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

Human buccal epithelial cells as a model system for molecular analysis of DNA, RNA and protein

We report use of human buccal epithelial cells as an easy model system for isolation and molecular analysis of genomic DNA, RNA, and protein to study any gene of interest by Polymerase Chain Reaction (PCR), RNA expression by Reverse Transcription-PCR (RT-PCR), protein-profiling, and expression by western blot as well as DNA-methylation by Msp I/Hpa II-restriction digestion. We used simple methods to isolate genomic DNA, RNA and protein from human buccal cells collected by oral swab and cultured them in-vitro. The microscopic observation of haematoxylin and eosin (EA-50) stained cells, genomic PCR of house-keeping genes (GAPDH and β-actin), RT-PCR of GAPDH and β-actin mRNAs and whole cell protein-profiling by Sodium Dodecyl Sulphate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) were carried out. Expression of β-actin protein in supernatant and pellet fractions of the cells was determined by western blot analysis. MTT-assay was carried out to assess the cell viability and cell growth. Green Fluorescence Protein (GFP)-DNA was expressed in these cells by transient transfection. DNA-methylation in the genome was analyzed by Msp I/ Hpa II restriction digestion and agarose gel electrophoresis. Thus these methods can be used for molecular analysis of DNA, RNA and protein from the human buccal epithelial cells for studying and monitoring health, disease, population genetics/genomics and epidemiology under different conditions.

Human Serum and Salivary Metabolomes: Diversity and Closeness

Saliva, which contains molecular information that may reflect an individual's health status, has become a valuable tool for discovering biomarkers of oral and general diseases. Due to the high vascularization of the salivary glands, there is a molecular exchange between blood and saliva. However, the composition of saliva is complex and influenced by multiple factors. This study aimed to investigate the possible relationships between the salivary and serum metabolomes to gain a comprehensive view of the metabolic phenotype under physiological conditions. Using 1H-NMR spectroscopy, we obtained the serum metabolite profiles of 20 healthy young individuals and compared them with the metabolomes of parotid, submandibular/sublingual, and whole-saliva samples collected concurrently from the same individuals using multivariate and univariate statistical analysis. Our results show that serum is more concentrated and less variable for most of the shared metabolites than the three saliva types. While we found moderate to strong correlations between serum and saliva concentrations of specific metabolites, saliva is not simply an ultrafiltrate of blood. The intense oral metabolism prevents very strong correlations between serum and salivary concentrations. This study contributes to a better understanding of salivary metabolic composition, which is crucial for utilizing saliva in laboratory diagnostics.

Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends

The assessment of volatile breath biomarkers has been targeted with a lot of interest by the scientific and medical communities during the past decades due to their suitability for an accurate, painless, non-invasive, and rapid diagnosis of health states and pathological conditions. This paper reviews the most relevant bibliographic sources aiming to gather the most pertinent volatile organic compounds (VOCs) already identified as putative cancer biomarkers. Here, a total of 265 VOCs and the respective bibliographic sources are addressed regarding their scientifically proven suitability to diagnose a total of six carcinogenic diseases, namely lung, breast, gastric, colorectal, prostate, and squamous cell (oesophageal and laryngeal) cancers. In addition, future trends in the identification of five other forms of cancer, such as bladder, liver, ovarian, pancreatic, and thyroid cancer, through perspective volatile breath biomarkers are equally presented and discussed. All the results already achieved in the detection, identification, and quantification of endogenous metabolites produced by all kinds of normal and abnormal processes in the human body denote a promising and auspicious future for this alternative diagnostic tool, whose future passes by the development and employment of newer and more accurate collection and analysis techniques, and the certification for utilisation in real clinical scenarios.

Correlation between use of different type protective facemasks and the oral ecosystem

BACKGROUND

Spread worldwide through droplets, the Virus Sars-Cov-19 has caused a global health emergency alarm. In order to limit its spread, the use of masks has become part of the daily life of the entire population, however, little is known about its constant use and the changes generated in the oral cavity. This work aims to investigate correlations between the continuous use of masks covering the nose and mouth for 3 h and changes in the ecological factors of the oral cavity.

METHODS

34 volunteers were divided into 2 groups: wear only the filtering facepiece code 2 (FFP2) mask (Group A) and wear the FFP2 mask covered by a surgical mask (Group B). Measurement of Volatile Organic Compounds (VOCs), saliva rehydration and consistency test, collection of basal saliva and saliva stimulated with paraffin gum and mucosal swab were collected and analyzed at two times: before using the mask(s) (T0) and 3 h after continuous use of the mask(s) (T1).

RESULTS

The results indicated a significant difference between the groups, in which the basal saliva volume and pH and the peaks of VOCs increased for group B between T0 and T1. The rehydration time decreased and the volume and pH of the stimulated saliva increased, but with no significant difference between the groups. Furthermore, group B showed a significant decrease in Candida albicans Colony Forming Units (CFUs) and Total Bacterial Count (TBC) between T0 and T1.

CONCLUSION

It is concluded that the prolonged use of the FFP2 mask covered by a surgical mask can generate oral alterations in the user.

Breath volatile organic compounds (VOCs) as biomarkers for the diagnosis of pathological conditions: A review

Normal and abnormal/pathological status of physiological processes in the human organism can be characterized through Volatile Organic Compounds (VOCs) emitted in breath. Recently, a wide range of volatile analytes has risen as biomarkers. These compounds have been addressed in the scientific and medical communities as an extremely valuable metabolic window. Once collected and analysed, VOCs can represent a tool for a rapid, accurate, non-invasive, and painless diagnosis of several diseases and health conditions. These biomarkers are released by exhaled breath, urine, faeces, skin, and several other ways, at trace concentration levels, usually in the ppbv (μg/L) range. For this reason, the analytical techniques applied for detecting and clinically exploiting the VOCs are extremely important. The present work reviews the most promising results in the field of breath biomarkers and the most common methods of detection of VOCs. A total of 16 pathologies and the respective database of compounds are addressed. An updated version of the VOCs biomarkers database can be consulted at: https://neomeditec.com/VOCdatabase/.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part III: Implementations for the Diagnosis of Non-Cancerous Disorders, Both Oral and Systemic

This communication represents Part III of our series of reports based on the applications of human saliva as a useful and conveniently collectable medium for the discovery, identification and monitoring of biomarkers, which are of some merit for the diagnosis of human diseases. Such biomarkers, or others reflecting the dysfunction of specific disease-associated metabolic pathways, may also be employed for the prognostic pathological tracking of these diseases. Part I of this series set the experimental and logistical groundwork for this report, and the preceding paper, Part II, featured the applications of newly developed metabolomics technologies to the diagnosis and severity grading of human cancer conditions, both oral and systemic. Clearly, there are many benefits, both scientific and economic, associated with the donation of human saliva samples (usually as whole mouth saliva) from humans consenting to and participating in investigations focused on the discovery of biomolecular markers of diseases. These include usually non-invasive collection protocols, relatively low cost when compared against blood sample collection, and no requirement for clinical supervision during collection episodes. This paper is centred on the employment and value of 'state-of-the-art' metabolomics technologies to the diagnosis and prognosis of a wide range of non-cancerous human diseases. Firstly, these include common oral diseases such as periodontal diseases (from type 1 (gingivitis) to type 4 (advanced periodontitis)), and dental caries. Secondly, a wide range of extra-oral (systemic) conditions are covered, most notably diabetes types 1 and 2, cardiovascular and neurological diseases, and Sjögren's syndrome, along with a series of viral infections, e.g., pharyngitis, influenza, HIV and COVID-19. Since the authors' major research interests lie in the area of the principles and applications of NMR-linked metabolomics techniques, many, but not all, of the studies reviewed were conducted using these technologies, with special attention being given to recommended protocols for their operation and management, for example, satisfactory experimental model designs; sample collection and laboratory processing techniques; the selection of sample-specific NMR pulse sequences for saliva analysis; and strategies available for the confirmation of resonance assignments for both endogenous and exogenous molecules in this biofluid. This article also features an original case study, which is focussed on the use of NMR-based salivary metabolomics techniques to provide some key biomarkers for the diagnosis of pharyngitis, and an example of how to 'police' such studies and to recognise participants who perceive that they actually have this disorder but do not from their metabolic profiles and multivariate analysis pattern-based clusterings. The biochemical and clinical significance of these multidimensional metabolomics investigations are discussed in detail.

A novel set of volatile urinary biomarkers for late-life major depressive and anxiety disorders upon the progression of frailty: a pilot study

Mood and anxiety disorders are frequent in the elderly and increase the risk of frailty. This study aimed to identify novel biomarkers of major depressive disorder (MDD) and anxiety in the elderly. We examined 639 participants in the community-dwelling Otassha Study (518 individuals considered healthy control, 77 with depression, anxiety, etc.), mean age 75 years, 58.4% of female. After exclusion criteria, we analyzed VOCs from 18 individuals (9 healthy control, 9 of MDD/agoraphobia case). Urinary volatile and semi-volatile organic compounds (VOCs) were profiled using solid-phase microextraction and gas chromatography-mass spectrometry. Six urinary VOCs differed in the absolute area of the base peak between participants with MDD and/or agoraphobia and controls. High area under the receiver-operating characteristic curve (AUC) values were found for phenethyl isothiocyanate (AUC: 0.86, p = 0.009), hexanoic acid (AUC: 0.85, p = 0.012), texanol (AUC: 0.99, p = 0.0005), and texanol isomer (AUC: 0.89, p = 0.005). The combined indices of dimethyl sulfone, phenethyl isothiocyanate, and hexanoic acid, and texanol and texanol isomer showed AUCs of 0.91 (p = 0.003) and 0.99 (p = 0.0005) and correlated with the GRID-HAMD and the Kihon Checklist (CL score), respectively. These VOCs may be valuable biomarkers for evaluating MDD and/or agoraphobia in the elderly.

Analysis of volatile organic compounds from deep airway in the lung through intubation sampling

Exhaled volatile organic compounds (VOCs) have been widely applied for the study of disease biomarkers. Oral exhalation and nasal exhalation are two of the most common sampling methods. However, VOCs released from food residues and bacteria in the mouth or upper respiratory tract were also sampled and usually mistaken as that produced from body metabolism. In this study, exhalation from deep airway was first directly collected through intubation sampling and analyzed. The exhalation samples of 35 subjects were collected through a catheter, which was inserted into the trachea or bronchus through the mouth and upper respiratory tract. Then, the VOCs in these samples were detected by proton transfer reaction mass spectrometry (PTR-MS). In addition, fast gas chromatography proton transfer reaction mass spectrometry (FGC-PTR-MS) was used to further determine the VOCs with the same mass-to-charge ratios. The results showed that there was methanol, acetonitrile, ethanol, methyl mercaptan, acetone, isoprene, and phenol in the deep airway. Compared with that in oral exhalation, ethanol, methyl mercaptan, and phenol had lower concentrations. In detail, the median concentrations of ethanol, methyl mercaptan, and phenol were 7.3, 0.6, and 23.9 ppbv, while those in the oral exhalation were 80.0, 5.1, and 71.3 ppbv, respectively, which meant the three VOCs mainly originated from the food residues and bacteria in the mouth or upper respiratory tract, rather than body metabolism. The research results in our study can provide references for expiratory VOC research based on oral and nasal exhalation samplings, which are more feasible in clinical practice.

Emerging Biosensors for Oral Cancer Detection and Diagnosis—A Review Unravelling Their Role in Past and Present Advancements in the Field of Early Diagnosis

Oral cancer is a serious concern to people all over the world because of its high mortality rate and metastatic spread to other areas of the body. Despite recent advancements in biomedical research, OC detection at an early stage remains a challenge and is complex and inaccurate with conventional diagnostics procedures. It is critical to study innovative approaches that can enable a faster, easier, non-invasive, and more precise diagnosis of OC in order to increase the survival rate of patients. In this paper, we conducted a review on how biosensors might be an excellent tool for detecting OC. This review covers the strategies that use different biosensors to target various types of biomarkers and focuses on biosensors that function at the molecular level viz. DNA biosensors, RNA biosensors, and protein biosensors. In addition, we reviewed non-invasive electrochemical methods, optical methods, and nano biosensors to analyze the OC biomarkers present in body fluids such as saliva and serum. As a result, this review sheds light on the development of ground-breaking biosensors for the early detection and diagnosis of OC.

Salivary Gland Function, Development and Regeneration

Salivary glands produce and secrete saliva, which is essential for maintaining oral health and overall health. Understanding both the unique structure and physiological function of salivary glands, as well as how they are affected by disease and injury will direct the development of therapy to repair and regenerate them. Significant recent advances, particularly in the OMICS field, increase our understanding of how salivary glands develop at the cellular, molecular and genetic levels; the signaling pathways involved, the dynamics of progenitor cell lineages in development, homeostasis and regeneration and the role of the extracellular matrix microenvironment. These provide a template for cell and gene therapies as well as bioengineering approaches to repair or regenerate salivary function.

Oxidation, Glycation, and Carbamylation of Salivary Biomolecules in Healthy Children, Adults, and the Elderly: Can Saliva Be Used in the Assessment of Aging?

Background

Aging is inextricably linked to oxidative stress, inflammation, and posttranslational protein modifications. However, no studies evaluate oxidation, glycation, and carbamylation of salivary biomolecules as biomarkers of aging. Saliva collection is non-invasive, painless, and inexpensive, which are advantages over other biofluids.

Methods

The study enrolled 180 healthy subjects divided into six groups according to age: 6–13, 14–19, 20–39, 40–59, 60–79, and 80–100 years. The number of individuals was determined a priori based on our previous experiment (power of the test = 0.8; α = 0.05). Non-stimulated saliva and plasma were collected from participants, in which biomarkers of aging were determined by colorimetric, fluorometric, and ELISA methods.

Results

The study have demonstrated that modifications of salivary proteins increase with age, as manifested by decreased total thiol levels and increased carbonyl groups, glycation (Nε-(carboxymethyl) lysine, advanced glycation end products (AGE)) and carbamylation (carbamyl-lysine) protein products in the saliva of old individuals. Oxidative modifications of lipids (4-hydroxynonenal) and nucleic acids (8-hydroxy-2’-deoxyguanosine (8-OHdG)) also increase with age. Salivary redox biomarkers correlate poorly with their plasma levels; however, salivary AGE and 8-OHdG generally reflect their blood concentrations. In the multivariate regression model, they are a predictor of aging and, in the receiver operating characteristic (ROC) analysis, significantly differentiate children and adolescents (under 15 years old) from the working-age population (15–64 years) and the older people (65 years and older).

Conclusion

Salivary AGE and 8-OHdG have the most excellent diagnostic utility in assessing the aging process. Saliva can be used to evaluate the aging of the body.

Malignancies and Biosensors: A Focus on Oral Cancer Detection through Salivary Biomarkers

Oral cancer is among the deadliest types of malignancy due to the late stage at which it is usually diagnosed, leaving the patient with an average five-year survival rate of less than 50%. The booming field of biosensing and point of care diagnostics can, in this regard, play a major role in the early detection of oral cancer. Saliva is gaining interest as an alternative biofluid for non-invasive diagnostics, and many salivary biomarkers of oral cancer have been proposed. While these findings are promising for the application of salivaomics tools in routine practice, studies on larger cohorts are still needed for clinical validation. This review aims to summarize the most recent development in the field of biosensing related to the detection of salivary biomarkers commonly associated with oral cancer. An introduction to oral cancer diagnosis, prognosis and treatment is given to define the clinical problem clearly, then saliva as an alternative biofluid is presented, along with its advantages, disadvantages, and collection procedures. Finally, a brief paragraph on the most promising salivary biomarkers introduces the sensing technologies commonly exploited to detect oral cancer markers in saliva. Hence this review provides a comprehensive overview of both the clinical and technological advantages and challenges associated with oral cancer detection through salivary biomarkers.

Evaluation of salivary VOC profile composition directed towards oral cancer and oral lesion assessment

OBJECTIVES

Endogenous substances have been analyzed in biological samples in order to be related with metabolic dysfunctions and diseases. The study aimed to investigate profiles of volatile organic compounds (VOCs) from fresh and incubated saliva donated by healthy controls, individuals with oral tissue lesions and with oral cancer, in order to assess case-specific biomarkers of oxidative stress.

MATERIALS AND METHODS

VOCs were pre-concentrated using headspace-solid phase microextraction and analyzed using gas chromatography-mass spectrometry. Then, VOCs positively modulated by incubation process were subtracted, yielding profiles with selected features. Principal component analysis and hierarchical cluster analysis were used to inspect data distribution, while univariate statistics was applied to indicate potential markers of oral cancer. Machine learning algorithm was implemented, aiming multiclass prediction.

RESULTS

The removal of bacterial contribution to VOC profiles allowed the obtaining of more specific case-related patterns. Artificial neural network model included 9 most relevant compounds (1-octen-3-ol, hexanoic acid, E-2-octenal, heptanoic acid, octanoic acid, E-2-nonenal, nonanoic acid, 2,4-decadienal and 9-undecenoic acid). Model performance was assessed using 10-fold cross validation and receiver operating characteristic curves. Obtained overall accuracy was 90%. Oral cancer cases were predicted with 100% of sensitivity and specificity.

CONCLUSIONS

The selected VOCs were ascribed to lipid oxidation mechanism and presented potential to differentiate oral cancer from other inflammatory conditions.

CLINICAL RELEVANCE

These results highlight the importance of interpretation of saliva composition and the clinical value of salivary VOCs. Elucidated metabolic alterations have the potential to aid the early detection of oral cancer and the monitoring of oral lesions.