Three-Dimensional Mass Spectrometry Imaging Reveals Distributions of Lipids and the Drug Metabolite Associated with the Enhanced Growth of Colon Cancer Cell Spheroids Treated with Triclosan

MassLite: An integrated python platform for single cell mass spectrometry metabolomics data pretreatment with graphical user interface and advanced peak alignment method

Mass spectrometry (MS) has been one of the most widely used tools for bioanalytical analysis due to its high sensitivity, capability of quantitative analysis, and compatibility with biomolecules. Among various MS techniques, single cell mass spectrometry (SCMS) is an advanced approach to molecular analysis of cellular contents in individual cells. In tandem with the creation of novel experimental techniques, the development of new SCMS data analysis tools is equally important. As most published software packages are not specifically designed for pretreatment of SCMS data, including peak alignment and background removal, their applicability on processing SCMS data is generally limited. Hereby we introduce a Python platform, MassLite, specifically designed for rapid SCMS metabolomics data pretreatment. This platform is made user-friendly with graphical user interface (GUI) and exports data in the forms of each individual cell for further analysis. A core function of this tool is to use a novel peak alignment method that avoids the intrinsic drawbacks of traditional binning method, allowing for more effective handling of MS data obtained from high resolution mass spectrometers. Other functions, such as void scan filtering, dynamic grouping, and advanced background removal, are also implemented in this tool to improve pretreatment efficiency.

Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows

The landscape of tissue-based imaging modalities is constantly and rapidly evolving. While formalin-fixed, paraffin-embedded material is still useful for histological imaging, the fixation process irreversibly changes the molecular composition of the sample. Therefore, many imaging approaches require fresh-frozen material to get meaningful results. This is particularly true for molecular imaging techniques such as mass spectrometry imaging, which are widely used to probe the spatial arrangement of the tissue metabolome. As high-quality fresh-frozen tissues are limited in their availability, any sample preparation workflow they are subjected to needs to ensure morphological and molecular preservation of the tissues and be compatible with as many of the established and emerging imaging techniques as possible to obtain the maximum possible insights from the tissues. Here we describe a universal sample preparation workflow, from the initial step of freezing the tissues to the cold embedding in a new hydroxypropyl methylcellulose/polyvinylpyrrolidone-enriched hydrogel and the generation of thin tissue sections for analysis. Moreover, we highlight the optimized storage conditions that limit molecular and morphological degradation of the sections. The protocol is compatible with human and plant tissues and can be easily adapted for the preparation of alternative sample formats (e.g., three-dimensional cell cultures). The integrated workflow is universally compatible with histological tissue analysis, mass spectrometry imaging and imaging mass cytometry, as well as spatial proteomic, genomic and transcriptomic tissue analysis. The protocol can be completed within 4 h and requires minimal prior experience in the preparation of tissue samples for multimodal imaging experiments.

Comparative profiling of Chlorella vulgaris cells, extracts, and intact chloroplasts using electron transfer matrix-assisted laser desorption/ionization mass spectrometry (ET-MALDI-MS)

The intricate composition of microalgal pigments plays a crucial role in various biological processes, from photosynthesis to biomarker identification. Traditional pigment analysis methods involve complex extraction techniques, posing challenges in maintaining analyte integrity. In this study, we employ Electron Transfer Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (ET-MALDI-MS) to compare the pigmentary profiles of Chlorella vulgaris intact cells, chloroplasts, and solvent extracts. We aim to obtain comprehensive extracts rich in polar and non-polar compounds using ultrasound-assisted and supercritical fluid extraction methods. Additionally, intact chloroplasts are isolated using a lysis buffer and sucrose density gradient centrifugation. Our ET-MALDI-MS analysis reveals distinct compositional differences, highlighting the impact of extraction protocols on microalgal pigment identification. We observe prominent signals corresponding to radical cations of key pigments, including chlorophylls and carotenoids, which are crucial for C. vulgaris identification. Furthermore, ET-MALDI-MS facilitates the identification of specific lipids within chloroplast membranes and other organelles. This study underscores the rapid and precise nature of ET-MALDI-MS in microalgal biomarker analysis, providing valuable insights into phytoplankton dynamics, trophic levels, and environmental processes. C. vulgaris emerges as a promising model for studying pigment composition and membrane lipid diversity, enhancing our understanding of microalgal ecosystems.

The Utility of Lipidomic Analysis in Colorectal Cancer Diagnosis and Prognosis-A Systematic Review of Recent Literature

Colorectal cancer (CRC) is among the most prevalent and lethal malignancies. Lipidomic investigations have revealed numerous disruptions in lipid profiles across various cancers. Studies on CRC exhibit potential for identifying novel diagnostic or prognostic indicators through lipidomic signatures. This review examines recent literature regarding lipidomic markers for CRC. PubMed database was searched for eligible articles concerning lipidomic biomarkers of CRC. After selection, 36 articles were included in the review. Several studies endeavor to establish sets of lipid biomarkers that demonstrate promising potential to diagnose CRC based on blood samples. Phosphatidylcholine, phosphatidylethanolamine, ceramides, and triacylglycerols (TAGs) appear to offer the highest diagnostic accuracy. In tissues, lysophospholipids, ceramides, and TAGs were among the most altered lipids, while unsaturated fatty acids also emerged as potential biomarkers. In-depth analysis requires both cell culture and animal studies. CRC involves multiple lipid metabolism alterations. Although numerous lipid species have been suggested as potential diagnostic markers, the establishment of standardized methods and the conduct of large-scale studies are necessary to facilitate their clinical application.

Characteristics of lipid metabolism after treatment of colon cancer mice with American ginseng vesicles

INTRODUCTION

Lipid molecules are present in tumours and play an important role in the anti-inflammatory response as well as in antiviral protection. Changes in the type and location of lipids in the intestine following exposure to environmental stressors play an important role in several disorders, including ulcerative colitis (UC), inflammatory bowel disease (IBD), and colorectal cancer.

OBJECTIVES

The aim of this work is to provide a new theoretical basis for tumour initiation and development by accurately measuring the spatial distribution of lipids and metabolites in intestinal tissue. Spatial metabolomics allows the detection of samples with minimal sample volume by label-free imaging of complex samples in their original state. The distribution of lipid molecules in tumours has not been reported, although the distribution of lipid molecules in intestinal tissue has been reported in the literature.

METHODS

The range of lipid profiles in colon cancer mouse tumour tissue was compiled using a spatial metabolomics: lipid extraction method. The changes in lipid distribution in two regions after oral administration of American Ginseng (Panax quinquefolius L.) vesicles were also compared. Tumour tissue samples were extracted with 80% methanol-20% formic acid in water.

RESULTS

The resulting spatial metabolic profile allowed the identification of seven lipid classes in mouse tumours. The distribution of fibre tissue cells was 23.2% higher than tumour tissue cells, with the exception of the fatty acid (FA) species.

[Application of multiomics mass spectrometry in the research of chemical exposome]

Environmental factors, such as environmental pollutants, behaviors, and lifestyles, are the leading causes of chronic noncommunicable diseases. Estimates indicate that approximately 50% of all deaths worldwide can be attributed to environmental factors. The exposome is defined as the totality of human environmental (i.e., all nongenetic) exposures from conception, including general external exposure (e.g., climate, education, and urban environment), specific external exposure (e.g., pollution, physical activity, and diet), and internal exposure (e.g., metabolic factors, oxidative stress, inflammation, and protein modification). As a new paradigm, this concept aims to comprehensively understand the link between human health and environmental factors. Therefore, a comprehensive measurement of the exposome, including accurate and reliable measurements of exposure to the external environment and a wide range of biological responses to the internal environment, is of great significance. The measurement of the general external exposome depends on advances in environmental sensors, personal-sensing technologies, and geographical information systems. The determination of exogenous chemicals to which individuals are exposed and endogenous chemicals that are produced or modified by external stressors relies on improvements in methodology and the development of instrumental approaches, including colorimetric, chromatographic, spectral, and mass-spectrometric methods. This article reviews the research strategies for chemical exposomes and summarizes existing exposome-measurement methods, focusing on mass spectrometry (MS)-based methods. The top-down and bottom-up approaches are commonly used in exposome studies. The bottom-up approach focuses on the identification of chemicals in the external environment (e.g., soil, water, diet, and air), whereas the top-down approach focuses on the evaluation of endogenous chemicals and biological processes in biological samples (e.g., blood, urine, and serum). Low- and high-resolution MS (LRMS and HRMS, respectively) have become the most popular methods for the direct measurement of exogenous and endogenous chemicals owing to their superior sensitivity, specificity, and dynamic range. LRMS has been widely applied in the targeted analysis of expected chemicals, whereas HRMS is a promising technique for the suspect and unknown screening of unexpected chemicals. The development of MS-based multiomics, including proteomics, metabolomics, epigenomics, and spatial omics, provides new opportunities to understand the effects of environmental exposure on human health. Metabolomics involves the sum of all low-molecular-weight metabolites in a living system. Nontargeted metabolomics can measure both endogenous and exogenous chemicals, which would directly link exposure to biological effects, internal dose, and disease pathobiology, whereas proteomics could play an important role in predicting potential adverse health outcomes and uncovering molecular mechanisms. MS imaging (MSI) is an emerging technique that provides unlabeled in-depth measurements of endogenous and exogenous molecules directly from tissue and cell sections without changing their spatial information. MSI-based spatial omics, which has been widely applied in biomarker discovery for clinical diagnosis, as well as drug and pollutant monitoring, is expected to become an effective method for exposome measurement. Integrating these response measurements from metabolomics, proteomics, spatial omics, and epigenomics will enable the generation of new hypotheses to discover the etiology of diseases caused by chemical exposure. Finally, we highlight the major challenges in achieving chemical exposome measurements.

Recent developments and applications of ambient mass spectrometry imaging in pharmaceutical research: an overview

The application of ambient mass spectrometry imaging "MSI" is expanding in the areas of fundamental research on drug delivery and multiple phases of the process of identifying and developing drugs. Precise monitoring of a drug's pharmacological workflows, such as intake, distribution, metabolism, and discharge, is made easier by MSI's ability to determine the concentrations of the initiating drug and its metabolites across dosed samples without losing spatial data. Lipids, glycans, and proteins are just a few of the many phenotypes that MSI may be used to concurrently examine. Each of these substances has a particular distribution pattern and biological function throughout the body. MSI offers the perfect analytical tool for examining a drug's pharmacological features, especially in vitro and in vivo effectiveness, security, probable toxic effects, and putative molecular pathways, because of its high responsiveness in chemical and physical environments. The utilization of MSI in the field of pharmacy has further extended from the traditional tissue examination to the early stages of drug discovery and development, including examining the structure-function connection, high-throughput capabilities in vitro examination, and ex vivo research on individual cells or tumor spheroids. Additionally, an enormous array of endogenous substances that may function as tissue diagnostics can be scanned simultaneously, giving the specimen a highly thorough characterization. Ambient MSI techniques are soft enough to allow for easy examination of the native sample to gather data on exterior chemical compositions. This paper provides a scientific and methodological overview of ambient MSI utilization in research on pharmaceuticals.

Isotope-Coded On-Tissue Derivatization for Quantitative Mass Spectrometry Imaging of Short-Chain Fatty Acids in Biological Tissues

Short-chain fatty acids (SCFAs), as the main metabolites of gut microbiota, are recognized as crucial players in the host's inflammatory response and metabolic disease. Imaging the spatial distributions and calculating the accurate contents of SCFAs in the heterogeneous intestinal tissue are critical to reveal their biological functions. Here, we develop an isotope-coded on-tissue derivatization method combined with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to map the spatial expressions of SCFAs in the colon tissue based on pair-labeled N,N,N-trimethyl-2-(piperazin-1-yl)ethan-1-aminium iodide (TMPA) and D3-TMPA. A noticeable increase in the MALDI-MSI sensitivity of SCFAs was achieved after on-tissue derivatization, which enables the visualization of acetic acid, propionic acid, butyric acid, valeric acid, hexanoic acid, hydroxy acetic acid, and hydroxy propionic acid in the colon tissue. Moreover, the introduction of D3-TMPA-tagged SCFAs as internal standards can significantly reduce quantitation deviation from the matrix effects, ensuring the quantitative MALDI-MSI of SCFAs. We further used this method to characterize the spatial alterations of SCFAs in the colon tissues of mice with enterocolitis. The development of this strategy provides a reliable approach to image the spatial expressions of SCFAs in tissues and paves an insight way to study the roles of SCFAs in the gut microbiota and disease.

Spatially Resolved Metabolomics Combined with the 3D Tumor-Immune Cell Coculture Spheroid Highlights Metabolic Alterations during Antitumor Immune Response

The metabolic cross-talk between tumor and immune cells plays key roles in immune cell function and immune checkpoint blockade therapy. However, the characterization of tumor immunometabolism and its spatiotemporal alterations during immune response in a complex tumor microenvironment is challenging. Here, a 3D tumor-immune cell coculture spheroid model was developed to mimic tumor-immune interactions, combined with mass spectrometry imaging-based spatially resolved metabolomics to visualize tumor immunometabolic alterations during immune response. The inhibition of T cells was simulated by coculturing breast tumor spheroids with Jurkat T cells, and the reactivation of T cells can be monitored through diminishing cancer PD-L1 expressions by berberine. This system enables simultaneously screening and imaging discriminatory metabolites that are altered during T cell-mediated antitumor immune response and characterizing the distributions of berberine and its metabolites in tumor spheroids. We discovered that the transport and catabolism of glutamine were significantly reprogrammed during the antitumor immune response at both metabolite and enzyme levels, corresponding to its indispensable roles in energy metabolism and building new biomass. The combination of spatially resolved metabolomics with the 3D tumor-immune cell coculture spheroid visually reveals metabolic interactions between tumor and immune cells and possibly helps decipher the role of immunometabolic alterations in tumor immunotherapy.

Spatial lipidomics and metabolomics of multicellular tumor spheroids using MALDI-2 and trapped ion mobility imaging

Lipids and metabolites are small biological molecules that act major roles in cellular functions. Multicellular tumor spheroids (MCTS) are a highly beneficial three-dimensional cellular model for cancer research due to their ability to imitate numerous characteristics of tumor tissues. Increasing studies have performed spatial lipidomics and metabolomics in MCTS using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). However, these approaches often lack the sensitivity and specificity to offer a comprehensive characterization of lipids and metabolites within MCTS. In this study, we addressed this challenge by utilizing MALDI combined with laser-induced postionization (MALDI-2) and trapped ion mobility spectrometry (TIMS) imaging in H295R adrenocortical MCTS. Our results showed that MALDI-2 could detect more lipids and metabolites in MCTS than the traditional MALDI. TIMS data revealed a successful separation of many isomeric and isobaric ions of lipids and metabolites with different locations (e.g., proliferative region and necrotic region) within MCTS, suggesting an enhanced peak capacity for spatial lipidomics and metabolomics. To further identify these isomeric and isobaric ions, we performed MS/MS imaging experiments to compare the differences in signal intensities and spatial distributions of product ions. Our data highlight the strong potential of MALDI-2 and TIMS imaging for analyzing lipids and metabolites in MCTS, which may serve as valuable tools for numerous fields of biological and medical research.

Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids

Three-dimensional (3D) cell spheroid models combined with mass spectrometry imaging (MSI) enables innovative investigation of in vivo-like biological processes under different physiological and pathological conditions. Herein, airflow-assisted desorption electrospray ionization-MSI (AFADESI-MSI) was coupled with 3D HepG2 spheroids to assess the metabolism and hepatotoxicity of amiodarone (AMI). High-coverage imaging of >1100 endogenous metabolites in hepatocyte spheroids was achieved using AFADESI-MSI. Following AMI treatment at different times, 15 metabolites of AMI involved in N-desethylation, hydroxylation, deiodination, and desaturation metabolic reactions were identified, and according to their spatiotemporal dynamics features, the metabolic pathways of AMI were proposed. Subsequently, the temporal and spatial changes in metabolic disturbance within spheroids caused by drug exposure were obtained via metabolomic analysis. The main dysregulated metabolic pathways included arachidonic acid and glycerophospholipid metabolism, providing considerable evidence for the mechanism of AMI hepatotoxicity. In addition, a biomarker group of eight fatty acids was selected that provided improved indication of cell viability and could characterize the hepatotoxicity of AMI. The combination of AFADESI-MSI and HepG2 spheroids can simultaneously obtain spatiotemporal information for drugs, drug metabolites, and endogenous metabolites after AMI treatment, providing an effective tool for in vitro drug hepatotoxicity evaluation.