Relative quantification of amine-containing metabolites using isobaric N,N-dimethyl leucine (DiLeu) reagents via LC-ESI-MS/MS and CE-ESI-MS/MS

Salivary metabolomic identification of biomarker candidates for oral melanoma and oral squamous cell carcinoma in dogs

BACKGROUND

Oral melanoma (OM) and oral squamous cell carcinoma (OSCC) are frequently diagnosed in dogs, presenting a challenge in distinguishing them from benign oral tumors (BN). Salivary metabolomic biomarkers offer a practical solution because of saliva's direct contact with tumors and the noninvasive nature of collection.

OBJECTIVE

Assess the diversity and abundance of the salivary metabolome in dogs with BN, OM, and OSCC using amine/phenol submetabolome analysis and high-performance chemical isotope labeling liquid chromatography-mass spectrometry (CIL LC-MS).

ANIMALS

Study included 11 BN, 24 OM, 10 OSCC, and 20 healthy control dogs.

METHODS

Case-control cross-sectional study was conducted to assess salivary submetabolic profiles in dogs with BN, OM, and OSCC and healthy dogs. Samples were labeled with 12C-dansyl chloride and analyzed using CIL LC-MS targeted to amine- and phenol-containing metabolites for amine/phenol submetabolome analysis.

RESULTS

Distinct clusters and significant differences in metabolite concentrations were observed among the oral cancer, BN, and control groups. A total of 154 and 66 metabolites showed significantly altered concentrations, particularly in OM and OSCC, respectively, when compared with BN (Padj < .05). Potential metabolic biomarkers were identified for each cancer, including decreased concentrations of seryl-arginine and sarcosine in OSCC. Moreover, high-confidence putative metabolites were identified, including an increase in tryptophyl-threonine and a decrease in 1,2-dihydroxynapthalene-6-sulfonic acid and hydroxyprolyl-hydroxyproline for OM.

CONCLUSIONS AND CLINICAL IMPORTANCE

We identified high coverage of the amine/phenol submetabolome, including seryl-arginine, and sarcosine, in OSCC. Our findings emphasize the potential of these biomarkers for distinguishing between oral OSCC and BN in dogs.

CHRISTMAS: Chiral Pair Isobaric Labeling Strategy for Multiplexed Absolute Quantitation of Enantiomeric Amino Acids

Amino acids (AAs) in the d-form are involved in multiple pivotal neurological processes, although their l-enantiomers are most commonly found. Mass spectrometry-based analysis of low-abundance d-AAs has been hindered by challenging enantiomeric separation from l-AAs, low sensitivity for detection, and lack of suitable internal standards for accurate quantification. To address these critical gaps, N,N-dimethyl-l-leucine (l-DiLeu) tags are first validated as novel chiral derivatization reagents for chromatographic separation of 20 pairs of d/l-AAs, allowing the construction of a 4-plex isobaric labeling strategy for enantiomer-resolved quantification through single step tagging. Additionally, the creative design of N,N-dimethyl-d-leucine (d-DiLeu) reagents offers an alternative approach to generate analytically equivalent internal references of d-AAs using d-DiLeu-labeled l-AAs. By labeling cost-effective l-AA standards using paired d- and l-DiLeu, this approach not only enables absolute quantitation of both d-AAs and l-AAs from complex biological matrices with enhanced precision but also significantly boosts the combined signal intensities from all isobaric channels, greatly improving the detection and quantitation of low-abundance AAs, particularly d-AAs. We term this quantitative strategy CHRISTMAS, which stands for chiral pair isobaric labeling strategy for multiplexed absolute quantitation. Leveraging the ion mobility collision cross section (CCS) alignment, interferences from coeluting isomers/isobars are effectively filtered out to provide improved quantitative accuracy. From wild-type and Alzheimer's disease (AD) mouse brains, we successfully quantified 20 l-AAs and 5 d-AAs. The significant presence and differential trends of certain d-AAs compared to those of their l-counterparts provide valuable insights into the involvement of d-AAs in aging, AD progression, and neurodegeneration.

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.

Isobaric 4-Plex Tagging for Absolute Quantitation of Biological Acids in Diabetic Urine Using Capillary LC-MS/MS

Isobaric labeling in mass spectrometry enables multiplexed absolute quantitation and high throughput, while minimizing full scan spectral complexity. Here, we use 4-plex isobaric labeling with a fixed positive charge tag to improve quantitation and throughput for polar carboxylic acid metabolites. The isobaric tag uses an isotope-encoded neutral loss to create mass-dependent reporters spaced 2 Da apart and was validated for both single- and double-tagged analytes. Tags were synthesized in-house using deuterated formaldehyde and methyl iodide in a total of four steps, producing cost-effective multiplexing. No chromatographic deuterium shifts were observed for single- or double-tagged analytes, producing consistent reporter ratios across each peak. Perfluoropentanoic acid was added to the sample to drastically increase retention of double-tagged analytes on a C18 column. Excess tag was scavenged and extracted using hexadecyl chloroformate after reaction completion. This allowed for removal of excess tag that typically causes ion suppression and column overloading. A total of 54 organic acids were investigated, producing an average linearity of 0.993, retention time relative standard deviation (RSD) of 0.58%, and intensity RSD of 12.1%. This method was used for absolute quantitation of acid metabolites comparing control and type 1 diabetic urine. Absolute quantitation of organic acids was achieved by using one isobaric lane for standards, thereby allowing for analysis of six urine samples in two injections. Quantified acids showed good agreement with previous work, and six significant changes were found. Overall, this method demonstrated 4-plex absolute quantitation of acids in a complex biological sample.

Multiplexed analysis of amino acids in mice brain microdialysis samples using isobaric labeling and liquid chromatography-high resolution tandem mass spectrometry

We developed a new multiplexed reversed phase liquid chromatography-high resolution tandem mass spectrometric (LC-MS/MS) method. The method is based on isobaric labeling with a tandem mass tag (TMT10-plex) and stable isotope-labeled internal standards, and was used to analyze amino acids in mouse brain microdialysis samples. The TMT10-plex labeling of amino acids allowed analysis of ten samples in one LC-MS/MS run, significantly increasing the sample throughput. The method provides good chromatographic performance (peak half-width between 0.04-0.12 min), allowing separation of all TMT-labeled amino acids with acceptable resolution and high sensitivity (limits of detection typically around 10 nM). The use of stable isotope-labeled internal standards, together with TMT10-plex labeling, ensured good repeatability (relative standard deviation ≤ 12.1 %) and linearity (correlation coefficient > 0.994), indicating good quantitative performance of the multiplexed method. The method was applied to study the effect of d-amphetamine microdialysis perfusion on amino acid concentrations in the mouse brain. All amino acids were reliably detected and quantified, indicating that the method is sensitive enough to detect low concentrations of amino acids in brain microdialysis samples.

Clinical Insights into Mitochondrial Neurodevelopmental and Neurodegenerative Disorders: Their Biosignatures from Mass Spectrometry-Based Metabolomics

Mitochondria are dynamic multitask organelles that function as hubs for many metabolic pathways. They produce most ATP via the oxidative phosphorylation pathway, a critical pathway that the brain relies on its energy need associated with its numerous functions, such as synaptic homeostasis and plasticity. Therefore, mitochondrial dysfunction is a prevalent pathological hallmark of many neurodevelopmental and neurodegenerative disorders resulting in altered neurometabolic coupling. With the advent of mass spectrometry (MS) technology, MS-based metabolomics provides an emerging mechanistic understanding of their global and dynamic metabolic signatures. In this review, we discuss the pathogenetic causes of mitochondrial metabolic disorders and the recent MS-based metabolomic advances on their metabolomic remodeling. We conclude by exploring the MS-based metabolomic functional insights into their biosignatures to improve diagnostic platforms, stratify patients, and design novel targeted therapeutic strategies.

Recent Advances in Analytical Approaches for Glycan and Glycopeptide Quantitation

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

Chemical Isotope Labeling LC-MS for Metabolomics

Due to the great diversity of chemical and physical properties of metabolites as well as a wide range of concentrations of metabolites present in metabolomic samples, performing comprehensive and quantitative metabolome analysis is a major analytical challenge. Conventional approach of combining various techniques and methods with each detecting a fraction of the metabolome can lead to the increase in overall metabolomic coverage. However, this approach requires extensive investment in equipment and analytical expertise with still relatively low coverage and low sample throughput. Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) offers an alternative means of increasing metabolomic coverage while maintaining high quantification precision and accuracy. This chapter describes the CIL LC-MS method and its key features for metabolomic analysis.

Nano-liquid chromatography-mass spectrometry and recent applications in omics investigations

Liquid chromatography coupled to mass spectrometry (LC-MS) is one of the most powerful tools in identifying and quantitating molecular species. Decreasing column diameter from the millimeter to micrometer scale is now a well-developed method which allows for sample limited analysis. Specific fabrication of capillary columns is required for proper implementation and optimization when working in the nanoflow regime. Coupling the capillary column to the mass spectrometer for electrospray ionization (ESI) requires reduction of the subsequent emitter tip. Reduction of column diameter to capillary scale can produce improved chromatographic efficiency and the reduction of emitter tip size increased sensitivity of the electrospray process. This improved sensitivity and ionization efficiency is valuable in analysis of precious biological samples where analytes vary in size, ion affinity, and concentration. In this review we will discuss common approaches and challenges in implementing nLC-MS methods and how the advantages can be leveraged to investigate a wide range of biomolecules.

Urinary Amine Metabolomics Characterization with Custom 12-Plex Isobaric DiLeu Labeling

Lower urinary tract symptoms (LUTS) is common in aging males. Disease etiology is largely unknown but likely includes inflammation and age-related changes in steroid hormones. Diagnosis is currently based on subjective symptom scores, and mainstay treatments can be ineffective and bothersome. Biomarker discovery efforts could facilitate objective diagnostic criteria for personalized medicine and new potential druggable pathways. To identify urine metabolite markers specific to hormone-induced bladder outlet obstruction, we applied our custom synthesized multiplex isobaric tags to monitor the development of bladder outlet obstruction across time in an experimental mouse model of LUTS. Mouse urine samples were collected before treatment and after 2, 4, and 8 weeks of steroid hormone treatment and subsequently analyzed by nanoflow ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry. Accurate and high-throughput quantification of amine-containing metabolites was achieved by 12-plex DiLeu isobaric labeling. Metandem, a novel online software tool for large-scale isobaric labeling-based metabolomics, was used for identification and relative quantification of labeled metabolites. A total of 59 amine-containing metabolites were identified and quantified, 9 of which were changed significantly by the hormone treatment. Metabolic pathway analyses showed that three metabolic pathways were potentially disrupted. Among them, the arginine and proline metabolism pathway was significantly dysregulated both in this model and in a prior analysis of LUTS patient samples. Proline and citrulline were significantly changed in both samples and serve as attractive candidate biomarkers. The 12-plex DiLeu isobaric labeling with Metandem data processing presents an accessible and efficient workflow for an amine-containing metabolome study in biological specimens.

Isobaric Labeling Strategy Utilizing 4-Plex N,N-Dimethyl Leucine (DiLeu) Tags Reveals Proteomic Changes Induced by Chemotherapy in Cerebrospinal Fluid of Children with B-Cell Acute Lymphoblastic Leukemia

The use of mass spectrometry for protein identification and quantification in cerebrospinal fluid (CSF) is at the forefront of research efforts to identify and explore biomarkers for the early diagnosis and prognosis of neurologic disorders. Here we implemented a 4-plex N,N-dimethyl leucine (DiLeu) isobaric labeling strategy in a longitudinal study aiming to investigate protein dynamics in children with B-cell acute lymphoblastic leukemia (B-cell ALL) undergoing chemotherapy. The temporal profile of CSF proteome during chemotherapy treatment at weeks 5, 10-14, and 24-28 highlighted many differentially expressed proteins, such as neural cell adhesion molecule, neuronal growth regulator 1, and secretogranin-3, all of which play important roles in neurodegenerative diseases. A total of 63 proteins were significantly altered across all of the time points investigated. The most over-represented biological processes from gene ontology analysis included platelet degranulation, complement activation, cell adhesion, fibrinolysis, neuron projection, regeneration, and regulation of neuron death. We expect that results from this and future studies will provide a means to monitor neurotoxicity and develop strategies to prevent central nervous system injury in response to chemotherapy in children.

Liquid Chromatography Tandem Mass Spectrometry Based Label-Free Quantification Method for Assessment of Allergen-Induced Anaphylactoid Reactions

Mast cells are essential in mediating inflammatory processes. When activated, mast cells can rapidly release characteristic granules and various mediators into the interstitium. Tryptase (TPS) and β-hexosaminidase (HEXB) are typical protease mediators stored in granules and released upon activation. They have been recognized as important biomarkers of anaphylaxis, and the released level is associated with the severity of allergic reactions. In this study, a sensitive, accurate, and selective liquid chromatography tandem mass spectrometry (LC-MS/MS) method for simultaneously quantifying the two biomarkers was developed and validated in LAD2 cell culture supernatant, and P₁₄R was used as internal standard. Good linearity was observed in the range of 50-2500 ng/mL for TPS and 10-2000 ng/mL for HEXB both with R² > 0.99. The matrix effect and recovery were both within acceptable limits. We quantified TPS and HEXB released from Laboratory of Allergic Disease 2 (LAD2) mast cells treated with several potential allergens, and the results demonstrate that the method can be used to investigate TPS and HEXB levels in LAD2 mast cell model during allergy research. We anticipate our approach to be a robust and sensitive assessment method for more biomarkers with similar kinetics characteristics and to be a major tool of allergic drug assessment or antiallergic drug development in research.

Revelation of the chiral recognition of alanine and leucine in an l-phenylalanine-based metal–organic framework

An l-phenylalanine-based Zn-MOF, namely [Zn₂(l-Phe)₂(bpe)₂]_n, was designed for experimentally revealing the chiral recognition mechanism to alanine and leucine by means of ¹³C CP MAS NMR spectroscopy, XPS and control experiment.

Metandem: An online software tool for mass spectrometry-based isobaric labeling metabolomics

Mass spectrometry-based stable isotope labeling provides the advantages of multiplexing capability and accurate quantification but requires tailored bioinformatics tools for data analysis. Despite the rapid advancements in analytical methodology, it is often challenging to analyze stable isotope labeling-based metabolomics data, particularly for isobaric labeling using MS/MS reporter ions for quantification. We report Metandem, a novel online software tool for isobaric labeling-based metabolomics, freely available at http://metandem.com/web/. Metandem provides a comprehensive data analysis pipeline integrating feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization, and statistical analysis. Systematic evaluation of the Metandem tool was demonstrated on UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS and MALDI-MS platforms, via duplex, 4-plex, 10-plex, and 12-plex isobaric labeling experiments and the application to various biological samples.

Quantitative proteomic analysis of a genetically induced prostate inflammation mouse model via custom 4-plex DiLeu isobaric labeling

Inflammation is involved in many prostate pathologies including infection, benign prostatic hyperplasia, and prostate cancer. Preclinical models are critical to our understanding of disease mechanisms, yet few models are genetically tractable. Here, we present a comparative quantitative proteomic analysis of urine from mice with and without prostate-specific inflammation induced by conditional prostate epithelial IL-1β expression. Relative quantification and sample multiplexing was achieved using custom 4-plex N,N-dimethyl leucine (DiLeu) isobaric tags and nanoflow ultrahigh-performance liquid chromatography coupled to high-resolution tandem mass spectrometry. Each set of 4-plex DiLeu reagents allows four urine samples to be analyzed simultaneously, providing high-throughput and accurate quantification of urinary proteins. Proteins involved in the acute phase response, including haptoglobin, inter-α-trypsin inhibitor, and α1-antitrypsin 1-1, were differentially represented in the urine of mice with prostate inflammation. Mass spectrometry-based quantitative urinary proteomics represents a promising bioanalytical strategy for biomarker discovery and the elucidation of molecular mechanisms in urological research.

Urinary Metabolomic and Proteomic Analyses in a Mouse Model of Prostatic Inflammation

Lower urinary tract symptoms (LUTS) are common among aging men. Since prostatic inflammation is one of its etiologies, it is plausible that urinary metabolite and protein biomarkers could be identified and used to diagnose inflammation-induced LUTS. We characterized the urine metabolome and proteome in a mouse model of bacterial-induced prostatic inflammation. Mass Spectrometry (MS)-based multi-omics analysis was employed to discover urinary protein and metabolite-based biomarkers. The investigation of isobaric dimethylated leucine (DiLeu) labeling on metabolites allowed metabolomics and proteomics analysis on the same liquid chromatography (LC)-MS platform. In total, 143 amine-containing metabolites and 1058 urinary proteins were identified and quantified (data are available via ProteomeXchange with identifier PXD018023); among them, 14 metabolites and 168 proteins were significantly changed by prostatic inflammation. Five metabolic pathways and four inflammation-related biological processes were potentially disrupted. By comparing our findings with urinary biomarkers identified in a mouse model of genetic-induced prostate inflammation and with those previously found to be associated with LUTS in older men, we identified creatine, haptoglobin, immunoglobulin kappa constant and polymeric Ig receptor as conserved biomarkers for prostatic inflammation associated with LUTS. These data suggest that these putative biomarkers could be used to identify men in which prostate inflammation is present and contributing to LUTS.

Current Trends in Cancer Biomarker Discovery Using Urinary Metabolomics: Achievements and New Challenges

BACKGROUND

The development of effective screening methods for early cancer detection is one of the foremost challenges facing modern cancer research. Urinary metabolomics has recently emerged as a potentially transformative approach to cancer biomarker discovery owing to its noninvasive sampling characteristics and robust analytical feasibility.

OBJECTIVE

To provide an overview of new developments in urinary metabolomics, cover the most promising aspects of hyphenated techniques in untargeted and targeted metabolomics, and to discuss technical and clinical limitations in addition to the emerging challenges in the field of urinary metabolomics and its application to cancer biomarker discovery.

METHODS

A systematic review of research conducted in the past five years on the application of urinary metabolomics to cancer biomarker discovery was performed. Given the breadth of this topic, our review focused on the five most widely studied cancers employing urinary metabolomics approaches, including lung, breast, bladder, prostate, and ovarian cancers.

RESULTS

As an extension of conventional metabolomics, urinary metabolomics has benefitted from recent technological developments in nuclear magnetic resonance, mass spectrometry, gas and liquid chromatography, and capillary electrophoresis that have improved urine metabolome coverage and analytical reproducibility. Extensive metabolic profiling in urine has revealed a significant number of altered metabolic pathways and putative biomarkers, including pteridines, modified nucleosides, and acylcarnitines, that have been associated with cancer development and progression.

CONCLUSION

Urinary metabolomics presents a transformative new approach toward cancer biomarker discovery with high translational capacity to early cancer screening.

Comprehensive urinary metabolomic characterization of a genetically induced mouse model of prostatic inflammation

Dysfunction of the lower urinary tract commonly afflicts the middle-aged and aging male population. The etiology of lower urinary tract symptoms (LUTS) is multifactorial. Benign prostate hyperplasia, fibrosis, smooth muscle contractility, and inflammation likely contribute. Here we aim to characterize the urinary metabolomic profile associated with prostatic inflammation, which could inform future personalized diagnosis or treatment, as well as mechanistic research. Quantitative urinary metabolomics was conducted to examine molecular changes following induction of inflammation via conditional Interleukin-1β expression in prostate epithelia using a novel transgenic mouse strain. To advance method development for urinary metabolomics, we also compared different urine normalization methods and found that normalizing urine samples based on osmolality prior to LC-MS most completely separated urinary metabolite profiles of mice with and without prostate inflammation via principal component analysis. Global metabolomics was combined with advanced machine learning feature selection and classification for data analysis. Key dysregulated metabolites and pathways were identified and were relevant to prostatic inflammation, some of which overlapped with our previous study of human LUTS patients. A binary classification model was established via the support vector machine algorithm to accurately differentiate control and inflammation groups, with an area-under-the-curve value of the receiver operating characteristic of 0.81, sensitivity of 0.974 and specificity of 0.995, respectively. This study generated molecular profiles of non-bacterial prostatic inflammation, which could assist future efforts to stratify LUTS patients and develop new therapies.

Targeted Neurotransmitters Profiling Identifies Metabolic Signatures in Rat Brain by LC-MS/MS: Application in Insomnia, Depression and Alzheimer's Disease

Epidemiological, cross-sectional, and prospective studies have suggested that insomnia, Alzheimer’s disease (AD) and depression are mutually interacting conditions and frequently co-occur. The monoamine and amino acid neurotransmitter systems in central nervous system were involved in the examination of neurobiological processes of this symptom complex. However, few studies have reported systematic and contrastive discussion of different neurotransmitters (NTs) changing in these neurological diseases. Thus, it is necessary to establish a reliable analytical method to monitoring NTs and their metabolite levels in rat brain tissues for elucidating the differences in pathophysiology of these neurological diseases. A rapid, sensitive and reliable LC-MS/MS method was established for simultaneous determination of the NTs and their metabolites, including tryptophan (Trp), tyrosine (Tyr), serotonin (5-HT), 5-hydroxyindolacetic acid (5-HIAA), dopamine (DA), acetylcholine (ACh), norepinephrine (NE), glutamic acid (Glu), and γ-aminobutyric acid (GABA) in rat brain tissues. The mobile phase consisting of methanol and 0.01% formic acid in water was performed on an Inertsil EP C18 column, and the developed method was validated well. Results demonstrated that there were significant differences for 5-HT, DA, NE, Trp, Tyr and ACh between model and control group in all three models, and a Bayes linear discriminant function was established to distinguish these three kinds of nervous system diseases by DA, Tyr and ACh for their significant differences among control and three model groups. It could be an excellent strategy to provide perceptions into the similarity and differentia of mechanisms from the point of NTs’ changing in brain directly and a new method to distinguish insomnia, depression and AD from view of essence.

Metabolomic analysis of mammalian cells and human tissue through one-pot two stage derivatizations using sheathless capillary electrophoresis-electrospray ionization-mass spectrometry

Analysis of metabolites is often performed using separations coupled to mass spectrometry which is challenging due to their vast structural heterogeneity and variable charge states. Metabolites are often separated based on their class/functional group which in large part determine their acidity or basicity. This charge state dictates the ionization mode and efficiency of the molecule. To improve the sensitivity and expand the coverage of the mammalian metabolome, multifunctional derivatization with sheathless CE-ESI-MS was undertaken. In this work, amines, hydroxyls and carboxylates were labeled with tertiary amines tags. This derivatization was performed in under 100 min and resulted in high positive charge states for all analytes investigated. Amino acids and organic acids showed average limits of detection of 76 nM with good linearity of 0.96 and 10% RSD for peak area. Applying this metabolomic profiling system to bovine aortic endothelial cells showed changes in 15 metabolites after treatment with high glucose. The sample injection volume on-capillary was <300 cells for quantitative analyses. Targeted metabolites were found in human tissue, which indicates possible application of the system complex metabolome quantitation.

Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease

Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer's disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.

Profiling of small molecule metabolites and neurotransmitters in crustacean hemolymph and neuronal tissues using reversed-phase LC-MS/MS

Crustaceans have been long used as model animals for neuromodulation studies because of their well-defined neural circuitry. The identification of small molecule metabolites and signaling molecules in circulating fluids and neuronal tissues presents unique challenges due to their diverse structures, biological functions, and wide range of concentrations. LC combined with high resolution MS/MS is one of the most powerful tools to uncover endogenous small molecules. Here we explored several sample preparation techniques (solid-phase extraction and denaturing) and MS data acquisition strategies (data-dependent acquisition and targeted MS2-based acquisition) that provided complementary coverage and improved overall identification rate in C18 LC-MS/MS experiment. By MS/MS spectral matching with mzCloud database and those generated from standard compounds, a total of 129 small molecule metabolites and neurotransmitters were identified from crustacean hemolymph and neuronal tissues. These confidently identified small molecules covered predominant biosynthetic pathways for major neurotransmitters, validating the effectiveness of the high-throughput RPLC-MS/MS approach in studying the metabolism of neurotransmitters.

Development of High-Performance Chemical Isotope Labeling LC-MS for Profiling the Carbonyl Submetabolome

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential ¹²C- and ¹³C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with ¹²C-labeling and spiked with a ¹³C-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 ¹²C-/¹³C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that ¹²C-/¹³C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.

Development of Chemical Isotope Labeling LC-MS for Milk Metabolomics: Comprehensive and Quantitative Profiling of the Amine/Phenol Submetabolome

Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 ¹²C-/¹³C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome. Since milk and milk products are consumed in large quantities on a daily basis, the intake of these milk metabolites even at low concentrations can be cumulatively high. The high-coverage analysis of the milk metabolome using CIL LC-MS should be very useful in future research involving the study of the effects of these metabolites on human health. It should also be useful in the dairy industry in areas such as improving milk production, developing new processing technologies, developing improved nutritional products, quality control, and milk product authentication.

Restenosis Inhibition and Re-differentiation of TGFβ/Smad3-activated Smooth Muscle Cells by Resveratrol

To date, there is no periadventitial drug delivery method available in the clinic to prevent restenotic failure of open vascular reconstructions. Resveratrol is a promising anti-restenotic natural drug but subject to low bioavailability when systemically administered. In order to reconcile these two prominent issues, we tested effects of periadventitial delivery of resveratrol on all three major pro-restenotic pathologies including intimal hyperplasia (IH), endothelium impairment, and vessel shrinkage. In a rat carotid injury model, periadventitial delivery of resveratrol either via Pluronic gel (2-week), or polymer sheath (3-month), effectively reduced IH without causing endothelium impairment and vessel shrinkage. In an in vitro model, primary smooth muscle cells (SMCs) were stimulated with elevated transforming growth factor (TGFβ) and its signaling protein Smad3, known contributors to IH. TGFβ/Smad3 up-regulated Kruppel-like factor (KLF5) protein, and SMC de-differentiation which was reversed by KLF5 siRNA. Furthermore, TGFβ/Smad3-stimulated KLF5 production and SMC de-differentiation were blocked by resveratrol via its inhibition of the Akt-mTOR pathway. Concordantly, resveratrol attenuated Akt phosphorylation in injured arteries. Taken together, periadventitial delivery of resveratrol produces durable inhibition of all three pro-restenotic pathologies - a rare feat among existing anti-restenotic methods. Our study suggests a potential anti-restenotic modality of resveratrol application suitable for open surgery.

Mass Defect-Based N,N-Dimethyl Leucine Labels for Quantitative Proteomics and Amine Metabolomics of Pancreatic Cancer Cells

Mass spectrometry-based stable isotope labeling has become a key technology for protein and small-molecule analyses. We developed a multiplexed quantification method for simultaneous proteomics and amine metabolomics analyses via nano reversed-phase liquid chromatography-tandem mass spectrometry (nanoRPLC-MS/MS), called mass defect-based N,N-dimethyl leucine (mdDiLeu) labeling. The duplex mdDiLeu reagents were custom-synthesized with a mass difference of 20.5 mDa, arising from the subtle variation in nuclear binding energy between the two DiLeu isotopologues. Optimal MS resolving powers were determined to be 240K for labeled peptides and 120K for labeled metabolites on the Orbitrap Fusion Lumos instrument. The mdDiLeu labeling does not suffer from precursor interference and dynamic range compression, providing excellent accuracy for MS¹-centric quantification. Quantitative information is only revealed at high MS resolution without increasing spectrum complexity and overlapping isotope distribution. Chromatographic performance of polar metabolites was dramatically improved by mdDiLeu labeling with modified hydrophobicity, enhanced ionization efficiency, and picomole levels of detection limits. Paralleled proteomics and amine metabolomics analyses using mdDiLeu were systematically evaluated and then applied to pancreatic cancer cells.

Investigation of signaling molecules and metabolites found in crustacean hemolymph via in vivo microdialysis using a multifaceted mass spectrometric platform

Neurotransmitters (NTs) are endogenous signaling molecules that play an important role in regulating various physiological processes in animals. Detection of these chemical messengers is often challenging due to their low concentration levels and fast degradation rate in vitro. In order to address these challenges, herein we employed in vivo microdialysis (MD) sampling to study NTs in the crustacean model Cancer borealis. Multifaceted separation tools, such as CE and ion mobility mass spectrometry (MS) were utilized in this work. Small molecules were separated by different mechanisms and detected by MALDI mass spectrometric imaging (MALDI-MSI). Performance of this separation-based MSI platform was also compared to LC-ESI-MS. By utilizing both MALDI and ESI-MS, a total of 208 small molecule NTs and metabolites were identified, of which 39 were identified as signaling molecules secreted in vivo. In addition, the inherent property of sub microscale sample consumption using CE enables shorter time of MD sample collection. Temporal resolution of MD was improved by approximately tenfold compared to LC-ESI-MS, indicating the significant advantage of applying separation-assisted MALDI-MS imaging platform.

Quantitative analysis of serotonin secreted by human embryonic stem cells-derived serotonergic neurons via pH-mediated online stacking-CE-ESI-MRM

A CE-ESI-MRM-based assay was developed for targeted analysis of serotonin released by human embryonic stem cells-derived serotonergic neurons in a chemically defined environment. A discontinuous electrolyte system was optimized for pH-mediated online stacking of serotonin. Combining with a liquid-liquid extraction procedure, LOD of serotonin in the Krebs'-Ringer's solution by CE-ESI-MS/MS on a 3D ion trap MS was0.15 ng/mL. The quantitative results confirmed the serotonergic identity of the in vitro developed neurons and the capacity of these neurons to release serotonin in response to stimulus.

Biomarker discovery in mass spectrometry-based urinary proteomics

Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians.

In vivo study on the neurotransmitters and their metabolites change in depressive disorder rat plasma by ultra high performance liquid chromatography coupled to tandem mass spectrometry

A sensitive and versatile, ultra-high performance, liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method coupled to pre-column derivatization for the simultaneous determination of 5-hydroxytryptamine (5-HT), 5-hydroxyindoleacetic acid (5-HIAA), dopamine (DA), norepinephrine (NE), homovanillic acid (HVA), γ-aminobutyric acid (GABA) and glutamic acid (Glu) was developed and validated in rat plasma. The analytes were dansylated under strong alkaline conditions after protein precipitation extraction, which were analyzed on a BEH C18 column using a gradient elution. The lower limit of quantification (LLOQ) values for 5-HT, 5-HIAA, DA, NE, HVA, GABA and Glu were 1.00, 1.00, 0.991, 0.992, 1.02, 1000, and 5030 pmol/mL, respectively. Good linearity was obtained (r > 0.99) and the intra- and inter-day precisions of the method (relative standard deviation, RSD%) were lower than 12%. The method was novel, sensitive and specific which can provide an alternative method for the quantification of neurotransmitters and their metabolites in plasma samples.