Untargeted metabolomic profiling in saliva of smokers and nonsmokers by a validated GC-TOF-MS method

A comprehensive non-targeted approach for the analysis of biomarkers in exhaled breath across different nicotine product categories

In the context of the evolving landscape of nicotine consumption, the assessment of biomarkers plays a crucial role in understanding the health impact of different product categories. Exhaled breath (EB) emerges as a promising, non-invasive matrix for biomarker analysis, complementary to conventional urine and plasma data. This study explores distinctive EB biomarker profiles among users of combustible cigarettes (CC), heated tobacco products (HTP), electronic cigarettes (EC), smokeless/oral tobacco (OT), and oral/dermal nicotine products (NRT). We have successfully developed and validated a non-targeted GC-TOF-MS method for the analysis of EB samples across the aforementioned product categories. A total of 66 compounds were identified, with significantly elevated levels in at least one study group. The study found that CC users had higher levels of established VOCs associated with smoking, which supports the proof-of-concept of the method. Breathomic analysis identified increased levels of p-cymene and α-pinene in EC users, while HTP users showed potential biomarker candidates like γ-butyrolactone. This study underscores the utility of EB biomarkers for a comprehensive evaluation of diverse nicotine products. The unique advantages offered by EB analysis position it as a valuable tool for understanding the relationship between exposure and health outcomes.

Metabolomics for dental caries diagnosis: Past, present, and future

Dental caries, a prevalent global infectious condition affecting over 95% of adults, remains elusive in its precise etiology. Addressing the complex dynamics of caries demands a thorough exploration of taxonomic, potential, active, and encoded functions within the oral ecosystem. Metabolomic profiling emerges as a crucial tool, offering immediate insights into microecosystem physiology and linking directly to the phenotype. Identified metabolites, indicative of caries status, play a pivotal role in unraveling the metabolic processes underlying the disease. Despite challenges in metabolite variability, the use of metabolomics, particularly via mass spectrometry and nuclear magnetic resonance spectroscopy, holds promise in caries research. This review comprehensively examines metabolomics in caries prevention, diagnosis, and treatment, highlighting distinct metabolite expression patterns and their associations with disease-related bacterial communities. Pioneering in approach, it integrates singular and combinatory metabolomics methodologies, diverse biofluids, and study designs, critically evaluating prior limitations while offering expert insights for future investigations. By synthesizing existing knowledge, this review significantly advances our comprehension of caries, providing a foundation for improved prevention and treatment strategies.

Maternal and newborn metabolomic changes associated with urinary polycyclic aromatic hydrocarbon metabolite concentrations at delivery: an untargeted approach

INTRODUCTION

Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse human health outcomes. To explore the plausible associations between maternal PAH exposure and maternal/newborn metabolomic outcomes, we conducted a cross-sectional study among 75 pregnant people from Cincinnati, Ohio.

METHOD

We quantified 8 monohydroxylated PAH metabolites in maternal urine samples collected at delivery. We then used an untargeted high-resolution mass spectrometry approach to examine alterations in the maternal (n = 72) and newborn (n = 63) serum metabolome associated with PAH metabolites. Associations between individual maternal urinary PAH metabolites and maternal/newborn metabolome were assessed using linear regression adjusted for maternal and newborn factors while accounting for multiple testing with the Benjamini-Hochberg method. We then conducted functional analysis to identify potential biological pathways.

RESULTS

Our results from the metabolome-wide associations (MWAS) indicated that an average of 1% newborn metabolome features and 2% maternal metabolome features were associated with maternal urinary PAH metabolites. Individual PAH metabolite concentrations in maternal urine were associated with maternal/newborn metabolome related to metabolism of vitamins, amino acids, fatty acids, lipids, carbohydrates, nucleotides, energy, xenobiotics, glycan, and organic compounds.

CONCLUSION

In this cross-sectional study, we identified associations between urinary PAH concentrations during late pregnancy and metabolic features associated with several metabolic pathways among pregnant women and newborns. Further studies are needed to explore the mediating role of the metabolome in the relationship between PAHs and adverse pregnancy outcomes.

Utility of salivary biomarkers for diagnosis and monitoring the prognosis of nicotine addiction - A systematic review

Objectives

Tobacco and smoke associated with tobacco comprises of a mixture of more than 9500 chemical compounds, most of which have been identified as harmful. Two of the most potent carcinogens found in cigarette smoke are N'-nitrosonornicotine (NNN) and polycyclic aromatic hydrocarbons (PAHs). The most commonly used method to detect and monitor nicotine addiction is via serum cotinine levels. Though considered the gold standard, there is a decline in preventive screening and diagnostic testing due to the fear of pain from invasive testing.

Data sources and study selection

A structured literature search was performed using the search engines PubMed and Google scholar following the PRISMA guidelines for systematic reviews. The titles and abstracts were retrieved and analysed, followed by full-text relevant data extraction in addition to a risk-of-bias analysis.

Data extraction and synthesis

A total of 37 studies were included in the systematic review. Salivary cotinine levels were compared between smokers and non-smokers, cigarette smokers and water pipe smokers, water pipe smokers and non-smokers. Lactate dehydrogenase salivary levels were compared between smokers and non-smokers, and salivary thiocyanate were compared between smokers and non-smokers.

Conclusions

Identifying biomarkers with high performance in terms of sensitivity and specificity will contribute to accelerating future research in this domain.

Preliminary Findings on the Salivary Metabolome of Hookah and Cigarette Smokers

The aim of the study was to evaluate the salivary metabolomic profile of patients who habitually smoke hookah and cigarettes. The groups consisted of 33 regular and exclusive hookah smokers, 26 regular and exclusive cigarette smokers, and 30 nonsmokers. Unstimulated whole saliva was collected for the measurement of salivary metabolites by gas chromatography coupled with tandem mass spectrometry (GC-MS/MS). The MetaboAnalyst software was used for statistical analysis and evaluation of biomarkers. 11 smoking salivary biomarkers were identified using the area under receiving-operator curver criterion and threshold of 0.9. Xylitol and octadecanol were higher in cigarette smokers compared to controls; arabitol and maltose were higher in controls compared to cigarette smokers; octadecanol and tyramine were higher in hookah smokers compared to controls; phenylalanine was higher in controls compared to hookah smokers; and fructose, isocitric acid, glucuronic acid, tryptamine, maltose, tyramine, and 3-hydroxyisolvaleric acid were higher in hookah smokers compared to cigarettes smokers. Conclusions: The evaluation of the salivary metabolome of hookah smokers, showing separation between the groups, especially between the control versus hookah groups and cigarette versus hookah groups, and it seems to demonstrate that the use of hookah tobacco is more damaging to health.

Saliva Metabolomic Profile in Dental Medicine Research: A Narrative Review

Metabolomic research tends to increase in popularity over the years, leading to the identification of new biomarkers related to specific health disorders. Saliva is one of the most newly introduced and systematically developed biofluids in the human body that can serve as an informative substance in the metabolomic profiling armamentarium. This review aims to analyze the current knowledge regarding the human salivary metabolome, its alterations due to physiological, environmental and external factors, as well as the limitations and drawbacks presented in the most recent research conducted, focusing on pre—analytical and analytical workflows. Furthermore, the use of the saliva metabolomic profile as a promising biomarker for several oral pathologies, such as oral cancer and periodontitis will be investigated.

A colorimetric electronic tongue for point-of-care detection of COVID-19 using salivary metabolites

The monitoring of profile concentrations of chemical markers in saliva samples can be used to diagnose COVID-19 patients, and differentiate them from healthy individuals. Here, this purpose is achieved by designing a paper-based colorimetric sensor with an origami structure, containing general receptors such as pH-sensitive organic dyes, Lewis donors or acceptors, functionalized nanoparticles, and ion metal complexes. The color changes taking place in the receptors in the presence of chemical markers are visually observed and recorded with a digital instrument. Different types and amounts of the chemical markers provide the sensor with a unique response for patients (60 samples) or healthy (55 samples) individuals. These two categories can be discriminated with 84.3% accuracy. This study evidences that the saliva composition of cured and healthy participants is different from each other with accuracy of 85.7%. Moreover, viral load values obtained from the rRT-PCR method can be estimated by the designed sensor. Besides COVID-19, it may possible to simultaneously identify smokers and people with kidney disease and diabetes using the specified electronic tongue. Due to its high efficiency, the prepared paper device can be employed as a rapid detection kit to detect COVID-19.

Contrasting Volatilomes of Livestock Dung Drive Preference of the Dung Beetle Bubas bison (Coleoptera: Scarabaeidae)

Volatile cues can play a significant role in the location and discrimination of food resources by insects. Dung beetles have been reported to discriminate among dung types produced by different species, thereby exhibiting behavioral preferences. However, the role of volatile organic compounds (VOCs) in dung localization and preference remains largely unexplored in dung beetles. Here we performed several studies: firstly, cage olfactometer bioassays were performed to evaluate the behavioral responses of Bubas bison (Coleoptera: Scarabaeidae) to VOCs emanating from fresh horse, sheep, and cattle dung; secondly, concurrent volatilome analysis was performed to characterize volatilomes of these dung types. Bubas bison adults exhibited greater attraction to horse dung and less attraction to cattle dung, and they preferred dung from horses fed a pasture-based diet over dung from those fed lucerne hay. Volatilomes of the corresponding dung samples from each livestock species contained a diverse group of alkanes, alkenes, alkynes, alcohols, aldehydes, ketones, esters, phenols, and sulfurous compounds, but the composition and abundance of annotated VOCs varied with dung type and livestock diet. The volatilome of horse dung was the most chemically diverse. Results from a third study evaluating electroantennogram response and supplementary olfactometry provided strong evidence that indole, butyric acid, butanone, p-cresol, skatole, and phenol, as well as toluene, are involved in the attraction of B. bison to dung, with a mixture of these components significantly more attractive than individual constituents.

High-Throughput Salivary Metabolite Profiling on an Ultralow Noise Tip-Enhanced Laser Desorption Ionization Mass Spectrometry Platform for Noninvasive Diagnosis of Early Lung Cancer

Lung cancer (LC) is a widespread cancer that is the cause of the highest mortality rate accounting for 25% of all cancer deaths. To date, most LC patients are diagnosed at the advanced stage owing to the lack of obvious symptoms in the early stage and the limitations of current clinical diagnostic techniques. Therefore, developing a high throughput technique for early screening is of great importance. In this work, we established an effective and rapid salivary metabolic analysis platform for early LC diagnosis and combined metabolomics and transcriptomics to reveal the metabolic fluctuations correlated to LC. Saliva samples were collected from a total of 150 volunteers including 89 patients with early LC, 11 patients with advanced LC, and 50 healthy controls. The metabolic profiling of noninvasive samples was investigated on an ultralow noise TELDI-MS platform. In addition, data normalization methods were screened and assessed to overcome the MS signal variation caused by individual difference for biomarker mining. For untargeted metabolic profiling of saliva samples, around 264 peaks could be reliably detected in each sample. After multivariate analysis, 23 metabolites were sorted out and verified to be related to the dysfunction of the amino acid and nucleotide metabolism in early LC. Notably, transcriptomic data from online TCGA repository were utilized to support findings from the salivary metabolomics experiment, including the disorder of amino acid biosynthesis and amino acid metabolism. Based on the verified differential metabolites, early LC patients could be clearly distinguished from healthy controls with a sensitivity of 97.2% and a specificity of 92%. The ultralow noise TELDI-MS platform displayed satisfactory ability to explore salivary metabolite information and discover potential biomarkers that may help develop a noninvasive screening tool for early LC.

Identification of biomarkers specific to five different nicotine product user groups: Study protocol of a controlled clinical trial

Background

Assessing biomarker profiles in various body fluids is of large value to discern between the sole use of nicotine products. In particular, the assessment of the product compliance is required for long-term clinical studies. The objective of this study was the identification of biomarkers and biomarker patterns in body fluids, to distinguish between combustibles, heated tobacco products, electronic cigarettes, oral tobacco and oral/dermal nicotine products used for nicotine replacement therapy (NRT), as well as a control group of non-users.

Methods

A controlled, single-center study was conducted with 60 healthy subjects, divided into 6 groups (5 nicotine product user groups and one non-user group) based on their sole use of the products of choice. The subjects were confined for 76 h, during which, free and uncontrolled use of the products was provided. Sample collections were performed according to the study time schedule provided in Table 2. The primary outcome will be validated through analysis of the collected biospecimens (urine, blood, saliva, exhaled breath and exhaled breath condensate) by means of untargeted omics approaches (i.e. exposomics, breathomics and adductomics). Secondary outcome will include established biomarker quantification methods to allow for the identification of typical biomarker patterns. Statistical analysis tools will be used to specifically discriminate different product use categories.

Results/Conclusions

The clinical trial was successfully completed in May 2020, resulting in sample management and preparations for the quantitative and qualitative analyses. This work will serve as a solid basis to discern between biomarker profiles of different nicotine product user groups. The knowledge collected during this research will be required to develop prototype diagnostic tools that can reliably assess the differences and evaluate possible health risks of various nicotine products.

Salivary metabolomics for the diagnosis of periodontal diseases: a systematic review with methodological quality assessment

INTRODUCTION

Early diagnosis of periodontitis by means of a rapid, accurate and non-invasive method is highly desirable to reduce the individual and epidemiological burden of this largely prevalent disease.

OBJECTIVES

The aims of the present systematic review were to examine potential salivary metabolic biomarkers and pathways associated to periodontitis, and to assess the accuracy of salivary untargeted metabolomics for the diagnosis of periodontal diseases.

METHODS

Relevant studies identified from MEDLINE (PubMed), Embase and Scopus databases were systematically examined for analytical protocols, metabolic biomarkers and results from the multivariate analysis (MVA). Pathway analysis was performed using the MetaboAnalyst online software and quality assessment by means of a modified version of the QUADOMICS tool.

RESULTS

Twelve studies met the inclusion criteria, with sample sizes ranging from 19 to 130 subjects. Compared to periodontally healthy individuals, valine, phenylalanine, isoleucine, tyrosine and butyrate were found upregulated in periodontitis patients in most studies; while lactate, pyruvate and N-acetyl groups were the most significantly expressed in healthy individuals. Metabolic pathways that resulted dysregulated are mainly implicated in inflammation, oxidative stress, immune activation and bacterial energetic metabolism. The findings from MVA revealed that periodontitis is characterized by a specific metabolic signature in saliva, with coefficients of determination ranging from 0.52 to 0.99.

CONCLUSIONS

This systematic review summarizes candidate metabolic biomarkers and pathways related to periodontitis, which may provide opportunities for the validation of diagnostic or predictive models and the discovery of novel targets for monitoring and treating such a disease (PROSPERO CRD42020188482).

Salivary metabolite levels in perinatally HIV-infected youth with periodontal disease

INTRODUCTION

Salivary metabolite profiles are altered in adults with HIV compared to their uninfected counterparts. Less is known about youth with HIV and how oral disorders that commonly accompany HIV infection impact salivary metabolite levels.

OBJECTIVE

As part of the Adolescent Master Protocol multi-site cohort study of the Pediatric HIV/AIDS Cohort Study (PHACS) network we compared the salivary metabolome of youth with perinatally-acquired HIV (PHIV) and youth HIV-exposed, but uninfected (PHEU) and determined whether metabolites differ in PHIV versus PHEU.

METHODS

We used three complementary targeted and discovery-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflows to characterize salivary metabolite levels in 20 PHIV and 20 PHEU youth with and without moderate periodontitis. We examined main effects associated with PHIV and periodontal disease, and the interaction between them.

RESULTS

We did not identify differences in salivary metabolite profiles that remained significant under stringent control for both multiple between-group comparisons and multiple metabolites. Levels of cadaverine, a known periodontitis-associated metabolite, were more abundant in individuals with periodontal disease with the difference being more pronounced in PHEU than PHIV. In the discovery-based dataset, we identified a total of 564 endogenous peptides in the metabolite extracts, showing that proteolytic processing and amino acid metabolism are important to consider in the context of HIV infection.

CONCLUSION

The salivary metabolite profiles of PHIV and PHEU youth were overall very similar. Individuals with periodontitis particularly among the PHEU youth had higher levels of cadaverine, suggesting that HIV infection, or its treatment, may influence the metabolism of oral bacteria.

Electronic nicotine delivery system-induced alterations in oral health via saliva assessment

IMPACT STATEMENT

The use of traditional tobacco products is a known risk factor for the development of diseases including periodontal disease. To date, the potential oral health effects related to electronic nicotine delivery systems (ENDS) use is unknown. This study collected saliva from ENDS users and never tobacco users to examine differences in the oral cavity of inflammatory cytokines and metabolites. The identification and measurement of these ENDS-related changes provide insight into disease pathways potentially associated with ENDS use. The utilization of saliva samples collected from human participates enhances the application of the findings compared to the majority of studies using cell culture and animal models. In addition, these foundational findings can inform future studies to examining specific pathways identified, interventional approaches, and application of translatable biomarkers of ENDS use.

HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota

In this work, a straightforward analytical approach based on headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry was developed for the analysis of salivary volatile organic compounds without any prior derivatization step. With a sample volume of 500 μL, optimal conditions were achieved by allowing the sample to equilibrate for 10 min at 50 °C and then extracting the samples for 10 min at the same temperature, using a carboxen/polydimethylsiloxane fibre. The method allowed the simultaneous identification and quantification of 20 compounds in sample headspace, including short-chain fatty acids and their derivatives which are commonly analysed after analyte derivatization. The proof of applicability of the methodology was performed with a case study regarding the analysis of the dynamics of volatile metabolites in saliva of a single subject undergoing 5-day treatment with rifaximin antibiotic. Non-stimulated saliva samples were collected over 3 weeks from a nominally healthy volunteer before, during, and after antibiotic treatment. The variations of some metabolites, known to be produced by the microbiota and by bacteria that are susceptible to antibiotics, suggest that the study of the dynamics of salivary metabolites can be an excellent indirect method for analysing the gut microbiota. This approach is novel from an analytical standpoint, and it encourages further studies combining saliva metabolite profiles and gut microbiota dynamics. Graphical abstract.

Pathway Analysis of Global Metabolomic Profiles Identified Enrichment of Caffeine, Energy, and Arginine Metabolism in Smokers but Not Moist Snuff Consumers

Existing US epidemiological data demonstrate that consumption of smokeless tobacco, particularly moist snuff, is less harmful than cigarette smoking. However, the molecular and biochemical changes due to moist snuff consumption relative to smoking remain incompletely understood. We previously reported that smokers (SMK) exhibit elevated oxidative stress and inflammation relative to moist snuff consumers (MSC) and non-tobacco consumers (NTC), based on metabolomic profiling data of saliva, plasma, and urine from MSC, SMK, and NTC. In this study, we investigated the effects of tobacco consumption on additional metabolic pathways using pathway-based analysis tools. To this end, metabolic pathway enrichment analysis and topology analysis were performed through pair-wise comparisons of global metabolomic profiles of SMK, MSC, and NTC. The analyses identified >8 significantly perturbed metabolic pathways in SMK compared with NTC and MSC in all 3 matrices. Among these differentially enriched pathways, perturbations of caffeine metabolism, energy metabolism, and arginine metabolism were mostly observed. In comparison, fewer enriched metabolic pathways were identified in MSC compared with NTC (5 in plasma, none in urine and saliva). This is consistent with our transcriptomics profiling results that show no significant differences in peripheral blood mononuclear cell gene expression between MSC and NTC. These findings, taken together with our previous biochemical, metabolomic, and transcriptomic analysis results, provide a better understanding of the relative changes in healthy tobacco consumers, and demonstrate that chronic cigarette smoking, relative to the use of smokeless tobacco, results in more pronounced biological changes, which could culminate in smoking-related diseases.

Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease

Metabolite profiling by mass spectrometry (MS) is an area of interest for disease diagnostics, biomarker discovery, and therapeutic evaluation. A recently developed approach, multiple reaction monitoring (MRM)-profiling, searches for metabolites with precursor (Prec) and neutral loss (NL) scans in a representative sample and creates a list of ion transitions. These are then used in an MRM method for fast screening of individual samples and discrimination between healthy and diseased. A large variety of functional groups are considered and all signals discovered are recorded in the individual samples, making this a largely unsupervised method. MRM-profiling is described here and then demonstrated with data for over 900 human plasma coronary artery disease (CAD) samples. Representative pooled samples for each condition were interrogated using a library of over a hundred Prec and NL scans on a triple quadrupole MS. The data from the Prec and NL experiments were converted into ion transitions, initially some 1266 transitions. Each ion transition was examined in the individual samples on a time scale of milliseconds per transition, which allows for rapid screening of large sample sets (<5 days for 1000 samples). Use of univariate and multivariate statistics allowed classification of the sample set with high accuracy. The metabolite profiles classified the CAD female, CAD male, and peripheral artery disease (PAD) samples relative to controls with an accuracy of 90%, 78%, and 85%, respectively. The compounds responsible for informative ion transitions were identified by chromatography and high resolution MS; some have been previously reported and found to be associated with coronary artery disease metabolism, indicating that the methodology generates a meaningful metabolite profile while being faster than traditional methodologies.

A distinct serum metabolic signature of distant metastatic papillary thyroid carcinoma

BACKGROUND

Although the incidence rate for thyroid cancer seems to have begun stabilizing in recent years, an increased rate of advanced stage of this disease has been reported. Additionally, distant metastasis is one of the most important prognostic factors of patients with papillary thyroid carcinoma (PTC). Unfortunately, the underlying mechanisms of distant metastasis, as well as cell status like metabolism changes in distant metastatic tumours have not been clearly elucidated.

OBJECTIVE

To identify serum metabolic signature of distant metastatic PTC.

DESIGN, PATIENTS AND MEASUREMENTS

In this study, gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) was used to analyse the serum from 77 patients diagnosed with PTC (37 in distant metastasis group and 40 in ablation group). Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) scores plots were used to analyse the data.

RESULTS

Principal component analysis and OPLS-DA analyses demonstrated an evident trend of separation between 40 serum samples from the ablation group and 37 samples from distant metastasis group. A total of 31 metabolites were identified, which are related to amino acid, lipid, glucose, vitamin metabolism and diet/gut microbiota interaction. Pathway analysis showed "alanine, aspartate and glutamate metabolism" and "inositol phosphate metabolism" were the most relevant pathways.

CONCLUSION

Serum metabolomics profiling could significantly discriminate papillary thyroid cancer patients according to distant metastasis. Potential metabolic aberration in distant metastatic PTC could be involved in different biological behaviours of tumour cells including proliferation, invasion/migration and immune escape. Diet/gut microbiota-produced metabolites could play an important role in these effects. This work may provide new clues to find the underlying mechanisms regarding the distant metastasis of PTC as well as potential adjuvant therapy targets.

Metabolomic Fingerprinting in Various Body Fluids of a Diet-Controlled Clinical Smoking Cessation Study Using a Validated GC-TOF-MS Metabolomics Platform

Untargeted GC-TOF-MS analysis proved to be a suitable analytical platform to determine alterations in the metabolic profile. Several metabolic pathways were found to be altered in a first clinical study comparing smokers against nonsmokers. Subsequently, we conducted a clinical diet-controlled study to investigate alterations in the metabolic profile during the course of 3 months of smoking cessation. Sixty male subjects were included in the study, and plasma, saliva, and urine samples were collected during four 24 h stationary visits: at baseline, while still smoking, after 1 week, after 1 month, and after 3 months of cessation. Additionally, subjects were monitored for their compliance by measurements of CO in exhaled breath and salivary cotinine throughout the study. GC-TOF-MS fingerprinting was applied to plasma, saliva, and urine samples derived from 39 compliant subjects. In total, 52 metabolites were found to be significantly altered including 26 in plasma, 20 in saliva, and 12 in urine, respectively. In agreement with a previous study comparing smokers and nonsmokers, the fatty acid and amino acid metabolism showed significant alterations upon 3 months of smoking cessation. Thus these results may indicate a partial recovery of metabolic pathway perturbations, even after a relatively short period of smoking cessation.

GC-MS based metabolomics used for the identification of cancer volatile organic compounds as biomarkers

A biomarker can be a metabolite, coming from a metabolic pathway or cell process, which might be employed in the diagnostic of diseases, predict patient response towards chemical therapies and/or monitor disease recurrences. Biomarkers, e.g. aldehydes or hydrocarbons, are often identified from different body fluids such as blood, urine, serum, saliva or from various tissues samples, and their concentration can vary from one sample to the other. However, the detection and the action of these biomarkers for diseases is a complicated process. Cancer is one of the main cause of death worldwide. The main characteristic of cancerous tumor is the uncontrolled growing of cells inside the organism. Likely, these uncontrolled growths are as consequence changes in the metabolism that could be analytically monitored. Depending on where the cancer cells are located, they provide different characteristics profiles. These profiles as fingerprints are used for differentiation in a comparison to normal cells. This critical study aimed at highlighting the latest progress in this area, especially in the employment of gas chromatography for the monitoring of volatile organic compounds (VOCs) and the identification of possible molecules used as biomarkers for cancer therapy.

Metabolic responses of the growing Daphnia similis to chronic AgNPs exposure as revealed by GC-Q-TOF/MS and LC-Q-TOF/MS

Silver nanoparticles (AgNPs) are one of the most widely used nanomaterials. Their fast-growing utilization has increased the occurrence of AgNPs in the environment, posing potential health and ecological risks. In this study, we conducted chronic toxicity tests and investigated the metabolic changes of the growing Daphna similis with exposure to 0, 0.02, and 1 ppb AgNPs, using non-targeted mass spectrometry-based metabolomics. To the best of our knowledge, this study is the first to report the baseline metabolite change of a common aquatic organism Daphnia crustacean through its life-cycle. The results show a dynamic kinetic pattern of the growing Daphnia's metabolome underwent a cycle from day 0 to day 21, with the level of metabolites gradually increasing from day 0 to day 13, before falling back to the baseline level of day 0 on day 21. As for the samples exposed to environmental concentrations of AgNPs, although without morphological or structural changes, numerous metabolite changes occurred abruptly during the first 10 days, and these changes reached steady state by day 13. The significant changes in certain metabolites, such as amino acids (serine, threonine and tyrosine), sugars (d-allose) and fatty acids (arachidonic acid) revealed new insights into how these metabolites in Daphnia respond to chronic AgNPs stress. These findings highlight the capability of metabolomics to discover early metabolic responses to environmental silver nanoparticles.

A fully validated GC-TOF-MS method for the quantification of fatty acids revealed alterations in the metabolic profile of fatty acids after smoking cessation

We developed and validated an efficient and robust method for the simultaneous quantification of 44 fatty acid species in human plasma via GC-TOF-MS. The method is characterized by its robustness, accuracy and precision covering a wide range of fatty acid species with various saturation degrees including short chain fatty acids (beginning with FA 4:0) and long chain fatty acids (up to FA 32:0). The fatty acids were methylated prior to analyses and subsequently detected as fatty acid methyl esters by means of GC-TOF-MS. A highly substituted polar column allowed the separation of geometrical and positional isomers of fatty acid species. The method was applied to plasma samples of a strictly diet controlled clinical smoking cessation study including 39 smokers followed over the course of three months after having quit. Statistical significant alterations within the fatty acid profile were observed when comparing the baseline (subjects still smoking) with one week, one month and three months of smoking cessation. After 3 months of smoking cessation, a partial recovery of alterations in the fatty acid profile evoked by smoking was observed. In conclusion, the developed fatty acid profiling method using GC-TOF-MS has proven as a reliable tool for the quantitative determination of 44 individual fatty acid species within clinical studies.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

Post-acquisition spectral stitching. An alternative approach for data processing in untargeted metabolomics by UHPLC-ESI(-)-HRMS

INTRODUCTION

In the case of the MS-based metabolomics, the large number of false positives remains a fundamental issue.

OBJECTIVE

The aim of this study was to develop a new strategy, which highlights the number of the reliable features i.e. the detected features that correspond to a consistent peak according to chromatographic and mass spectrometric criteria.

METHOD

For the analysis blood samples from 20 chickens, which were administrated with naringin and 9 samples from control, were analyzed by UHPLC-HRMS (Orbitrap Velos). Two methodologies have been compared for data processing. In the first one (classical approach), all data in the 100-900 m/z mass-to charge range were included for the data processing procedure whereas for the newly developed methodology, the data were shred in 100Da slices generating 8 datasets, which have been then subjected to the downstream MS data processing. Each dataset was treated separately and the m/z_t_R features obtained by either VIP's or t-test values were merged and used as the input for the construction of the general model.

RESULTS

The new methodology resulted to a 4-fold increase of the peaks that could be considered chromatographically and mass spectrometrically valid.

CONCLUSION

A new strategy was reported on the detection of chromatographically reliable features during a metabolomic approach. The shredding of the LC-MS chromatograms into multiple m/z ranges increased the number of the identified chromatographically reliable features.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Mass spectrometry for the assessment of the occurrence and biological consequences of DNA adducts

Exogenous and endogenous sources of chemical species can react, directly or after metabolic activation, with DNA to yield DNA adducts. If not repaired, DNA adducts may compromise cellular functions by blocking DNA replication and/or inducing mutations. Unambiguous identification of the structures and accurate measurements of the levels of DNA adducts in cellular and tissue DNA constitute the first and important step towards understanding the biological consequences of these adducts. The advances in mass spectrometry (MS) instrumentation in the past 2-3 decades have rendered MS an important tool for structure elucidation, quantification, and revelation of the biological consequences of DNA adducts. In this review, we summarized the development of MS techniques on these fronts for DNA adduct analysis. We placed our emphasis of discussion on sample preparation, the combination of MS with gas chromatography- or liquid chromatography (LC)-based separation techniques for the quantitative measurement of DNA adducts, and the use of LC-MS along with molecular biology tools for understanding the human health consequences of DNA adducts. The applications of mass spectrometry-based DNA adduct analysis for predicting the therapeutic outcome of anti-cancer agents, for monitoring the human exposure to endogenous and environmental genotoxic agents, and for DNA repair studies were also discussed.

Application of CE-MS to a metabonomics study of human urine from cigarette smokers and non-smokers

BACKGROUND

Novel biomarkers of exposure and early adverse effects are needed for comparative studies of combustible and non-combustible tobacco products for regulatory authority evaluation. Metabolic biomarkers reflect both gene and environmental effects.

RESULTS

CE-MS has been applied to human urine samples from non-smokers and smokers of cigarettes at two tar levels. Validated chemometric models were able to separate smokers from non-smokers, with discrimination mainly based on the presence of nicotine metabolites. With these removed, it still proved possible to discriminate smokers from non-smokers with models now based on endogenous metabolites. The biochemical relevance of these biomarkers is discussed.

CONCLUSION

This proof-of-principle metabonomics study illustrates the potential of CE-MS to discover novel biomarkers in urine from tobacco users.

Influence of glutathione-S-transferase (GST) inhibition on lung epithelial cell injury: role of oxidative stress and metabolism

Oxidant-mediated tissue injury is key to the pathogenesis of acute lung injury. Glutathione- S-transferases (GSTs) are important detoxifying enzymes that catalyze the conjugation of glutathione with toxic oxidant compounds and are associated with acute and chronic inflammatory lung diseases. We hypothesized that attenuation of cellular GST enzymes would augment intracellular oxidative and metabolic stress and induce lung cell injury. Treatment of murine lung epithelial cells with GST inhibitors, ethacrynic acid (EA), and caffeic acid compromised lung epithelial cell viability in a concentration-dependent manner. These inhibitors also potentiated cell injury induced by hydrogen peroxide (H2O2), tert-butyl-hydroperoxide, and hypoxia and reoxygenation (HR). SiRNA-mediated attenuation of GST-π but not GST-μ expression reduced cell viability and significantly enhanced stress (H2O2/HR)-induced injury. GST inhibitors also induced intracellular oxidative stress (measured by dihydrorhodamine 123 and dichlorofluorescein fluorescence), caused alterations in overall intracellular redox status (as evidenced by NAD+/NADH ratios), and increased protein carbonyl formation. Furthermore, the antioxidant N-acetylcysteine completely prevented EA-induced oxidative stress and cytotoxicity. Whereas EA had no effect on mitochondrial energetics, it significantly altered cellular metabolic profile. To explore the physiological impact of these cellular events, we used an ex vivo mouse-isolated perfused lung model. Supplementation of perfusate with EA markedly affected lung mechanics and significantly increased lung permeability. The results of our combined genetic, pharmacological, and metabolic studies on multiple platforms suggest the importance of GST enzymes, specifically GST-π, in the cellular and whole lung response to acute oxidative and metabolic stress. These may have important clinical implications.

Biomarkers of tobacco smoke exposure

Diseases and death caused by exposure to tobacco smoke have become the single most serious preventable public health concern. Thus, biomarkers that can monitor tobacco exposure and health effects can play a critical role in tobacco product regulation and public health policy. Biomarkers of exposure to tobacco toxicants are well established and have been used in population studies to establish public policy regarding exposure to second-hand smoke, an example being the nicotine metabolite cotinine, which can be measured in urine. Biomarkers of biological response to tobacco smoking range from those indicative of inflammation to mRNA and microRNA patterns related to tobacco use and/or disease state. Biomarkers identifying individuals with an increased risk for a pathological response to tobacco have also been described. The challenge for any novel technology or biomarker is its translation to clinical and/or regulatory application, a process that requires first technical validation of the assay and then careful consideration of the context the biomarker assay may be used in the regulatory setting. Nonetheless, the current efforts to investigate new biomarker of tobacco smoke exposure promise to offer powerful new tools in addressing the health hazards of tobacco product use. This review will examine such biomarkers, albeit with a focus on those related to cigarette smoking.