Systematic comparison of the human saliva and plasma proteomes

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.

Gut dysbiosis and neurological modalities: An engineering approach via proteomic analysis of gut-brain axis

The human gut microbiota is a complex and dynamic community of microorganisms, that influence metabolic, neurodevelopmental, and immune pathways. Microbial dysbiosis, characterized by changes in microbial diversity and relative abundances, is implicated in the development of various chronic neurological and neurodegenerative disorders. These disorders are marked by the accumulation of pathological protein aggregates, leading to the progressive loss of neurons and behavioural functions. Dysregulations in protein-protein interaction networks and signalling complexes, critical for normal brain function, are common in neurological disorders but challenging to unravel, particularly at the neuron and synapse-specific levels. To advance therapeutic strategies, a deeper understanding of neuropathogenesis, especially during the progressive disease phase, is needed. Biomarkers play a crucial role in identifying disease pathophysiology and monitoring disease progression. Proteomics, a powerful technology, shows promise in accelerating biomarker discovery and aiding in the development of novel treatments. In this chapter, we provide an in-depth overview of how proteomic techniques, utilizing various biofluid samples from patients with neurological conditions and diverse animal models, have contributed valuable insights into the pathogenesis of numerous neurological disorders. We also discuss the current state of research, potential challenges, and future directions in proteomic approaches to unravel neuro-pathological conditions.

Characterization of Extracellular Vesicles from Human Saliva: Effects of Age and Isolation Techniques

Salivary extracellular vesicles (EVs) represent an attractive source of biomarkers due to the accessibility of saliva and its non-invasive sampling methods. However, the lack of comparative studies assessing the efficacy of different EV isolation techniques hampers the use of salivary EVs in clinical settings. Moreover, the effects of age on salivary EVs are largely unknown, hindering the identification of salivary EV-associated biomarkers across the lifespan. To address these questions, we compared salivary EV concentration, size mode, protein concentration, and purity using eight EV isolation techniques before and after magnetic bead immunocapture with antibodies against CD9, CD63, and CD81. The effects of age on salivary EVs obtained with each isolation technique were further investigated. Results showed higher expression of CD63 on isolated salivary EVs compared to the expression of CD81 and flotillin-1. Overall, magnetic bead immunocapture was more efficient in recovering salivary EVs with Norgen's Saliva Exosome Purification Kit and ExoQuick-TC ULTRA at the cost of EV yield. Regardless of age, Invitrogen Total Exosome Isolation Solution showed the highest level of protein concentration, whereas Izon qEVOriginal-70nm columns revealed the highest purity. This study provides the first comprehensive comparison of salivary EVs in younger and older adults using different EV isolation techniques, which represents a step forward for assessing salivary EVs as a source of potential biomarkers of tissue-specific diseases throughout the life cycle.

Protein profile pattern analysis: A multifarious, in vitro diagnosis technique for universal screening

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.

Detection and quantification of TIMP1 and miR-141 through RT-LAMP and TT-LAMP in serum samples during estrous cycle in buffalo

Estrus identification is a common problem in the reproductive management of farm animals. Hence, several studies have been conducted to explore biomarkers for estrus detection. One of our previous studies identified the abundance of RNA biomarkers such as TIMP1 and miR-141 in buffalo saliva during the estrus stage. However, the level of these RNA biomarkers in buffalo serum during estrous cycle is undetected. Therefore, the present study was designed to quantify TIMP1 and miR-141 in serum during buffalo estrous cycle. Blood samples were collected in different stages of estrous cycle from four healthy cyclic buffaloes. The quantification of TIMP1 and miR-141 was performed with direct serum using RT-LAMP and TT-LAMP technologies, respectively. The LAMP amplification was confirmed by agarose gel electrophoresis and the color change was quantified in comparison to a non-template control using ImageJ software. A decreased abundance of TIMP1 at the diestrus stage and a decreasing trend of miR-141 from proestrus to diestrus stages were observed, which was further reinforced by simulated random populations generated with R programming. Specifically, TIMP1 was found significantly (P < 0.0001) abundant at estrus and metestrus stages as compared to the diestrus stage, whereas miR-141 was significantly (P < 0.001) higher during the proestrus stage as compared to the other stages of estrous cycle. The ROC curve analysis showed miR-141 to be a better biomarker than TIMP1 as it distinguished the proestrus stage from diestrus with a sensitivity and specificity of 83 % and 98 %. This study also marked the first use of TT-LAMP technology for rapid miRNA detection in livestock.

Prosthodontic implications of saliva and salivary gland dysfunction

PURPOSE

To provide a detailed overview of the fundamentals of saliva constituents and production. The review outlines the clinical manifestations as a consequence of salivary gland dysfunction and management strategies for patients with salivary gland dysfunction. Prosthodontic implications of saliva and salivary gland dysfunction are presented.

MATERIALS AND METHODS

English-language literature relating to saliva constituents, physiologic saliva production, clinical manifestations secondary to salivary gland dysfunction, salivary biomarkers, and management strategies were retrieved via electronic search. Relevant articles were summarized for this manuscript with a view toward providing pragmatic information.

RESULTS

Saliva is produced by three pairs of major and minor salivary glands. The major salivary glands, namely, the parotid, submandibular, and sublingual glands, contribute approximately 90% of saliva production. Saliva contains serous and mucinous secretions produced by different types of cells within salivary glands. Parasympathetic and sympathetic fibers innervate the major salivary glands, and upon stimulation, the parasympathetic innervation increases serous secretions, while the sympathetic innervation increases protein secretion. Stimulated saliva is mainly derived from the parotid glands which are composed of serous acini, while unstimulated saliva is mainly derived from the submandibular glands which are composed of mixed seromucous acini. As major salivary glands contribute the most to salivary flow, local or systemic factors influencing those glands can disrupt saliva production resulting in clinically significant oral manifestations.

CONCLUSION

This review provides a fundamental overview of saliva production. In addition, the review highlights the various clinical manifestations secondary to salivary gland dysfunction, explores salivary biomarkers for screening of systemic diseases, discusses management strategies for patients with salivary gland dysfunction, and outlines the prosthodontic implications of saliva and salivary gland dysfunction.

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.

Oral Infection, Oral Pathology and Salivary Diagnostics of Mpox Disease: Relevance in Dentistry and OMICs Perspectives

In this narrative review, we aim to point out the close relationship between mpox virus (MPXV) infection and the role of saliva as a diagnostic tool for mpox, considering the current molecular approach and in the perspective of OMICs application. The MPXV uses the host cell's rough endoplasmic reticulum, ribosomes, and cytoplasmic proteins to replicate its genome and synthesize virions for cellular exit. The presence of oral mucosa lesions associated with mpox infection is one of the first signs of infection; however, current diagnostic tools find it difficult to detect the virus before the rashes begin. MPXV transmission occurs through direct contact with an infected lesion and infected body fluids, including saliva, presenting a potential use of this fluid for diagnostic purposes. Currently available diagnostic tests for MPXV detection are performed either by real-time quantitative PCR (RT-qPCR) or ELISA, which presents several limitations since they are invasive tests. Despite current clinical trials with restricted sample size, MPXV DNA was detected in saliva with a sensitivity of 85%-100%. In this context, the application of transcriptomics, metabolomics, lipidomics, or proteomics analyses coupled with saliva can identify novel disease biomarkers. Thus, it is important to note that the identification and quantification of salivary DNA, RNA, lipid, protein, and metabolite can provide novel non-invasive biomarkers through the use of OMICs platforms aiding in the early detection and diagnosis of MPXV infection. Untargeted mass spectrometry (MS)-based proteomics reveals that some proteins also expressed in saliva were detected with greater expression differences in blood plasma when comparing mpox patients and healthy subjects, suggesting a promising alternative to be applied in screening or diagnostic platforms for mpox salivary diagnostics coupled to OMICs.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

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.

Immunoassay Detects Salivary Anti-SSA/Ro-52 Autoantibodies in Seronegative Patients with Primary Sjögren's Syndrome

The diagnostic work-up for Sjögren's syndrome is challenging and complex, including testing for serum autoantibodies to SSA/Ro and a labial salivary gland biopsy. Furthermore, the diagnosis is often delayed. In this study, we tested the hypothesis that anti-SSA/Ro autoantibodies are detectable in the saliva of patients with primary Sjögren's syndrome (pSS) because the disease affects the salivary glands, and these autoantibodies display greater discriminatory performance in saliva than in serum. SSA/Ro-52 Ags were used to develop what is, to our knowledge, a novel quantitative electrochemical-based immunoassay: the electric field-induced release and measurement (EFIRM) platform. The clinical utility was determined by measuring salivary anti-SSA/Ro-52 autoantibodies in patients with pSS and sicca (n = 34), patients without pSS with sicca (n = 35), and healthy subjects (n = 41). The statistical analysis of discrimination included the area under the receiver operating characteristic curve. Salivary anti-SSA/Ro-52 autoantibodies were measured in 94% (32 of 34) of patients with pSS with 85% (29 of 34) seropositivity. Four of the five seronegative patients with pSS had EFIRM-measurable anti-SSA/Ro-52 autoantibodies in saliva. Additionally, 60% (21 of 35) of the seronegative patients without pSS who had sicca had EFIRM-detectable SSA/Ro-52 autoantibodies in saliva, indicating the onset of autoimmune disease. Two of the 41 healthy control subjects had EFIRM-detectable SSA/Ro-52 autoantibodies in their saliva. Salivary SSA/Ro-52 autoantibodies significantly discriminated patients with pSS or patients with the initial stage of autoimmune disease from healthy subjects with an area under the receiver operating characteristic curve of 0.91. Our findings suggest that the proposed saliva SSA/Ro-52 immunoassay improves early and accurate diagnosis of seronegative patients with pSS and patients with early-onset autoimmune disease.

Salivary level of microRNA-146a and microRNA-155 biomarkers in patients with oral lichen planus versus oral squamous cell carcinoma

BACKGROUND

Oral lichen planus (OLP) is a chronic inflammatory disease of the oral mucosa, which has potential for malignant transformation. MicroRNAs play an important role in immunopathogenesis of OLP, and may be used for prediction of its malignant transformation. This study aimed to assess the salivary level of microRNA-146a and microRNA-155 biomarkers in patients with OLP and oral squamous cell carcinoma (OSCC).

METHODS

In this case-control study, unstimulated saliva samples were collected from 60 patients, including 15 patients with dysplastic OLP, 15 OLP patients without dysplasia, 15 patients with OSCC, and 15 healthy controls according to the Navazesh technique. After RNA extraction, the expression of microRNA-146a and microRNA-155 was quantified by real-time quantitative polymerase chain reaction (RT-qPCR). The data were analyzed by the Kruskal-Wallis and Dunn-Bonferroni tests.

RESULTS

The difference in expression of microRNA-146a and microRNA-155 among the four groups was significant (P < 0.05). Pairwise comparisons of the groups showed significantly higher expression of microRNA-146a in OLP (P = 0.004) and dysplastic OLP (P = 0.046) patients compared with the control group. Up-regulation of this biomarker in OSCC patients was not significant compared with the control group (P = 0.076). Up-regulation of micro-RNA-155 was only significant in OLP group, compared with the control group (P = 0.009). No other significant differences were found (P > 0.05).

CONCLUSION

Considering the altered expression of MicroRNA-146a and microRNA-155 in dysplastic OLP and OSCC, their altered expression may serve as an alarming sign of malignancy. However, further investigations are still required.

Effects of filtration and alpha-amylase depletion on salivary biochemical composition measurements

The effects of filtration (F) and alpha-amylase depletion (AD) were assessed in n = 34 saliva samples. Each saliva sample was split into three aliquots and treated as follows: (1) no treatment; (2) 0.45μm commercial filter; and (3) 0.45μm commercial filter and affinity depletion of alpha-amylase. Then, a panel of biochemical biomarkers consisting of amylase, lipase, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), creatine kinase (CK), calcium, phosphorus, total protein, albumin, urea, creatinine, cholesterol, triglycerides, and uric acid was measured. Differences between the different aliquots were observed in all measured analytes. The most marked changes were found in triglycerides and lipase data for filtered samples, and in alpha-amylase, uric acid, triglycerides, creatinine, and calcium results in alpha-amylase-depleted aliquots. In conclusion, the salivary filtration and amylase depletion methods employed in this report caused significant changes in saliva composition measurements. Based on these results, it would be recommended to consider the possible effects of these treatments in salivary biomarkers when filtration or amylase depletion is performed.

Structure-activity relationship analysis of activity-based probes targeting HTRA family of serine proteases

High temperature requirement A serine proteases (HTRA) are ubiquitously expressed and participate in protein quality control and cellular stress responses. They are linked to several clinical illnesses, including bacterial infection, cancer, age-related macular degeneration, and neurodegenerative diseases. In addition, several recent studies have revealed HTRAs as important biomarkers and potential therapeutic targets, necessitating the development of an effective detection method to evaluate their functional states in various disease models. We developed a new series of HTRA-targeting activity-based probes with enhanced subtype selectivity and reactivity. In conjunction with our previously developed tetrapeptide probes, we established the structure-activity relationship of the new probes for different HTRA subtypes. Our probes are cell-permeable and have potent inhibitory effects against HTRA1 and HTRA2, making them valuable for identifying and validating HTRAs as an important biomarker.

Diet and phytogenic supplementation substantially modulate the salivary proteome in dairy cows

Phytogenic compounds may influence salivation or salivary properties. However, their effects on the bovine salivary proteome have not been evaluated. We investigated changes in the bovine salivary proteome due to transition from forage to high-concentrate diet, with and without supplementation with a phytogenic feed additive. Eight non-lactating cows were fed forage, then transitioned to a 65% concentrate diet (DM basis) over a week. Cows were control (n = 4, CON) or supplemented with a phytogenic feed additive (n = 4, PHY). Proteomic analysis was conducted using liquid chromatography coupled with mass spectrometry. We identified 1233 proteins; 878 were bovine proteins, 189 corresponded to bacteria, and 166 were plant proteins. Between forage and high-concentrate, 139 proteins were differentially abundant (P < 0.05), with 48 proteins having a log2FC difference > |2|. The salivary proteome reflected shifts in processes involving nutrient utilization, body tissue accretion, and immune response. Between PHY and CON, 195 proteins were differently abundant (P < 0.05), with 37 having a log2FC difference > |2|; 86 proteins were increased by PHY, including proteins involved in smell recognition. Many differentially abundant proteins correlated (r > |0.70|) with salivary bicarbonate, total mucins or pH. Results provide novel insights into the bovine salivary proteome using a non-invasive approach, and the association of specific proteins with major salivary properties influencing rumen homeostasis. SIGNIFICANCE: Phytogenic compounds may stimulate salivation due to their olfactory properties, but their effects on the salivary proteome have not been investigated. We investigated the effect of high-concentrate diets and supplementation with a phytogenic additive on the salivary proteome of cows. We show that analysis of cows' saliva can be a non-invasive approach to detect effects occurring not only in the gut, but also systemically including indications for gut health and immune response. Thus, results provide unique insights into the bovine salivary proteome, and will have a crucial contribution to further understand animal response in terms of nutrient utilization and immune activity due to the change from forage to a high-energy diet. Additionally, our findings reveal changes due to supplementation with a phytogenic feed additive with regard to health and olfactory stimulation. Furthermore, findings suggest an association between salivary proteins and other components like bicarbonate content.

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

Translational research into frailty from bench to bedside: Salivary biomarkers for inflammaging

Frailty is a complex physiological syndrome associated with adverse ageing and decreased physiological reserves. Frailty leads to cognitive and physical disability and is a significant cause of morbidity, mortality and economic costs. The underlying cause of frailty is multifaceted, including immunosenescence and inflammaging, changes in microbiota and metabolic dysfunction. Currently, salivary biomarkers are used as early predictors for some clinical diseases, contributing to the effective prevention and treatment of diseases, including frailty. Sample collection for salivary analysis is non-invasive and simple, which are paramount factors for testing in the vulnerable frail population. The aim of this review is to describe the current knowledge on the association between frailty and the inflammatory process and discuss methods to identify putative biomarkers in salivary fluids to predict this syndrome. This study describes the relationship between i.-inflammatory process and frailty; ii.-infectious, chronic, skeletal, metabolic and cognitive diseases with inflammation and frailty; iii.-inflammatory biomarkers and salivary fluids. There is a limited number of previous studies focusing on the analysis of inflammatory salivary biomarkers and frailty syndrome; hence, the study of salivary fluids as a source for biomarkers is an open area of research with the potential to address the increasing demands for frailty-associated biomarkers.

Peri-implant Bone Healing: Its Basic Osteogenesis and Biomarkers

The continuous sequence of bone healing phases starts off with osteoconduction to the implant surface, depending on the migration of osteogenic cells. Osteoneogenesis ensues resulting in a mineralised interfacial matrix and is followed by bone remodelling to the implant interface at discrete sites. Dental implant drilling procedure and placement produce osseous defect which is filled by blood. Within seconds, blood proteins are adsorbed onto the implant surface and platelets are activated resulting in the release of cytokines and growth factors. Further platelet aggregation initiates osteoconduction to the surface, followed by osteoneogenesis, forming an extracellular matrix. Subsequently, remodelling creates a bone to implant interface which can be explained through distance and contact osteogenesis. The dental implant surface has been shown to influence osteoconduction by modifying protein properties and adsorption around the implant. Salivary biomarkers may be considered as a specific and sensitive diagnostic tool to detect these changes in protein expressions after implant placement. Thus, the purpose of this narrative review is to provide a detailed account of the bone healing mechanism associated with dental implant placement, as well as how the implant surface architecture and protein release play a role in bone healing, and the potential use of saliva to detect these biomarkers.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Comparative Analysis of Saliva and Plasma Proteins Patterns in Pregnant Cows—Preliminary Studies

Simple Summary

One of the most crucial topics about cattle breeding is pregnancy. During this state, there are many changes in protein expression and abundance. These changes find reflection not only in plasma protein patterns but also in saliva, which is easier to obtain than blood. The aim of this study was the analysis of plasma and salivary protein profiles in pregnant cows in order to search for valuable markers of pregnancy status. In this study, the presence of apolipoproteins possibly related to bovine pregnancy was confirmed both in plasma and saliva. This means that saliva can be considered a good source of information about the condition of the organism, including during pregnancy. It is possible that the comparison of salivary and plasma proteomes can be a helpful tool to assess the pregnancy status of cattle, and can be useful for developing rapid tests from saliva.

Abstract

Pregnancy is a physiological state that can be described, from a biochemical point of view, using protein patterns. The present study focused on the comparison of protein patterns between the saliva and plasma of pregnant cows to search for possible markers which are present both in plasma and saliva. Saliva and plasma were collected from healthy, pregnant (3–4 months) and non-pregnant (C; n = 4) cows aged between 4 and 8 years (P; n = 8) from the same farm. Biological material was analyzed using 2D electrophoresis and MS identification. Among identified spots, there were those which could be related to pregnancy (e.g., apolipoproteins I and II in all examined matrices or transforming growth factor-beta-induced protein ig-h3 in albumin-free plasma) as well as those which are responsible for regulating of cellular processes (e.g., pyruvate kinase and aspartate aminotransferase in all examined matrices, or lactate dehydrogenase, phosphoglycerate kinase, and NADH dehydrogenase in plasma). Further identification of common spots and those only specific to saliva as well as the comparison between other periods of pregnancy are necessary; it is already clear that saliva can be considered a valuable diagnostic matrix containing potential markers of physiological and pathological status.

Time-domain ultrasound as prior information for frequency-domain compressive ultrasound for intravascular cell detection: A 2-cell numerical model

This study proposes a new method for the detection of a weak scatterer among strong scatterers using prior-information ultrasound (US) imaging. A perfect application of this approach is in vivo cell detection in the bloodstream, where red blood cells (RBCs) serve as identifiable strong scatterers. In vivo cell detection can help diagnose cancer at its earliest stages, increasing the chances of survival for patients. This work combines time-domain US with frequency-domain compressive US imaging to detect a 20-μ MCF-7 circulating tumor cell (CTC) among a number of RBCs within a simulated venule inside the mouth. The 2D image reconstructed from the time-domain US is employed to simulate the reflected and scattered pressure field from the RBCs, which is then measured at the location of the receivers. The RBCs are tagged one time by a human operator and another time, automatically, by template-based computer vision. Next, the resulting signal from the RBCs is subtracted from the measured total signal in frequency domain to generate the scattered-field data, coming from the CTC alone. Feeding that signal and the background pressure field into a norm-one-based compressive sensing code enables detecting the CTC at various locations. As errors could arise in determining the location of the RBCs and their acoustic properties in the real world, small errors (up to 10% in the former and 5% in the latter) are purposefully introduced to the model, to which the proposed method is shown to be resilient. Localization errors are smaller than 12 μ when a human tags the RBCs and smaller than 25 μ when computer vision is applied. Despite its limitations, this study, for the first time, reports the results of combining two US modalities aimed at cell detection and introduces a unique and useful application for ultrahigh-frequency US imaging. It should be noted that this method can be used in detecting weak scatterers with ultrasound waves in other applications as well.

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

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.

Evaluation of the Use of Saliva Metabolome as a Surrogate of Blood Metabolome in Assessing Internal Exposures to Traffic-Related Air Pollution

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Proteomics in Multiple Sclerosis: The Perspective of the Clinician

Multiple sclerosis (MS) is the inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS) that affects approximately 2.8 million people worldwide. In the last decade, a new era was heralded in by a new phenotypic classification, a new diagnostic protocol and the first ever therapeutic guideline, making personalized medicine the aim of MS management. However, despite this great evolution, there are still many aspects of the disease that are unknown and need to be further researched. A hallmark of these research are molecular biomarkers that could help in the diagnosis, differential diagnosis, therapy and prognosis of the disease. Proteomics, a rapidly evolving discipline of molecular biology may fulfill this dire need for the discovery of molecular biomarkers. In this review, we aimed to give a comprehensive summary on the utility of proteomics in the field of MS research. We reviewed the published results of the method in case of the pathogenesis of the disease and for biomarkers of diagnosis, differential diagnosis, conversion of disease courses, disease activity, progression and immunological therapy. We found proteomics to be a highly effective emerging tool that has been providing important findings in the research of MS.

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.

Stabilization of Salivary Biomarkers

The use of saliva as a diagnostic biofluid has been increasing in recent years, thanks to the identification and validation of new biomarkers and improvements in test accuracy, sensitivity, and precision that enable the development of new noninvasive and cost-effective devices. However, the lack of standardized methods for sample collection, treatment, and storage contribute to the overall variability and lack of reproducibility across analytical evaluations. Furthermore, the instability of salivary biomarkers after sample collection hinders their translation into commercially available technologies for noninvasive monitoring of saliva in home settings. The present review aims to highlight the status of research on the challenges of collecting and using diagnostic salivary samples, emphasizing the methodologies used to preserve relevant proteins, hormones, genomic, and transcriptomic biomarkers during sample handling and analysis.

Diagnostic Role of Extracellular Vesicles in Cancer: A Comprehensive Systematic Review and Meta-Analysis

Background: Cancer-derived extracellular vesicles (EVs) are regarded to have significant function in most steps during cancer progression. This meta-analysis aims to investigate the accuracy of EVs as a biomarker in cancer diagnosis.

Methods: The diagnostic efficacy of EVs for different cancers was assessed using pooled sensitivity and specificity, diagnostic odds ratio (DOR), and overall area under the curve (AUC) of the summary receiver operating characteristic (SROC). The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were verified to estimate the diagnostic efficacy of EV at a clinical level.

Results: In all, 6,183 cancer patients and 2,437 healthy controls from 75 eligible studies reported in 42 publications were included in the study. The overall pooled sensitivity, specificity, PLR, NLR, and DOR were 0.62 (95% CI: 0.60–0.63), 0.76 (95% CI: 0.75–0.78), 3.07 (95% CI: 2.52–3.75), 0.34 (95% CI: 0.28–0.41), and 10.98 (95% CI: 7.53–16.00), respectively. Similarly, the AUC of the SROC was 0.88, indicating a high conservation of EVs as an early diagnostic marker. Furthermore, subgroup analysis suggested that the use of small EVs as a biomarker was more accurate in serum-based samples of nervous system cancer (p < 0.001). As a result, ultracentrifugation and quantification and size determination methods, such as Western blotting and ELISA were the most reliable identification methods for EV detection. We also indicated that increased secretion of EVs made them a capable biomarker for diagnosing cancer in elderly European individuals.

Conclusions: Our study provides evidence that EVs are a promising non-invasive biomarker for cancer diagnosis. Well-designed cohort studies should be conducted to warrant the clinical diagnostic value of EVs.

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/

Salivary biomarkers and neuropsychological outcomes: A non-invasive approach to investigate pollutants-associated neurotoxicity and its effects on cognition in vulnerable populations

The occurrence of neurotoxicity caused by xenobiotics such as pesticides (dichlorodiphenyltrichloroethane, organophosphates, pyrethroids, etc.) or metals (mercury, lead, aluminum, arsenic, etc.) is a growing concern around the world, particularly in vulnerable populations with difficulties on both detection and symptoms treatment, due to low economic status, remote access, poor infrastructure, and low educational level, among others features. Despite the numerous molecular markers and questionnaires/clinical evaluations, studying neurotoxicity and its effects on cognition in these populations faces problems with samples collection and processing, and information accuracy. Assessing cognitive changes caused by neurotoxicity, especially those that are subtle in the initial stages, is fundamentally challenging. Finding accurate, non-invasive, and low-cost strategies to detect the first signals of brain injury has the potential to support an accelerated development of the research with these populations. Saliva emerges as an ideal pool of biomarkers (with interleukins and neural damage-related proteins, among others) and potential alternative diagnostic fluid to molecularly investigate neurotoxicity. As a source of numerous neurological biomarkers, saliva has several advantages compared to blood, such as easier storage, requires less manipulation, and the procedure is cheaper, safer and well accepted by patients compared with drawing blood. Regarding cognitive dysfunction, neuropsychological batteries represent, with their friendly interface, a feasible and accurate method to evaluate the eventual cognitive deficits associated with neurotoxicity in people from diverse cultural and educational backgrounds. The association of these two tools, saliva and neuropsychological batteries, to cover the molecular and cognitive aspects of neurotoxicity in vulnerable populations, could potentially increase the prevalence of early intervention and successful treatment.

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.

Hyphenated sample preparation-electrospray and nano-electrospray ionization mass spectrometry for biofluid analysis

Stand-alone electrospray ionization mass spectrometry (ESI-MS) has been advancing through enhancements in throughput, selectivity and sensitivity of mass spectrometers. Unlike traditional MS techniques which usually require extensive offline sample preparation and chromatographic separation, many sample preparation techniques are now directly coupled with stand-alone MS to enable outstanding throughput for bioanalysis. In this review, we summarize the different sample clean-up and/or analyte enrichment strategies that can be directly coupled with ESI-MS and nano-ESI-MS for the analysis of biological fluids. The overview covers the hyphenation of different sample preparation techniques including solid phase extraction (SPE), solid phase micro-extraction (SPME), slug flow micro-extraction/nano-extraction (SFME/SFNE), liquid extraction surface analysis (LESA), extraction electrospray, extraction using digital microfluidics (DMF), and electrokinetic extraction (EkE) with ESI-MS and nano-ESI-MS.

Peripheral Blood and Salivary Biomarkers of Blood-Brain Barrier Permeability and Neuronal Damage: Clinical and Applied Concepts

Within the neurovascular unit (NVU), the blood–brain barrier (BBB) operates as a key cerebrovascular interface, dynamically insulating the brain parenchyma from peripheral blood and compartments. Increased BBB permeability is clinically relevant for at least two reasons: it actively participates to the etiology of central nervous system (CNS) diseases, and it enables the diagnosis of neurological disorders based on the detection of CNS molecules in peripheral body fluids. In pathological conditions, a suite of glial, neuronal, and pericyte biomarkers can exit the brain reaching the peripheral blood and, after a process of filtration, may also appear in saliva or urine according to varying temporal trajectories. Here, we specifically examine the evidence in favor of or against the use of protein biomarkers of NVU damage and BBB permeability in traumatic head injury, including sport (sub)concussive impacts, seizure disorders, and neurodegenerative processes such as Alzheimer's disease. We further extend this analysis by focusing on the correlates of human extreme physiology applied to the NVU and its biomarkers. To this end, we report NVU changes after prolonged exercise, freediving, and gravitational stress, focusing on the presence of peripheral biomarkers in these conditions. The development of a biomarker toolkit will enable minimally invasive routines for the assessment of brain health in a broad spectrum of clinical, emergency, and sport settings.

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.

Salivary biomarkers associated with obstructive sleep apnea: a systematic review

Introduction: This study aimed to define and characterize current literature describing salivary biomarker changes with the goal of improving diagnosis and treatment outcomes for sleep apnea.Area Covered: A search of six databases yielded 401 peer-reviewed articles published through October 2019 corresponded to 221 unique references following deduplication. Twenty studies were selected. The sample size ranged from 17 to 99. The samples were mostly whole saliva and selected glandular areas.Expert Opinion: Most targeted studies focused on the level of salivary cortisol and ɑ-amylase. One study used RNA transcriptome analysis of 96 genes. Only two explored novel targets using mass spectrometry. ɑ-amylase, myeloperoxidase, and IL-6 were among those biomarkers found associated with OSA. Cytokeratin, CystatinB, calgranulin A, and alpha-2-HS-glycoprotein are upregulated in OSA patients based on non-targeting mass spectrometry. Salivary cortisol and ɑ-amylase and others appeared to be associated with severity of OSA and OSA treatment. There were inconsistencies in saliva collection and processing protocols. More studies are needed in exploring novel biomarkers to examine if these biomarkers are capable of diagnosing and monitoring OSA through proteomics or transcriptomics. Salivary biomarkers have a potential to be a noninvasive measure for the disease diagnosis and treatment outcome monitoring for sleep apnea.

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.

Peptidomics-Driven Strategy Reveals Peptides and Predicted Proteases Associated With Oral Cancer Prognosis

Protease activity has been associated with pathological processes that can lead to cancer development and progression. However, understanding the pathological unbalance in proteolysis is challenging because changes can occur simultaneously at protease, their inhibitor, and substrate levels. Here, we present a pipeline that combines peptidomics, proteomics, and peptidase predictions for studying proteolytic events in the saliva of 79 patients and their association with oral squamous cell carcinoma (OSCC) prognosis. Our findings revealed differences in the saliva peptidome of patients with (pN+) or without (pN0) lymph-node metastasis and delivered a panel of ten endogenous peptides correlated with poor prognostic factors plus five molecules able to classify pN0 and pN+ patients (area under the receiver operating characteristic curve > 0.85). In addition, endopeptidases and exopeptidases putatively implicated in the processing of differential peptides were investigated using cancer tissue gene expression data from public repositories, reinforcing their association with poorer survival rates and prognosis in oral cancer. The dynamics of the OSCC-related proteolysis were further explored via the proteomic profiling of saliva. This revealed that peptidase/endopeptidase inhibitors exhibited reduced levels in the saliva of pN+ patients, as confirmed by selected reaction monitoring-mass spectrometry, while minor changes were detected in the level of saliva proteases. Taken together, our results indicated that proteolytic activity is accentuated in the saliva of patients with OSCC and lymph-node metastasis and, at least in part, is modulated by reduced levels of salivary peptidase inhibitors. Therefore, this integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis.

Analysis of Multimerin 1 (MMRN1) expression in ovarian cancer

Ovarian cancer, the most lethal gynecological cancer, is the fifth most common cause of cancer-related deaths in women. A cost-effective and non-invasive early screening method for ovarian cancer is required to reduce the high mortality rate. Saliva is a clinically informative unique fluid, which is useful for novel approaches to prognosis, clinical diagnosis, and monitoring for non-invasive detection of disease. Multimerin1 (MMRN1) is a di-sulfide linked homo-polymeric glycoprotein from EMILIN family. Altered expression of MMRN1 has been reported in hepatocellular carcinoma, cervical cancer, and ovarian cancer. But, its role in epithelial ovarian cancer (EOC) is not clear and well documented. In this study, expression of Multimerin 1 was validated in saliva and tissues of EOC patients and age-matched controls by western blotting, ELISA, RT-PCR, and immunohistochemistry. Significant over expression of MMRN1 was observed by western blot and ELISA in saliva samples of EOC patients. The average concentration of MMRN1 in the saliva of healthy controls was 28.7 pg/ml (SE ± 1.76), 42.53 pg/ml (SE ± 4.06) in low grade and 52.91 pg/ml (SE ± 4.24) with p < 0.01 in high-grade EOC. Upregulated cytoplasmic expression of MMRN1 was observed in EOC tissue by immunohistochemistry. Our results suggest that MMRN1 expression is associated with EOC progression and MMRN1 may be potential biomarker candidates for early-stage EOC detection however further experiments are required in a large cohort to establish this proposition. Also, saliva can be explored as a novel medium for ovarian cancer diagnosis.

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.

Functional Specialization of Human Salivary Glands and Origins of Proteins Intrinsic to Human Saliva

Salivary proteins are essential for maintaining health in the oral cavity and proximal digestive tract, and they serve as potential diagnostic markers for monitoring human health and disease. However, their precise organ origins remain unclear. Through transcriptomic analysis of major adult and fetal salivary glands and integration with the saliva proteome, the blood plasma proteome, and transcriptomes of 28+ organs, we link human saliva proteins to their source, identify salivary-gland-specific genes, and uncover fetal- and adult-specific gene repertoires. Our results also provide insights into the degree of gene retention during gland maturation and suggest that functional diversity among adult gland types is driven by specific dosage combinations of hundreds of transcriptional regulators rather than by a few gland-specific factors. Finally, we demonstrate the heterogeneity of the human acinar cell lineage. Our results pave the way for future investigations into glandular biology and pathology, as well as saliva's use as a diagnostic fluid.

THE ROLE OF NEW TECHNOLOGIES IN DEFINING SALIVARY PROTEIN COMPOSITION FOLLOWING PLACEMENT OF FIXED ORTHODONTIC APPLIANCES - BREAKTHROUGH IN THE DEVELOPMENT OF NOVEL DIAGNOSTIC AND THERAPEUTIC PROCEDURES

Human saliva is rich in proteins of variable functions (e.g., enzymes, immunoglobulins, cytokines) and origin (blood plasma, salivary glands, or oral microflora). Circadian dynamics, volume and composition (electrolytes, pH, protein, etc.) of secreted saliva vary with local and systemic physiological and pathophysiological conditions. Therefore, the composition of saliva, protein in particular, has been intensively investigated to identify the potential markers and/or mechanisms of systemic and local diseases. Proteomic techniques used for the analysis of biological fluids have enabled great advances in salivary protein stabilization (as the main precondition for their analysis) and detection of those found in saliva in very low concentrations, including small proteins and peptides. This review brings the main characteristics of current proteomic techniques such as liquid chromatography-mass spectrometry, two-dimensional electrophoresis-mass spectrometry, and surface-enhanced laser desorption ionization/time of flight/mass spectrometry. These techniques enable simultaneous identification of hundreds and thousands of protein molecules, as well as identifying those of a potential biological value in particular states. This literature review is focused on the state-of-the-art and possibilities offered by proteomic techniques in analyzing the effects of orthodontic appliances on salivary protein composition and searching for potential markers of therapeutic success/failure or for the molecules by which therapeutic effects are achieved.

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.

Is there thrombin-activatable fibrinolysis inhibitor in saliva?

The purpose of this study was to identify thrombin-activatable fibrinolysis inhibitor (TAFI) in saliva and to investigate the correlation between TAFI levels in saliva and plasma. Subjects included were healthy adults without diseases or medication that could affect coagulation. Samples of stimulated saliva and blood samples were obtained from 33 subjects. Levels of TAFI in saliva and plasma were analysed. The association between levels of TAFI in saliva and plasma was calculated using linear regression. Low levels of TAFIa/TAFIai were found in most saliva samples but only one sample had levels that were above the lower limit of detection of the assay used. TAFI (proenzyme) was not found in saliva, so no correlations could be calculated. In this study there was no indication that there is TAFI present in secreted saliva. Either TAFIa/TAFIai in saliva were much lower than in plasma and under the detection limit of the assay used, or there was no TAFIa/TAFIai in the saliva tested.

Salivary proteome signatures in the early and middle stages of human pregnancy with term birth outcome

The establishment and maintenance of pregnancy in humans proceed through a continuous change of biochemical and biophysical processes. It requires a constant interaction between the fetus and the maternal system. The present prospective study aims to elucidate changes in salivary proteome from the early to middle stages of term pregnancy, and establishing an expressional trajectory for modulated proteins. To date, a comprehensive characterization of the longitudinal salivary proteome in pregnancy has not been performed and it is our immediate interest. In the discovery phase, maternal saliva (N = 20) at 6–13, 18–21, and 26–29 weeks of gestation was analyzed using level-free proteomics (SWATH-MS) approach. The expression levels of 65 proteins were found to change significantly with gestational age and distributed into two distinct clusters with a unique expression trajectory. The results revealed that altered proteins are involved in maternal immune modulation, metabolism, and host defense mechanism. Further, verification of 12 proteins was employed using targeted mass spectrometry (MRM-MS) in a separate subset of saliva (N = 14). The MRM results of 12 selected proteins confirmed a similar expression pattern as in SWATH-MS analysis. Overall, the results not only demonstrate the longitudinal maternal saliva proteome for the first time but also set the groundwork for comparative analysis between term birth and adverse pregnancy outcomes.

Usefulness of saliva for perampanel therapeutic drug monitoring

OBJECTIVE

Therapeutic drug monitoring (TDM) of antiepileptic drugs (AEDs) helps optimize drug management for patients with epilepsy. Salivary testing is both noninvasive and easy, and has several other advantages. Due to technical advances, salivary TDM has become feasible for several drugs, including AEDs, and its value has been investigated. Until recently, saliva TDM of perampanel (PER) had not been reported. The purpose of our study was to confirm whether saliva is a biological substitute for plasma in PER TDM.

METHODS

Adult patients diagnosed with epilepsy who received PER from August 2018 to March 2019 at Seoul National University Hospital were enrolled. Total and free PER were measured in simultaneously obtained plasma and saliva samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatographic (HPLC). We examined the correlations between saliva and plasma PER concentrations and whether the use of concomitant medications classified as cytochrome P450 (CYP)3A4 inducers affected the correlations.

RESULTS

Thirty patients were enrolled, aged 16 to 60; 10 (33%) were women. Patients received 2 to 12 mg (mean, 6 mg) of PER. The average total and free concentrations of PER were 343.02 (46.6-818.0) and 1.53 (0.51-2.92) ng/mL in plasma and 9.74 (2.21-33.0) and 2.83 (1.01-6.8) ng/mL in saliva, respectively. A linear relationship was observed between the total PER concentrations in saliva and the total and free PER concentrations in plasma (both P < .001; r = .678 and r = .619, respectively). The change in the PER concentration caused by the CYP3A4 inducer did not affect the correlation between saliva and plasma concentrations (all P < .001).

SIGNIFICANCE

The PER concentration in saliva was correlated with that in plasma. This correlation was not affected by CYP3A4 inducers. Our results demonstrate for the first time that PER is measurable in saliva and suggest the potential for the clinical application of the saliva PER TDM matrix.

Correlation of molecular biomarker concentrations between synovial fluid and saliva of the patients with temporomandibular disorders

OBJECTIVES

The synovial membrane and fluid are involved in the pathogenesis of temporomandibular joint (TMJ) disorders. This study aims to assess the relationship between matrix metalloproteinase-2 (MMP-2), chemerin and prostaglandin (PGE₂) levels in the synovial fluid (SF) and saliva of patients with TMJ disorder regarding their role in inflammation and the value of being a candidate for predictive biomarkers in the disease. Also, it is aimed to find out whether chemerin's main function triggers the formation inflammatory cytokine markers in the associated area.

MATERIALS AND METHODS

Thirty-two samples of SF and saliva were obtained from patients with disc displacement without reduction with limited opening (DDWORwLO). Mann-Whitney-U test was used for the comparisons of the biomarker levels in SF and saliva. The correlation between chemerin and BMI (Body Mass Index) is analyzed by non-parametric Spearman's rho correlation coefficient.

RESULTS

For all of the three biomarkers, statistically significant differences were found between SF and saliva. An unexpectedly high level expression of chemerin was observed in SF. A statistically significant, positive correlation was observed between PGE₂ -MMP-2, and chemerin-PGE₂ in saliva, chemerin and MMP-2 in SF, respectively (p = 0.031, r = 0.382 / p = 0.039, r = 0.366 / p = 0.032, r = 0.379). A positive correlation was determined between saliva and SF levels of PGE₂ (p = 0.016, r = 0.421).

CONCLUSIONS

Chemerin, MMP-2, and PGE₂ can play a role as an inflammatory factor for the development of TMJ disorder.

CLINICAL RELEVANCE

The search for molecular markers in TMJ and the inhibition of the associated molecular signaling mechanism is important to reduce joint inflammation and cartilage degradation.

Proteomic profile of the saliva and plasma protein layer adsorbed on Ti-Zr alloy: the effect of sandblasted and acid-etched surface treatment

Titanium-zirconium (Ti-Zr) alloy has been widely used as a biomaterial for implant devices, and it is commonly treated by sandblasting followed by acid etching (SLA) to improve biological responses. Although protein adsorption is the first biological response, the effect of this SLA treatment on the proteomic profile of proteins adsorbed from saliva and blood plasma has not been tested. In this study, the proteomic profile was evaluated by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Streptococcus sanguinis was used to test whether the protein layer affects bacterial adhesion. SLA treatment affected the proteomic profile, showing exclusive proteins adsorbed from saliva (14) and plasma (3). However, both groups exhibited close patterns of intensity for common proteins, molecular functions and biological processes mediated by proteins. Interestingly, Ti-Zr_SLA showed higher bacterial adhesion (∼1.9 fold over) for the surface coated with plasma proteins. Therefore, SLA treatment of Ti-Zr alloy changed the proteomic profile, which may affect bacterial adhesion.

Classifying dementia progression using microbial profiling of saliva

INTRODUCTION

There is increasing evidence linking periodontal infections to Alzheimer's disease (AD). Saliva sampling can reveal information about the host and pathogen interactions that can inform about physiological and pathological brain states.

METHODS

A cross-sectional cohort of age-matched participants (78) was segmented according to their chemosensory (University of Pennsylvania Smell Identification Test; UPSIT) and cognitive scores (Mini-Mental State Exam; MMSE and clinical dementia rating; CDR). Mid-morning saliva was sampled from each participant and processed for microbiome composition and cytokine analysis. Linear discriminant analysis (LDA) was used to unravel specific changes in microbial and immunological signatures and logistic regression analysis (LRA) was employed to identify taxa that varied in abundance among patient groups.

RESULTS

Using olfaction we distinguish in the cognitively normal population a segment with high chemosensory scores (CNh, 27) and another segment with chemosensory scores (CNr, 16) as low as mild cognitive impairment (MCI, 21) but higher than the AD group (17). We could identify stage-specific microbial signatures changes but no clearly distinct cytokine profiles. Periodontal pathogen species as Filifactor villosus decline with the increasing severity of AD, whereas opportunistic oral bacteria such as Leptotrichia wadei show a significant enrichment in MCI.

CONCLUSIONS

The salivary microbiome indicates stage-dependent changes in oral bacteria favoring opportunistic species at the expense of periodontal bacteria, whereas the inflammatory profiles remain mainly unchanged in the sampled population.