of sEVs was processed by LC-MS/MS. sEVs were morphologically compatible with EVs, with the presence of Syntenin-1 and CD81 EV markers. The sEV pellet showed 1417 proteins: 1288 in COVID-19(+) cases and 1382 in HCC. In total, 124 proteins were differentially expressed in sEVs from COVID-19(+) subjects. "Coronavirus-disease response", "complement and coagulation cascades", and "PMN extracellular trap formation" were the most enriched KEGG pathways in COVID-19(+) cases. The most represented biological processes were "Hemoglobin and haptoglobin binding" and "oxygen carrier activity", and the best-denoted molecular functions were "regulated exocytosis and secretion" and "leucocyte and PMN mediated immunity". sEV proteomic cargo in COVID-19(+) suggests activity related to immune response processes, oxygen transport, and antioxidant mechanisms. In contrast, in HCC, sEV signature profiles are mainly associated with epithelial homeostasis.

A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls

Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.

Advances in Research on Pig Salivary Analytes: A Window to Reveal Pig Health and Physiological Status

Saliva is an important exocrine fluid that is easy to collect and is a complex mixture of proteins and other molecules from multiple sources from which considerable biological information can be mined. Pig saliva, as an easily available biological liquid rich in bioactive ingredients, is rich in nucleic acid analytes, such as eggs, enzymes, amino acids, sugars, etc. The expression levels of these components in different diseases have received extensive attention, and the analysis of specific proteins, metabolites, and biological compositions in pig saliva has become a new direction for disease diagnosis and treatment. The study of the changes in analytes in pig saliva can provide a new strategy for early diagnosis, prognosis assessment, and treatment of diseases. In this paper, the detection methods and research progress of porcine salivary analytes are reviewed, the application and research progress of porcine salivary analytes in diseases are discussed, and the future application prospect is presented.

Identification of the Major Protein Components of Human and Cow Saliva

Cows produce saliva in very large quantities to lubricate and facilitate food processing. Estimates indicate an amount of 50-150 L per day. Human saliva has previously been found to contain numerous antibacterial components, such as lysozyme, histatins, members of the S-100 family and lactoferrin, to limit pathogen colonization. Cows depend on a complex microbial community in their digestive system for food digestion. Our aim here was to analyze how this would influence the content of their saliva. We therefore sampled saliva from five humans and both nose secretions and saliva from six cows and separated the saliva on SDS-PAGE gradient gels and analyzed the major protein bands with LC-MS/MS. The cow saliva was found to be dominated by a few major proteins only, carbonic anhydrase 6, a pH-stabilizing enzyme and the short palate, lung and nasal epithelium carcinoma-associated protein 2A (SPLUNC2A), also named bovine salivary protein 30 kDa (BSP30) or BPIFA2B. This latter protein has been proposed to play a role in local antibacterial response by binding bacterial lipopolysaccharides (LPSs) and inhibiting bacterial growth but may instead, according to more recent data, primarily have surfactant activity. Numerous peptide fragments of mucin-5B were also detected in different regions of the gel in the MS analysis. Interestingly, no major band on gel was detected representing any of the antibacterial proteins, indicating that cows may produce them at very low levels that do not harm the microbial flora of their digestive system. The nose secretions of the cows primarily contained the odorant protein, a protein thought to be involved in enhancing the sense of smell of the olfactory receptors and the possibility of quickly sensing potential poisonous food components. High levels of secretory IgA were also found in one sample of cow mouth drippings, indicating a strong upregulation during an infection. The human saliva was more complex, containing secretory IgA, amylase, carbonic anhydrase 6, lysozyme, histatins and a number of other less abundant proteins, indicating a major difference to the saliva of cows that show very low levels of antibacterial components, most likely to not harm the microbial flora of the rumen.

Point-of-Care Disease Screening in Primary Care Using Saliva: A Biospectroscopy Approach for Lung Cancer and Prostate Cancer

Saliva is a largely unexplored liquid biopsy that can be readily obtained noninvasively. Not dissimilar to blood plasma or serum, it contains a vast array of bioconstituents that may be associated with the absence or presence of a disease condition. Given its ease of access, the use of saliva is potentially ideal in a point-of-care screening or diagnostic test. Herein, we developed a swab "dip" test in saliva obtained from consenting patients participating in a lung cancer-screening programme being undertaken in north-west England. A total of 998 saliva samples (31 designated as lung-cancer positive and 17 as prostate-cancer positive) were taken in the order in which they entered the clinic (i.e., there was no selection of participants) during the course of this prospective screening programme. Samples (sterile Copan blue rayon swabs dipped in saliva) were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. In addition to unsupervised classification on resultant infrared (IR) spectra using principal component analysis (PCA), a range of feature selection/extraction algorithms were tested. Following preprocessing, the data were split between training (70% of samples, 22 lung-cancer positive versus 664 other) and test (30% of samples, 9 lung-cancer positive versus 284 other) sets. The training set was used for model construction and the test set was used for validation. The best model was the PCA-quadratic discriminant analysis (QDA) algorithm. This PCA-QDA model was built using 8 PCs (90.4% of explained variance) and resulted in 93% accuracy for training and 91% for testing, with clinical sensitivity at 100% and specificity at 91%. Additionally, for prostate cancer patients amongst the male cohort (n = 585), following preprocessing, the data were split between training (70% of samples, 12 prostate-cancer positive versus 399 other) and test (30% of samples, 5 prostate-cancer positive versus 171 other) sets. A PCA-QDA model, again the best model, was built using 5 PCs (84.2% of explained variance) and resulted in 97% accuracy for training and 93% for testing, with clinical sensitivity at 100% and specificity at 92%. These results point to a powerful new approach towards the capability to screen large cohorts of individuals in primary care settings for underlying malignant disease.

A Catalog of Coding Sequence Variations in Salivary Proteins' Genes Occurring during Recent Human Evolution

Saliva houses over 2000 proteins and peptides with poorly clarified functions, including proline-rich proteins, statherin, P-B peptides, histatins, cystatins, and amylases. Their genes are poorly conserved across related species, reflecting an evolutionary adaptation. We searched the nucleotide substitutions fixed in these salivary proteins' gene loci in modern humans compared with ancient hominins. We mapped 3472 sequence variants/nucleotide substitutions in coding, noncoding, and 5'-3' untranslated regions. Despite most of the detected variations being within noncoding regions, the frequency of coding variations was far higher than the general rate found throughout the genome. Among the various missense substitutions, specific substitutions detected in PRB1 and PRB2 genes were responsible for the introduction/abrogation of consensus sequences recognized by convertase enzymes that cleave the protein precursors. Overall, these changes that occurred during the recent human evolution might have generated novel functional features and/or different expression ratios among the various components of the salivary proteome. This may have influenced the homeostasis of the oral cavity environment, possibly conditioning the eating habits of modern humans. However, fixed nucleotide changes in modern humans represented only 7.3% of all the substitutions reported in this study, and no signs of evolutionary pressure or adaptative introgression from archaic hominins were found on the tested genes.

Salivary Cystatin D Interactome in Patients with Systemic Mastocytosis: An Exploratory Study

Mastocytosis, a rare blood disorder characterized by the proliferation of clonal abnormal mast cells, has a variegated clinical spectrum and diagnosis is often difficult and delayed. Recently we proposed the cathepsin inhibitor cystatin D-R26 as a salivary candidate biomarker of systemic mastocytosis (SM). Its C26 variant is able to form multiprotein complexes (mPCs) and since protein-protein interactions (PPIs) are crucial for studying disease pathogenesis, potential markers, and therapeutic targets, we aimed to define the protein composition of the salivary cystatin D-C26 interactome associated with SM. An exploratory affinity purification-mass spectrometry method was applied on pooled salivary samples from SM patients, SM patient subgroups with and without cutaneous symptoms (SM+C and SM-C), and healthy controls (Ctrls). Interactors specifically detected in Ctrls were found to be implicated in networks associated with cell and tissue homeostasis, innate system, endopeptidase regulation, and antimicrobial protection. Interactors distinctive of SM-C patients participate to PPI networks related to glucose metabolism, protein S-nitrosylation, antibacterial humoral response, and neutrophil degranulation, while interactors specific to SM+C were mainly associated with epithelial and keratinocyte differentiation, cytoskeleton rearrangement, and immune response pathways. Proteins sensitive to redox changes, as well as proteins with immunomodulatory properties and activating mast cells, were identified in patients; many of them were involved directly in cytoskeleton rearrangement, a process crucial for mast cell activation. Although preliminary, these results demonstrate that PPI alterations of the cystatin D-C26 interactome are associated with SM and provide a basis for future investigations based on quantitative proteomic analysis and immune validation.

Saliva diagnostics: Salivaomics, saliva exosomics, and saliva liquid biopsy

BACKGROUND

Each day, humans produce approximately 0.5 through 1.5 liters of saliva, a biofluid that is rich in biological omic constituents. Our lack of understanding how omic biomarkers migrate from diseased tissue to the saliva has impeded the clinical translation of saliva testing. Although such biomarkers must be conveyed via the vascular and lymphatic systems to the salivary glands, the molecular mechanisms that underlie this transport remain unclear. Although COVID-19 highlighted the need for rapid and reliable testing for infectious diseases, it represents only one of the many health conditions that potentially can be diagnosed using a saliva sample.

TYPES OF STUDIES REVIEWED

The authors discuss salivaomics, saliva exosomics, and the mechanisms on which saliva diagnostics are based and introduce a novel electrochemical sensing technology that may be exploited for saliva liquid biopsy.

RESULTS

The utility of saliva for screening for lung cancer is under investigation. Saliva testing may be used to stratify patients, monitor treatment response, and detect disease recurrence. The authors also highlight the landscapes of saliva-based SARS-CoV-2 testing and ultrashort cell-free DNA and outline how these fields are likely to evolve in the near future.

PRACTICAL IMPLICATIONS

Breakthroughs in the study of saliva research, therefore, will facilitate clinical deployment of saliva-based testing.

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.

Chronic exposure to multiple stressors alters the salivary proteome of piglets

Monitoring chronic stress in pigs is not only essential in view of animal welfare but is also important for the farmer, given that stress influences the zootechnical performance of the pigs and increases their susceptibility to infectious diseases. To investigate the use of saliva as a non-invasive, objective chronic stress monitoring tool, twenty-four 4-day-old piglets were transferred to artificial brooders. At the age of 7 days, they were assigned to either the control or the stressed group and reared for three weeks. Piglets in the stressed group were exposed to overcrowding, absence of cage enrichment, and frequent mixing of animals between pens. Shotgun analysis using an isobaric labelling method (iTRAQ) for tandem mass spectrometry performed on saliva samples taken after three weeks of chronic stress identified 392 proteins, of which 20 proteins displayed significantly altered concentrations. From these 20 proteins, eight were selected for further validation using parallel reaction monitoring (PRM). For this validation, saliva samples that were taken one week after the start of the experiment and samples that were taken at the end of the experiment were analysed to verify the profile over time. We wanted to investigate whether the candidate biomarkers responded fast or rather slowly to the onset of chronic exposure to multiple stressors. Furthermore, this validation could indicate whether age influenced the baseline concentrations of these salivary proteins, both in healthy and stressed animals. This targeted PRM analysis confirmed that alpha-2-HS-glycoprotein was upregulated in the stressed group after one and three weeks, while odorant-binding protein, chitinase, long palate lung and nasal epithelium protein 5, lipocalin-1, and vomeromodulin-like protein were present in lower concentrations in the saliva of the stressed pigs, albeit only after three weeks. These results indicate that the porcine salivary proteome is altered by chronic exposure to multiple stressors. The affected proteins could be used as salivary biomarkers to identify welfare problems at the farm and facilitate research to optimise rearing conditions.

Surface-Enhanced Raman Analysis of Uric Acid and Hypoxanthine Analysis in Fractionated Bodily Fluids

In recent years, the disease burden of hyperuricemia has been increasing, especially in high-income countries and the economically developing world with a Western lifestyle. Abnormal levels of uric acid and hypoxanthine are associated with many diseases, and therefore, to demonstrate improved methods of uric acid and hypoxanthine detection, three different bodily fluids were analysed using surface-enhanced Raman spectroscopy (SERS) and high-performance liquid chromatography (HPLC). Gold nanostar suspensions were mixed with series dilutions of uric acid and hypoxanthine, 3 kDa centrifugally filtered human blood serum, urine and saliva. The results show that gold nanostars enable the quantitative detection of the concentration of uric acid and hypoxanthine in the range 5-50 μg/mL and 50-250 ng/mL, respectively. The peak areas of HPLC and maximum peak intensity of SERS have strongly correlated, notably with the peaks of uric acid and hypoxanthine at 1000 and 640 cm^-1, respectively. The r² is 0.975 and 0.959 for uric acid and hypoxanthine, respectively. Each of the three body fluids has a number of spectral features in common with uric acid and hypoxanthine. The large overlap of the spectral bands of the SERS of uric acid against three body fluids at spectra peaks were at 442, 712, 802, 1000, 1086, 1206, 1343, 1436 and 1560 cm^-1. The features at 560, 640, 803, 1206, 1290 and 1620 cm^-1 from hypoxanthine were common to serum, saliva and urine. There is no statistical difference between HPLC and SERS for determination of the concentration of uric acid and hypoxanthine (p > 0.05). For clinical applications, 3 kDa centrifugal filtration followed by SERS can be used for uric acid and hypoxanthine screening is, which can be used to reveal the subtle abnormalities enhancing the great potential of vibrational spectroscopy as an analytical tool. Our work supports the hypnosis that it is possible to obtain the specific concentration of uric acid and hypoxanthine by comparing the SER signals of serum, saliva and urine. In the future, the analysis of other biofluids can be employed to detect biomarkers for the diagnosis of systemic pathologies.

Salivary Biglycan-neo-epitope-BGN262: a novel surrogate biomarker for equine osteoarthritic sub-chondral bone sclerosis and to monitor the effect of short-term training and surface arena

Objective

We aimed to delineate a novel soluble Biglycan Neo-epitope-BGN262 in saliva from young reference and osteoarthritic horses in conjunction with the influence of short-term training exercise, riding surface hardness, circadian rhythm, and feeding on its soluble levels.

Design

A custom-made inhibition ELISA was used for the quantification of BGN262 in saliva. Cohort 1: A cross-sectional study comprising reference (N ​= ​19) and OA horses (N ​= ​9) with radiographically classified subchondral bone sclerosis. Receiver operating characteristic curve analysis was performed to evaluate the robustness of BGN262. Cohorts 2 (N ​= ​5) & 3 (N ​= ​7): Longitudinal studies of sampling during a short-term training exercise (sand-fibre) and a cross-over design of short-training exercise on 2 different riding arenas (sand and sand-fibre), respectively. Capillary western immunoassay was used to determine the BGN262 molecular size in a selection of saliva samples collected from cohort 1.

Results

Cohort 1: Salivary BGN262 levels were significantly higher in the OA group. The Receiver operating characteristic curve analysis showed an area under the curve of 0.8304 [0.6386 to 1.022], indicating a good separation from the reference group. Cohorts 2 & 3: Salivary BGN262 levels significantly changed during the exercise on sand and sand-fibre arena, with a trend towards higher levels for sand-fibre. The size of the BGN262 fragment determined by Capillary western assay was 18 ​kDa.

Conclusions

The data presented show saliva BGN262 levels as a novel biomarker in evaluating the influence of exercise, and interaction with riding arenas alongside assessing osteoarthritis severity.

Quantitative analysis of fucosylated glycoproteins by immobilized lectin-affinity fluorescent labeling

Human biofluids are often used to discover disease-specific glycosylation, since abnormal changes in protein glycosylation can discern physiopathological states. Highly glycosylated proteins in biofluids make it possible to identify disease signatures. Glycoproteomic studies on saliva glycoproteins showed that fucosylation was significantly increased during tumorigenesis and that glycoproteins became hyperfucosylated in lung metastases, and tumor stage is associated with fucosylation. Quantification of salivary fucosylation can be achieved by mass spectrometric analysis of fucosylated glycoproteins or fucosylated glycans; however, the use of mass spectrometry is non-trivial for clinical practice. Here, we developed a high-throughput quantitative method, lectin-affinity fluorescent labeling quantification (LAFLQ), to quantify fucosylated glycoproteins without relying on mass spectrometry. Lectins with a specific affinity for fucoses are immobilized on the resin and effectively capture fluorescently labeled fucosylated glycoproteins, which are further quantitatively characterized by fluorescence detection in a 96-well plate. Our results demonstrated that serum IgG can be accurately quantified by lectin and fluorescence detection. Quantification in saliva showed significantly higher fucosylation in lung cancer patients compared to healthy controls or other non-cancer diseases, suggesting that this method has the potential to quantify stage-related fucosylation in lung cancer saliva.

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.

Saliva Diagnostics

Cancer remains one of the leading causes of death, and early detection of this disease is crucial for increasing survival rates. Although cancer can be diagnosed following tissue biopsy, the biopsy procedure is invasive; liquid biopsy provides an alternative that is more comfortable for the patient. While blood, urine, and cerebral spinal fluid can all be used as a source of liquid biopsy, saliva is an ideal source of body fluid that is readily available and easily collected in the most noninvasive manner. Characterization of salivary constituents in the disease setting provides critical data for understanding pathophysiology and the evaluation of diagnostic potential. The aim of saliva diagnostics is therefore to develop a rapid and noninvasive detection of oral and systemic diseases that could be used together with compact analysis systems in the clinic to facilitate point-of-care diagnostics.

The Microbiome in Periodontitis and Diabetes

Objectives

To perform a comprehensive and integrative review of the available literature on the potential changes in the microbiome of healthy and individuals with diabetes under periodontal health and disease.

Materials and Methods

The review was conducted by two independent reviewers. Indexed electronic databases (PubMed/Medline, Cochrane Library, Web of Science and Scopus) were searched, including articles published in English and dated from 5 years ago until December 2021. A manual search also was performed to identify co-related articles. Following the removal of duplicates and eligibility criteria, the articles were included in tables for analysis and described in the manuscript.

Results

According to this review, diabetes mellitus was associated with significant changes in the subgingival and salivary microbiome, either in its association with periodontitis or in cases of periodontal health. In addition to affecting microbial diversity in terms of taxonomy, metagenomic studies have shown that this endocrine disorder may also be directly related to increased pathogenicity in the oral microbiome.

Conclusion

Although the reviewed studies demonstrate important differences in the subgingival and salivary microbiome composition because of diabetes mellitus, further studies are needed to clarify the real effects of hyperglycemia on oral microbial profiles and support new diagnostic approaches and innovative treatments.

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 long-term antibiofilm effect of a surface coating with dual functionality of antibacterial and protein-repellent effects

The provision of antibacterial properties to resinous restorative/reconstructive materials by incorporating polymerizable bactericides such as 12-methacryloyloxydodecylpyridinium bromide (MDPB) has been attempted. Previously, MDPB was combined with 2-methacryloyloxyethyl phosphorylcholine (MPC) to fabricate a copolymer coating to increase antibacterial effectiveness by protein repelling. In this study, we assessed the longevity of the protein-repelling, antibacterial, and antibiofilm effects of the MDPB-MPC copolymer. After 28 days of water immersion, MPC-containing copolymers exhibited lower adsorption of bovine serum albumin and salivary proteins; after 24 h of incubation, MDPB-containing copolymers demonstrated antibacterial effects against Streptococcus mutans. The copolymer containing both MDPB and MPC showed thinner biofilm formation with a higher percentage of membrane-compromised bacteria than control. The results were consistent with those before aging, indicating the long-lasting antibacterial, protein-repellent, and antibiofilm effects of this copolymer. The durable copolymer developed in this study can be applied to dental resins to control bacteria in the oral environment.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

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.

SecProCT: In Silico Prediction of Human Secretory Proteins Based on Capsule Network and Transformer

Identifying secretory proteins from blood, saliva or other body fluids has become an effective method of diagnosing diseases. Existing secretory protein prediction methods are mainly based on conventional machine learning algorithms and are highly dependent on the feature set from the protein. In this article, we propose a deep learning model based on the capsule network and transformer architecture, SecProCT, to predict secretory proteins using only amino acid sequences. The proposed model was validated using cross-validation and achieved 0.921 and 0.892 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively. Meanwhile, the proposed model was validated on an independent test set and achieved 0.917 and 0.905 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively, which are better than conventional machine learning methods and other deep learning methods for biological sequence analysis. The main contributions of this article are as follows: (1) a deep learning model based on a capsule network and transformer architecture is proposed for predicting secretory proteins. The results of this model are better than the those of existing conventional machine learning methods and deep learning methods for biological sequence analysis; (2) only amino acid sequences are used in the proposed model, which overcomes the high dependence of existing methods on the annotated protein features; (3) the proposed model can accurately predict most experimentally verified secretory proteins and cancer protein biomarkers in blood and saliva.

Liquid Biopsy: A Family of Possible Diagnostic Tools

Liquid biopsies could be considered an excellent diagnostic tool, in different physiological or pathological conditions. The possibility of using liquid biopsies for non-invasive clinical purposes is quite an old idea: indeed many years ago it was already being used in the field of non-invasive prenatal tests (NIPT) for autosomal fetal aneuploidy evaluation. In 1997 Lo et al. had identified fetal DNA in maternal plasma and serum, showing that about 10–15% of cfDNA in maternal plasma is derived from the placenta, and biologic fluid represents an important and non-invasive technique to evaluate state diseases and possible therapies. Nowadays, several body fluids, such as blood, urine, saliva and other patient samples, could be used as liquid biopsy for clinical non-invasive evaluation. These fluids contain numerous and various biomarkers and could be used for the evaluation of pathological and non-pathological conditions. In this review we will analyze the different types of liquid biopsy, their potential role in clinical diagnosis and the functional involvement of extracellular vesicles in these fluids as carriers.

Clinical Proteomics of Biofluids in Haematological Malignancies

Since the emergence of high-throughput proteomic techniques and advances in clinical technologies, there has been a steady rise in the number of cancer-associated diagnostic, prognostic, and predictive biomarkers being identified and translated into clinical use. The characterisation of biofluids has become a core objective for many proteomic researchers in order to detect disease-associated protein biomarkers in a minimally invasive manner. The proteomes of biofluids, including serum, saliva, cerebrospinal fluid, and urine, are highly dynamic with protein abundance fluctuating depending on the physiological and/or pathophysiological context. Improvements in mass-spectrometric technologies have facilitated the in-depth characterisation of biofluid proteomes which are now considered hosts of a wide array of clinically relevant biomarkers. Promising efforts are being made in the field of biomarker diagnostics for haematologic malignancies. Several serum and urine-based biomarkers such as free light chains, β-microglobulin, and lactate dehydrogenase are quantified as part of the clinical assessment of haematological malignancies. However, novel, minimally invasive proteomic markers are required to aid diagnosis and prognosis and to monitor therapeutic response and minimal residual disease. This review focuses on biofluids as a promising source of proteomic biomarkers in haematologic malignancies and a key component of future diagnostic, prognostic, and disease-monitoring applications.

Saliva based non invasive screening of Oral Submucous Fibrosis using ATR-FTIR spectroscopy

Oral Submucous Fibrosis (OSMF) is a type of precancerous condition of Oral cancer and considered to have the greatest malignant potential. Biopsy is an ultimate option for the conformation of the malignancy. But the invasiveness of the procedure makes it interdict. Therefore, there is an urgent need to identify effective screening and diagnostic methods which would be less invasive, rapid, more accurate and cost effective. Here, we used Attenuated Total Reflection- Fourier transform infrared spectroscopy (ATR-FTIR) with Chemometric analysis coupled with estimation of total salivary protein to discriminate OSMF and Healthy Control (HC). The present study showed the specific Infrared spectrum for OSMF patients, which was specifically differentiated from HC based on the spectral shift of proteins/amide II, carbohydrate and nucleic acid using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) with small data sets. ATR-FTIR spectroscopy of saliva coupled with total protein estimation can be used to discriminate between OSMF and HC. However, large sample size should be needed to evaluate the ATR-FTIR for consideration as a screening tool for an early diagnosis OSMF.

The Human Salivary Proteome Wiki: A Community-Driven Research Platform

Saliva has become an attractive body fluid for on-site, remote, and real-time monitoring of oral and systemic health. At the same time, the scientific community needs a saliva-centered information platform that keeps pace with the rapid accumulation of new data and knowledge by annotating, refining, and updating the salivary proteome catalog. We developed the Human Salivary Proteome (HSP) Wiki as a public data platform for researching and retrieving custom-curated data and knowledge on the saliva proteome. The HSP Wiki is dynamically compiled and updated based on published saliva proteome studies and up-to-date protein reference records. It integrates a wide range of available information by funneling in data from established external protein, genome, transcriptome, and glycome databases. In addition, the HSP Wiki incorporates data from human disease-related studies. Users can explore the proteome of saliva simply by browsing the database, querying the available data, performing comparisons of data sets, and annotating existing protein entries using a simple, intuitive interface. The annotation process includes both user feedback and curator committee review to ensure the quality and validity of each entry. Here, we present the first overview of features and functions the HSP Wiki offers. As a saliva proteome-centric, publicly accessible database, the HSP Wiki will advance the knowledge of saliva composition and function in health and disease for users across a wide range of disciplines. As a community-based data- and knowledgebase, the HSP Wiki will serve as a worldwide platform to exchange salivary proteome information, inspire novel research ideas, and foster cross-discipline collaborations. The HSP Wiki will pave the way for harnessing the full potential of the salivary proteome for diagnosis, risk prediction, therapy of oral and systemic diseases, and preparedness for emerging infectious diseases.Database URL: https://salivaryproteome.nidcr.nih.gov/.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Longitudinal saliva omics responses to immune perturbation: a case study

Saliva omics has immense potential for non-invasive diagnostics, including monitoring very young or elderly populations, or individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over three periods (100 timepoints) involving: (1) hourly sampling over 24 h without intervention, (2) hourly sampling over 24 h including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (3) daily sampling for 33 days profiling the post-vaccination response. At each timepoint total saliva transcriptome and proteome, and small RNA from salivary extracellular vesicles were profiled, including mRNA, miRNA, piRNA and bacterial RNA. The two 24-h periods were used in a paired analysis to remove daily variation and reveal vaccination responses. Over 18,000 omics longitudinal series had statistically significant temporal trends compared to a healthy baseline. Various immune response and regulation pathways were activated following vaccination, including interferon and cytokine signaling, and MHC antigen presentation. Immune response timeframes were concordant with innate and adaptive immunity development, and coincided with vaccination and reported fever. Overall, mRNA results appeared more specific and sensitive (timewise) to vaccination compared to other omics. The results suggest saliva omics can be consistently assessed for non-invasive personalized monitoring and immune response diagnostics.

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 comparison between the structures of reconstituted salivary pellicles and oral mucin (MUC5B) films

HYPOTHESIS

Salivary pellicles i.e., thin films formed upon selective adsorption of saliva, protect oral surfaces against chemical and mechanical insults. Pellicles are also excellent aqueous lubricants. It is generally accepted that reconstituted pellicles have a two-layer structure, where the outer layer is mainly composed of MUC5B mucins. We hypothesized that by comparing the effect of ionic strength on reconstituted pellicles and MUC5B films we could gain further insight into the pellicle structure.

EXPERIMENTS

Salivary pellicles and MUC5B films reconstituted on solid surfaces were investigated at different ionic strengths by Force Spectroscopy, Quartz Crystal Microbalance with Dissipation, Null Ellipsometry and Neutron Reflectometry.

FINDINGS

Our results support the two-layer structure for reconstituted salivary pellicles. The outer layer swelled when ionic strength decreased, indicating a weak polyelectrolyte behavior. While initially the MUC5B films exhibited a similar tendency, this was followed by a drastic collapse indicating an interaction between exposed hydrophobic domains. This suggests that mucins in the pellicle outer layer form complexes with other salivary components that prevent this interaction. Lowering ionic strength below physiological values also led to a partial removal of the pellicle inner layer. Overall, our results highlight the importance that the interactions of mucins with other pellicle components play on their structure.

Agonists of Orally Expressed TRP Channels Stimulate Salivary Secretion and Modify the Salivary Proteome

Natural compounds that can stimulate salivary secretion are of interest in developing treatments for xerostomia, the perception of a dry mouth, that affects between 10 and 30% of the adult and elderly population. Chemesthetic transient receptor potential (TRP) channels are expressed in the surface of the oral mucosa. The TRPV1 agonists capsaicin and piperine have been shown to increase salivary flow when introduced into the oral cavity but the sialogogic properties of other TRP channel agonists have not been investigated. In this study we have determined the influence of different TRP channel agonists on the flow and protein composition of saliva. Mouth rinsing with the TRPV1 agonist nonivamide or menthol, a TRPM8 agonist, increased whole mouth saliva (WMS) flow and total protein secretion compared with unstimulated saliva, the vehicle control mouth rinse or cinnamaldehyde, a TRPA1 agonist. Nonivamide also increased the flow of labial minor gland saliva but parotid saliva flow rate was not increased. The influence of TRP channel agonists on the composition and function of the salivary proteome was investigated using a multi-batch quantitative MS method novel to salivary proteomics. Inter-personal and inter-mouth rinse variation was observed in the secreted proteomes and, using a novel bioinformatics method, inter-day variation was identified with some of the mouth rinses. Significant changes in specific salivary proteins were identified after all mouth rinses. In the case of nonivamide, these changes were attributed to functional shifts in the WMS secreted, primarily the over representation of salivary and nonsalivary cystatins which was confirmed by immunoassay. This study provides new evidence of the impact of TRP channel agonists on the salivary proteome and the stimulation of salivary secretion by a TRPM8 channel agonist, which suggests that TRP channel agonists are potential candidates for developing treatments for sufferers of xerostomia.

Salivary Cytokines in Children with Nephrotic Syndrome versus Healthy Children: A Comparative Study

Background: The aims of this study were to compare salivary cytokines and total protein between children with nephrotic syndrome (NS) and healthy children, and to examine whether saliva parameters can differentiate between steroid sensitivity and resistance and between disease remission and relapse. Methods: Twenty-seven children with nephrotic syndrome were classified according to steroid sensitivity and resistance, and disease remission and relapse. Twenty healthy children served as controls. Whole saliva samples were collected from all the participants. Urine and blood tests done on the same day as the saliva collection were recorded. Salivary total protein was quantified using bicinchoninic acid and IFNγ, IL-4, IL-8, IL-6, and IL1β levels using ELISA. Results: The mean ages of the nephrotic syndrome and control groups were 11.3 ± 2.4 and 9 ± 4.2, respectively. Compared to the control group, for the nephrotic syndrome group, total salivary protein was significantly lower, as were the levels of all the cytokines examined except IFNγ. Statistically significant differences were not found in any of the salivary markers examined between the children with nephrotic syndrome who were treatment sensitive (n = 19) and resistant (n = 8). Protein and IL-8 salivary levels were lower in the active (n = 7) than in the remission (n = 20) group. Conclusions: Salivary parameters distinguished children with nephrotic syndrome in relapse from healthy children. This may be due to decreased salivary protein excretion, which reflects decreased plasma levels, consequent to proteinuria. Accordingly, salivary markers may be developed as a diagnostic or screening tool for NS activity.

Top-Down Proteomics of Human Saliva Discloses Significant Variations of the Protein Profile in Patients with Mastocytosis

Mastocytosis is a myeloproliferative neoplasm causing abnormal clonal mast cell accumulation in different tissues, such as skin and bone marrow. A cutaneous subtype (CM) is distinguished from a systemic one (SM); SM patients can be grouped into SM with (SM+C) or without (SM-C) additional cutaneous lesions, and their classification is often challenging. This study was purposed to highlight variations in the salivary proteome of patients with different mastocytosis subtypes and compared to healthy controls. A top-down proteomics approach coupled to a label-free quantitation revealed salivary profiles in patients different from those of controls and a down-regulation of peptides/proteins involved in the mouth homeostasis and defense, such as statherin, histatins, and acidic proline-rich proteins (aPRPs), and in innate immunity and inflammation, such as the cathepsin inhibitors, suggesting a systemic condition associated with an exacerbated inflammatory state. The up-regulation of antileukoproteinase and S100A8 suggested a protective role against the disease status. The two SM forms were distinguished by the lower levels of truncated forms of aPRPs, statherin, P-B peptide, and cystatin D and the higher levels of thymosin β4 and α-defensins 1 and 4 in SM-C patients with respect to SM+C. Data are available via ProteomeXchange with identifier PXD017759.

Top-Down Proteomics of Human Saliva Discloses Significant Variations of the Protein Profile in Patients with Mastocytosis

Mastocytosis is a myeloproliferative neoplasm causing abnormal clonal mast cell accumulation in different tissues, such as skin and bone marrow. A cutaneous subtype (CM) is distinguished from a systemic one (SM); SM patients can be grouped into SM with (SM+C) or without (SM-C) additional cutaneous lesions, and their classification is often challenging. This study was purposed to highlight variations in the salivary proteome of patients with different mastocytosis subtypes and compared to healthy controls. A top-down proteomics approach coupled to a label-free quantitation revealed salivary profiles in patients different from those of controls and a down-regulation of peptides/proteins involved in the mouth homeostasis and defense, such as statherin, histatins, and acidic proline-rich proteins (aPRPs), and in innate immunity and inflammation, such as the cathepsin inhibitors, suggesting a systemic condition associated with an exacerbated inflammatory state. The up-regulation of antileukoproteinase and S100A8 suggested a protective role against the disease status. The two SM forms were distinguished by the lower levels of truncated forms of aPRPs, statherin, P-B peptide, and cystatin D and the higher levels of thymosin β4 and α-defensins 1 and 4 in SM-C patients with respect to SM+C. Data are available via ProteomeXchange with identifier PXD017759.

Proteomic Profiling of Emiliania huxleyi Using a Three-Dimensional Separation Method Combined with Tandem Mass Spectrometry

Emiliania huxleyi is one of the most abundant marine planktons, and it has a crucial feature in the carbon cycle. However, proteomic analyses of Emiliania huxleyi have not been done extensively. In this study, a three-dimensional liquid chromatography (3D-LC) system consisting of strong cation exchange, high- and low-pH reversed-phase liquid chromatography was established for in-depth proteomic profiling of Emiliania huxleyi. From tryptic proteome digest, 70 fractions were generated and analyzed using liquid chromatography-tandem mass spectrometry. In total, more than 84,000 unique peptides and 10,000 proteins groups were identified with a false discovery rate of ≤0.01. The physicochemical properties of the identified peptides were evaluated. Using ClueGO, approximately 700 gene ontology terms and 15 pathways were defined from the identified protein groups with p-value ≤0.05, covering a wide range of biological processes, cellular components, and molecular functions. Many biological processes associated with CO₂ fixation, photosynthesis, biosynthesis, and metabolic process were identified. Various molecular functions relating to protein binding and enzyme activities were also found. The 3D-LC strategy is a powerful approach for comparative proteomic studies on Emiliania huxleyi to reveal changes in its protein level and related mechanism.

CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins

Background

Compared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection. Therefore, identifying human saliva-secretory proteins and further detecting protein biomarkers in saliva have significant value in clinical medicine. There are only a few methods for predicting saliva-secretory proteins based on conventional machine learning algorithms, and all are highly dependent on annotated protein features. Unlike conventional machine learning algorithms, deep learning algorithms can automatically learn feature representations from input data and thus hold promise for predicting saliva-secretory proteins.

Results

We present a novel end-to-end deep learning model based on multilane capsule network (CapsNet) with differently sized convolution kernels to identify saliva-secretory proteins only from sequence information. The proposed model CapsNet-SSP outperforms existing methods based on conventional machine learning algorithms. Furthermore, the model performs better than other state-of-the-art deep learning architectures mostly used to analyze biological sequences. In addition, we further validate the effectiveness of CapsNet-SSP by comparison with human saliva-secretory proteins from existing studies and known salivary protein biomarkers of cancer.

Conclusions

The main contributions of this study are as follows: (1) an end-to-end model based on CapsNet is proposed to identify saliva-secretory proteins from the sequence information; (2) the proposed model achieves better performance and outperforms existing models; and (3) the saliva-secretory proteins predicted by our model are statistically significant compared with existing cancer biomarkers in saliva. In addition, a web server of CapsNet-SSP is developed for saliva-secretory protein identification, and it can be accessed at the following URL: http://www.csbg-jlu.info/CapsNet-SSP/. We believe that our model and web server will be useful for biomedical researchers who are interested in finding salivary protein biomarkers, especially when they have identified candidate proteins for analyzing diseased tissues near or distal to salivary glands using transcriptome or proteomics.

Review of Three-Dimensional Liquid Chromatography Platforms for Bottom-Up Proteomics

Proteomics is a large-scale study of proteins, aiming at the description and characterization of all expressed proteins in biological systems. The expressed proteins are typically highly complex and large in abundance range. To fulfill high accuracy and sensitivity of proteome analysis, the hybrid platforms of multidimensional (MD) separations and mass spectrometry have provided the most powerful solution. Multidimensional separations provide enhanced peak capacity and reduce sample complexity, which enables mass spectrometry to analyze more proteins with high sensitivity. Although two-dimensional (2D) separations have been widely used since the early period of proteomics, three-dimensional (3D) separation was barely used by low reproducibility of separation, increased analysis time in mass spectrometry. With developments of novel microscale techniques such as nano-UPLC and improvements of mass spectrometry, the 3D separation becomes a reliable and practical selection. This review summarizes existing offline and online 3D-LC platforms developed for proteomics and their applications. In detail, setups and implementation of those systems as well as their advances are outlined. The performance of those platforms is also discussed and compared with the state-of-the-art 2D-LC. In addition, we provide some perspectives on the future developments and applications of 3D-LC in proteomics.

RP-HPLC-ESI-IT Mass Spectrometry Reveals Significant Variations of the Human Salivary Protein Profile Associated with Predominantly Antibody Deficiencies

PURPOSE

Present study is designed to discover potential salivary biomarkers associated with predominantly antibody deficiencies, which include a large spectrum of disorders sharing failure of antibody production, and B cell defects resulting in recurrent infections, autoimmune and inflammatory manifestations, and tumor susceptibility. Understanding and clinical classification of these syndromes is still challenging.

METHODS

We carried out a study of human saliva based on liquid chromatography-mass spectrometry measurements of intact protein mass values. Salivary protein profiles of patients (n = 23) and healthy controls (n = 30) were compared.

RESULTS

Patients exhibited lower abundance of α-defensins 1-4, cystatins S1 and S2, and higher abundance of glutathionylated cystatin B and cystatin SN than controls. Patients could be clustered in two groups on the basis of different levels of cystatin SN, S1 and S2, suggesting that these proteins may play different roles in the disease.

CONCLUSIONS

Quantitative variations of these pro-inflammatory and antimicrobial peptides/proteins may be related to immunodeficiency and infectious condition of the patients. The high incidence of tumors in the group with the highest level of cystatin SN, which is recognized as tumoral marker, appeared an intriguing result deserving of future investigations. Data are available via ProteomeXchange with identifier PXD012688.

RP-HPLC-ESI-IT Mass Spectrometry Reveals Significant Variations of the Human Salivary Protein Profile Associated with Predominantly Antibody Deficiencies

PURPOSE

Present study is designed to discover potential salivary biomarkers associated with predominantly antibody deficiencies, which include a large spectrum of disorders sharing failure of antibody production, and B cell defects resulting in recurrent infections, autoimmune and inflammatory manifestations, and tumor susceptibility. Understanding and clinical classification of these syndromes is still challenging.

METHODS

We carried out a study of human saliva based on liquid chromatography-mass spectrometry measurements of intact protein mass values. Salivary protein profiles of patients (n = 23) and healthy controls (n = 30) were compared.

RESULTS

Patients exhibited lower abundance of α-defensins 1-4, cystatins S1 and S2, and higher abundance of glutathionylated cystatin B and cystatin SN than controls. Patients could be clustered in two groups on the basis of different levels of cystatin SN, S1 and S2, suggesting that these proteins may play different roles in the disease.

CONCLUSIONS

Quantitative variations of these pro-inflammatory and antimicrobial peptides/proteins may be related to immunodeficiency and infectious condition of the patients. The high incidence of tumors in the group with the highest level of cystatin SN, which is recognized as tumoral marker, appeared an intriguing result deserving of future investigations. Data are available via ProteomeXchange with identifier PXD012688.

Role of Saliva and Salivary Diagnostics in the Advancement of Oral Health

The objective of this article was to provide an account of some of the developments related to saliva over the first 100 years of the Journal of Dental Research and to outline some of the many biomarkers identified in saliva in the last few years. The first section covers findings in salivary physiology, biochemistry, calcium phosphate chemistry related to saliva, microbiology, and the role of saliva in maintaining oral health. The second section highlights salivary diagnostics, salivaomics, and saliva exosomics in the context of the emerging theme of personalized and precision medicine.

Human salivary protein extraction from RNAPro·SAL™, Pure·SAL™, and passive drooling method

Objective:

The aim of the current study was to carry out a preliminary validation of devices for standardized collection of whole mouth fluid (WMF) in comparison to the passive drooling method for protein analysis in healthy subjects.

Materials and Methods:

A carefully designed sample collection/pretreatment protocol is crucial to the success of any saliva proteomics project. In this study, WMF was collected from healthy volunteers (n = 10, ages: 18–26 years). Individuals with any oral disease were excluded from the study group. In our study, we evaluated the following collection methods; the classical passive drooling method (unstimulated whole saliva) and standardized tools for saliva collection (Pure·SAL™, and RNAPro·SAL™) from Oasis Diagnostics^® Corporation (Vancouver WA, USA). For estimation of protein levels, we used the bicinchoninic acid assay and protein assay kit (Thermo Fisher). The two-dimensional gel electrophoresis sample analysis was carried out for the estimation of proteins in one of the samples.

Results:

When gels were compared, the difference was seen in the resolution of spots. Protein spots were fading from high- to low-molecular weight masses. Hence, advanced devices in comparison to spitting method resulted in much clearer protein spots which in turn prove the validation of devices.

Conclusions:

In this study, we concluded that protein extraction could be possible by both methods such as passive drooling method and through advanced saliva collection devices (Pure·SAL™ and RNAPro·SAL™).

Salivary Extracellular Vesicle-Associated exRNA as Cancer Biomarker

Extracellular vesicles (EVs) secreted in biological fluids contain several transcripts of the cell of origin, which may modify the functions and phenotype of proximal and distant cells. Cancer-derived EVs may promote a favorable microenvironment for cancer growth and invasion by acting on stroma and endothelial cells and may favor metastasis formation. The transcripts contained in cancer EVs may be exploited as biomarkers. Protein and extracellular RNA (exRNA) profiling in patient bio-fluids, such as blood and urine, was performed to identify molecular features with potential diagnostic and prognostic values. EVs are concentrated in saliva, and salivary EVs are particularly enriched in exRNAs. Several studies were focused on salivary EVs for the detection of biomarkers either of non-oral or oral cancers. The present paper provides an overview of the available studies on the diagnostic potential of exRNA profiling in salivary EVs.

Diagnostic potential of saliva proteome analysis: a review and guide to clinical practice

Proteomic techniques have become popular in medicine and dentistry because of their widespread use in analyzing bodily fluids such as blood, saliva, urine, and gingival crevicular fluids as well as hard tissues such as enamel, dentine, and cementum. This review is a guide to proteomic techniques in general dentistry, summarizing techniques and their clinical application in understanding and diagnosing diseases and their use in identifying biomarkers of various diseases.

Proteomic profiling of whole-saliva reveals correlation between Burning Mouth Syndrome and the neurotrophin signaling pathway

Burning mouth syndrome (BMS) is characterized by a spontaneous and chronic sensation of burning in the oral mucosa, with no apparent signs. The underlying pathophysiological and neuropathic mechanisms remain unclear. Here, we attempt to elucidate some of these mechanisms using proteomic profiling and bioinformatic analyses of whole-saliva (WS) from BMS patients compared to WS from healthy individuals. Qualitative and quantitative proteomic profiling was performed using two dimensional gel electrophoresis (2-DE) and quantitative mass spectrometry (q-MS). In order to improve protein visibility, 21 high abundance proteins were depleted before proteomic profiling. Quantitative proteomic analysis revealed 100 BMS specific proteins and an additional 158 proteins up-regulated by more than threefold in those with BMS. Bioinformatic analyses of the altered protein expression profile of BMS group indicated high correlations to three cellular mechanisms including the neurotrophin signaling pathway. Based on this finding, we suggest that neurotrophin signaling pathway is involved in the pathophysiology of BMS by amplifying P75NTR activity, which in turn increases neural apoptosis thereby reducing sub-papillary nerve fiber density in the oral mucosa.

Salivary Exosomes as Nanocarriers for Cancer Biomarker Delivery

Human saliva is an ideal body fluid for developing non-invasive diagnostics. Saliva contains naturally-occurring nanoparticles with unique structural and biochemical characteristics. The salivary exosome, a nanoscale extracellular vesicle, has been identified as a highly informative nanovesicle with clinically-relevant information. Salivary exosomes have brought forth a pathway and mechanism by which cancer-derived biomarkers can be shuttled through the systemic circulation into the oral cavity. Despite such clinical potential, routine and reliable analyses of exosomes remain challenging due to their small sizes. Characterization of individual exosome nanostructures provides critical data for understanding their pathophysiological condition and diagnostic potential. In this review, we summarize a current array of discovered salivary biomarkers and nanostructural properties of salivary exosomes associated with specific cancers. In addition, we describe a novel electrochemical sensing technology, EFIRM (electric field-induced release and measurement), that advances saliva liquid biopsy, covering the current landscape of point-of-care saliva testing.

Deep sequencing salivary proteins for periodontitis using proteomics

OBJECTIVES

Saliva is a bodily fluid transuded from gingival crevice fluid and blood and contains many proteins. Proteins in saliva have been studied as markers for periodontal diseases. Mass spectrometric analysis is applied to investigate biomarker proteins that are related to periodontitis.

MATERIAL AND METHODS

Saliva samples were collected from 207 participants including 36 pairs matched for age, sex, and smoking who joined Yangpyeong health cohort. Periodontitis was defined by 2005 5th European guideline. Shotgun proteomics was applied to detect proteins from saliva samples. Principal component analysis and Ingenuity Pathway Analysis for canonical pathway and protein pathway were applied. Protein-protein interaction was also applied. Enzyme-linked immunosorbent assay (ELISA) was used to verify the candidate protein markers among another matched participants (n = 80).

RESULTS

Shotgun proteomics indicated that salivary S100A8 and S100A9 were candidate biomarkers for periodontitis. ELISA confirmed that both salivary S100A8 and S100A9 were higher in those with periodontitis compared to those without periodontitis (paired-t test, p < 0.05).

CONCLUSION

Our proteomics data showed that S100A8 and S100A9 in saliva could be candidate biomarkers for periodontitis. The rapid-test-kit using salivary S100A8 and S100A9 will be a practical tool for reducing the risk of periodontitis and promotion of periodontal health.

CLINICAL RELEVANCE

A rapid-test-kit using salivary biomarkers, S100A8 and S100A9, could be utilized by clinicians and individuals for screening periodontitis, which might reduce the morbidity of periodontitis and promote periodontal health.