Imaging mass spectrometry enables molecular profiling of mouse and human pancreatic tissue

Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements

Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.

Hierarchical Biclustering of Mouse Pancreas Mass Spectrometry Imaging Data Using Recursive Rank-2 Non-negative Matrix Factorization

One of the main challenges in mass spectrometry imaging data analysis remains the analysis of m/z-spectra displaying a low signal-to-noise ratio caused by their low abundance, sample preparation, matrix effects, fragmentation, and other artifacts. Additionally, we observe that molecules with a high abundance suppress those with lower intensities and misdirect classical tools for MSI data analysis, such as principal component analysis. As a result, the observed significance of a molecule may not always be directly related to its abundance. In this work, we present a recursive rank-2 non-negative matrix factorization (rr2-NMF) algorithm that automatically returns spectral and spatial visualization of colocalized molecules, both highly and lowly abundant. Using this hierarchical decomposition, our method finds spatial and spectral correlations on different levels of abundances. The quality of the analysis is evaluated on MALDI-TOF data of healthy mouse pancreatic tissue for the annotation of molecules of interest in the lower abundances. The results show interesting findings regarding the functioning and colocalization of certain molecules.

Spatially resolved distribution of pancreatic hormones proteoforms by MALDI-imaging mass spectrometry

Zinc plays a crucial role both in the immune system and endocrine processes. Zinc restriction in the diet has been shown to lead to degeneration of the endocrine pancreas, resulting in hormonal imbalance within the β-cells. Proteostasismay vary depending on the stage of a pathophysiological process, which underscores the need for tools aimed at directly analyzing biological status. Among proteomics methods, MALDI-ToF-MS can serve as a rapid peptidomics tool for analyzing extracts or by histological imaging. Here we report the optimization of MALDI imaging mass spectrometry analysis of histological thin sections from mouse pancreas. This optimization enables the identification of the major islet peptide hormones as well as the major accumulated precursors and/or proteolytic products of peptide hormones. Cross-validation of the identified peptide hormones was performed by LC-ESI-MS from pancreatic islet extracts. Mice subjected to a zinc-restricted diet exhibited a relatively lower amount of peptide intermediates compared to the control group. These findings provide evidence for a complex modulation of proteostasis by micronutrients imbalance, a phenomenon directly accessed by MALDI-MSI.

Data Acquisition and Intraoperative Tissue Analysis on a Mobile, Battery-Operated, Orbitrap Mass Spectrometer

Mass spectrometry has been increasingly explored in intraoperative studies as a potential technology to help guide surgical decision making. Yet, intraoperative experiments using high-performance mass spectrometry instrumentation present a unique set of operational challenges. For example, standard operating rooms are often not equipped with the electrical requirements to power a commercial mass spectrometer and are not designed to accommodate their permanent installation. These obstacles can impact progress and patient enrollment in intraoperative clinical studies because implementation of MS instrumentation becomes limited to specific operating rooms that have the required electrical connections and space. To expand our intraoperative clinical studies using the MasSpec Pen technology, we explored the feasibility of transporting and acquiring data on Orbitrap mass spectrometers operating on battery power in hospital buildings. We evaluated the effect of instrument movement including acceleration and rotational speeds on signal stability and mass accuracy by acquiring data using direct infusion electrospray ionization. Data were acquired while rolling the systems in/out of operating rooms and while descending/ascending a freight elevator. Despite these movements and operating the instrument on battery power, the relative standard deviation of the total ion current was <5% and the magnitude of the mass error relative to the internal calibrant never exceeded 5.06 ppm. We further evaluated the feasibility of performing intraoperative MasSpec Pen analysis while operating the Orbitrap mass spectrometer on battery power during an ovarian cancer surgery. We observed that the rich and tissue-specific molecular profile commonly detected from ovarian tissues was conserved when running on battery power. Together, these results demonstrate that Orbitrap mass spectrometers can be operated and acquire data on battery power while in motion and in rotation without losses in signal stability or mass accuracy. Furthermore, Orbitrap mass spectrometers can be used in conjunction to the MasSpec Pen while on battery power for intraoperative tissue analysis.

Spatial Multi-Omics in Alzheimer's Disease: A Multi-Dimensional Approach to Understanding Pathology and Progression

Alzheimer's Disease (AD) presents a complex neuropathological landscape characterized by hallmark amyloid plaques and neurofibrillary tangles, leading to progressive cognitive decline. Despite extensive research, the molecular intricacies contributing to AD pathogenesis are inadequately understood. While single-cell omics technology holds great promise for application in AD, particularly in deciphering the understanding of different cell types and analyzing rare cell types and transcriptomic expression changes, it is unable to provide spatial distribution information, which is crucial for understanding the pathological processes of AD. In contrast, spatial multi-omics research emerges as a promising and comprehensive approach to analyzing tissue cells, potentially better suited for addressing these issues in AD. This article focuses on the latest advancements in spatial multi-omics technology and compares various techniques. Additionally, we provide an overview of current spatial omics-based research results in AD. These technologies play a crucial role in facilitating new discoveries and advancing translational AD research in the future. Despite challenges such as balancing resolution, increasing throughput, and data analysis, the application of spatial multi-omics holds immense potential in revolutionizing our understanding of human disease processes and identifying new biomarkers and therapeutic targets, thereby potentially contributing to the advancement of AD research.

Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level

This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Imaging and Structural Characterization of Phosphatidylcholine Isomers from Rat Brain Tissue Using Sequential Collision-Induced Dissociation/Electron-Induced Dissociation

The chemical complexity of biological tissues creates challenges in the analysis of lipids via imaging mass spectrometry. The presence of isobaric and isomeric compounds introduces chemical noise that makes it difficult to unambiguously identify and accurately map the spatial distributions of these compounds. Electron-induced dissociation (EID) has previously been shown to profile phosphatidylcholine (PCs) sn-isomers directly from rat brain tissue in matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry. However, the acquisition of true pixel-by-pixel images, as opposed to regional profiling measurements, using EID is difficult due to low fragmentation efficiency and precursor ion signal dilution into multiple fragment ion channels, resulting in low sensitivity. In this work, we have developed a sequential collision-induced dissociation (CID)/EID method to visualize the distribution of sn-isomers in MALDI imaging mass spectrometry experiments. Briefly, CID is performed on sodium-adducted PCs, which results in facile loss of the phosphocholine headgroup. This ion is then subjected to an EID analysis. Since the lipid headgroup is removed prior to EID, a major fragmentation pathway common to EID ion activation is eliminated, resulting in a more sensitive analysis. This sequential CID/EID workflow generates sn-specific fragment ions allowing for the assignment of the sn-positions. Carbon-carbon double-bond (C═C) positions are also localized along the fatty acyl tails by the presence of a 2 Da shift pattern in the fragment ions arising from carbon-carbon bond cleavages. Moreover, the integration of the CID/EID method into MALDI imaging mass spectrometry enables the mapping of the absolute and relative distribution of sn-isomers at every pixel. The localized relative abundances of sn-isomers vary throughout brain substructures and likely reflect different biological functions and metabolism.

Advances and Emerging Medical Applications of Direct Mass Spectrometry Technologies for Tissue Analysis

Offering superb speed, chemical specificity, and analytical sensitivity, direct mass spectrometry (MS) technologies are highly amenable for the molecular analysis of complex tissues to aid in disease characterization and help identify new diagnostic, prognostic, and predictive markers. By enabling detection of clinically actionable molecular profiles from tissues and cells, direct MS technologies have the potential to guide treatment decisions and transform sample analysis within clinical workflows. In this review, we highlight recent health-related developments and applications of direct MS technologies that exhibit tangible potential to accelerate clinical research and disease diagnosis, including oncological and neurodegenerative diseases and microbial infections. We focus primarily on applications that employ direct MS technologies for tissue analysis, including MS imaging technologies to map spatial distributions of molecules in situ as well as handheld devices for rapid in vivo and ex vivo tissue analysis.

Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks

Despite numerous diagnostic and therapeutic advances, pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate, and is the fourth leading cause of cancer death in developing countries. Besides its increasing prevalence, pancreatic malignancies are characterized by poor prognosis. Omics technologies have potential relevance for PDAC assessment but are time-intensive and relatively cost-intensive and limited by tissue heterogeneity. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can obtain spatially distinct peptide-signatures and enables tumor classification within a feasible time with relatively low cost. While MALDI-MSI data sets are inherently large, machine learning methods have the potential to greatly decrease processing time. We present a pilot study investigating the potential of MALDI-MSI in combination with neural networks, for classification of pancreatic ductal adenocarcinoma. Neural-network models were trained to distinguish between pancreatic ductal adenocarcinoma and other pancreatic cancer types. The proposed methods are able to correctly classify the PDAC types with an accuracy of up to 86% and a sensitivity of 82%. This study demonstrates that machine learning tools are able to identify different pancreatic carcinoma from complex MALDI data, enabling fast prediction of large data sets. Our results encourage a more frequent use of MALDI-MSI and machine learning in histopathological studies in the future.

Mouse Pancreatic Peptide Hormones Probed at the Sub-Single-Islet Level: The Effects of Acute Corticosterone Treatment

We combine liquid chromatography coupled with ion mobility spectrometry-mass spectrometry to elucidate how short exposure to corticosterone (Cort) alters the output of mouse pancreatic islet hormones. The workflow enables the robust separation of mouse insulin 1 (Ins1) and insulin 2 (Ins2) and the detection of major islet hormones in a homogenate equivalent to 100-150 islet cells. We show that Ins2 has a unique structure and is degraded much faster than Ins1. Further investigation indicates that Ins2 may populate both T and R states, whereas Ins1 may not. The assemblies of Ins1's B-chain also introduce more structural heterogeneity than Ins2. Collectively, these features account for their unique degradation profiles, the diabetes risk associated with Ins1, and the protective effect of Ins2. In the same experiments, we observe that the ratio of amylin to Ins1 increased significantly in Cort-treated mice (15:1) compared to the control mice (42:1), correlating well with β-cell proliferation observed in immunoassays on the same animal model. We observe no increase in intact full-length insulin levels but more of the truncated forms, indicating that enzymatic activity is accelerated. Our data provide a molecular basis for reduced insulin action induced by Cort and connections between insulin turnover and insulin resistance.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Mass Spectrometry Approaches Empowering Neuropeptide Discovery and Therapeutics

The discovery of insulin in the early 1900s ushered in the era of research related to peptides acting as hormones and neuromodulators, among other regulatory roles. These essential gene products are found in all organisms, from the most primitive to the most evolved, and carry important biologic information that coordinates complex physiology and behavior; their misregulation has been implicated in a variety of diseases. The evolutionary origins of at least 30 neuropeptide signaling systems have been traced to the common ancestor of protostomes and deuterostomes. With the use of relevant animal models and modern technologies, we can gain mechanistic insight into orthologous and paralogous endogenous peptides and translate that knowledge into medically relevant insights and new treatments. Groundbreaking advances in medicine and basic science influence how signaling peptides are defined today. The precise mechanistic pathways for over 100 endogenous peptides in mammals are now known and have laid the foundation for multiple drug development pipelines. Peptide biologics have become valuable drugs due to their unique specificity and biologic activity, lack of toxic metabolites, and minimal undesirable interactions. This review outlines modern technologies that enable neuropeptide discovery and characterization, and highlights lessons from nature made possible by neuropeptide research in relevant animal models that is being adopted by the pharmaceutical industry. We conclude with a brief overview of approaches/strategies for effective development of peptides as drugs. SIGNIFICANCE STATEMENT: Neuropeptides, an important class of cell-cell signaling molecules, are involved in maintaining a range of physiological functions. Since the discovery of insulin's activity, over 100 bioactive peptides and peptide analogs have been used as therapeutics. Because these are complex molecules not easily predicted from a genome and their activity can change with subtle chemical modifications, mass spectrometry (MS) has significantly empowered peptide discovery and characterization. This review highlights contributions of MS-based research towards the development of therapeutic peptides.

A simple preparation step to remove excess liquid lipids in white adipose tissue enabling improved detection of metabolites via MALDI-FTICR imaging MS

Matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) imaging mass spectrometry (MS) is a powerful technology used to analyze metabolites in various tissues. However, it faces significant challenges in studying adipose tissues. Poor matrix distribution and crystallization caused by excess liquid lipids on the surface of tissue sections hamper m/z species detection, an adverse effect that particularly presents in lipid-rich white adipose tissue (WAT). In this study, we integrated a simple and low-cost preparation step into the existing MALDI-FTICR imaging MS pipeline. The new method—referred to as filter paper application—is characterized by an easy sample handling and high reproducibility. The aforementioned filter paper is placed onto the tissue prior to matrix application in order to remove the layer of excess liquid lipids. Consequently, MALDI-FTICR imaging MS detection was significantly improved, resulting in a higher number of detected m/z species and higher ion intensities. After analyzing various durations of filter paper application, 30 s was found to be optimal, resulting in the detection of more than 3700 m/z species. Apart from the most common lipids found in WAT, other molecules involved in various metabolic pathways were detected, including nucleotides, carbohydrates, and amino acids. Our study is the first to propose a solution to a specific limitation of MALDI-FTICR imaging MS in investigating lipid-rich WAT. The filter paper approach can be performed quickly and is particularly effective for achieving uniform matrix distribution on fresh frozen WAT while maintaining tissue integrity. It thus helps to gain insight into the metabolism in WAT.

Reduced Hemoglobin Signal and Improved Detection of Endogenous Proteins in Blood-Rich Tissues for MALDI Mass Spectrometry Imaging

Mass spectrometry imaging provides a powerful approach for the direct analysis and spatial visualization of molecules in tissue sections. Using matrix-assisted laser desorption/ionization mass spectrometry, intact protein imaging has been widely investigated for biomarker analysis and diagnosis in a variety of tissue types and diseases. However, blood-rich or highly vascular tissues present a challenge in molecular imaging due to the high ionization efficiency of hemoglobin, which leads to ion suppression of endogenous proteins. Here, we describe a protocol to selectively reduce hemoglobin signal in blood-rich tissues that can easily be integrated into mass spectrometry imaging workflows.

Correlation between metabolomic profile constituents and feline pancreatic lipase immunoreactivity

Background

Feline pancreatic lipase immunoreactivity (fPLI) is commonly used to diagnose pancreatitis in cats (FP). Untargeted metabolomics has been extensively applied in human and veterinary medicine, but no metabolomic studies regarding FP have been conducted.

Objectives

To identify metabolites significantly associated with increased fPLI.

Animals

Forty‐nine client‐owned cats: 11 clinically healthy and 38 with various clinical conditions.

Methods

Analytical cross‐sectional study with convenience sampling. A panel of 630 metabolites belonging to 26 biochemical classes was quantified in plasma using a commercial metabolomic assay. The correlation between plasma metabolite concentrations and serum fPLI was evaluated using Spearman's rank correlation coefficient (R_s) with Bonferroni correction. Multivariable analysis then was performed to control for glomerular filtration rate, liver damage, and blood glucose concentration. The accuracy of selected metabolites in discriminating between cats with normal (≤3.5 μg/L) and increased (>5.3 μg/L) fPLI was estimated using the area under the receiver operating characteristic curve (AUROC).

Results

Four hundred and seven of 630 metabolites (64.6%) were quantified in all cats. When controlled for potential confounders only 3 sphingolipids were significantly positively correlated with fPLI: 2 cerebrosides: HexCer(d18:1/24:0); (R_s = .56), and HexCer(d18:1/24:1); (R_s = .58) and 1 sphingomyelin: SM C18:0 (R_s = .55). Their AUROCs in identifying cats with increased fPLI were 82% (95% confidence interval [CI 95%], 70%‐94%), 84% (CI 95%, 72%‐96%), and 78% (CI 95%, 65%‐92%), respectively.

Conclusions and Clinical Importance

Selected sphingolipids are moderately positively correlated with fPLI and appear to have fair to moderate diagnostic accuracy in discriminating between cats with normal and increased fPLI.

Application of Mass Spectrometry in Pancreatic Cancer Translational Research

Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment.

The Human Islet: Mini-Organ With Mega-Impact

This review focuses on the human pancreatic islet-including its structure, cell composition, development, function, and dysfunction. After providing a historical timeline of key discoveries about human islets over the past century, we describe new research approaches and technologies that are being used to study human islets and how these are providing insight into human islet physiology and pathophysiology. We also describe changes or adaptations in human islets in response to physiologic challenges such as pregnancy, aging, and insulin resistance and discuss islet changes in human diabetes of many forms. We outline current and future interventions being developed to protect, restore, or replace human islets. The review also highlights unresolved questions about human islets and proposes areas where additional research on human islets is needed.

[Mass spectrometry imaging technology and its application in breast cancer research]

乳腺癌是女性最常见的恶性肿瘤,其发病率在世界范围内呈现上升趋势,是威胁女性健康的重要疾病之一。随着现代医学技术的快速发展,早期有效的诊断和筛查方法能够改善乳腺癌患者生存率和提高其生活质量。由于乳腺癌肿瘤具有非常显著的异质性,这对于诊断和筛查带来了较大困难,亟须在肿瘤演进时间信息中,继续引入生物分子的空间信息,从而对其异质性、肿瘤微环境等进行准确的追踪。质谱成像技术,可在免标记的前提下利用离子质荷比的特性发现生物组织中的各种分子,并研究这些分子的时间和空间信息,对其进行准确的定性、定量和空间定位。目前,通过质谱成像技术可直接获取药物及其代谢物、内源性代谢物、脂质、多肽和蛋白质等在组织中的空间分布信息,为肿瘤分子分型诊断和确认以及相关抗肿瘤药物的筛选提供了新的思路和研究方向。该综述以乳腺癌相关的生物样品制备和研究进展为主要内容,从小分子样本、大分子样本、石蜡包埋样本、基质喷涂方式、常用离子源等方面阐述质谱成像中样本制备的重要性以及样品制备过程中存在的难点问题。同时,以细胞模型、动物模型和临床肿瘤标本为研究对象,汇总了质谱成像技术在乳腺癌方面的应用进展,并进行了展望,为开展癌症精准分型研究和药物药效的快速筛查提供了重要依据。

State-of-the-art microscopy to understand islets of Langerhans: what to expect next?

The discovery of Langerhans and microscopic description of islets in the pancreas were crucial steps in the discovery of insulin. Over the past 150 years, many discoveries in islet biology and type 1 diabetes have been made using powerful microscopic techniques. In the past decade, combination of new probes, animal and tissue models, application of new biosensors and automation of light and electron microscopic methods and other (sub)cellular imaging modalities have proven their potential in understanding the beta cell under (patho)physiological conditions. The imaging evolution, from fluorescent jellyfish to real‐time intravital functional imaging, the revolution in automation and data handling and the increased resolving power of analytical imaging techniques are now converging. Here, we review innovative approaches that address islet biology from new angles by studying cells and molecules at high spatiotemporal resolution and in live models. Broad implementation of these cellular imaging techniques will shed new light on cause/consequence of (mal)function in islets of Langerhans in the years to come.

Perspective on Emerging Mass Spectrometry Technologies for Comprehensive Lipid Structural Elucidation

Lipids and metabolites are of interest in many clinical and research settings because it is the metabolome that is increasingly recognized as a more dynamic and sensitive molecular measure of phenotype. The enormous diversity of lipid structures and the importance of biological structure-function relationships in a wide variety of applications makes accurate identification a challenging yet crucial area of research in the lipid community. Indeed, subtle differences in the chemical structures of lipids can have important implications in cellular metabolism and many disease pathologies. The speed, sensitivity, and molecular specificity afforded by modern mass spectrometry has led to its widespread adoption in the field of lipidomics on many different instrument platforms and experimental workflows. However, unambiguous and complete structural identification of lipids by mass spectrometry remains challenging. Increasingly sophisticated tandem mass spectrometry (MS/MS) approaches are now being developed and seamlessly integrated into lipidomics workflows to meet this challenge. These approaches generally either (i) alter the type of ion that is interrogated or (ii) alter the dissociation method in order to improve the structural information obtained from the MS/MS experiment. In this Perspective, we highlight recent advances in both ion type alteration and ion dissociation methods for lipid identification by mass spectrometry. This discussion is aimed to engage investigators involved in fundamental ion chemistry and technology developments as well as practitioners of lipidomics and its many applications. The rapid rate of technology development in recent years has accelerated and strengthened the ties between these two research communities. We identify the common characteristics and practical figures of merit of these emerging approaches and discuss ways these may catalyze future directions of lipid structural elucidation research.

Evidence for the existence and potential roles of intra-islet glucagon-like peptide-1

Glucagon-Like Peptide-1 (GLP-1) is an important peptide hormone secreted by L-cells in the gastrointestinal tract in response to nutrients. It is produced by the differential cleavage of the proglucagon peptide. GLP-1 elicits a wide variety of physiological responses in many tissues that contribute to metabolic homeostasis. For these reasons, therapies designed to either increase endogenous GLP-1 levels or introduce exogenous peptide mimetics are now widely used in the management of diabetes. In addition to GLP-1 production from L-cells, recent reports suggest that pancreatic islet alpha cells may also synthesize and secrete GLP-1. Intra-islet GLP-1 may therefore play an unappreciated role in islet health and glucose regulation, suggesting a potential functional paracrine role for islet-derived GLP-1. In this review, we assess the current literature from an islet-centric point-of-view to better understand the production, degradation, and actions of GLP-1 within the endocrine pancreas in rodents and humans. The relevance of intra-islet GLP-1 in human physiology is discussed regarding the potential role of intra-islet GLP-1 in islet health and dysfunction.

Accumulation of long-chain fatty acids in the tumor microenvironment drives dysfunction in intrapancreatic CD8+ T cells

CD8⁺ T cells are master effectors of antitumor immunity, and their presence at tumor sites correlates with favorable outcomes. However, metabolic constraints imposed by the tumor microenvironment (TME) can dampen their ability to control tumor progression. We describe lipid accumulation in the TME areas of pancreatic ductal adenocarcinoma (PDA) populated by CD8⁺ T cells infiltrating both murine and human tumors. In this lipid-rich but otherwise nutrient-poor TME, access to using lipid metabolism becomes particularly valuable for sustaining cell functions. Here, we found that intrapancreatic CD8⁺ T cells progressively accumulate specific long-chain fatty acids (LCFAs), which, rather than provide a fuel source, impair their mitochondrial function and trigger major transcriptional reprogramming of pathways involved in lipid metabolism, with the subsequent reduction of fatty acid catabolism. In particular, intrapancreatic CD8⁺ T cells specifically exhibit down-regulation of the very-long-chain acyl-CoA dehydrogenase (VLCAD) enzyme, which exacerbates accumulation of LCFAs and very-long-chain fatty acids (VLCFAs) that mediate lipotoxicity. Metabolic reprogramming of tumor-specific T cells through enforced expression of ACADVL enabled enhanced intratumoral T cell survival and persistence in an engineered mouse model of PDA, overcoming one of the major hurdles to immunotherapy for PDA.

β-Cell Dysfunction, Hepatic Lipid Metabolism, and Cardiovascular Health in Type 2 Diabetes: New Directions of Research and Novel Therapeutic Strategies

Cardiovascular disease (CVD) remains a major problem for people with type 2 diabetes mellitus (T2DM), and dyslipidemia is one of the main drivers for both metabolic diseases. In this review, the major pathophysiological and molecular mechanisms of β-cell dysfunction and recovery in T2DM are discussed in the context of abnormal hepatic lipid metabolism and cardiovascular health. (i) In normal health, continuous exposure of the pancreas to nutrient stimulus increases the demand on β-cells. In the long term, this will not only stress β-cells and decrease their insulin secretory capacity, but also will blunt the cellular response to insulin. (ii) At the pre-diabetes stage, β-cells compensate for insulin resistance through hypersecretion of insulin. This increases the metabolic burden on the stressed β-cells and changes hepatic lipoprotein metabolism and adipose tissue function. (iii) If this lipotoxic hyperinsulinemic environment is not removed, β-cells start to lose function, and CVD risk rises due to lower lipoprotein clearance. (iv) Once developed, T2DM can be reversed by weight loss, a process described recently as remission. However, the precise mechanism(s) by which calorie restriction causes normalization of lipoprotein metabolism and restores β-cell function are not fully established. Understanding the pathophysiological and molecular basis of β-cell failure and recovery during remission is critical to reduce β-cell burden and loss of function. The aim of this review is to highlight the link between lipoprotein export and lipid-driven β-cell dysfunction in T2DM and how this is related to cardiovascular health. A second aim is to understand the mechanisms of β-cell recovery after weight loss, and to explore new areas of research for developing more targeted future therapies to prevent T2DM and the associated CVD events.

Single-Cell Metabolomics by Mass Spectrometry Imaging

Multicellular organisms achieve their complex living activities through the highly organized metabolic interplay of individual cells and tissues. This complexity has driven the need to spatially resolve metabolomics down to the cellular and subcellular level. Recent technological advances have enabled mass spectrometry imaging (MSI), especially matrix-assisted laser desorption/ionization (MALDI), to become a powerful tool for the visualization of molecular species down to subcellular spatial resolution. In the present chapter, we summarize recent advances in the field of MALDI-MSI, with respect to single-cell level resolution metabolomics directly on tissue. In more detail, we focus on advancements in instrumentation for MSI at single-cell resolution, and the applications towards metabolomic scale imaging. Finally, we discuss new computational tools to aid in metabolite identification, future perspective, and the overall direction that the field of single-cell metabolomics directly on tissue may take in the years to come.

Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine

Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.

Dynamic Range Expansion by Gas-Phase Ion Fractionation and Enrichment for Imaging Mass Spectrometry

In the analysis of biological tissue by imaging mass spectrometry (IMS), the limit of detection and dynamic range are of paramount importance in obtaining experimental results that provide insight into underlying biological processes. Many important biomolecules are present in the tissue milieu in low concentrations and in complex mixtures with other compounds of widely ranging abundances, challenging the limits of analytical technologies. In many IMS experiments, the ion signal can be dominated by a few highly abundant ion species. On trap-based instrument platforms that accumulate ions prior to mass analysis, these high abundance ions can diminish the detection and dynamic range of lower abundance ions. Herein, we describe two strategies for combating these challenges during IMS experiments on a hybrid QhFT-ICR MS. In one iteration, the mass resolving capabilities of a quadrupole mass filter are used to selectively enrich ions of interest via a technique previously termed continuous accumulation of selected ions. Second, we have introduced a supplemental dipolar AC waveform to the quadrupole mass filter of a commercial QhFT-ICR mass spectrometer to perform selected ion ejection prior to the ion accumulation region. This setup allows the selective ejection of the most abundant ion species prior to ion accumulation, thereby greatly improving the molecular depth with which IMS can probe tissue samples. The gain in sensitivity of both of these approaches roughly scales with the number of accumulated laser shots up to the charge capacity of the ion accumulation cell. The efficiencies of these two strategies are described here by performing lipid imaging mass spectrometry analyses of a rat brain.

Multifunctional Reactive MALDI Matrix Enabling High-Lateral Resolution Dual Polarity MS Imaging and Lipid C═C Position-Resolved MS2 Imaging

Local lipid variations in tissues are readily revealed with mass spectrometry imaging (MSI) methods, and the resulting lipid distributions serve as bioanalytical signatures to reveal cell- or tissue-specific lipids. Comprehensive MSI lipid mapping requires measurements in both ion polarities. Additionally, structural lipid characterization is necessary to link the lipid structure to lipid function. Whereas some structural elements of lipids are readily derived from high-resolution mass spectrometry (MS) and tandem-MS (MSⁿ), the localization of C═C double bonds (DBs) requires specialized fragmentation and/or functionalization methods. In this work, we identify a multifunctional matrix-assisted laser desorption/ionization (MALDI) matrix for spatially resolved lipidomics investigations that reacts with lipids in Paternò-Büchi (PB) reactions during laser irradiation facilitating DB-position assignment and allows dual-polarity high-resolution MALDI-MSI and MALDI MS²I studies. By screening 12 compounds for improved ionization efficiency in positive-/negative-ion mode and the functionalization yield compared to the previously introduced reactive MALDI matrix benzophenone, 2-benzoylpyridine (BzPy) is identified as the best candidate. The new matrix enables DB localization of authentic standards belonging to 12 lipid classes and helps to assign 133/58 lipid features in positive-/negative-ion mode from mouse cerebellum tissue. The analytical capabilities of BzPy as a multifunctional MALDI-MSI matrix are demonstrated by imaging endogenous and PB-functionalized lipids in mouse kidney sections with 7 μm lateral resolution in both ion modes. Tracking diagnostic lipid DB-position fragment ions in mouse pancreatic tissue with down to 10 μm pixel size allows us to identify the islets of Langerhans associated with lipid isomer upregulation and depletion.

Use of Single-Cell -Omic Technologies to Study the Gastrointestinal Tract and Diseases, From Single Cell Identities to Patient Features

Single cells are the building blocks of tissue systems that determine organ phenotypes, behaviors, and functions. Understanding the differences between cell types and their activities might provide us with insights into normal tissue physiology, development of disease, and new therapeutic strategies. Although -omic level single-cell technologies are a relatively recent development that have been used only in research settings, these approaches might eventually be used in the clinic. We review the prospects of applying single-cell genome, transcriptome, epigenome, proteome, and metabolome analyses to gastroenterology and hepatology research. Combining data from multi-omic platforms coupled to rapid technological development could lead to new diagnostic, prognostic, and therapeutic approaches.

Sphingolipids in food and their critical roles in human health

Sphingolipids (SLs) are ubiquitous structural components of cell membranes and are essential for cell functions under physiological conditions or during disease progression. Abundant evidence supports that SLs and their metabolites, including ceramide (Cer), ceramide-1-phosphate (C1P), sphingosine (So), sphingosine-1-phosphate (S1P), are signaling molecules that regulate a diverse range of cellular processes and human health. However, there are limited reviews on the emerging roles of exogenous dietary SLs in human health. In this review, we discuss the ubiquitous presence of dietary SLs, highlighting their structures and contents in foodstuffs, particularly in sea foods. The digestion and metabolism of dietary SLs is also discussed. Focus is given to the roles of SLs in both the etiology and prevention of diseases, including bacterial infection, cancers, neurogenesis and neurodegenerative diseases, skin integrity, and metabolic syndrome (MetS). We propose that dietary SLs represent a "functional" constituent as emerging strategies for improving human health. Gaps in research that could be of future interest are also discussed.

De novo discovery of metabolic heterogeneity with immunophenotype-guided imaging mass spectrometry

Imaging mass spectrometry enables in situ label-free detection of thousands of metabolites from intact tissue samples. However, automated steps for multi-omics analyses and interpretation of histological images have not yet been implemented in mass spectrometry data analysis workflows. The characterization of molecular properties within cellular and histological features is done via time-consuming, non-objective, and irreproducible definitions of regions of interest, which are often accompanied by a loss of spatial resolution due to mass spectra averaging.

Methods: We developed a new imaging pipeline called Spatial Correlation Image Analysis (SPACiAL), which is a computational multimodal workflow designed to combine molecular imaging data with multiplex immunohistochemistry (IHC). SPACiAL allows comprehensive and spatially resolved in situ correlation analyses on a cellular resolution. To demonstrate the method, matrix-assisted laser desorption-ionization (MALDI) Fourier-transform ion cyclotron resonance (FTICR) imaging mass spectrometry of metabolites and multiplex IHC staining were performed on the very same tissue section of mouse pancreatic islets and on human gastric cancer tissue specimens. The SPACiAL pipeline was used to perform an automatic, semantic-based, functional tissue annotation of histological and cellular features to identify metabolic profiles. Spatial correlation networks were generated to analyze metabolic heterogeneity associated with cellular features.

Results: To demonstrate the new method, the SPACiAL pipeline was used to identify metabolic signatures of alpha and beta cells within islets of Langerhans, which are cell types that are not distinguishable via morphology alone. The semantic-based, functional tissue annotation allows an unprecedented analysis of metabolic heterogeneity via the generation of spatial correlation networks. Additionally, we demonstrated intra- and intertumoral metabolic heterogeneity within HER2/neu-positive and -negative gastric tumor cells.

Conclusions: We developed the SPACiAL workflow to provide IHC-guided in situ metabolomics on intact tissue sections. Diminishing the workload by automated recognition of histological and functional features, the pipeline allows comprehensive analyses of metabolic heterogeneity. The multimodality of immunohistochemical staining and extensive molecular information from imaging mass spectrometry has the advantage of increasing both the efficiency and precision for spatially resolved analyses of specific cell types. The SPACiAL method is a stepping stone for the objective analysis of high-throughput, multi-omics data from clinical research and practice that is required for diagnostics, biomarker discovery, or therapy response prediction.

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Novel method enables phenotype-guided in situ metabolomics on intact tissue sections.

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Metabolic heterogeneity can be objectified under (patho-)physiological conditions.

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Innovative approach for tissue-based, preclinical, and clinical research.

UHPLC/QTOF-MS-based metabolomics reveal the effect of Melastoma dodecandrum extract in type 2 diabetic rats

Context: Melastoma dodecandrum Lour. (Melastomataceae) is a traditional Chinese medicine. This is the first study to report a protective effect of the ethanol extract from M. dodecandrum (MDE) in type 2 diabetic (T2DM) rats.Objective: To investigate the therapeutic mechanism of MDE in T2DM rats.Materials and methods: Sprague-Dawley rats were fed a high-fat diet for 6 consecutive weeks, followed by intraperitoneal injection of streptozotocin (STZ) (30 mg/kg) to induce diabetes. T2DM rats were divided into untreated diabetic, metformin-treated and MDE-treated groups. Additionally, normal rats without treatment served as the control group (n = 6). Metformin (250 mg/kg) and MDE (600 mg/kg) were intragastrically administered to T2DM rats for 5 consecutive weeks. Serum samples were evaluated via ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS), followed by principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA).Results: The 17 identified potential biomarkers were mainly involved in lipid, amino acid, arachidonic acid, taurine and nicotinic acid metabolism. MDE also significantly reduced the level of fasting blood glucose (FBG), oral glucose tolerance, insulin, total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), malondialdehyde (MDA), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and urea nitrogen (BUN) in T2DM rats. The high-density lipoprotein (HDL), serum creatinine (Scr), superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GSH-Px) levels were elevated in MDE-treated group.Discussion and conclusion: MDE possesses substantial antidiabetic activity, especially in lipid disorder regulation. This suggests that the use of MDE can be generalized to broader pharmacological studies, such as obesity and hyperlipidaemia.

The Combination of Whole Cell Lipidomics Analysis and Single Cell Confocal Imaging of Fluidity and Micropolarity Provides Insight into Stress-Induced Lipid Turnover in Subcellular Organelles of Pancreatic Beta Cells

Modern omics techniques reveal molecular structures and cellular networks of tissues and cells in unprecedented detail. Recent advances in single cell analysis have further revolutionized all disciplines in cellular and molecular biology. These methods have also been employed in current investigations on the structure and function of insulin secreting beta cells under normal and pathological conditions that lead to an impaired glucose tolerance and type 2 diabetes. Proteomic and transcriptomic analyses have pointed to significant alterations in protein expression and function in beta cells exposed to diabetes like conditions (e.g., high glucose and/or saturated fatty acids levels). These nutritional overload stressful conditions are often defined as glucolipotoxic due to the progressive damage they cause to the cells. Our recent studies on the rat insulinoma-derived INS-1E beta cell line point to differential effects of such conditions in the phospholipid bilayers in beta cells. This review focuses on confocal microscopy-based detection of these profound alterations in the plasma membrane and membranes of insulin granules and lipid droplets in single beta cells under such nutritional load conditions.