Monitoring dynamic changes in lymph metabolome of fasting and fed rats by electrospray ionization-ion mobility mass spectrometry (ESI-IMMS)

Modern machine-learning applications in ambient ionization mass spectrometry

This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.

Advances in mass spectrometry for metabolomics: Strategies, challenges, and innovations in disease biomarker discovery

Mass spectrometry (MS) plays a crucial role in metabolomics, especially in the discovery of disease biomarkers. This review outlines strategies for identifying metabolites, emphasizing precise and detailed use of MS techniques. It explores various methods for quantification, discusses challenges encountered, and examines recent breakthroughs in biomarker discovery. In the field of diagnostics, MS has revolutionized approaches by enabling a deeper understanding of tissue-specific metabolic changes associated with disease. The reliability of results is ensured through robust experimental design and stringent system suitability criteria. In the past, data quality, standardization, and reproducibility were often overlooked despite their significant impact on MS-based metabolomics. Progress in this field heavily depends on continuous training and education. The review also highlights the emergence of innovative MS technologies and methodologies. MS has the potential to transform our understanding of metabolic landscapes, which is crucial for disease biomarker discovery. This article serves as an invaluable resource for researchers in metabolomics, presenting fresh perspectives and advancements that propels the field forward.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.

Electrospray Ionization Ion Mobility Mass Spectrometry

Electrospray ionization ion mobility mass spectrometry (ESI-IMS-MS) is a rapidly progressing analytical technique for the examination of complex compounds in the gas phase. ESI-IMS-MS separates isomers, provides structural information, and quantitatively identifies peptides, lipids, carbohydrates, polymers, and metabolites in biological samples. ESI-IMS-MS has pharmaceutical, environmental, and manufacturing applications quickly characterizing drugs, petroleum products, and metal macromolecules. This review provides the history of ESI-IMS-MS development and applications to date.

Glucagon-like peptide 1 and glucose-dependent insulinotropic polypeptide stimulate release of substance P from TRPV1- and TRPA1-expressing sensory nerves

Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are released from enteroendocrine cells (EECs) in response to nutrient ingestion and lower blood glucose levels by stimulation of insulin secretion and thus are defined as incretins. GLP-1 receptor (GLP-1R) expression has been identified on enteric neurons that include intrinsic afferent neurons, extrinsic spinal, and vagal sensory afferents but has not been shown to have an incretin effect through these nerves. GLP-1 and GIP enter the mesenteric lymphatic fluid (MLF) after a meal via the interstitial fluid (IF) from local tissue secretion and/or blood capillaries. We tested if MLF could induce diet-dependent intransient increases in intracellular calcium ([Ca²⁺]_i) in cultured sensory neurons. Postprandial rat MLF, collected from the superior mesenteric lymphatic duct, induced a significant twofold higher intransient increase in [Ca²⁺]_i in primary-cultured sensory neurons than MLF from fasted rats. Inhibition of transient receptor potential vanilloid 1 (TRPV1) and TRPV1 and ankyrin 1 cation channels (TRPA1) with ruthenium red eliminated the difference. Substance P (SP) (a peptide that stimulates insulin secretion) sensor cells cocultured with sensory neurons showed both the GLP-1R agonist exendin-4 (Ex-4) and GIP induced transient increases in [Ca²⁺]_i directly coupled to SP secretion in the sensory nerves. Ex-4-induced release of SP required expression of either TRPA1 or TRPV1. These data identify unrecognized actions of GLP-1 and GIP as incretins by acting as neurolymphocrines and suggest a mechanism for sensory nerves to respond to the postprandial state through MLF.NEW & NOTEWORTHY Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are secreted upon eating to lower blood sugar. GLP-1 and GIP were found to induce the secretion of substance P (SP) from cultured sensory nerves. SP enhances insulin secretion. Mesenteric lymphatic fluid (MLF) also stimulates sensory neurons in a diet-dependent manner. These studies identify new actions of GLP-1 and GIP as incretins and suggest a mechanism for sensory nerves to respond to diet through MLF.

Traveling Wave Ion Mobility Mass Spectrometry: Metabolomics Applications

Ion mobility (IM) spectrometry can separate gas-phase ions according to their charge, molecular shape, and size. In recent years, several IM technologies have been integrated with mass spectrometry (MS) and launched as commercially available instrumentation for metabolomics analysis. The addition of IM to MS-based metabolomics workflows provides an additional degree of separation to chromatography and MS resolving power, improving peak capacity and signal-to-noise ratio. Moreover, it makes possible to experimentally derive collision cross section (CCS), which can be used as an additional coordinate for metabolite identification, together with accurate mass and fragmentation information. The addition of CCS to current metabolome database would allow to filter and score molecules based on their CCS values, adding more confidence in the identification process during metabolomics experiments.In this chapter, we present procedures for the integration of travelling-wave (TW)-IM into traditional MS-based metabolomics workflows.

Ion Mobility Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses

Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. Graphical Abstract ᅟ.

Ion mobility spectrometry combined with ultra performance liquid chromatography/mass spectrometry for metabolic phenotyping of urine: Effects of column length, gradient duration and ion mobility spectrometry on metabolite detection

The need for rapid and efficient high throughput metabolic phenotyping (metabotyping) in metabolomic/metabonomic studies often requires compromises to be made between analytical speed and metabolome coverage. Here the effect of column length (150, 75 and 30 mm) and gradient duration (15, 7.5 and 3 min respectively) on the number of features detected when untargeted metabolic profiling of human urine using reversed-phase gradient ultra performance chromatography with, and without, ion mobility spectrometry, has been examined. As would be expected, reducing column length from 150 to 30 mm, and gradient duration, from 15 to 3 min, resulted in a reduction in peak capacity from 311 to 63 and a similar reduction in the number of features detected from over ca. 16,000 to ca. 6500. Under the same chromatographic conditions employing UPLC/IMS/MS to provide an additional orthogonal separation resulted in an increase in the number of MS features detected to nearly 20,000 and ca. 7500 for the 150 mm and the 30 mm columns respectively. Based on this limited study the potential of LC/IMS/MS as a tool for improving throughput and increasing metabolome coverage clearly merits further in depth study.

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Ion mobility spectrometry (IMS) significantly increased the number of analytes detected during the LC-MS of urine.

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Nearly ca. 20,000 features were seen for urine using LC-IMS-MS in a 15 min analysis compared to ca. 16,000 by LC-MS alone.

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In a 3 min analysis using a 30 mm column nearly 7600 features were detected with combined IMS and MS.

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For high throughput analysis a 75 mm column and a 3 min analysis was a good compromise between speed and features detected.

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The use of IMS also improved the quality of the mass spectra obtained.

Performance of a High-Pressure Liquid Chromatography-Ion Mobility-Mass Spectrometry System for Metabolic Profiling

A commercial liquid chromatography/drift tube ion mobility-mass spectrometer (LC/IM-MS) was evaluated for its utility in global metabolomics analysis. Performance was assessed using 12 targeted metabolite standards where the limit of detection (LOD), linear dynamic range, resolving power, and collision cross section (Ω) are reported for each standard. Data were collected in three different instrument operation modes: flow injection analysis with IM-MS (FIA/IM-MS), LC/MS, and LC/IM-MS. Metabolomics analyses of human plasma and HaCaT cells were used to compare the above three operation modes. LC/MS provides linearity in response, data processing automation, improved limits of detection, and ease of use. Advantages of LC/IM-MS and FIA/IM-MS include the ability to develop mobility-mass trend lines for structurally similar biomolecules, increased peak capacity, reduction of chemical/matrix noise, improvement in signal-to-noise, and separations of isobar/isomer compounds that are not resolved by LC. We further tested the feasibility of incorporating IM-MS into conventional LC/MS metabolomics workflows. In general, the addition of ion mobility dimension has increased the separation of compounds in complex biological matrixes and has the potential to largely improve the throughput of metabolomics analysis.

Metabolomics and lipidomics using traveling-wave ion mobility mass spectrometry

Metabolomics and lipidomics aim to profile the wide range of metabolites and lipids that are present in biological samples. Recently, ion mobility spectrometry (IMS) has been used to support metabolomics and lipidomics applications to facilitate the separation and the identification of complex mixtures of analytes. IMS is a gas-phase electrophoretic technique that enables the separation of ions in the gas phase according to their charge, shape and size. Occurring within milliseconds, IMS separation is compatible with modern mass spectrometry (MS) operating with microsecond scan speeds. Thus, the time required for acquiring IMS data does not affect the overall run time of traditional liquid chromatography (LC)-MS-based metabolomics and lipidomics experiments. The addition of IMS to conventional LC-MS-based metabolomics and lipidomics workflows has been shown to enhance peak capacity, spectral clarity and fragmentation specificity. Moreover, by enabling determination of a collision cross-section (CCS) value-a parameter related to the shape of ions-IMS can improve the accuracy of metabolite identification. In this protocol, we describe how to integrate traveling-wave ion mobility spectrometry (TWIMS) into traditional LC-MS-based metabolomic and lipidomic workflows. In particular, we describe procedures for the following: tuning and calibrating a SYNAPT High-Definition MS (HDMS) System (Waters) specifically for metabolomics and lipidomics applications; extracting polar metabolites and lipids from brain samples; setting up appropriate chromatographic conditions; acquiring simultaneously m/z, retention time and CCS values for each analyte; processing and analyzing data using dedicated software solutions, such as Progenesis QI (Nonlinear Dynamics); and, finally, performing metabolite and lipid identification using CCS databases and TWIMS-derived fragmentation information.

Fecal Metabolome in Hmga1 Transgenic Mice with Polyposis: Evidence for Potential Screen for Early Detection of Precursor Lesions in Colorectal Cancer

Because colorectal cancer (CRC) remains a leading cause of cancer mortality worldwide, more accessible screening tests are urgently needed to identify early stage lesions. We hypothesized that highly sensitive, metabolic profile analysis of stool samples will identify metabolites associated with early stage lesions and could serve as a noninvasive screening test. We therefore applied traveling wave ion mobility mass spectrometry (TWIMMS) coupled with ultraperformance liquid chromatography (UPLC) to investigate metabolic aberrations in stool samples in a transgenic model of premalignant polyposis aberrantly expressing the gene encoding the high mobility group A (Hmga1) chromatin remodeling protein. Here, we report for the first time that the fecal metabolome of Hmga1 mice is distinct from that of control mice and includes metabolites previously identified in human CRC. Significant alterations were observed in fatty acid metabolites and metabolites associated with bile acids (hypoxanthine xanthine, taurine) in Hmga1 mice compared to controls. Surprisingly, a marked increase in the levels of distinctive short, arginine-enriched, tetra-peptide fragments was observed in the transgenic mice. Together these findings suggest that specific metabolites are associated with Hmga1-induced polyposis and abnormal proliferation in intestinal epithelium. Although further studies are needed, these data provide a compelling rationale to develop fecal metabolomic analysis as a noninvasive screening tool to detect early precursor lesions to CRC in humans.

Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd.

Application of ion mobility tandem mass spectrometry to compositional and structural analysis of glycopeptides extracted from the urine of a patient diagnosed with Schindler disease

RATIONALE

Schindler disease is caused by the deficient activity of α-N-acetylgalactosaminidase, which leads to an abnormal accumulation of O-glycopeptides in tissues and body fluids. In this work the Schindler condition is for the first time approached by ion mobility (IMS) tandem mass spectrometry (MS/MS), for determining urine glycopeptide fingerprints and discriminate isomeric structures.

METHODS

IMS-MS experiments were conducted on a Synapt G2s mass spectrometer operating in negative ion mode. A glycopeptide mixture extracted from the urine of a patient suffering from Schindler disease was dissolved in methanol and infused into the mass spectrometer by electrospray ionization using a syringe-pump system. MS/MS was performed by collision-induced dissociation (CID) at low energies, after mobility separation in the transfer cell. Data acquisition and processing were performed using MassLynx and Waters Driftscope software.

RESULTS

IMS-MS data indicated that the attachment of one or two amino acids to the carbohydrate backbone has a minimal influence on the molecule conformation, which limits the discrimination of the free oligosaccharides from the glycosylated amino acids and dipeptides. The structural analysis by CID MS/MS in combination with IMS-MS of species exhibiting the same m/z but different configurations demonstrated for the first time the presence of positional isomers for some of the Schindler disease biomarker candidates.

CONCLUSIONS

The IMS-MS and CID MS/MS platform was for the first time optimized and applied to Schindler disease glycourinome. By this approach the separation and characterization of Neu5Ac positional isomers was possible. IMS CID MS/MS showed the ability to determine the type of the glycopeptide isomers from a series of possible candidates.

Structural mass spectrometry of tissue extracts to distinguish cancerous and non-cancerous breast diseases

Aberrant metabolism in breast cancer tumors has been widely studied by both targeted and untargeted analyses to characterize the affected metabolic pathways. In this work, we utilize ultra-performance liquid chromatography (UPLC) in tandem with ion mobility-mass spectrometry (IM-MS), which provides chromatographic, structural, and mass information, to characterize the aberrant metabolism associated with breast diseases such as cancer. In a double-blind analysis of matched control (n = 3) and disease tissues (n = 3), samples were homogenized, polar metabolites were extracted, and the extracts were characterized by UPLC-IM-MS/MS. Principle component analysis revealed a strong separation between disease tissues, with one diseased tissue clustering with the control tissues along PC1 and two others separated along PC2. Using post-ion mobility MS/MS spectra acquired by data-independent acquisition, the features giving rise to the observed grouping were determined to be biomolecules associated with aggressive breast cancer tumors, including glutathione, oxidized glutathione, thymosins β4 and β10, and choline-containing species. Pathology reports revealed the outlier of the disease tissues to be a benign fibroadenoma, whereas the other disease tissues represented highly metabolic benign and aggressive tumors. This IM-MS-based workflow bridges the transition from untargeted metabolomic profiling to tentative identifications of key descriptive molecular features using data acquired in one analysis, with additional experiments performed only for validation. The ability to resolve cancerous and non-cancerous tissues at the biomolecular level demonstrates UPLC-IM-MS/MS as a robust and sensitive platform for metabolomic profiling of tissues.

Characterizing metabolic changes in human colorectal cancer

Colorectal cancer (CRC) remains a leading cause of cancer death worldwide, despite the fact that it is a curable disease when diagnosed early. The development of new screening methods to aid in early diagnosis or identify precursor lesions at risk for progressing to CRC will be vital to improving the survival rate of individuals predisposed to CRC. Metabolomics is an advancing area that has recently seen numerous applications to the field of cancer research. Altered metabolism has been studied for many years as a means to understand and characterize cancer. However, further work is required to establish standard procedures and improve our ability to identify distinct metabolomic profiles that can be used to diagnose CRC or predict disease progression. The present study demonstrates the use of direct infusion traveling wave ion mobility mass spectrometry to distinguish metabolic profiles from CRC samples and matched non-neoplastic epithelium as well as metastatic and primary tumors at different stages of disease (T1-T4). By directly infusing our samples, the analysis time was reduced significantly, thus increasing the speed and efficiency of this method compared to traditional metabolomics platforms. Partial least squares discriminant analysis was used to visualize differences between the metabolic profiles of sample types and to identify the specific m/z features that led to this differentiation. Identification of the distinct m/z features was made using the human metabolome database. We discovered alterations in fatty acid biosynthesis and oxidative, glycolytic, and polyamine pathways that distinguish tumors from non-malignant colonic epithelium as well as various stages of CRC. Although further studies are needed, our results indicate that colonic epithelial cells undergo metabolic reprogramming during their evolution to CRC, and the distinct metabolites could serve as diagnostic tools or potential targets in therapy or primary prevention. Graphical Abstract Colon tissue biopsy samples were collected from patients after which metabolites were extracted via sonication. Two-dimensional data were collected via IMS in tandem with MS (IMMS). Data were then interpreted statistically via PLS-DA. Scores plots provided a visualization of statistical separation and groupings of sample types. Loading plots allowed identification of influential ion features. Lists of these features were exported and analyzed for specific differences. Direct comparisons of the ion features led to the identification and comparative analyses of candidate biomarkers. These differences were then expressed visually in charts and tables.

Applications of ion-mobility mass spectrometry for lipid analysis

The high chemical complexity of the lipidome is one of the major challenges in lipidomics research. Ion-mobility spectrometry (IMS), a gas-phase electrophoretic technique, makes possible the separation of ions in the gas phase according to their charge, shape, and size. IMS can be combined with mass spectrometry (MS), adding three major benefits to traditional lipidomic approaches. First, IMS-MS allows the determination of the collision cross section (CCS), a physicochemical measure related to the conformational structure of lipid ions. The CCS is used to improve the confidence of lipid identification. Second, IMS-MS provides a new set of hybrid fragmentation experiments. These experiments, which combine collision-induced dissociation with ion-mobility separation, improve the specificity of MS/MS-based approaches. Third, IMS-MS improves the peak capacity and signal-to-noise ratio of traditional analytical approaches. In doing so, it allows the separation of complex lipid extracts from interfering isobaric species. Developing in parallel with advances in instrumentation, informatics solutions enable analysts to process and exploit IMS-MS data for qualitative and quantitative applications. Here we review the current approaches for lipidomics research based on IMS-MS, including liquid chromatography-MS and direct-MS analyses of "shotgun" lipidomics and MS imaging.

HMGA1 drives metabolic reprogramming of intestinal epithelium during hyperproliferation, polyposis, and colorectal carcinogenesis

Although significant progress has been made in the diagnosis and treatment of colorectal cancer (CRC), it remains a leading cause of cancer death worldwide. Early identification and removal of polyps that may progress to overt CRC is the cornerstone of CRC prevention. Expression of the High Mobility Group A1 (HMGA1) gene is significantly elevated in CRCs as compared with adjacent, nonmalignant tissues. We investigated metabolic aberrations induced by HMGA1 overexpression in small intestinal and colonic epithelium using traveling wave ion mobility mass spectrometry (TWIMMS) in a transgenic model in which murine Hmga1 was misexpressed in colonic epithelium. To determine if these Hmga1-induced metabolic alterations in mice were relevant to human colorectal carcinogenesis, we also investigated tumors from patients with CRC and matched, adjacent, nonmalignant tissues. Multivariate statistical methods and manual comparisons were used to identify metabolites specific to Hmga1 and CRC. Statistical modeling of data revealed distinct metabolic patterns in Hmga1 transgenics and human CRC samples as compared with the control tissues. We discovered that 13 metabolites were specific for Hmga1 in murine intestinal epithelium and also found in human CRC. Several of these metabolites function in fatty acid metabolism and membrane composition. Although further validation is needed, our results suggest that high levels of HMGA1 protein drive metabolic alterations that contribute to CRC pathogenesis through fatty acid synthesis. These metabolites could serve as potential biomarkers or therapeutic targets.

Ion mobility-derived collision cross section as an additional measure for lipid fingerprinting and identification

Despite recent advances in analytical and computational chemistry, lipid identification remains a significant challenge in lipidomics. Ion-mobility spectrometry provides an accurate measure of the molecules' rotationally averaged collision cross-section (CCS) in the gas phase and is thus related to ionic shape. Here, we investigate the use of CCS as a highly specific molecular descriptor for identifying lipids in biological samples. Using traveling wave ion mobility mass spectrometry (MS), we measured the CCS values of over 200 lipids within multiple chemical classes. CCS values derived from ion mobility were not affected by instrument settings or chromatographic conditions, and they were highly reproducible on instruments located in independent laboratories (interlaboratory RSD < 3% for 98% of molecules). CCS values were used as additional molecular descriptors to identify brain lipids using a variety of traditional lipidomic approaches. The addition of CCS improved the reproducibility of analysis in a liquid chromatography-MS workflow and maximized the separation of isobaric species and the signal-to-noise ratio in direct-MS analyses (e.g., "shotgun" lipidomics and MS imaging). These results indicate that adding CCS to databases and lipidomics workflows increases the specificity and selectivity of analysis, thus improving the confidence in lipid identification compared to traditional analytical approaches. The CCS/accurate-mass database described here is made publicly available.

Characterization of N-glycan heterogeneities of erythropoietin products by liquid chromatography/mass spectrometry and multivariate analysis

RATIONALE

Glycan heterogeneity on recombinant human erythropoietin (rEPO) product is considered to be one of the critical quality attributes, and similarity tests of glycan heterogeneities are required in the manufacturing process changes and developments of biosimilars. A method for differentiating highly complex and diverse glycosylations is needed to evaluate comparability and biosimilarity among rEPO batches and products manufactured by different processes.

METHODS

The glycan heterogeneities of nine rEPO products (four innovator products and five biosimilar products) were distinguished by multivariate analysis (MVA) using the peak area ratios of each glycan to the total peak area of glycans in mass spectra obtained by liquid chromatography/mass spectrometry (LC/MS) of N-glycans from rEPOs.

RESULTS

Principal component analysis (PCA) using glycan profiles obtained by LC/MS proved to be a useful method for differentiating glycan heterogeneities among nine rEPOs. Using PC values as indices, we were able to visualize and digitalize the glycan heterogeneities of each rEPO. The characteristic glycans of each rEPO were also successfully identified by orthogonal partial least-squares discrimination analysis (OPLS-DA), an MVA method, using the glycan profile data.

CONCLUSIONS

PCA values were useful for evaluating the relative differences among the glycan heterogeneities of rEPOs. The characteristic glycans that contributed to the differentiation were also successfully identified by OPLS-DA. PCA and OPLS-DA based on mass spectrometric data are applicable for distinguishing glycan heterogeneities, which are virtually indistinguishable on rEPO products.

Feeding-dependent activation of enteric cells and sensory neurons by lymphatic fluid: evidence for a neurolymphocrine system

Lymphatic fluid is a plasma filtrate that can be viewed as having biological activity through the passive accumulation of molecules from the interstitial fluid. The possibility that lymphatic fluid is part of an active self-contained signaling process that parallels the endocrine system, through the activation of G-protein coupled receptors (GPCR), has remained unexplored. We show that the GPCR lysophosphatidic acid 5 (LPA5) is found in sensory nerve fibers expressing calcitonin gene-related peptide (CGRP) that innervate the lumen of lymphatic lacteals and enteric nerves. Using LPA5 as a model for nutrient-responsive GPCRs present on sensory nerves, we demonstrate that dietary protein hydrolysate (peptone) can induce c-Fos expression in enterocytes and nerves that express LPA5. Mesenteric lymphatic fluid (MLF) mobilizes intracellular calcium in cell models expressing LPA5 upon feeding in a time- and dose-dependent manner. Primary cultured neurons of the dorsal root ganglia expressing CGRP are activated by MLF, which is enhanced upon LPA5 overexpression. Activation is independent of the known LPA5 agonists, lysophosphatidic acid and farnesyl pyrophosphate. These data bring forth a pathway for the direct stimulation of sensory nerves by luminal contents and interstitial fluid. Thus, by activating LPA5 on sensory nerves, MLF provides a means for known and yet to be identified constituents of the interstitial fluid to act as signals to comprise a "neurolymphocrine" system.

Ion mobility derived collision cross sections to support metabolomics applications

Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.

Metabolic analysis of striatal tissues from Parkinson's disease-like rats by electrospray ionization ion mobility mass spectrometry

Electrospray ionization ion mobility mass spectrometry (ESI-IMMS) was used to study the striatal metabolomes in a Parkinson's like disease (PD-like) rat model. Striatal tissue samples from Berlin Druckrey IV (BD-IV) with PD-like disease 20 dpn-affected and 15 dpn-affected rats (dpn: days postnatal) were investigated and compared with age-matched controls. An ion mobility mass spectrometer (IMMS) produced multidimensional spectra with mass to charge ratio (m/z), ion mobility drift time, and intensity information for each individual metabolite. Principle component analysis (PCA) was applied in this study for pattern recognition and significant metabolites selection (68% data was modeled in PCA). Both IMMS spectra and PCA results showed that there were clear global metabolic differences between PD-like samples and healthy controls. Nine metabolites were selected by PCA and identified as potential biomarkers using the Human Metabolome Database (HMDB). One targeted metabolite in this study was dopamine. Selected-mass mobility analysis indicated the absence of dopamine in PD-like striatal metabolomes. A major discovery of this work, however, was the existence of an isomer of dopamine. By using ion mobility spectrometry, the dopamine isomer, which has not previously been reported, was separated from dopamine.

Ion mobility mass spectrometry analysis of isomeric disaccharide precursor, product and cluster ions

RATIONALE

Carbohydrates are highly variable in structure owing to differences in their anomeric configurations, monomer stereochemistry, inter-residue linkage positions and general branching features. The separation of carbohydrate isomers poses a great challenge for current analytical techniques.

METHODS

The isomeric heterogeneity of disaccharide ions and monosaccharide-glycolaldehyde product ions was evaluated using electrospray traveling wave ion mobility mass spectrometry (Synapt G2 high-definition mass spectrometer) in both positive and negative ion modes.

RESULTS

The separation of isomeric disaccharide ions was observed but not fully achieved based on their mobility profiles. The mobilities of isomeric product ions, the monosaccharide-glycolaldehydes, derived from different disaccharide isomers were measured. Multiple mobility peaks were observed for both monosaccharide-glycolaldehyde cations and anions, indicating that there was more than one structural configuration in the gas phase as verified by NMR in solution. More importantly, the mobility patterns for isomeric monosaccharide-glycolaldehyde product ions were different, which enabled partial characterization of their respective disaccharide ions. Abundant disaccharide cluster ions were also observed. The results showed that a majority of isomeric cluster ions had different drift times and, moreover, more than one mobility peak was detected for a number of specific cluster ions.

CONCLUSIONS

It is demonstrated that ion mobility mass spectrometry is an advantageous method to assess the isomeric heterogeneity of carbohydrate compounds. It is capable of differentiating different types of carbohydrate ions having identical m/z values as well as multiple structural configurations of single compounds.

Metabolomics of colorectal cancer: past and current analytical platforms

Metabolomics is coming of age as an important area of investigation which may help reveal answers to questions left unanswered or only partially understood from proteomic or genomic approaches. Increased knowledge of the relationship of genes and proteins to smaller biomolecules (metabolites) will advance our ability to diagnose, treat, and perhaps prevent cancer and other diseases that have eluded scientists for generations. Colorectal tumors are the second leading cause of cancer mortality in the USA, and the incidence is rising. Many patients present late, after the onset of symptoms, when the tumor has spread from the primary site. Once metastases have occurred, the prognosis is significantly worse. Understanding alterations in metabolic profiles that occur with tumor onset and progression could lead to better diagnostic tests as well as uncover new approaches to treat or even prevent colorectal cancer (CRC). In this review, we explore the various analytical technologies that have been applied in CRC metabolomics research and summarize all metabolites measured in CRC and integrate them into metabolic pathways. Early studies with nuclear magnetic resonance and gas-chromatographic mass spectrometry suggest that tumor cells are characterized by aerobic glycolysis, increased purine metabolism for DNA synthesis, and protein synthesis. Liquid chromatography, capillary electrophoresis, and ion mobility, each coupled with mass spectrometry, promise to advance the field and provide new insight into metabolic pathways used by cancer cells. Studies with improved technology are needed to identify better biomarkers and targets for treatment or prevention of CRC.

Ion Mobility-Mass Correlation Trend Line Separation of Glycoprotein Digests without Deglycosylation

A high-throughput ion mobility mass spectrometer (IMMS) was used to rapidly separate and analyze peptides and glycopeptides derived from glycoproteins. Two glycoproteins, human α-1-acid glycoprotein and antithrombin III were digested with trypsin and subjected to electrospray traveling wave IMMS analysis. No deglycosylation steps were performed; samples were complex mixtures of peptides and glycopeptides. Peptides and glycosylated peptides with different charge states (up to 4 charges) were observed and fell on distinguishable trend lines in 2-D IMMS spectra in both positive and negative modes. The trend line separation patterns matched between both modes. Peptide sequence was identified based on the corresponding extracted mass spectra and collision induced dissociated (CID) experiments were performed for selected compounds to prove class identification. The signal-to-noise ratio of the glycopeptides was increased dramatically with ion mobility trend line separation compared to non-trend line separation, primarily due to selection of precursor ion subsets within specific mobility windows. In addition, isomeric mobility peaks were detected for specific glycopeptides. IMMS demonstrated unique capabilities and advantages for investigating and separating glycoprotein digests in this study and suggests a novel strategy for rapid glycoproteomics studies in the future.

Carbohydrate structure characterization by tandem ion mobility mass spectrometry (IMMS)2

A high resolution ion mobility spectrometer was interfaced to a Synapt G2 high definition mass spectrometer (HDMS) to produce IMMS-IMMS analysis. The hybrid instrument contained an electrospray ionization source, two ion gates, an ambient pressure linear ion mobility drift tube, a quadrupole mass filter, a traveling wave ion mobility spectrometer (TWIMS), and a time-of-flight mass spectrometer. The dual gate drift tube ion mobility spectrometer (DTIMS) could be used to acquire traditional IMS spectra but also could selectively transfer specific mobility selected precursor ions to the Synapt G2 HDMS for mass filtration (quadrupole). The mobility and mass selected ions could then be introduced into a collision cell for fragmentation followed by mobility separation of the fragment ions with the traveling wave ion mobility spectrometer. These mobility separated fragment ions are finally mass analyzed using a time-of-flight mass spectrometer. This results in an IMMS-IMMS analysis and provides a method to evaluate the isomeric heterogeneity of precursor ions by both DTIMS and TWIMS to acquire a mobility-selected and mass-filtered fragmentation pattern and to additionally obtain traveling wave ion mobility spectra of the corresponding product ions. This new IMMS(2) instrument enables the structural diversity of carbohydrates to be studied in greater detail. The physical separation of isomeric oligosaccharide mixtures was achieved by both DTIMS and TWIMS, with DTIMS demonstrating higher resolving power (70-80) than TWIMS (30-40). Mobility selected MS/MS spectra were obtained, and TWIMS evaluation of product ions showed that isomeric forms of fragment ions existed for identical m/z values.

Neuronal metabolomics by ion mobility mass spectrometry: cocaine effects on glucose and selected biogenic amine metabolites in the frontal cortex, striatum, and thalamus of the rat

We report results of studies of global and targeted neuronal metabolomes by ambient pressure ion mobility mass spectrometry. The rat frontal cortex, striatum, and thalamus were sampled from control nontreated rats and those treated with acute cocaine or pargyline. Quantitative evaluations were made by standard additions or isotopic dilution. The mass detection limit was ~100 pmol varying with the analyte. Targeted metabolites of dopamine, serotonin, and glucose followed the rank order of distribution expected between the anatomical areas. Data was evaluated by principal component analysis on 764 common metabolites (identified by m/z and reduced mobility). Differences between anatomical areas and treatment groups were observed for 53 % of these metabolites using principal component analysis. Global and targeted metabolic differences were observed between the three anatomical areas with contralateral differences between some areas. Following drug treatments, global and targeted metabolomes were found to shift relative to controls and still maintained anatomical differences. Pargyline reduced 3,4-dihydroxyphenylacetic acid below detection limits, and 5-HIAA varied between anatomical regions. Notable findings were: (1) global metabolomes were different between anatomical areas and were altered by acute cocaine providing a broad but targeted window of discovery for metabolic changes produced by drugs of abuse; (2) quantitative analysis was demonstrated using isotope dilution and standard addition; (3) cocaine changed glucose and biogenic amine metabolism in the anatomical areas tested; and (4) the largest effect of cocaine was on the glycolysis metabolome in the thalamus confirming inferences from previous positron emission tomography studies using 2-deoxyglucose.

Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry

Metabolism has an essential role in biological systems. Identification and quantitation of the compounds in the metabolome is defined as metabolic profiling, and it is applied to define metabolic changes related to genetic differences, environmental influences and disease or drug perturbations. Chromatography-mass spectrometry (MS) platforms are frequently used to provide the sensitive and reproducible detection of hundreds to thousands of metabolites in a single biofluid or tissue sample. Here we describe the experimental workflow for long-term and large-scale metabolomic studies involving thousands of human samples with data acquired for multiple analytical batches over many months and years. Protocols for serum- and plasma-based metabolic profiling applying gas chromatography-MS (GC-MS) and ultraperformance liquid chromatography-MS (UPLC-MS) are described. These include biofluid collection, sample preparation, data acquisition, data pre-processing and quality assurance. Methods for quality control-based robust LOESS signal correction to provide signal correction and integration of data from multiple analytical batches are also described.

Overtone mobility spectrometry: part 3. On the origin of peaks

The origin of non-integer overtone peaks in overtone mobility spectrometry (OMS) spectra is investigated by ion trajectory simulations. Simulations indicate that these OMS features arise from higher-order overtone series. An empirically-derived formula is presented as a means of describing the positions of peaks. The new equation makes it possible to determine collision cross sections from any OMS peak. Additionally, it is extended as a means of predicting the resolving power for any peak in an OMS distribution.

Metabolic profiling of Escherichia coli by ion mobility-mass spectrometry with MALDI ion source

Comprehensive metabolome analysis using mass spectrometry (MS) often results in a complex mass spectrum and difficult data analysis resulting from the signals of numerous small molecules in the metabolome. In addition, MS alone has difficulty measuring isobars and chiral, conformational and structural isomers. When a matrix-assisted laser desorption ionization (MALDI) source is added, the difficulty and complexity are further increased. Signal interference between analyte signals and matrix ion signals produced by MALDI in the low mass region (<1500 Da) cause detection and/or identification of metabolites difficult by MS alone. However, ion mobility spectrometry (IMS) coupled with MS (IM-MS) provides a rapid analytical tool for measuring subtle structural differences in chemicals. IMS separates gas-phase ions based on their size-to-charge ratio. This study, for the first time, reports the application of MALDI to the measurement of small molecules in a biological matrix by ion mobility-time of flight mass spectrometry (IM-TOFMS) and demonstrates the advantage of ion-signal dispersion in the second dimension. Qualitative comparisons between metabolic profiling of the Escherichia coli metabolome by MALDI-TOFMS, MALDI-IM-TOFMS and electrospray ionization (ESI)-IM-TOFMS are reported. Results demonstrate that mobility separation prior to mass analysis increases peak-capacity through added dimensionality in measurement. Mobility separation also allows detection of metabolites in the matrix-ion dominated low-mass range (m/z < 1500 Da) by separating matrix signals from non-matrix signals in mobility space.

Separation of isomers L-alanine and sarcosine in urine by electrospray ionization and tandem differential mobility analysis-mass spectrometry

Sarcosine, an isomer of L-alanine, has been proposed as a prostate cancer progression biomarker [1]. Both compounds are detected in urine, where the measured sarcosine/alanine ratio has been found to be higher in prostate biopsy-positive group versus controls. We present here preliminary evidence showing that urine samples spiked with sarcosine/alanine can be partially resolved in 3 min via tandem differential mobility analysis-mass spectrometry (DMA-MS). Based on the calibration curves obtained for two mobility peaks, we finally estimate their concentration ratio in urine.

Trend analysis of time-series data: A novel method for untargeted metabolite discovery

A new strategy for biomarker discovery is presented that uses time-series metabolomics data. Data sets from samples analysed at different time points after an intervention are searched for compounds that show a meaningful trend following the intervention. Obviously, this requires new data-analytical tools to distinguish such compounds from those showing only random variation. Two univariate methods, autocorrelation and curve-fitting, are used either as stand-alone methods or in combination to discover unknown metabolites in data sets originating from target-compound analysis. Both techniques reduce the long list of detected compounds in the kinetic sample set to include only those having a pre-defined interesting time profile. Thus, new metabolites may be discovered within data structures that are usually only used for target-compound analysis. The new strategy is tested on a sample set obtained from a gut fermentation study of a polyphenol-rich diet. For this study, the initial list of over 9000 potentially interesting features was reduced to less than 150, thus significantly reducing the expensive and time-consuming manual examination.