Single cell matrix-assisted laser desorption/ionization mass spectrometry imaging

Exploring Single-Probe Single-Cell Mass Spectrometry: Current Trends and Future Directions

The Single-probe single-cell mass spectrometry (SCMS) is an innovative analytical technique designed for metabolomic profiling, offering a miniaturized, multifunctional device capable of direct coupling to mass spectrometers. It is an ambient technique leveraging microscale sampling and nanoelectrospray ionization (nanoESI), enabling the analysis of cells in their native environments without the need for extensive sample preparation. Due to its miniaturized design and versatility, this device allows for applications in diverse research areas, including single-cell metabolomics, quantification of target molecules in single cell, MS imaging (MSI) of tissue sections, and investigation of extracellular molecules in live single spheroids. This review explores recent advancements in Single-probe-based techniques and their applications, emphasizing their potential utility in advancing MS methodologies in microscale bioanalysis.

Critical Evaluation of Sphingolipids Detection by MALDI-MSI

The increasing interest in the role of sphingolipids in (patho)physiology has led to the demand for visualization of these lipids within tissue samples (both from animal models and patient specimens) using techniques such as matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). While increasingly adopted, detection of sphingolipids with MALDI-MSI is challenging due to: i) the significant structural variations of sphingolipid molecules, ii) the potential breakdown of the more complex molecules into structurally simpler species which may confound the analysis, and iii) the great difference in levels among sphingolipid classes and subspecies, with the low-abundant ones often being close to the detection limit. In this study, we adopted a multi-pronged approach to establish a robust pipeline for the detection of sphingolipids by MALDI-MSI and to establish best practices and limitations of this technology. First, we evaluated the more commonly adopted methods [2,5-Dihydroxyacetophenon (DHA) or 2,5-Dihydroxybenzoic acid (DHB) matrix in positive ion mode and 1,5-Diaminonaphthalene (DAN) matrix in negative ion mode] using MALDI-MS on reference standards. These standards were used at ratios similar to their relative levels in biological samples to evaluate signal artifacts originating from fragmentation of more complex sphingolipids and impacting low level species. Next, by applying the most appropriate protocol for each sphingolipid class, MALDI-MSI signals were validated in cell culture by modulating specific sphingolipid species using sphingolipid enzymes and inhibitors. Finally, the optimized parameters were utilized on breast cancer tissue from the PyMT mouse model. We report the optimal signal for sphingomyelin (SM) and, for the first time, Sph in DHB positive ion mode (in cells and PyMT tissue), and the validated detection of ceramides and glycosphingolipids in DAN negative ion mode. We document the extensive fragmentation of SM into sphingosine-1-phosphate (S1P) and even more so into ceramide-1-phosphate (C1P) using DAN in negative ion mode and its effect in generating an artifactual C1P tissue signal; we also report the lack of detectable signal for S1P and C1P in biological samples (cells and tissue) using the more suitable DHB positive ion mode protocol.

Single cell lipid biology

Lipids are major cell constituents endowed with astonishing structural diversity. The pathways responsible for the assembly and disposal of different lipid species are energetically demanding, and genes encoding lipid metabolic factors and lipid-related proteins comprise a sizable fraction of our coding genome. Despite the importance of lipids, the biological significance of lipid structural diversity remains largely obscure. Recent technological developments have enabled extensive lipid analysis at the single cell level, revealing unexpected cell-cell variability in lipid composition. This new evidence suggests that lipid diversity is exploited in multicellularity and that lipids have a role in the establishment and maintenance of cell identity. In this review, we highlight the emerging concepts and technologies in single cell lipid analysis and the implications of this research for future studies.

Thermal evaporation as sample preparation for silver-assisted laser desorption/ionization mass spectrometry imaging of cholesterol in amyloid tissues

Cholesterol plays an important biological role in the body, and its disruption in homeostasis and synthesis has been implicated in several diseases. Mapping the locations of cholesterol is crucial for gaining a better understanding of these conditions. Silver deposition has proven to be an effective method for analyzing cholesterol using mass spectrometry imaging (MSI). We optimized and evaluated thermal evaporation as an alternative deposition technique to sputtering for silver deposition in MSI of cholesterol. A silver layer with a thickness of 6 nm provided an optimal combination of cholesterol signal intensity and mass resolution. The deposition of an ultrathin nanofilm of silver enabled high-resolution MSI with a pixel size of 10 μm. We used this optimized method to visualize the distribution of cholesterol in the senile plaques in the brains of APP/PS1 mice, a model that resembles Alzheimer's disease pathology. We found that cholesterol was evenly distributed across the frontal cortex tissue, with no evidence of plaque-like accumulation. Additionally, we investigated the presence and distribution of cholesterol in myocardial sections of a human heart affected by wild-type ATTR amyloidosis. We identified the presence of cholesterol in areas with amyloid deposition, but complete colocalization was not observed.

Single Cell mass spectrometry: Towards quantification of small molecules in individual cells

Studying cell heterogeneity can provide a deeper understanding of biological activities, but appropriate studies cannot be performed using traditional bulk analysis methods. The development of diverse single cell bioanalysis methods is in urgent need and of great significance. Mass spectrometry (MS) has been recognized as a powerful technique for bioanalysis for its high sensitivity, wide applicability, label-free detection, and capability for quantitative analysis. In this review, the general development of single cell mass spectrometry (SCMS) field is covered. First, multiple existing SCMS techniques are described and compared. Next, the development of SCMS field is discussed in a chronological order. Last, the latest quantification studies on small molecules using SCMS have been described in detail.

Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis

Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Quantification of Nitric Oxide in Single Cells Using the Single-Probe Mass Spectrometry Technique

Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.

Nanoparticle-based applications by atmospheric pressure matrix assisted desorption/ionization mass spectrometry

Recently, the development of atmospheric pressure matrix assisted desorption/ionization mass spectrometry (AP MALDI MS) has made contributions not only to biomolecule analysis but also to spatial distribution. This has positioned AP MALDI as a powerful tool in multiple domains, thanks to its comprehensive advantages compared to conventional MALDI MS. These developments have addressed challenges associated with previous AP MALDI analysis systems, such as optimization of apparatus settings, synthesis of novel matrices, preconcentration and isolation strategies before analysis. Herein, applications in different fields using AP MALDI MS were described, including peptide and protein analysis, metabolite analysis, pharmaceutical analysis, and mass spectrometry imaging.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Intracellular spatiotemporal metabolism in connection to target engagement

The metabolism in eukaryotic cells is a highly ordered system involving various cellular compartments, which fluctuates based on physiological rhythms. Organelles, as the smallest independent sub-cell unit, are important contributors to cell metabolism and drug metabolism, collectively designated intracellular metabolism. However, disruption of intracellular spatiotemporal metabolism can lead to disease development and progression, as well as drug treatment interference. In this review, we systematically discuss spatiotemporal metabolism in cells and cell subpopulations. In particular, we focused on metabolism compartmentalization and physiological rhythms, including the variation and regulation of metabolic enzymes, metabolic pathways, and metabolites. Additionally, the intricate relationship among intracellular spatiotemporal metabolism, metabolism-related diseases, and drug therapy/toxicity has been discussed. Finally, approaches and strategies for intracellular spatiotemporal metabolism analysis and potential target identification are introduced, along with examples of potential new drug design based on this.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Recent advances in mass spectrometry imaging of single cells

Mass spectrometry imaging (MSI) is a sensitive, specific, label-free imaging analysis technique that can simultaneously obtain the spatial distribution, relative content, and structural information of hundreds of biomolecules in cells and tissues, such as lipids, small drug molecules, peptides, proteins, and other compounds. The study of molecular mapping of single cells can reveal major scientific issues such as the activity pattern of living organisms, disease pathogenesis, drug-targeted therapy, and cellular heterogeneity. Applying MSI technology to the molecular mapping of single cells can provide new insights and ideas for the study of single-cell metabolomics. This review aims to provide an informative resource for those in the MSI community who are interested in single-cell imaging. Particularly, we discuss advances in imaging schemes and sample preparation, instrumentation improvements, data processing and analysis, and 3D MSI over the past few years that have allowed MSI to emerge as a powerful technique in the molecular imaging of single cells. Also, we highlight some of the most cutting-edge studies in single-cell MSI, demonstrating the future potential of single-cell MSI. Visualizing molecular distribution at the single-cell or even sub-cellular level can provide us with richer cell information, which strongly contributes to advancing research fields such as biomedicine, life sciences, pharmacodynamic testing, and metabolomics. At the end of the review, we summarize the current development of single-cell MSI technology and look into the future of this technology.

Development of mass spectrometry imaging techniques and its latest applications

Mass spectrometry imaging (MSI) is a novel molecular imaging technology that collects molecular information from the surface of samples in situ. The spatial distribution and relative content of various compounds can be visualized simultaneously with high spatial resolution. The prominent advantages of MSI promote the active development of ionization technology and its broader applications in diverse fields. This article first gives a brief introduction to the vital parts of the processes during MSI. On this basis, provides a comprehensive overview of the most relevant MS-based imaging techniques from their mechanisms, pros and cons, and applications. In addition, a critical issue in MSI, matrix effects is also discussed. Then, the representative applications of MSI in biological, forensic, and environmental fields in the past 5 years have been summarized, with a focus on various types of analytes (e.g., proteins, lipids, polymers, etc.) Finally, the challenges and further perspectives of MSI are proposed and concluded.

Mass Spectrometry Imaging for Single-Cell or Subcellular Lipidomics: A Review of Recent Advancements and Future Development

Mass Spectrometry Imaging (MSI) has emerged as a powerful imaging technique for the analysis of biological samples, providing valuable insights into the spatial distribution and structural characterization of lipids. The advancements in high-resolution MSI have made it an indispensable tool for single-cell or subcellular lipidomics. By preserving both intracellular and intercellular information, MSI enables a comprehensive analysis of lipidomics in individual cells and organelles. This enables researchers to delve deeper into the diversity of lipids within cells and to understand the role of lipids in shaping cell behavior. In this review, we aim to provide a comprehensive overview of recent advancements and future prospects of MSI for cellular/subcellular lipidomics. By keeping abreast of the cutting-edge studies in this field, we will continue to push the boundaries of the understanding of lipid metabolism and the impact of lipids on cellular behavior.

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed t-SNE of Mass Spectrometry Imaging Data

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue.

Absolute quantification of cholesterol from thin tissue sections by silver-assisted laser desorption ionization mass spectrometry imaging

Cholesterol is essential to all animal life, and its dysregulation is observed in many diseases. For some of these, the precise determination of cholesterol's histological location and absolute abundance at cellular length scales within tissue samples would open the door to a more fundamental understanding of the role of cholesterol in disease onset and progression. We have developed a fast and simple method for absolute quantification of cholesterol within brain samples based on the sensitive detection and mapping of cholesterol by silver-assisted laser desorption ionization mass spectrometry imaging (AgLDI MSI) from thin tissue sections. Reproducible calibration curves were generated by depositing a range of cholesterol-D₇ concentrations on brain homogenate tissue sections combined with the homogeneous spray deposition of a non-animal steroid reference standard detectable by AgLDI MSI to minimize experimental variability. Results obtained from serial brain sections gave consistent cholesterol quantitative values in very good agreement with those obtained with other mass spectrometry-based methods.

Protein Profiling of Breast Cancer for Treatment Decision-Making

The increasing use of neoadjuvant therapy has resulted in therapeutic decisions being made on the basis of diagnostic needle core biopsy. For many patients, this method might yield the only fragment of tumor available for biomarker analysis, necessitating judicious use. Many multiplex protein analytic methods have been developed that employ fluorescence or other tags to overcome the limitations of immunohistochemistry while still retaining the spatial annotation. Interpretation of the data can be difficult because of the limitations of the human eye. Computational deconvolution of the signals may be necessary for some of these methods to enable identification of cell-specific localization and coexpression of biomarkers. Herein, we present the different methods that are coming of age and their application in cancer research, with a focus on breast cancer. We also discuss the limitations, which include high costs and long turnaround times. The methods are also based on the premise that preanalytical factors will have identical impact on all proteins analyzed. There is a need to establish standards to normalize the data and enable cross-sample comparisons. In spite of these limitations, the multiplex technologies are extremely valuable discovery tools and can provide novel insights into the biology of cancer and mechanisms of drug resistance.

Surface-assisted laser desorption/ionization mass spectrometry imaging: A review

In the last decades, surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) has attracted increasing interest due to its unique capabilities, achievable through the nanostructured substrates used to promote the analyte desorption/ionization. While the most widely recognized asset of SALDI-MS is the untargeted analysis of small molecules, this technique also offers the possibility of targeted approaches. In particular, the implementation of SALDI-MS imaging (SALDI-MSI), which is the focus of this review, opens up new opportunities. After a brief discussion of the nomenclature and the fundamental mechanisms associated with this technique, which are still highly controversial, the analytical strategies to perform SALDI-MSI are extensively discussed. Emphasis is placed on the sample preparation but also on the selection of the nanosubstrate (in terms of chemical composition and morphology) as well as its functionalization possibilities for the selective analysis of specific compounds in targeted approaches. Subsequently, some selected applications of SALDI-MSI in various fields (i.e., biomedical, biological, environmental, and forensic) are presented. The strengths and the remaining limitations of SALDI-MSI are finally summarized in the conclusion and some perspectives of this technique, which has a bright future, are proposed in this section.

Sphingolipids control dermal fibroblast heterogeneity

Human cells produce thousands of lipids that change during cell differentiation and can vary across individual cells of the same type. However, we are only starting to characterize the function of these cell-to-cell differences in lipid composition. Here, we measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging with single-cell transcriptomics. We found that the cell-to-cell variations of specific lipid metabolic pathways contribute to the establishment of cell states involved in the organization of skin architecture. Sphingolipid composition is shown to define fibroblast subpopulations, with sphingolipid metabolic rewiring driving cell-state transitions. Therefore, cell-to-cell lipid heterogeneity affects the determination of cell states, adding a new regulatory component to the self-organization of multicellular systems.

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues

Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues.

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tissues can be performed by histological examination, which is still time-consuming and restricted to target-specific staining methods. The histological approaches can be complemented with chemical imaging analysis. Chemical imaging of tissue sections is typically performed using a single imaging approach. However, for toxicological testing of environmental pollutants, a multimodal approach combined with improved data acquisition and evaluation is desirable, since it may allow for more rapid tissue characterization and give further information on ecotoxicological effects at the tissue level. Therefore, using the soil model organism Eisenia fetida as a model, we developed a sequential workflow combining Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) for chemical analysis of the same tissue sections. Data analysis of the FTIR spectra via random decision forest (RDF) classification enabled the rapid identification of target tissues (e.g., digestive tissue), which are relevant from an ecotoxicological point of view. MALDI imaging analysis provided specific lipid species which are sensitive to metabolic changes and environmental stressors. Taken together, our approach provides a fast and reproducible workflow for label-free histochemical tissue analyses in E. fetida, which can be applied to other model organisms as well.

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

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

Quantitation of amiodarone and N-desethylamiodarone in single HepG2 cells by single-cell printing-liquid vortex capture-mass spectrometry

Quantitative measure of a drug and its associated metabolite(s) with single-cell resolution is often limited by sampling throughput or other compromises that limit broad use. Here, we demonstrate the use of single-cell printing-liquid vortex capture-mass spectrometry (SCP-LVC-MS) to quantitatively measure the intracellular concentrations of amiodarone (AMIO) and its metabolite, N-desethylamiodarone (NDEA), from thousands of single cells across several AMIO incubation concentrations ranging from 0 to 10 μM. Concentrations obtained by SCP-LVC-MS were validated through comparison with average assays and traditional measurement of cells in bulk. Average of SCP-LVC-MS measurements and aggregate vial collection assay the concentrations differed by < 5%. Both AMIO and NDEA had clear log-normal distributions with similar standard deviation of concentrations in the cell population. The mean of both AMIO and NDEA intracellular concentrations were positively correlated with AMIO incubation concentration, increasing from 0.026 to 0.520 and 0.0055 to 0.048 mM for AMIO and NDEA, respectively. The standard deviation of AMIO and NDEA log-normal distribution fits were relatively similar in value across incubation concentrations, 0.15-0.19 log₁₀ (mM), and exhibited a linear trend with respect to each other. The single cell-resolved conversion ratio of AMIO to NDEA increased with decreasing incubation concentration, 7 ± 2%, 18 ± 3%, and 20 ± 7% for 10.0, 1.0, and 0.1 μM AMIO incubation concentrations, respectively. Association with simultaneously measured lipids had several ions with statistically significant difference in intensity but no clear correlations with AMIO intracellular content was observed.

Plug-and-play laser ablation-mass spectrometry for molecular imaging by means of dielectric barrier discharge ionization

The plug-and-play hyphenation of UV-laser ablation (LA) and mass spectrometry is presented, using dielectric barrier discharge ionization (DBDI). The DBDI source employed here is characterized by its unique geometry, being directly mounted onto the inlet capillary of a mass spectrometer. In the literature, this particular kind of DBDI source is also referred to as active capillary plasma ionization. It has been commercialized as soft ionization by chemical reaction in transfer (SICRIT) and will be addressed as DBDI in this study. LA-DBDI-MS was used for the direct, molecule-specific and spatially resolved analysis of various solid samples, such as coffee beans and pain killer tablets without extensive sample preparation. The combination of fast washout UV-laser ablation and the principle of the DBDI source used here allowed for highly efficient soft ionization as well as high spatial resolution down to 10 μm for molecular imaging.

MASS SPECTROMETRY TECHNOLOGIES TO ADVANCE CARE FOR CANCER PATIENTS IN CLINICAL AND INTRAOPERATIVE USE

Developments in mass spectrometry technologies have driven a widespread interest and expanded their use in cancer-related research and clinical applications. In this review, we highlight the developments in mass spectrometry methods and instrumentation applied to direct tissue analysis that have been tailored at enhancing performance in clinical research as well as facilitating translation and implementation of mass spectrometry in clinical settings, with a focus on cancer-related studies. Notable studies demonstrating the capabilities of direct mass spectrometry analysis in biomarker discovery, cancer diagnosis and prognosis, tissue analysis during oncologic surgeries, and other clinically relevant problems that have the potential to substantially advance cancer patient care are discussed. Key challenges that need to be addressed before routine clinical implementation including regulatory efforts are also discussed. Overall, the studies highlighted in this review demonstrate the transformative potential of mass spectrometry technologies to advance clinical research and care for cancer patients. © 2020 Wiley Periodicals, Inc. Mass Spec Rev.

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

Immunotherapies play critical roles in cancer treatment. However, given that only a few patients respond to immune checkpoint blockades and other immunotherapeutic strategies, more novel technologies are needed to decipher the complicated interplay between tumor cells and the components of the tumor immune microenvironment (TIME). Tumor immunomics refers to the integrated study of the TIME using immunogenomics, immunoproteomics, immune-bioinformatics, and other multi-omics data reflecting the immune states of tumors, which has relied on the rapid development of next-generation sequencing. High-throughput genomic and transcriptomic data may be utilized for calculating the abundance of immune cells and predicting tumor antigens, referring to immunogenomics. However, as bulk sequencing represents the average characteristics of a heterogeneous cell population, it fails to distinguish distinct cell subtypes. Single-cell-based technologies enable better dissection of the TIME through precise immune cell subpopulation and spatial architecture investigations. In addition, radiomics and digital pathology-based deep learning models largely contribute to research on cancer immunity. These artificial intelligence technologies have performed well in predicting response to immunotherapy, with profound significance in cancer therapy. In this review, we briefly summarize conventional and state-of-the-art technologies in the field of immunogenomics, single-cell and artificial intelligence, and present prospects for future research.

Mass Spectrometry Imaging of Fibroblasts: Promise and Challenge

INTRODUCTION

Fibroblasts maintain tissue and organ homeostasis through output of extracellular matrix that affects nearby cell signaling within the stroma. Altered fibroblast signaling contributes to many disease states and extracellular matrix secreted by fibroblasts has been used to stratify patient by outcome, recurrence, and therapeutic resistance. Recent advances in imaging mass spectrometry allow access to single cell fibroblasts and their ECM niche within clinically relevant tissue samples.

AREAS COVERED

We review biological and technical challenges as well as new solutions to proteomic access of fibroblast expression within the complex tissue microenvironment. Review topics cover conventional proteomic methods for single fibroblast analysis and current approaches to accessing single fibroblast proteomes by imaging mass spectrometry approaches. Strategies to target and evaluate the single cell stroma proteome on the basis of cell signaling are presented.

EXPERT OPINION

The promise of defining proteomic signatures from fibroblasts and their extracellular matrix niches is the discovery of new disease markers and the ability to refine therapeutic treatments. Several imaging mass spectrometry approaches exist to define the fibroblast in the setting of pathological changes from clinically acquired samples. Continued technology advances are needed to access and understand the stromal proteome and apply testing to the clinic.

Transmission-Mode MALDI Mass Spectrometry Imaging of Single Cells: Optimizing Sample Preparation Protocols

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) makes it possible to simultaneously visualize the spatial distribution of dozens to hundreds of different biomolecules (e.g., phospho- and glycolipids) in tissue sections and in cell cultures. The implementation of novel desorption and (post-)ionization techniques has recently pushed the pixel size of this imaging technique to the low micrometer scale and below and thus to a cellular and potentially sub-cellular level. However, to fully exploit this potential for cell biology and biomedicine, sample preparation becomes highly demanding. Here, we investigated the effect of several key parameters on the quality of the sample preparation and achievable spatial resolution, that include the washing, drying, chemical fixation, and matrix coating steps. The incubation of cells with formalin for about 5 min in combination with isotonic washing and mild drying produced a robust protocol that largely preserved not only cell morphologies, but also the molecular integrities of amine group-containing cell membrane phospholipids (phosphatidylethanolamines and -serines). A disadvantage of the chemical fixation is an increased permeabilization of cell membranes, resulting in leakage of cytosolic compounds. We demonstrate the pros and cons of the protocols with four model cell lines, cultured directly on indium tin oxide (ITO)-coated glass slides. Transmission (t-)mode MALDI-2-MSI enabled on a Q Exactive plus Orbitrap mass spectrometer was used to analyze the cultures at a pixel size of 2 μm. Phase contrast light microscopy and scanning electron microscopy were used as complementary methods. The protocols described could prove to be an important contribution to the advancement of single-cell MALDI imaging, especially for the characterization of cell-to-cell heterogeneities at a molecular level.

Mass spectrometry-based phospholipid imaging: methods and findings

Introduction: Imaging is a technique used for direct visualization of the internal structure or distribution of biomolecules of a living system in a two-dimensional or three-dimensional fashion. Phospholipids are important structural components of biological membranes and have been reported to be associated with various human diseases. Therefore, the visualization of phospholipids is crucial to understand the underlying mechanism of cellular and molecular processes in normal and diseased conditions. Areas covered: Mass spectrometry imaging (MSI) has enabled the label-free imaging of individual phospholipids in biological tissues and cells. The commonly used MSI techniques include matrix-assisted laser desorption ionization-MSI (MALDI-MSI), desorption electrospray ionization-MSI (DESI-MSI), and secondary ion mass spectrometry (SIMS) imaging. This special report described those methods, summarized the findings, and discussed the future development for the imaging of phospholipids. Expert opinion: Phospholipids imaging in complex biological samples has been significantly benefited from the development of MSI methods. In MALDI-MSI, novel matrix that produces homogenous crystals exclusively with polar lipids is important for phospholipids imaging with greater efficiency and higher spatial resolution. DESI-MSI has the potential of live imaging of the biological surface while SIMS is expected to image at the subcellular level in the near future.

Lipidomic profiling of single mammalian cells by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

To better understand cell-to-cell heterogeneity, advanced analytical tools are in a growing demand for elucidating chemical compositions of each cell within a population. However, the progress of single-cell chemical analysis has been restrained by the limitations of small cell volumes and minute cellular concentrations. Here, we present a rapid and sensitive method for investigating the lipid profiles of isolated single cells using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS). In this work, HeLa cells were dispersed onto a glass slide, and the cellular contents were ionized by IR-MALDESI and measured using a Q-Exactive HF-X mass spectrometer. Importantly, this approach does not require extraction and/or enrichment of analytes prior to MS analysis. Using this approach, 45 distinct lipid species, predominantly phospholipids, were detected and putatively annotated from the single HeLa cells. The proof-of-concept study demonstrates the feasibility and efficacy of IR-MALDESI-MS for rapid lipidomic profiling of single cells, which provides an important basis for future work on differentiation between normal and diseased cells at various developmental states, which can offer new insights into cellular metabolic pathways and pathological processes. Although not yet accomplished, we believe this approach can be readily used as an assessment tool to compare the number of identified species during source evolution and method optimization (intra-laboratory), and also disclose the complementary nature of different direct analytical approaches for the coverage of different types of endogenous analytes (inter-laboratory).Graphical abstract.

Cell-Type-Specific Metabolic Profiling Achieved by Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Immunofluorescence Staining

Cell-type-specific metabolic profiling in tissue with heterogeneous composition has been of great interest across all mass spectrometry imaging (MSI) technologies. We report here a powerful new chemical imaging capability in desorption electrospray ionization (DESI) MSI, which enables cell-type-specific and in situ metabolic profiling in complex tissue samples. We accomplish this by combining DESI-MSI with immunofluorescence staining using specific cell-type markers. We take advantage of the variable frequency of each distinct cell type in the lateral septal nucleus (LSN) region of mouse forebrain. This allows computational deconvolution of the cell-type-specific metabolic profile in neurons and astrocytes by convex optimization-a machine learning method. Based on our approach, we observed 107 metabolites that show different distributions and intensities between astrocytes and neurons. We subsequently identified 23 metabolites using high-resolution mass spectrometry (MS) and tandem MS, which include small metabolites such as adenosine and N-acetylaspartate previously associated with astrocytes and neurons, respectively, as well as accumulation of several phospholipid species in neurons which have not been studied before. Overall, this method overcomes the relatively low spatial resolution of DESI-MSI and provides a new platform for in situ metabolic investigation at the cell-type level in complex tissue samples with heterogeneous cell-type composition.

Genomic Cytometry and New Modalities for Deep Single-Cell Interrogation

In the past few years, the rapid development of single-cell analysis techniques has allowed for increasingly in-depth analysis of DNA, RNA, protein, and epigenetic states, at the level of the individual cell. This unprecedented characterization ability has been enabled through the combination of cytometry, microfluidics, genomics, and informatics. Although traditionally discrete, when properly integrated, these fields create the synergistic field of Genomic Cytometry. In this review, we look at the individual methods that together gave rise to the broad field of Genomic Cytometry. We further outline the basic concepts that drive the field and provide a framework to understand this increasingly complex, technology-intensive space. Thus, we introduce Genomic Cytometry as an emerging field and propose that synergistic rationalization of disparate modalities of cytometry, microfluidics, genomics, and informatics under one banner will enable massive leaps forward in the understanding of complex biology. © 2020 International Society for Advancement of Cytometry.

Improving spatial resolution of a LTQ Orbitrap MALDI source

Here we present a simple and cost effective procedure to improve the spatial resolution of the commercial MALDI source of a LTQ Orbitrap. Based in spatial filtering techniques, we demonstrate that, with minimal modifications of the original set up, the system resolution can be pushed forward to <10 μm. The improved system performance is demonstrated by means of MALDI imaging of human colon biopsies.

Preparation of Frozen Sections of Multicellular Tumor Spheroids Coated with Ice for Mass Spectrometry Imaging

Increasing studies have utilized mass spectrometry imaging (MSI) that is a label-free tool to investigate drug penetration and drug biotransformation in multicellular tumor spheroids (MCTS). Currently, the gelatin-assisted sectioning method is widely used to prepare frozen sections of MCTS for MSI. However, owing to the limited transparency of frozen gelatin, MCTS with diameters less than 500 μm that closely mimic solid tumors are difficult to be detected when cryosectioning. In order to identify the presence of MCTS, hematoxylin and eosin staining for frozen sections and dye pretreatment for MCTS were employed in previous works, which either increased the analytical time and cost in sample preparation or caused signal suppression in sample analysis. Herein, a new sectioning method was developed to prepare MCTS frozen sections. MCTS was coated with ice to ensure good visibility for small-size MCTS. The optimal cutting temperature compound was added around the ice block to assist the formation of frozen sections. A precast frozen mold was prepared to allow the acquisition of complete MCTS frozen sections. The developed method was applied to investigate lipid distribution in MCTS by using matrix-assisted laser desorption/ionization MSI. Compared to the gelatin-assisted sectioning method, our method did not cause signal suppression and analyte delocalization. Thus, this method provides an easy, universal, and innovative strategy to prepare MCTS frozen sections for further MSI analysis. Besides, we applied our method to investigate the penetration of bisphenol A in MCTS.

Discovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry

Identifying the spatial distributions of biomolecules in tissue is crucial for understanding integrated function. Imaging mass spectrometry (IMS) allows simultaneous mapping of thousands of biosynthetic products such as lipids but has needed a means of identifying specific cell-types or functional states to correlate with molecular localization. We report, here, advances starting from identity marking with a genetically encoded fluorophore. The fluorescence emission data were integrated with IMS data through multimodal image processing with advanced registration techniques and data-driven image fusion. In an unbiased analysis of spleens, this integrated technology enabled identification of ether lipid species preferentially enriched in germinal centers. We propose that this use of genetic marking for microanatomical regions of interest can be paired with molecular information from IMS for any tissue, cell-type, or activity state for which fluorescence is driven by a gene-tracking allele and ultimately with outputs of other means of spatial mapping.

Metal-Labeled Aptamers as Novel Nanoprobes for Imaging Mass Cytometry Analysis

Imaging mass cytometry (IMC) is an emerging imaging technology that exploits the multiplexed analysis capabilities of the CyTOF mass cytometer to make spatially resolved measurements for tissue sections. In a comprehensive view of tissue composition and marker distribution, recent developments of IMC require highly sensitive, multiplexed assays. Approaching the sensitivity of the IMC technique, we designed a novel type of biocompatible metal-labeled aptamer nanoprobe (MAP), named ¹⁶⁷Er-A10-3.2. The small molecular probe was synthesized by conjugating ¹⁶⁷Er-polymeric pentetic acid (¹⁶⁷Er-DTPA) with an RNA aptamer A10-3.2. For demonstration, ¹⁶⁷Er-A10-3.2 was applied for observing protein spatial distribution on prostatic epithelium cell of paraffin embedded Prostatic adenocarcinoma (PaC) tissue sections by IMC technology. The ¹⁶⁷Er-A10-3.2 capitalizes on the ability of the aptamer to specifically bind target cancer cells as well as the small size of ¹⁶⁷Er-A10-3.2 can accommodate multiple aptamer binding antigen labeled at high density. The detection signal of ¹⁶⁷Er-A10-3.2 probe was 3-fold higher than that of PSMA antibody probe for a targeted cell under lower temperature epitope retrieval (37 °C) of PaC tissue. Furthermore, we successfully demonstrated the simultaneously staining ability of aptamer probes in IMC analysis. The successful imaging acquisition using aptamers probes in IMC technology may offer opportunity for the diagnosis of malignancies in the future.

Development of a relative quantification method for infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging of Arabidopsis seedlings

RATIONALE

Mass spectrometry imaging of young seedlings is an invaluable tool in understanding how mutations affect metabolite accumulation in plant development. However, due to numerous biological considerations, established methods for the relative quantification of analytes using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging are not viable options. In this study, we report a method for the quantification of auxin-related compounds using stable-isotope-labelled (SIL) indole-3-acetic acid (IAA) doped into agarose substrate.

METHODS

Wild-type Arabidopsis thaliana seedlings, sur2 and wei8 tar2 loss-of-function mutants, and YUC1 gain-of-function line were grown for 3 days in the dark in standard growth medium. SIL-IAA was doped into a 1% low-melting-point agarose gel and seedlings were gently laid on top for IR-MALDESI imaging with Orbitrap mass spectrometry analysis. Relative quantification was performed post-acquisition by normalization of auxin-related compounds to SIL-IAA in the agarose. Amounts of auxin-related compounds were compared between genotypes to distinguish the effects of the mutations on the accumulation of indolic metabolites of interest.

RESULTS

IAA added to agarose was found to remain stable, with repeatability and abundance features of IAA comparable with those of other compounds used in other methods for relative quantification in IR-MALDESI analyses. Indole-3-acetaldoxime was increased in sur2 mutants compared with wild-type and other mutants. Other auxin-related metabolites were either below the limits of quantification or successfully quantified but showing little difference among mutants.

CONCLUSIONS

Agarose was shown to be an appropriate sampling surface for IR-MALDESI mass spectrometry imaging of Arabidopsis seedlings. SIL-IAA doping of agarose was demonstrated as a viable technique for relative quantification of metabolites in live seedlings or tissues with similar biological considerations.

Influence of Lipid Fragmentation in the Data Analysis of Imaging Mass Spectrometry Experiments

Imaging mass spectrometry (IMS) is becoming an essential technique in lipidomics. Still, many questions remain open, precluding it from achieving its full potential. Among them, identification of species directly from the tissue is of paramount importance. However, it is not an easy task, due to the abundance and variety of lipid species, their numerous fragmentation pathways, and the formation of a significant number of adducts, both with the matrix and with the cations present in the tissue. Here, we explore the fragmentation pathways of 17 lipid classes, demonstrating that in-source fragmentation hampers identification of some lipid species. Then, we analyze what type of adducts each class is more prone to form. Finally, we use that information together with data from on-tissue MS/MS and MS³ to refine the peak assignment in a real experiment over sections of human nevi, to demonstrate that statistical analysis of the data is significantly more robust if unwanted peaks due to fragmentation, matrix, and other species that only introduce noise in the analysis are excluded.

Identification to species level of live single microalgal cells from plankton samples with matrix-free laser/desorption ionization mass spectrometry

INTRODUCTION

Marine planktonic communities are complex microbial consortia often dominated by microscopic algae. The taxonomic identification of individual phytoplankton cells usually relies on their morphology and demands expert knowledge. Recently, a live single-cell mass spectrometry (LSC-MS) pipeline was developed to generate metabolic profiles of microalgae.

OBJECTIVE

Taxonomic identification of diverse microalgal single cells from collection strains and plankton samples based on the metabolic fingerprints analyzed with matrix-free laser desorption/ionization high-resolution mass spectrometry.

METHODS

Matrix-free atmospheric pressure laser-desorption ionization mass spectrometry was performed to acquire single-cell mass spectra from collection strains and prior identified environmental isolates. The computational identification of microalgal species was performed by spectral pattern matching (SPM). Three similarity scores and a bootstrap-derived confidence score were evaluated in terms of their classification performance. The effects of high and low-mass resolutions on the classification success were evaluated.

RESULTS

Several hundred single-cell mass spectra from nine genera and nine species of marine microalgae were obtained. SPM enabled the identification of single cells at the genus and species level with high accuracies. The receiver operating characteristic (ROC) curves indicated a good performance of the similarity measures but were outperformed by the bootstrap-derived confidence scores.

CONCLUSION

This is the first study to solve taxonomic identification of microalgae based on the metabolic fingerprints of the individual cell using an SPM approach.

Single-Probe Mass Spectrometry Analysis of Metabolites in Single Cells

Mass spectrometry (MS) is an indispensable analytical technique for bioanalysis. Based on the measurement of mass/charge ratios (m/z) of ions, MS can be used for sensitive detection and accurate identification of species of interest. In traditional studies, MS is utilized to measure analytes in prepared solutions or gas-phase samples. Benefited from recent development of sampling and ionization approaches, MS has been extensively applied to the analysis of broad ranges of biological samples. We have developed a new device, the Single-probe, that can be used for in situ, real-time MS analysis of metabolites inside individual living cells. The Single-probe is a miniaturized multifunctional sampling and ionization device that is directly coupled to the mass spectrometer. With a sampling tip size smaller than 10 μm, we can insert the Single-probe tip into single cells to extract intracellular compounds, which are analyzed using MS in real-time. We have successfully used the Single-probe MS technique to detect a variety of endogenous and exogenous cellular metabolites in individual eukaryotic cells. Single cell mass spectrometry (SCMS) is a new scientific technology that has the potential to reshape approaches in biological and pharmaceutical bioanalytical research.

Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics

The metabolic network is the endpoint in the flow of information that begins with the "gene" and ends with "phenotype" (observable function) of the cell. Previously, due to the variety of metabolites analyzed inside cells, the metabolomic measurements were performed with samples including multiple cells. Unfortunately, this sampling process may mask important metabolic phenomena, such as cell-to-cell heterogeneity. For these studies, we must use analytical techniques that can robustly deliver reproducible results with single-cell sensitivity. In this chapter, we summarize laser-based methods for single-cell analysis and a novel approach of MicroArrays for Mass Spectrometry (or MAMS) is described in full detail. This particular type of microarrays was tailored for the study of cells grown in liquid medium using multiple-analytical read-outs, such as optical and laser desorption/ionization (LDI) or MALDI mass spectrometry.

Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics

We conducted single cell metabolomics studies of live cancer cells through online single cell mass spectrometry (SCMS) experiments combined with a generalized comprehensive data analysis workflow. The SCMS experiments were carried out using the Single-probe device coupled with a mass spectrometer to measure molecular profiles of cells in response to two mitotic inhibitors, taxol and vinblastine, under a series of treatment conditions. SCMS metabolomic data were analyzed using a comprehensive approach, including data pre-treatment, visualization, statistical analysis, machine learning, and pathway enrichment analysis. For comparative studies, traditional liquid chromatography-MS (LC-MS) experiments were conducted using lysates prepared from bulk cell samples. Metabolomic profiles of single cells were visualized through Partial Least Square-Discriminant Analysis (PLS-DA), and the phenotypic biomarkers associated with emerging phenotypes induced by drug treatment were discovered and compared through a series of rigorous statistical analysis. Species of interest were further identified at both the single cell and population levels. In addition, four biological pathways potentially involved in the drug treatment were determined through pathway enrichment analysis. Our work demonstrated the capability of comprehensive pipeline studies of single cell metabolomics. This method can be potentially applied to broader types of SCMS datasets for future pharmaceutical and chemotherapeutic research.

Imaging Mass Spectrometry: A New Tool to Assess Molecular Underpinnings of Neurodegeneration

Neurodegenerative diseases are prevalent and devastating. While extensive research has been done over the past decades, we are still far from comprehensively understanding what causes neurodegeneration and how we can prevent it or reverse it. Recently, systems biology approaches have led to a holistic examination of the interactions between genome, metabolome, and the environment, in order to shed new light on neurodegenerative pathogenesis. One of the new technologies that has emerged to facilitate such studies is imaging mass spectrometry (IMS). With its ability to map a wide range of small molecules with high spatial resolution, coupled with the ability to quantify them at once, without the need for a priori labeling, IMS has taken center stage in current research efforts in elucidating the role of the metabolome in driving neurodegeneration. IMS has already proven to be effective in investigating the lipidome and the proteome of various neurodegenerative diseases, such as Alzheimer's, Parkinson's, Huntington's, multiple sclerosis, and amyotrophic lateral sclerosis. Here, we review the IMS platform for capturing biological snapshots of the metabolic state to shed more light on the molecular mechanisms of the diseased brain.