STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY

Fast neonicotinoid quantification in honey using the one-point internal calibration approach

Neonicotinoids, a highly effective class of insecticides used worldwide, have been identified as a major cause of concern for biodiversity. To assess the ecological and environmental consequences of neonicotinoids' use, reliable analytical methodologies, including calibration approaches, are needed. Here, we compared the performance of internal calibration (IC) using a single concentration of stable isotope-labeled standard (SIL) with classical multipoint external calibration (EC) for the quantification of six neonicotinoids in honey. IC showed acceptable levels of trueness (86.3% - 116.0%) and precision (1.4% - 20.8%), although slight biases were observed at very low concentrations compared to EC. When applied to 32 original honey samples, both approaches showed strong agreement (R2 > 0.998) with proportional biases lower than 5%. These results highlight the possibility of implementing IC to simplify quantification in liquid chromatography-mass spectrometry-based pesticide applications.

Challenges and recent advances in quantitative mass spectrometry-based metabolomics

The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

Spectrofluorimetric determination of vitamin D in the serum of autistic and healthy children using functionalized graphene quantum dots

Vitamin D is one of the most essential nutrients for brain development, and deficiencies during pregnancy and early childhood development might be associated with autism. Regular monitoring of serum 25-hydroxyvitamin D3 level could help in early diagnosis and therapy. Analytical measurement of serum 25-hydroxyvitamin D3 level using the traditional matrix-matched calibration technique yields inaccurate results due to absence of serum matrix free from 25-hydroxyvitamin D3. The aim of this work was to develop a validated spectrofluorimetric methodology based on the standard addition approach for quantifying 25-hydroxyvitamin D3 levels in real serum samples of autistic children. The spectrofluorimetric methodology utilizes functionalized graphene quantum dots as a fluorescent probe for selective quantification of 25-hydroxyvitamin D3 level, which is based on measuring the quenching properties of 25-hydroxyvitamin D3 on a fluorescent probe. The standard addition approach exhibits a minimal matrix interference since it identically utilizes the same matrix of each study sample for creating its own calibration curve. The method was validated using the guidelines outlined in ICH M10 draft for endogenous compounds quantification. The method was successfully applied for quantifying the serum 25-hydroxyvitamin D3 levels in autistic and healthy children, and autistic children had significantly lower serum 25-hydroxyvitamin D3 levels (with a mean ± SD of 23.80 ± 17.19) when compared to healthy children (with a mean ± SD of 50.13 ± 18.74, P < 0.001). These results suggested an association between vitamin D deficiency and autism.

Study on the effect of calibration standards prepared with different matrix on the accuracy of bile acid quantification using LC-MS/MS

The transition from relative to absolute quantification of metabolites is the future development trend of mass spectrometry-based metabolomics research, which could fundamentally solve the problem of comparability of data between different laboratories. However, absolute quantification of endogenous molecules is largely hampered by the lack of analyte-free matrix, leading to uncertainty and inconsistency in the preparation of calibration standards. Bile acids (BAs) are an important class of biomarkers that play a key role in disease progression. In this paper, the quantitative accuracy of calibration curves prepared in neat solvent (NSCCs), charcoal stripped matrix (SMCCs) and authentic matrix (AMCCs) were validated using quality control samples (QCs) prepared in authentic matrix. Results suggested that AMCCs could largely minimize the confidence interval (C.I.) and the deviation in accuracy compared with NSCCs and SMCCs when measured concentration is higher than 20% of the background level. In addition, experimental data demonstrated that two-step calibration strategy proposed here is a promising and reliable alternative strategy to quantify endogenous BAs in biological sample.

High throughput LC-MS/MS method for steroid hormone analysis in rat liver and plasma - unraveling methodological challenges

Comprehensive reference data for steroid hormones are lacking in rat models, particularly for early developmental stages and unconventional matrices as the liver. Therefore, we developed and validated an enzymatic, solid-phase extraction (SPE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify a panel of 23 steroid hormones in liver and plasma from adult and neonatal rats. Our approach tackles methodological challenges, focusing on undesired byproducts associated with specific enzymatic treatment, and enables a thorough assessment of potential interferences in complex matrices by utilizing unstripped plasma and liver. We propose an optimized enzymatic hydrolysis protocol using a recombinant β-glucuronidase/sulfatase mix (BGS mix) to efficiently deconjugate steroid phase II conjugates. The streamlined sample preparation and high-throughput solid phase extraction in a 96-well plate significantly accelerate sample processing for complex matrices and alarge number of samples. We were able to achieve the necessary sensitivity for accurately measuring the target analytes, particularly estrogens, in small sample sizes of 5-20 mg of liver tissue and 100 μL of plasma. Through the analysis of liver and plasma samples from adult and neonatal rats, including both sexes, our study showed a novel set of steroid hormone reference intervals. This study provides a reliable diagnostic tool for the quantification of steroids in rat models and gives insight in liver and plasma-related steroid hormone dynamics at early developmental stages. In addition, the method covers several pathway intermediates and extend the list of steroid hormones to be investigated.

Chilling-induced peach flavor loss is associated with expression and DNA methylation of functional genes

INTRODUCTION

Flavor is a major contributor to consumer preference. Despite being effective at extending the fruit's commercial life, cold storage also results in a significant loss of flavor volatiles. To date, there has been few studies on the metabolic dynamics and the mechanism underlying the regulatory networks that modulate flavor loss during cold storage for fruit.

METHODS

The volatile contents were detected by Gas Chromatography-Mass Spectrometer (GC-MS). Weighted gene co-expression network analysis (WGCNA) was used to identify structure genes and transcription factors (TFs). DNA methylation was analyzed by whole-genome methylation sequencing during cold storage.

RESULTS

We generated a temporal map, over hourly to weekly timescales, for the effects of chilling on flavor volatiles by combining metabolome, transcriptome, and DNA methylome in peach fruit. Based on the big data analysis, we developed a regulatory network for volatile formation and found that a decrease in volatiles during cold storage was significantly correlated with a decrease in the expression of synthesis genes. Moreover, TFs associated with these structure genes were identified. Expression of genes involved in ethylene biosynthesis was reduced while cold tolerance pathway was activated in response to low temperature. Functions of those genes were confirmed through transgenic experiments and across peach cultivars, suggesting our dataset is a useful tool for elucidating regulatory factors that have not yet been clarified in relation to flavor and cold tolerance. Genome wide DNA methylation was induced by chilling and peaked at 7 d followed by a decline during 28 d cold storage. Reduction of gene expression was accompanied by major changes in the methylation status of their promoters, including PpACS1, PpAAT1, PpTPS3 and PpMADS2.

CONCLUSION

Our study revealed the mechanism for chilling-induced flavor loss of peach fruit through time-course transcriptome and DNA methylome analysis.

Multitargeted Internal Calibration for the Quantification of Chronic Kidney Disease-Related Endogenous Metabolites Using Liquid Chromatography-Mass Spectrometry

Accurate quantitative analysis in liquid chromatography-mass spectrometry (LC-MS) benefits from calibration curves generated in the same matrix as the study sample. In the case of endogenous compound quantification, as no blank matrix exists, the multitargeted internal calibration (MTIC) is an attractive and straightforward approach to avoid the need for extensive matrix similarity evaluation. Its principle is to take advantage of stable isotope labeled (SIL) standards as internal calibrants to simultaneously quantify authentic analytes using a within sample calibration. An MTIC workflow was developed for the simultaneous quantification of metabolites related to chronic kidney disease (CKD) using a volumetric microsampling device to collect 20 μL of serum or plasma, followed by a single-step extraction with acetonitrile/water and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Since a single concentration of internal calibrant is necessary to calculate the study sample concentration, the instrument response function was investigated to determine the best SIL concentration. After validation, the trueness of 16 endogenous analytes in authentic human serum ranged from 72.2 to 116.0%, the repeatability from 1.9 to 11.3%, and the intermediate precision ranged overall from 2.1 to 15.4%. The proposed approach was applied to plasma samples collected from healthy control participants and two patient groups diagnosed with CKD. Results confirmed substantial concentration differences between groups for several analytes, including indoxyl sulfate and cortisone, as well as metabolite enrichment in the kynurenine and indole pathways. Multitargeted methodologies represent a major step toward rapid and straightforward LC-MS/MS absolute quantification of endogenous biomarkers, which could change the paradigm of MS use in clinical laboratories.

Advances and Challenges in Plant Sterol Research: Fundamentals, Analysis, Applications and Production

Plant sterols (PS) are cholesterol-like terpenoids widely spread in the kingdom Plantae. Being the target of extensive research for more than a century, PS have topped with evidence of having beneficial effects in healthy subjects and applications in food, cosmetic and pharmaceutical industries. However, many gaps in several fields of PS's research still hinder their widespread practical applications. In fact, many of the mechanisms associated with PS supplementation and their health benefits are still not fully elucidated. Furthermore, compared to cholesterol data, many complex PS chemical structures still need to be fully characterized, especially in oxidized PS. On the other hand, PS molecules have also been the focus of structural modifications for applications in diverse areas, including not only the above-mentioned but also in e.g., drug delivery systems or alternative matrixes for functional foods and fats. All the identified drawbacks are also superimposed by the need of new PS sources and technologies for their isolation and purification, taking into account increased environmental and sustainability concerns. Accordingly, current and future trends in PS research warrant discussion.

An alternative approach to validation of liquid chromatography-mass spectrometry methods for the quantification of endogenous compounds

Despite the progress in the quantification of xenobiotics, the development and validation of methods designed for endogenous substances still remain challenging due to the natural presence of the analytes in a biological matrix, leading to the inability to obtain a blank sample. Several generally recognized procedures are described to solve this issue, like using surrogate or analyte-depleted matrices or surrogate analytes. However, the workflows used do not always meet the requirements for developing a reliable analytical method or are cost-intensive. This study aimed to design an alternative approach for preparing validation reference samples using authentic analytical standards while preserving the nature of the biological matrix and solving the problem with the inherent presence of analyzed compounds in a studied matrix. The methodology used is based on the standard-addition type procedure. However, unlike the original method, the addition is modified according to a previously measured basal concentration of monitored substances in the pooled biological sample to obtain a predefined concentration in reference samples according to the European Medicines Agency (EMA) validation guideline. The study shows the advantages of described approach on an example of LC-MS/MS analysis of 15 bile acids in human plasma and compares it with other methods commonly used in this field. The method was successfully validated according to the EMA guideline with lower limit of quantification of 5 nmol/L and linearity in the range of 5 - 2000 nmol/L. Finally, the method was used in a metabolomic study on a cohort of pregnant women (n = 28) to confirm intrahepatic cholestasis, the major liver disease observed in pregnancy.

Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics

Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

Straightforward quantification of endogenous steroids with liquid chromatography-tandem mass spectrometry: Comparing calibration approaches

Different calibration strategies are used in liquid chromatography hyphenated to mass spectrometry (LC-MS) bioanalysis. Currently, the surrogate matrix and surrogate analyte represent the most widely used approaches to compensate for the lack of analyte-free matrices in endogenous compounds quantification. In this context, there is a growing interest in rationalizing and simplifying quantitative analysis using a one-point concentration level of stable isotope-labeled (SIL) standards as surrogate calibrants. Accordingly, an internal calibration (IC) can be applied when the instrument response is translated into analyte concentration via the analyte-to-SIL ratio performed directly in the study sample. Since SILs are generally used as internal standards to normalize variability between authentic study sample matrix and surrogate matrix used for the calibration, IC can be calculated even if the calibration protocol was achieved for an external calibration (EC). In this study, a complete dataset of a published and fully validated method to quantify an extended steroid profile in serum was recomputed by adapting the role of SIL internal standards as surrogate calibrants. Using the validation samples, the quantitative performances for IC were comparable with the original method, showing acceptable trueness (79%-115%) and precision (0.8%-11.8%) for the 21 detected steroids. The IC methodology was then applied to human serum samples (n = 51) from healthy women and women diagnosed with mild hyperandrogenism, showing high agreement (R² > 0.98) with the concentrations obtained using the conventional quantification based on EC. For IC, Passing-Bablok regression showed proportional biases between -15.0% and 11.3% for all quantified steroids, with an average difference of -5.8% compared to EC. These results highlight the reliability and the advantages of implementing IC in clinical laboratories routine to simplify quantification in LC-MS bioanalysis, especially when a large panel of analytes is monitored.

A pentasaccharide for monitoring pharmacodynamic response to gene therapy in GM1 gangliosidosis

BACKGROUND

GM1 gangliosidosis is a rare, fatal, neurodegenerative disease caused by mutations in the GLB1 gene and deficiency in β-galactosidase. Delay of symptom onset and increase in lifespan in a GM1 gangliosidosis cat model after adeno-associated viral (AAV) gene therapy treatment provide the basis for AAV gene therapy trials. The availability of validated biomarkers would greatly improve assessment of therapeutic efficacy.

METHODS

The liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to screen oligosaccharides as potential biomarkers for GM1 gangliosidosis. The structures of pentasaccharide biomarkers were determined with mass spectrometry, as well as chemical and enzymatic degradations. Comparison of LC-MS/MS data of endogenous and synthetic compounds confirmed the identification. The study samples were analyzed with fully validated LC-MS/MS methods.

FINDINGS

We identified two pentasaccharide biomarkers, H3N2a and H3N2b, that were elevated more than 18-fold in patient plasma, cerebrospinal fluid (CSF), and urine. Only H3N2b was detectable in the cat model, and it was negatively correlated with β-galactosidase activity. Following intravenous (IV) AAV9 gene therapy treatment, reduction of H3N2b was observed in central nervous system, urine, plasma, and CSF samples from the cat model and in urine, plasma, and CSF samples from a patient. Reduction of H3N2b accurately reflected normalization of neuropathology in the cat model and improvement of clinical outcomes in the patient.

INTERPRETATIONS

These results demonstrate that H3N2b is a useful pharmacodynamic biomarker to evaluate the efficacy of gene therapy for GM1 gangliosidosis. H3N2b will facilitate the translation of gene therapy from animal models to patients.

FUNDING

This work was supported by grants U01NS114156, R01HD060576, ZIAHG200409, and P30 DK020579 from the National Institutes of Health (NIH) and a grant from National Tay-Sachs and Allied Diseases Association Inc.

Metabolomics of infectious diseases in the era of personalized medicine

Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.

Standard addition method (SAM) in LC-MS/MS to quantify gluten-derived metabolites in urine samples

A tight adherence to a gluten-free diet (GFD), the most effective treatment currently available for celiac disease, is important to reduce symptoms, avoid nutritional deficiencies and improve quality of life in celiac patients. The development of analytical methods allowing detecting gluten exposure due to occasional or involuntary food transgressions could represent a useful tool to monitor patient habits and conditions and prevent long-term complications. The aim of this work was to develop and validate an approach based on the standard addition methodology (SAM) for the detection and quantification of two main metabolites of alkylresorcinols, 3,5-dihydroxybenzoic acid (DHBA) and 3-(3,5-dihydroxyphenyl)-propanoic acid (DHPPA), whose presence in urine samples is related to the intake of gluten-containing foods. Analytically, the method consisted of a protein precipitation step followed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis. The chromatographic method involved the use of a hydrophilic interaction liquid chromatography (HILIC) in a direct phase approach; LC-MS/MS analyses were performed in selected reaction monitoring (SRM) mode. Manipulation and instrumental errors were normalised using stable isotopic standards (ISs). The SAM approach here described requires less than 1 mL of urine per sample, thus greatly reducing the sample volume needed. Noteworthy, despite the small cohort of samples analysed, our data allowed to identify a potential "threshold" value, around 200 ng/mL for DHBA and 400 ng/mL for DHPPA, to discriminate between a GFD and a gluten rich diet (GRD).

Applied Clinical Tandem Mass Spectrometry-Based Quantification Methods for Lipid-Derived Biomarkers, Steroids and Cannabinoids: Fit-for-Purpose Validation Methods

The emergence of metabolomics and quantification approaches is revealing new biomarkers applied to drug discovery. In this context, tandem mass spectrometry is the method of choice, requiring a specific validation process for preclinical and clinical applications. Research on the two classes of lipid mediators, steroids and cannabinoids, has revealed a potential interaction in cannabis addiction and metabolism-related disorders. Here we present the development of GC-MS/MS and LC-MS/MS methods for routine quantification of targeted steroids and cannabinoids, respectively. The methods were developed using an isotopic approach, including validation for linearity, selectivity, LLOQ determination, matrix effect, carryover, between- and within-run accuracy and precision, and stability tests to measure 11 steroids and seven cannabinoids in human plasma. These methods were satisfactory for most validity conditions, although not all met the acceptance criteria for all analytes. A comparison of calibration curves in biological and surrogate matrices and in methanol showed that the latter condition was more applicable for our quantification of endogenous compounds. In conclusion, the validation of our methods met the criteria for GLP-qualified rather than GLP-validated methods, which can be used for routine analytical studies for dedicated preclinical and clinical purposes, by combining appropriate system suitability testing, including quality controls in the biological matrix.

Metabolomics: Going Deeper, Going Broader, Going Further

Metabolomics is a continuously dynamic field of research that is driven by demanding research questions and technological advances alike. In this review we highlight selected recent and ongoing developments in the area of mass spectrometry-based metabolomics. The field of view that can be seen through the metabolomics lens can be broadened by adoption of separation techniques such as hydrophilic interaction chromatography and ion mobility mass spectrometry (going broader). For a given biospecimen, deeper metabolomic analysis can be achieved by resolving smaller entities such as rare cell populations or even single cells using nano-LC and spatially resolved metabolomics or by extracting more useful information through improved metabolite identification in untargeted metabolomic experiments (going deeper). Integration of metabolomics with other (omics) data allows researchers to further advance in the understanding of the complex metabolic and regulatory networks in cells and model organisms (going further). Taken together, diverse fields of research from mechanistic studies to clinics to biotechnology applications profit from these technological developments.

Metabolites Identification and Mechanism Prediction of Neobavaisoflavone In Vitro and In Vivo of Rats through UHPLC-Q-Exactive Plus Orbitrap MS Integrated Network Pharmacology

Neobavaisoflavone is an important isoflavone component isolated from Psoraleae Fructus. It is used extensively worldwide because of its antibacterial, antioxidant, anti-inflammatory, anticancer, and anti-osteoporotic activities. However, there is no systematic and comprehensive research on the metabolism of neobavaisoflavone in vivo and in vitro. The study aimed to analyze the metabolic characteristics and mechanism of neobavaisoflavone for the first time. Firstly, biological samples were pretreated by the solid-phase extraction (SPE) method, methanol precipitation, and acetonitrile precipitation. Secondly, the samples were analyzed on UHPLC-Q-Exactive Plus Orbitrap MS. Thirdly, metabolites were tentatively identified based on retention time, parallel reaction monitoring strategy, diagnostic product ions, and neutral loss fragments. A total of 72 metabolites of neobavaisoflavone were tentatively identified, including 28 in plasma, 43 in urine, 18 in feces, six in the liver, and four in the liver microsome. The results suggested that neobavaisoflavone mainly underwent glucuronidation, sulfation, hydroxylation, methylation, cyclization, hydration, and their composite reactions in vivo and in vitro. In addition, nine active components with high bioavailability and 191 corresponding targets were predicted by the Swiss Drug Design database. The 1806 items of GO and 183 KEGG signaling pathways were enriched. These results showed that metabolites expanded the potential effects of neobavaisoflavone. The present study would provide the scientific basis for the further exploitation and application of neobavaisoflavone.

Synthesis of the biologically important dideuterium-labelled adenosine triphosphate analogue ApppI(d2)

The chemical synthesis of the dideuterium-labelled ATP analogue 1-adenosin-5’-yl-3-(3-methylbut-3-en-1,1-d₂-1-ol) triphosphoric acid diester (ApppI(d₂)) is described. ApppI has been reported to be an important mevalonate pathway metabolite, induced by nitrogen-containing bisphosphonates used for the treatment of several diseases related to the calcium metabolism, of which osteoporosis is the most well-known. The availability of ApppI(d₂) opens possibilities to quantitative measurements of ApppI in biological samples by mass spectrometry. The synthesized target compound ApppI(d₂) was purified by high-performance counter current chromatography and characterized by ¹H, ¹³C, and ³¹P NMR spectroscopy as well as high-resolution mass spectrometry.

Validation of a high-throughput method for simultaneous determination of areca nut and tobacco biomarkers in hair using microwave-assisted extraction and isotope dilution liquid chromatography tandem mass spectrometry

For people with habits of chewing betel nuts and smoking, the probability of suffering from oral cancer is ten to a hundred times higher than others. Due to the serious health consequences of areca nut and tobacco, a reliable cessation program is needed. Hair is the best option to document long-term exposure. Unfortunately, the research on betel nut in hair did not attract much attention. In this study, a high-throughput method based on microwave-assisted extraction (MAE) and isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) was developed to measure the four biomarkers of betel nuts and cigarettes, including areca alkaloids (arecoline), tobacco alkaloids (nicotine), and their metabolites (arecaidine and cotinine). The hair sample was washed, cut, weighed, and incubated for 3 min MAE with methanol/trifluoroacetic acid, then evaporated and reconstituted for LC-MS/MS analysis. The total experiment time was 50 min. The lower limits of quantification (LOQ) were 5-10 pg/mg. The intra-day and inter-day precision were 2.2-7.6%. Intra-day and inter-day accuracy were - 6.1-8.2%. The method showed good linearity (r2 > 0.995) over LOQ - 1000 pg/mg concentration ranges. It was successfully applied to analyze 11 subjects of regular areca nut chewers, also smokers. Eight samples were black hair; three samples were naturally black hair with partially gray hair. Measured concentrations in black hair were in the range 56.9 pg/mg to 3.2 ng/mg for arecoline, 12.8 pg/mg to 222.2 pg/mg for arecaidine, 3.8 ng/mg to 33.4 ng/mg for nicotine and 1.1 ng/mg to 6.1 ng/mg for cotinine. The results showed lower levels in gray hair. This method was utilized successfully to analyze pg/mg levels of arecoline, arecaidine, nicotine, and cotinine, and good recoveries were obtained. The mean concentration of arecaidine and cotinine in hair was 15% and 20% of arecoline and nicotine, respectively. A good positive correlation was found between the concentrations of these compounds and self-report. This method improved extraction speed, concentration, and analysis of samples and is useful for monitoring betel nut and smoking cessation programs.

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1-2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. This platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

Quantitative analysis of 20 purine and pyrimidine metabolites by HILIC-MS/MS in the serum and hippocampus of depressed mice

Purine and pyrimidine metabolism are vital metabolic pathways in the development, proliferation or repairment of cells or tissues associated with various diseases. Here, a simple, all-in-one injection hydrophilic interaction liquid chromatography-tandem mass spectrometry method was developed for simultaneous determination of 20 metabolites: adenine, adenosine, deoxyadenosine, adenosine 5'-monophosphate, cyclic adenosine monophosphate, hypoxanthine, xanthine, inosine, deoxyinosine, xanthosine, xanthosine 5'-monophosphate and uric acid, which are products of purine metabolism; uridine, deoxyuridine, uridine 5'-monophosphate and uracil, are products of pyrimidine metabolism; and corticosterone, methionine, acetylcholine and serotonin. To minimize interference of endogenous molecules in sample matrixes, a combination of activated carbon adsorption and a serum substitute matrix (5% bovine serum albumin in phosphate buffered saline) was utilized and jointly applied. The sensitivity, linearity, stability, precision, accuracy and extraction recovery were evaluated, and the method was demonstrated to be accurate, sensitive and reliable. An analytical strategy was successfully applied to quantitatively determine 20 metabolite levels in the serum and hippocampus of mice with chronic social defeat stress-induced depression. The results showed greatly perturbed purine metabolism in the depressed mice, which was primarily characterized by dramatic increases in hypoxanthine, xanthine and inosine in serum and reduced levels of adenine, adenosine and adenosine 5'-monophosphate in the hippocampus. These findings suggest that this novel strategy can facilitate the quantitative analysis of adenine and other purine and pyrimidine metabolites in tissue and serum and exhibits great potential in the exploration of metabolism-related mechanisms of relevant diseases.

Simultaneous determination of areca nut- and tobacco-specific alkaloids in saliva by LC-MS/MS: Distribution and transformation of alkaloids in oral cavity

Areca nut and tobacco are frequently used in combination. Cigarette smoking and betel quid (BQ) chewing habits impose greater oral cancer risk than either habit alone. Saliva is a better noninvasive diagnostic material as it is in direct contact with oral mucosa and cancerous lesions. This study describes the application of isotope-dilution LC-MS/MS for simultaneous quantitation of five areca nut-specific alkaloids (ASAs) and three tobacco-specific alkaloids (TSAs) in human saliva. With this method, we demonstrate that the distribution of ASAs vary significantly in smokers who chew BQ habitually, due to the hydrolysis of ASAs and metabolic activity in the oral cavity. The alkaline condition formed due to slaked lime in BQ, plays an important role in the distribution of ASAs and TSAs, by catalyzing the hydrolysis of ester forms of ASAs to their respective carboxylic acid forms besides facilitating the TSA (i.e., nicotine) absorption in the oral cavity. Moreover, our results reveal that oral mucosa rather than saliva contributes to the metabolism of ASAs at oral cavity. Less than 2.1% of ASAs were metabolized by saliva, as determined by in vitro test. Our findings may provide a better insight into the pathobiology of oral carcinogenesis due to BQ chewing.

Advancement in Analytical Strategies for Quantification of Biomarkers with a Special Emphasis on Surrogate Approaches

Accurate quantification of biomarkers has always been a challenge for many bioanalytical scientists due to their endogenous nature and low concentration in biological matrices. Different analytical approaches have been developed for quantifying biomarkers including enzyme-linked immunosorbent assay, immunohistochemistry, western blotting, and chromatographic techniques assisted with mass spectrometry. Liquid chromatography-tandem mass spectrometry-based quantification of biomarkers has gained more attention over other traditional techniques due to its higher sensitivity and selectivity. However, the primary challenge lies with this technique includes the unavailability of a blank matrix for method development. To overcome this challenge, different analytical approaches are being developed including surrogate analyte and surrogate matrix approach. Such approaches include quantification of biomarkers in a surrogate matrix or quantification of an isotopically labeled surrogate analyte in an authentic matrix. To demonstrate the authenticity of the surrogate approach, it is mandatory to establish quantitative parallelism through validation employing respective surrogate analytes and surrogate matrices. In this review, different bioanalytical approaches for biomarker quantification and recent advancements in the field aiming for improvement in the specificity of the techniques have been discussed. Liquid chromatography-tandem mass spectrometry-based surrogate approaches for biomarker quantification and significance of parallelism establishment in both surrogate matrix and surrogate analyte-based approaches have been critically discussed. In addition, different methods for demonstrating parallelism in the surrogate method have been explained.

Distribution visualization of the chlorinated disinfection byproduct of diazepam in zebrafish with desorption electrospray ionization mass spectrometry imaging

Diazepam (DZP) was routinely prescribed to a large population troubled with anxiety disorders. However, due to the overuse and misuse, DZP and its chlorination disinfection byproduct 2-methylamino-5-chlorobenzophenone (MACB) caused environmental pollution and can be detected ubiquitously in drinking water in Beijing, China. However, little information is known about the metabolic dynamics of MACB. Here, we established desorption electrospray ionization mass spectrometry (DESI-MS) imaging method to visually and quantitatively assess the distribution and metabolism of MACB in zebrafish. The results showed that MACB specifically accumulated in spinal cord particularly in female zebrafish. Meanwhile, the accumulation of MACB could pass through the blood-brain barrier (BBB) and induced microglial phagocytosis of neurons. Therefore, the intervention strategies should be explored to restrict the release of such substances, eliminating the potential risks for both human beings and the eco-environment.

A new update of MALDI-TOF mass spectrometry in lipid research

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.

Analysis of urinary organic acids by gas chromatography tandem mass spectrometry method for metabolic profiling applications

A sensitive, accurate and precise method was developed for the quantification of a large number of organic acids in human urine by GC-MS/MS. The analytes were selected based on their role as key metabolic intermediates; intermediates of Krebs cycle, fatty acid oxidation, glycolysis, down-stream metabolites of neurotransmitter synthesis and degradation, metabolites indicative of nutritional deficiencies, byproducts of microbial activity in the gastrointestinal tract (GI) etc. The most efficient sample preparation protocol was selected based on tests for extraction with different solvents such as MTBE and ethyl acetate under acidic conditions, whereas finally a more general protocol was applied with methanol. Regarding derivatization, methoxyamine with MSTFA, 1% TMCS was applied. The method was extensively validated, including stability study, ensuring accurate determination of the studied organic acids in human urine. Proof of its utility was exhibited in a set of samples from human volunteers. The method can find wide applicability in the context of metabolomics for clinical or nutritional studies.

The value of coupling thin-layer chromatography to mass spectrometry in lipid research - a review

Mass spectrometry has emerged as an extremely powerful analytical tool, which is widely used in many fields. This broad application range became possible with the invention of MALDI and ESI as "soft ionization" techniques that keep fragmentation of the analyte to a minimum. However, when these techniques are applied to mixture analysis, less-sensitively detectable compounds may be suppressed by more sensitively detectable compounds, a process called "ion suppression". Thus, previous separation of the mixture into the individual lipid classes is necessary to be able to detect all compounds. This review summarizes the current knowledge in the field of combined TLC/MS and discusses the most important strengths and weaknesses of the different MS (particularly ionization) techniques with respect to phospholipids. This comprises techniques such as MALDI and ESI, but less established approaches such as plasma desorption will be also discussed.

A novel, sensitive, and widely accessible besifloxacin quantification method by HPLC-fluorescence: Application to an ocular pharmacokinetic study

Besifloxacin has been embraced for the treatment of ocular bacterial infections. While LC-MS/MS has been used in investigating BSF pharmacokinetics, those costly instruments are not universally available and have complicated requirements for operation and maintenance. Additionally, pharmacokinetics of besifloxacin in dose-intense regimens are still unknown. Herein, a new quantification method was developed employing the widely accessible HPLC with fluorescence detection and applied to an ocular pharmacokinetic study with an intense regimen. Biosamples were pre-treated using protein precipitation. Chromatographic separation was achieved on a C18 column using mobile phase of 0.1% trifluoroacetic acid and acetonitrile. To address the weak fluorescence issue of besifloxacin, effects of detection parameters, elution pattern, pH of mobile phase, and reconstitution solvents were investigated. The method was fully validated per US-FDA guidelines and demonstrated precision (<13%), accuracy (91-112%), lower limit of quantification (5 ng/mL), linearity over clinically relevant concentrations (R² > 0.999), matrix-effects (93-105%), recoveries (95-106%), and excellent selectivity. The method showed agreement with agar disk diffusion assays for in vitro screening and comparable in vivo performance to LC-MS/MS (Deming Regression, y = 1.010x + 0.123, r = 0.997; Bland-Altman analysis, mean difference was -6.3%; n = 21). Pharmacokinetic parameters suggested superior surface-retentive properties of besifloxacin. Maximum concentrations were 1412 ± 1910 and 0.15 ± 0.12 μg/mL; area under the curve was 1,637 and 1.08 µg·h/g; and half-life was 4.9 and 4.1 h; and pharmacokinetic-to-pharmacodynamic ratios were ≥ 409 and ≤ 17.8 against ocular pathogens in tears and aqueous humor, respectively. This readily available method is sensitive for biosamples and practical for routine use, facilitating besifloxacin therapy development.

Isotope-Coding Derivatization for Quantitative Profiling of Reactive α-Dicarbonyl Species in Processed Botanicals by Liquid Chromatography-Tandem Mass Spectrometry

α-Dicarbonyls (α-DCs) are key reactive Maillard intermediates with structural diversity and are widely found in foods and in vivo, but little is known regarding the complete molecular profiles of these potentially harmful electrophiles. Herein, we reported a novel isotope-coding derivatization (ICD) strategy for the broad-spectrum, quantitative profiling of (non)target α-DC species in natural foodstuffs. It utilized differential isotope labeling (DIOL) with a reagent pair o-phenylenediamine (OPD)/OPD-d₄ (deuterated) to form stable quinoxalines for class-specific fragmentation-dependent acquisition using liquid chromatography-hybrid quadrupole linear ion trap mass spectrometry (LC-QqLIT). A combination of facile one-pot quantitative labeling and convenient cleanup protocol afforded satisfactory sensitivity, linearity, accuracy (81-116%), and process recovery (86-109% with RSDs < 10%) by matrix-matched ICD-internal standard calibration, without significant matrix interference (-9 to 5%), isotopic effect (<0.5%), and cocktail effect. A more generic DIOL-based LC-QqLIT algorithm integrated double precursor ion and neutral loss scan to trigger enhanced product ions with the unique isobaric doublet tags (4 Da shift), enabling simultaneous screening and relative quantitation of nontarget α-DC analogues in a single analysis. This study has widened the vision on complex α-DC profiles in traditional botanicals, which revealed a wide occurrence of α-DCs in such processed sugar-rich products, yet their abundance varied greatly among different samples.

Novel Fast Chromatography-Tandem Mass Spectrometric Quantitative Approach for the Determination of Plant-Extracted Phytosterols and Tocopherols

Phytosterols and tocopherols are commonly used in food and pharmaceutical industries for their health benefits. Current analysis methods rely on conventional liquid chromatography, using an analytical column, which can be tedious and time consuming. However, simple, and fast analytical methods can facilitate their qualitative and quantitative analysis. In this study, a fast chromatography-tandem mass spectrometric (FC-MS/MS) method was developed and validated for the quantitative analysis of phytosterols and tocopherols. Omitting chromatography by employing flow injection analysis—mass spectrometry (FIA-MS) failed in the quantification of target analytes due to analyte-to-analyte interferences from phytosterols. These interferences arise from their ambiguous MS fingerprints that would lead to false identification and inaccurate quantification. Therefore, a C18 guard column with a 1.9 µm particle size was employed for FC-MS/MS under isocratic elution using acetonitrile/methanol (99:1 v/v) at a flow rate of 600 µL/min. Analyte-to-analyte interferences were identified and eliminated. The false peaks could then be easily identified due to chromatographic separation. In addition, two internal standards were evaluated, namely cholestanol and deuterated cholesterol. Both internal standards contributed to the observed analyte-to-analyte interferences; however, adequate shift in the retention time for deuterated cholesterol eliminated its interferences and allowed for an accurate quantification. The method is fast (1.3 min) compared to published methods and can distinguish false peaks observed in FIA-MS. Seven analytes were quantified simultaneously, namely brassicasterol, campesterol, stigmasterol, β-sitosterol, α-tocopherol, δ-tocopherol, and γ-tocopherol. The method was successfully applied in the quantitative analysis of phytosterols and tocopherols present in the unsaponifiable matter of canola oil deodorizer distillate (CODD). β-sitosterol and γ-tocopherol were the most abundant phytosterols and tocopherols, respectively.

Hydrogels as Drug Delivery Systems: A Review of Current Characterization and Evaluation Techniques

Owing to their tunable properties, controllable degradation, and ability to protect labile drugs, hydrogels are increasingly investigated as local drug delivery systems. However, a lack of standardized methodologies used to characterize and evaluate drug release poses significant difficulties when comparing findings from different investigations, preventing an accurate assessment of systems. Here, we review the commonly used analytical techniques for drug detection and quantification from hydrogel delivery systems. The experimental conditions of drug release in saline solutions and their impact are discussed, along with the main mathematical and statistical approaches to characterize drug release profiles. We also review methods to determine drug diffusion coefficients and in vitro and in vivo models used to assess drug release and efficacy with the goal to provide guidelines and harmonized practices when investigating novel hydrogel drug delivery systems.

Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.

Preparation and Application of 13C-Labeled myo-Inositol to Identify New Catabolic Products in Inositol Metabolism in Lactobacillus casei

myo-Inositol (mI) is widely distributed in all domains of life and is important for several cellular functions, including bacterial survival. The enzymes responsible for the bacterial catabolism of mI, encoded in the iol operon, can vary from one organism to another, and these pathways have yet to be fully characterized. We previously identified a new scyllo-inositol dehydrogenase (sIDH) in the iol operon of Lactobacillus casei that can oxidize mI in addition to the natural substrate, scyllo-inositol, but the product of mI oxidation was not determined. Here we report the identification of these metabolites by monitoring the reaction with ¹³C nuclear magnetic resonance. We prepared all six singly ¹³C-labeled mI isotopomers through a biocatalytic approach and used these labeled inositols as substrates for sIDH. The use of all six singly labeled mI isotopomers allowed for metabolite characterization without isolation steps. sIDH oxidation of mI produces 1l-5-myo-inosose preferentially, but also two minor products, 1d-chiro-inosose and 1l-chiro-inosose. Together with previous crystal structure data for sIDH, we were able to rationalize the observed oxidation preference. Our relatively simple procedure for the preparation of isotopically labeled mI standards can have broad applications for the study of mI biotransformations.

Chromatographic methods development for clinical practice: requirements and limitations

Development of a chromatographic method in bioanalysis is a challenging and complex procedure with many pitfalls and often unexpected reversals that can require several months to accomplish. Even an experienced analytical team must contend many limitations mainly in connection with the strict requirements imposed on current clinical research. These restrictions typically persist throughout the whole development process, from clinical trial assignment, across optimization of extraction of biological materials and chromatographic separation, to validation and data interpretation. This paper describes questions and their possible answers raised during the pre-analytical phase such as use of modern sample preparation techniques in clinical methods, application of internal standards, as well as selection of stationary phases and detection techniques in the analytical phase. Validation problems and interpretation of results are demonstrated with three typical examples of characteristics to be considered, i.e. recovery, matrix effect, and limit of detection vs. lower limit of quantification.

Fast Quantification Without Conventional Chromatography, The Growing Power of Mass Spectrometry

Mass spectrometry (MS) in hyphenated techniques is widely accepted as the gold standard quantitative tool in life sciences. However, MS possesses intrinsic analytical capabilities that allow it to be a stand-alone quantitative technique, particularly with current technological advancements. MS has a great potential for simplifying quantitative analysis without the need for tedious chromatographic separation. Its selectivity relies on multistage MS analysis (MSⁿ), including tandem mass spectrometry (MS/MS), as well as the ever-growing advancements of high-resolution MS instruments. This perspective describes various analytical platforms that utilize MS as a stand-alone quantitative technique, namely, flow injection analysis (FIA), matrix assisted laser desorption ionization (MALDI), including MALDI-MS imaging and ion mobility, particularly high-field asymmetric waveform ion mobility spectrometry (FAIMS). When MS alone is not capable of providing reliable quantitative data, instead of conventional liquid chromatography (LC)-MS, the use of a guard column (i.e., fast chromatography) may be sufficient for quantification. Although the omission of chromatographic separation simplifies the analytical process, extra procedures may be needed during sample preparation and clean-up to address the issue of matrix effects. The discussion of this manuscript focuses on key parameters underlying the uniqueness of each technique for its application in quantitative analysis without the need for a chromatographic separation. In addition, the potential for each analytical strategy and its challenges are discussed as well as improvements needed to render them as mainstream quantitative analytical tools. Overcoming the hurdles for fully validating a quantitative method will allow MS alone to eventually become an indispensable quantitative tool for clinical and toxicological studies.

A Set of Global Metabolomic Biomarker Candidates to Predict the Risk of Dry Eye Disease

Purpose

We used ultraperformance liquid chromatography coupled with quadrupole/time-of-flight tandem mass spectrometry (UPLC-Q/TOF-MS/MS) to analyze the metabolic profile of reflex tears obtained from patients with dry eye disorders.

Methods

We performed a cross-sectional study involving 113 subjects: 85 patients diagnosed with dry eye syndrome (dry eye group) and 28 healthy volunteers (control group). Reflex tears (20–30 μl) were collected from the tear meniscus of both eyes of each subject using a Schirmer I test strip. MS data were acquired with a standard workflow by UPLC-Q/TOF-MS/MS. Metabolites were quantitatively analyzed and matched with entries in the Metlin, Massbank, and HMDB databases. Least absolute shrinkage and selection operator (LASSO) regression was conducted to detect important metabolites. Multiple logistic regression was used to identify the significant metabolic biomarker candidates for dry eye syndrome. Open database sources, including the Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst, were used to identify metabolic pathways.

Results

After the LASSO regression and multiple logistic regression analysis, 4 of 20 metabolic biomarker candidates were significantly correlated with Ocular Surface Disease Index score, 42 of 57 with fluorescein breakup time, and 26 of 57 with fluorescein staining. By focusing on the overlap of these three sets, 48 of 51 metabolites contributed to the incidence of dry eye and there were obvious changes in different age groups. Metabolic pathway analysis revealed that the main pathways were glucose metabolism, amino acid metabolism, and glutathione metabolism.

Conclusion

Dry eye syndrome induces changes in the metabolic profile of tears, and the trend differs with age. This evidence reveals the relationship between changes in metabolites, symptoms of dry eye syndrome, and age.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Mapping Metabolite and ICD-10 Associations

The search for novel metabolic biomarkers is intense but has had limited practical outcomes for medicine. Part of the problem is that we lack knowledge of how different comorbidities influence biomarkers’ performance. In this study, 49 metabolites were measured by targeted LC/MS protocols in the serum of 1011 volunteers. Their performance as potential biomarkers was evaluated by the area under the curve of receiver operator characteristics (AUC-ROC) for 105 diagnosis codes or code groups from the 10th revision of the international classification of diseases (ICD-10). Additionally, the interferences between diagnosis codes were investigated. The highest AUC-ROC values for individual metabolites and ICD-10 code combinations reached a moderate (0.7) range. Most metabolites that were found to be potential markers remained so independently of the control group composition or comorbidities. The precise value of the AUC-ROC, however, could vary depending on the comorbidities. Moreover, networks of metabolite and disease associations were built in order to map diseases, which may interfere with metabolic biomarker research on other diseases.

Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality

During the last years, an extraordinary effort has been made to identify biomarkers as potential tools for improving prevention, diagnosis, drug response and drug development in psychiatric disorders. Contrary to other diseases, mental illnesses are classified by diagnostic categories with a broad variety list of symptoms. Consequently, patients diagnosed from the same psychiatric illness present a great heterogeneity in their clinical presentation. This fact together with the incomplete knowledge of the neurochemical alterations underlying mental disorders, contribute to the limited efficacy of current pharmacological options. In this respect, the identification of biomarkers in psychiatry is becoming essential to facilitate diagnosis through the developing of markers that allow to stratify groups within the syndrome, which in turn may lead to more focused treatment options. In order to shed light on this issue, this review summarizes the concept and types of biomarkers including an operational definition for therapeutic development. Besides, the advances in this field were summarized and sorted into five categories, which include genetics, transcriptomics, proteomics, metabolomics, and epigenetics. While promising results were achieved, there is a lack of biomarker investigations especially related to treatment response to psychiatric conditions. This review includes a final conclusion remarking the future challenges required to reach the goal of developing valid, reliable and broadly-usable biomarkers for psychiatric disorders and their treatment. The identification of factors predicting treatment response will reduce trial-and-error switches of medications facilitating the discovery of new effective treatments, being a crucial step towards the establishment of greater personalized medicine.