Isotope Corrected Chiral and Achiral Nontargeted Metabolomics: An Approach for High Accuracy and Precision Metabolomics Based on Derivatization and Its Application to Cerebrospinal Fluid of Patients with Alzheimer’s Disease

Comprehensive Profiling of Amine-Containing Metabolite Isomers with Chiral Phosphorus Reagents

Metabolite isomers play diverse and crucial roles in various metabolic processes. However, in untargeted metabolomics analysis, it remains a great challenge to distinguish between the constitutional isomers and enantiomers of amine-containing metabolites due to their similar chemical structures and physicochemical properties. In this work, the triplex stable isotope N-phosphoryl amino acids labeling (SIPAL) is developed to identify and relatively quantify the amine-containing metabolites and their isomers by using chiral phosphorus reagents coupled with high-resolution tandem mass spectroscopy. The constitutional isomers could be effectively distinguished with stereo isomers by using the diagnosis ions in MS/MS spectra. The in-house software MS-Isomerism has been parallelly developed for high-throughput screening and quantification. The proposed strategy enables the unbiased detection and relative quantification of isomers of amine-containing metabolites. Based on the characteristic triplet peaks with SIPAL tags, a total of 854 feature peaks with 154 isomer groups are successfully recognized as amine-containing metabolites in liver cells, in which 37 amine-containing metabolites, including amino acids, polyamines, and small peptides, are found to be significantly different between liver cancer cells and normal cells. Notably, it is the first time to identify S-acetyl-glutathione as an endogenous metabolite in liver cells. The SIPAL strategy could provide spectacular insight into the chemical structures and biological functions of the fascinating amine-containing metabolite isomers. The feasibility of SIPAL in isomeric metabolomics analysis may reach a deeper understanding of the mirror-chemistry in life and further advance the discovery of novel biomarkers for disease diagnosis.

Systems biology strategy through integrating metabolomics and network pharmacology to reveal the mechanisms of Xiaopi Hewei Capsule improves functional dyspepsia

Functional dyspepsia (FD) is one of the more common functional disorders, with a prevalence of 20-25 %. It seriously affects the quality life of patients. Xiaopi Hewei Capsule (XPHC) is a classic formula originated from the Chinese Miao minority. Clinical studies have demonstrated that XPHC can effectively alleviate the symptoms of FD, but the molecular mechanism has not been elucidated. The purpose of this work is to investigate the mechanism of XPHC on FD by integrating metabolomics and network pharmacology. The mice models of FD were established, and gastric emptying rate, small intestine propulsion rate, serum level of motilin and gastrin were evaluate to study the interventional effect of XPHC on FD. Next, a metabolomics strategy has been developed to screen differential metabolites and related metabolic pathways induced by XPHC. Then, prediction of active compounds, targets and pathways of XPHC in treating FD were carried out by commonly used network pharmacological method. Finally, two parts of the results were integrated to investigate therapeutic mechanism of XPHC on FD, which were preliminary validated based on molecular docking. Thus, twenty representative different metabolites and thirteen related pathways of XPHC in treating FD were identified. Most of these metabolites were restored using modulation after XPHC treatment. The results of the network pharmacology analysis showed ten crucial compounds and nine hub genes related to the treatment of FD with XPHC. The further integrated analysis focused on four key targets, such as albumin (ALB), epidermal growth factor receptor (EGFR), tumor necrosis factor (TNF) and roto-oncogene tyrosine-protein kinase Src (SRC), and three representative biomarkers such as citric acid, L-leucine and eicosapentaenoic acid. Furthermore, molecular docking results showed that ten bioactive compounds from XPHC have good binding interactions with the four key genes. The functional enrichment analysis indicated that the potential mechanism of XPHC in treating FD was mainly associated with energy metabolism, amino acid metabolism, lipid metabolism, inflammatory reactions and mucosal repair. Our work confirms that network pharmacology-integrated metabolomics strategyis a powerful means to reveal the therapeutic mechanisms of XPHC improves FD, which contribute its further scientific research.

Instrument-type effects on chemical isotope labeling LC-MS metabolome analysis: Quadrupole time-of-flight MS vs. Orbitrap MS

Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with markedly improved metabolomic coverage and quantification accuracy over the conventional LC-MS technique. In addition, with differential isotope labeling, each labeled metabolite is detected as a peak pair in the mass spectra, offering the possibility of differentiating true metabolite peaks from the singlet noise or background peaks. In this study, we examined the effects of instrument type on the detectability of true metabolites with a focus on the comparison of quadrupole time-of-flight (QTOF) and Orbitrap mass spectrometers. Using the same ultra-high-performance liquid chromatography setup and optimized running conditions for QTOF and Orbitrap, we compared the total number of peak pairs detected and identified from the two instruments using human urine and serum as the test samples. Many common peak pairs were detected from the two instruments; however, there were a significant number of unique peak pairs detected in each type of instrument. By combining the datasets obtained using QTOF and Orbitrap, the total number of peak pairs detected could be significantly increased. We also examined the effect of mass resolving power on peak pair detection in Orbitrap (60,000 vs. 120,000 resolution). The observed differences in peak pair detectability were much less than those of QTOF vs. Orbitrap. However, the type of peak pairs detected using different resolutions could be somewhat different, offering the possibility of increasing the overall number of peak pairs by combining the two datasets obtained at two different resolutions. The results from this study clearly indicate that instrument type can have a profound effect on metabolite detection in CIL LC-MS. Therefore, comparison of metabolome data generated using different instruments needs to be carefully done. Moreover, future research (e.g., hardware modifications) is warranted to minimize the differences in order to generate more reproducible metabolome data from different types of instruments.

Indirect Enantioseparations: Recent Advances in Chiral Metabolomics for Biomedical Research

Chiral metabolomics is starting to become a well-defined research field, powered by the recent advances in separation techniques. This review aimed to cover the most relevant advances in indirect enantioseparations of endogenous metabolites that were published over the last 10 years, including improvements and development of new chiral derivatizing agents, along with advances in separation methodologies. Moreover, special emphasis is put on exciting advances in separation techniques combined with mass spectrometry, such as chiral discrimination by ion-mobility mass spectrometry together with untargeted strategies for profiling of chiral metabolites in complex matrices. These advances signify a leap in chiral metabolomics technologies that will surely offer a solid base to better understand the specific roles of enantiomeric metabolites in systems biology.

High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer's Disease with Mouse Models

Alzheimer's disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Enantioselective metabolomics by liquid chromatography-mass spectrometry

Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.

Dimethylcysteine (DiCys)/o-Phthalaldehyde Derivatization for Chiral Metabolite Analyses: Cross-Comparison of Six Chiral Thiols

Metabolomics profiling using liquid chromatography-mass spectrometry (LC-MS) has become an important tool in biomedical research. However, resolving enantiomers still represents a significant challenge in the metabolomics study of complex samples. Here, we introduced N,N-dimethyl-l-cysteine (dimethylcysteine, DiCys), a chiral thiol, for the o-phthalaldehyde (OPA) derivatization of enantiomeric amine metabolites. We took interest in DiCys because of its potential for multiplex isotope-tagged quantification. Here, we characterized the usefulness of DiCys in reversed-phase LC-MS analyses of chiral metabolites, compared against five commonly used chiral thiols: N-acetyl-l-cysteine (NAC); N-acetyl-d-penicillamine (NAP); isobutyryl-l-cysteine (IBLC); N-(tert-butoxycarbonyl)-l-cysteine methyl ester (NBC); and N-(tert-butylthiocarbamoyl)-l-cysteine ethyl ester (BTCC). DiCys and IBLC showed the best overall performance in terms of chiral separation, fluorescence intensity, and ionization efficiency. For chiral separation of amino acids, DiCys/OPA also outperformed Marfey’s reagents: 1-fluoro-2-4-dinitrophenyl-5-l-valine amide (FDVA) and 1-fluoro-2-4-dinitrophenyl-5-l-alanine amide (FDAA). As proof of principle, we compared DiCys and IBLC for detecting chiral metabolites in aqueous extracts of rice. By LC–MS analyses, both methods detected twenty proteinogenic l-amino acids and seven d-amino acids (Ala, Arg, Lys, Phe, Ser, Tyr, and Val), but DiCys showed better analyte separation. We conclude that DiCys/OPA is an excellent amine-derivatization method for enantiomeric metabolite detection in LC-MS analyses.

Experimental design of a stable isotope labeling derivatized UHPLC-MS/MS method for the detection/quantification of primary/secondary bile acids in biofluids

An efficient analytical platform is required to characterize the human metabolome in pathology. For this purpose, ultra-high performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) combined with chemical derivatization stands out as one of the most powerful techniques. A targeted metabolomics platform for 11 bile acids (BAs) profiling in human serum and bile samples using a stable isotope labeling derivatization (SILD) was applied. For SILD, the design of experiments (DoE) was employed to optimize the reaction conditions such five factors in three levels. The sample preparation built upon a liquid-liquid extraction requiring small volumes (20 μL). In application, the relation between the BA and short-chain fatty acid levels in human serum and bile samples from patients with bile duct diseases were investigated. The proposed method offers significant utility in the large-scale biological analyses of hepato-biliary-pancreatic-related diseases.

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

Metabolic Profiling of Urinary Chiral Amino-Containing Biomarkers for Gastric Cancer Using a Sensitive Chiral Chlorine-Labeled Probe by HPLC-MS/MS

Screening of characteristic biomarkers from chiral amino-containing metabolites in biological samples is difficult and important for the noninvasive diagnosis of gastric cancer (GC). Here, an enantiomeric pair of chlorine-labeled probes d-BPCl and l-BPCl was synthesized to selectively label d- and l-amino-containing metabolites in biological samples, respectively. Incorrect structural annotations were excluded according to the characteristic 3:1 abundance ratio of natural chlorine isotopes (³⁵Cl and ³⁷Cl) derived from the probes. A sensitive C18 HPLC-QQQ-MS/MS method in combination with the probes was then developed and applied in metabolomic analysis of amino-containing metabolites in urine samples. A total of 161 amino-containing metabolites were rapidly separated and determined, and 28 chiral amino acids and achiral glycine were quantified with good precision and accuracy. A total of 18 differential variables were discriminated by analyzing chiral amino-containing metabolites in urine samples of the GC patient and healthy person using the probe-based HPLC-MS/MS-MRM method combined with the orthogonal partial least squares discriminant analysis and Mann-Whitney U test with false discovery rate correction for multiple hypotheses. A diagnostic regression model including d-isoleucine, d-serine, and β-(pyrazol-1-yl)-l-alanine and age was then constructed with an average prediction correctness of 88.9% in the validation set. This work established a close connection between gastric cancer and chiral amino-containing metabolites. The mass spectrometry data analyzed in the study are publicly available via Mendeley Data (DOI: 10.17632/4bd93j9yrr.1).

Novel Strategy for Untargeted Chiral Metabolomics using Liquid Chromatography-High Resolution Tandem Mass Spectrometry

Stereospecific recognition of metabolites plays a significant role in the detection of potential disease biomarkers thereby providing new insights in diagnosis and prognosis. D-Hdroxy/amino acids are recognized as potential biomarkers in several metabolic disorders. Despite continuous advances in metabolomics technologies, the simultaneous measurement of different classes of enantiomeric metabolites in a single analytical run remains challenging. Here, we develop a novel strategy for untargeted chiral metabolomics of hydroxy/amine groups (-OH/-NH₂) containing metabolites, including all hydroxy acids (HAs) and amino acids (AAs), by chiral derivatization coupled with liquid chromatography-high resolution tandem mass spectrometry (LC-HR-MS/MS). Diacetyl-tartaric anhydride (DATAN) was used for the simultaneous derivatization of-OH/-NH₂ containing metabolites as well as the resulting diastereomers, and all the derivatized metabolites were resolved in a single analytical run. Data independent MS/MS acquisition (DIA) was applied to positively identify DATAN-labeled metabolites based on reagent specific diagnostic fragment ions. We discriminated chiral from achiral metabolites based on the reversal of elution order of D and L isomers derivatized with the enantiomeric pair (±) of DATAN in an untargeted manner. Using the developed strategy, a library of 301 standards that consisted of 214 chiral and 87 achiral metabolites were separated and detected in a single analytical run. This approach was then applied to investigate the enantioselective metabolic profile of the bone marrow (BM) and peripheral blood (PB) plasma samples from patients with acute myeloid leukemia (AML) at diagnosis and following completion of the induction phase of chemotherapeutic treatment. The sensitivity and selectivity of the developed method enabled the detection of trace levels of the D-enantiomer of HAs and AAs in primary plasma patient samples. Several of these metabolites were significantly altered in response to chemotherapy. The developed LC-HR-MS method entails a valuable step forward in chiral metabolomics.

Introducing an Experimental Design Approach for Efficient Optimization of Chiral Derivatization Conditions for D- and L-Glyceric Acids

A sensitive analytical method was developed for individual analyses of D- and L-glyceric acids by chiral derivatization - liquid chromatography-tandem mass spectrometry. To elucidate rapid and efficient optimization for derivatization we newly introduced a concept of design of experiments (DOE). The optimization of major 5 factors in the derivatization could be predicted with only 28 measurements. By applying DOE to optimization, the yields of desired derivatives increased five-fold against before optimization.