Spermidine and other functional phytochemicals in soybean seeds: Spatial distribution as visualized by mass spectrometry imaging

Revolutionizing food science with mass spectrometry imaging: A comprehensive review of applications and challenges

Food science encounters increasing complexity and challenges, necessitating more efficient, accurate, and sensitive analytical techniques. Mass spectrometry imaging (MSI) emerges as a revolutionary tool, offering more molecular-level insights. This review delves into MSI's applications and challenges in food science. It introduces MSI principles and instruments such as matrix-assisted laser desorption/ionization, desorption electrospray ionization, secondary ion mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry, highlighting their application in chemical composition analysis, variety identification, authenticity assessment, endogenous substance, exogenous contaminant and residue analysis, quality control, and process monitoring in food processing and food storage. Despite its potential, MSI faces hurdles such as the complexity and cost of instrumentation, complexity in sample preparation, limited analytical capabilities, and lack of standardization of MSI for food samples. While MSI has a wide range of applications in food analysis and can provide more comprehensive and accurate analytical results, challenges persist, demanding further research and solutions. The future development directions include miniaturization of imaging devices, high-resolution and high-speed MSI, multiomics and multimodal data fusion, as well as the application of data analysis and artificial intelligence. These findings and conclusions provide valuable references and insights for the field of food science and offer theoretical and methodological support for further research and practice in food science.

Imaging plant metabolism in situ

Mass spectrometry imaging (MSI) has emerged as an invaluable analytical technique for investigating the spatial distribution of molecules within biological systems. In the realm of plant science, MSI is increasingly employed to explore metabolic processes across a wide array of plant tissues, including those in leaves, fruits, stems, roots, and seeds, spanning various plant systems such as model species, staple and energy crops, and medicinal plants. By generating spatial maps of metabolites, MSI has elucidated the distribution patterns of diverse metabolites and phytochemicals, encompassing lipids, carbohydrates, amino acids, organic acids, phenolics, terpenes, alkaloids, vitamins, pigments, and others, thereby providing insights into their metabolic pathways and functional roles. In this review, we present recent MSI studies that demonstrate the advances made in visualizing the plant spatial metabolome. Moreover, we emphasize the technical progress that enhances the identification and interpretation of spatial metabolite maps. Within a mere decade since the inception of plant MSI studies, this robust technology is poised to continue as a vital tool for tackling complex challenges in plant metabolism.

Quantitative Mass Spectrometry Imaging Using Multivariate Curve Resolution and Deep Learning: A Case Study

In the present contribution, a novel approach based on multivariate curve resolution and deep learning (DL) is proposed for quantitative mass spectrometry imaging (MSI) as a potent technique for identifying different compounds and creating their distribution maps in biological tissues without need for sample preparation. As a case study, chlordecone as a carcinogenic pesticide was quantitatively determined in mouse liver using matrix-assisted laser desorption ionization-MSI (MALDI-MSI). For this purpose, data from seven standard spots containing 0 to 20 picomoles of chlordecone and four unknown tissues from the mouse livers infected with chlordecone for 1, 5, and 10 days were analyzed using a convolutional neural network (CNN). To solve the lack of sufficient data for CNN model training, each pixel was considered as a sample, the designed CNN models were trained by pixels in training sets, and their corresponding amounts of chlordecone were obtained by multivariate curve resolution-alternating least-squares (MCR-ALS). The trained models were then externally evaluated using calibration pixels in test sets for 1, 5, and 10 days of exposure, respectively. Prediction R² for all three data sets ranged from 0.93 to 0.96, which was superior to support vector machine (SVM) and partial least-squares (PLS). The trained CNN models were finally used to predict the amount of chlordecone in mouse liver tissues, and their results were compared with MALDI-MSI and GC-MS methods, which were comparable. Inspection of the results confirmed the validity of the proposed method.

Visualizing the Distribution of Lipids in Peanut Seeds by MALDI Mass Spectrometric Imaging

Peanut (also called groundnut, Arachis hypogaea L.) seeds are used for producing edible oils and functional foods, and offer a rich source of lipids, proteins and carbohydrates. However, the location of these metabolites has not yet been firmly established. In the present study, the matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) technique was applied to investigate spatial distribution of lipids and other key components in seeds of three peanut cultivars (ZH9, KQBH, HP). A total of 103 metabolites, including 34 lipid compounds, were putatively identified by MALDI-MSI. The abundance and spatial distribution of glycerolipids (GLs) and glycerophospholipids (GPs) were compared among the three peanut cultivars. All the identified lysophosphatidylcholine (LPC), phosphatidylethanolamine (PE) and phosphatidylcholines (PCs) were distributed mainly in the inner part of seeds. The visualization of phosphatidic acids (PAs) and triacylglycerols (TGs) revealed a dramatic metabolic heterogeneity between the different tissues making up the seed. The non-homogeneous spatial distribution of metabolites appeared to be related to the different functions of particular tissue regions. These results indicated that MALDI-MSI could be useful for investigating the lipids of foodstuffs from a spatial perspective. The present study may contribute to the development of oil crops with higher oil yields, and to improvement of food processing.

A Comprehensive Review of Natural Alternatives for Treatment of Alopecia with an Overview of Market Products

Alopecia or hair loss is a widespread issue that has significant effects on personal well-being for both genders nationally and internationally. In addition, alopecia causes extreme emotional stress and negatively impacts the psychological health and self-esteem of cancer patients suffering from chemotherapy-induced alopecia. Unfortunately, available synthetic medications are costly, invasive, or have extreme adverse effects. On the contrary, natural and herbal hair loss products are widely available in the local and international markets in variable pharmaceutical forms with different mechanisms of action, namely, androgen antagonists, nutritional supplements, vasodilators, and 5α-reductase inhibitors or dihydrotestosterone blockers. Thus, it is of great importance to encourage researchers to investigate these natural alternatives that can act as potent therapeutic agents having diverse mechanisms of action as well as limited side effects. Currently, natural remedies are considered a fast-rising pharmaceutical segment with demand from a wide range of consumers. In this study, we present a review of reported herbal remedies and herb combinations recommended for hair loss and their mode of action, along with an overview of available market products and formulations, their composition, and declared effects. In addition, a general outline of the different forms of alopecia, its causes, and recommended treatments are mentioned as well. This was all done with the aim of assisting further studies with developing standardized natural formulations for alopecia as many were found to lack standardization of their bioactive ingredients and efficiency confirmation.

Spatial lipidomics of eight edible nuts by desorption electrospray ionization with ion mobility mass spectrometry imaging

Nuts have long been known for their health benefits which are mainly contributed by their lipid components. However, the spatial distribution of lipids in nuts has not been firmly established. In this study, desorption electrospray ionization combined with ion mobility and quadrupole time-of-flight mass spectrometry in positive and negative ion modes was applied to visualize spatially the lipids in eight edible nuts, namely almonds, hazelnuts, cashews, walnuts, peanuts, peach seeds, bitter almonds, and Chinese dwarf cherry seeds. The glycerophospholipids were first imaged in nuts in the negative ion mode, while the glycerolipids and phosphatidylcholines were mainly detected in the positive ion mode. In total 87 characterized components, including 47 glycerophospholipids, 24 glycerolipids, eight alkyl phenolic acids, three fatty acid acyl metabolites, four oligosaccharides, and amygdalin, were visualized in the eight nuts, and the collision cross-sectional values of these components were obtained. The outer shell of the nut cotyledon concentrated more abundant components than the center, while for the hydrolyzed glycerophospholipids, the reverse was observed. The results provide a more comprehensive and in-depth understanding of the location of the diverse metabolite profiles in nuts and of their relationship to their respective health benefits.

Advanced applications of mass spectrometry imaging technology in quality control and safety assessments of traditional Chinese medicines

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicines (TCMs) have made great contributions to the prevention and treatment of human diseases in China, and especially in cases of COVID-19. However, due to quality problems, the lack of standards, and the diversity of dosage forms, adverse reactions to TCMs often occur. Moreover, the composition of TCMs makes them extremely challenging to extract and isolate, complicating studies of toxicity mechanisms.

AIM OF THE REVIEW

The aim of this paper is therefore to summarize the advanced applications of mass spectrometry imaging (MSI) technology in the quality control, safety evaluations, and determination of toxicity mechanisms of TCMs.

MATERIALS AND METHODS

Relevant studies from the literature have been collected from scientific databases, such as "PubMed", "Scifinder", "Elsevier", "Google Scholar" using the keywords "MSI", "traditional Chinese medicines", "quality control", "metabolomics", and "mechanism".

RESULTS

MSI is a new analytical imaging technology that can detect and image the metabolic changes of multiple components of TCMs in plants and animals in a high throughput manner. Compared to other chemical analysis methods, such as liquid chromatography-mass spectrometry (LC-MS), this method does not require the complex extraction and separation of TCMs, and is fast, has high sensitivity, is label-free, and can be performed in high-throughput. Combined with chemometrics methods, MSI can be quickly and easily used for quality screening of TCMs. In addition, this technology can be used to further focus on potential biomarkers and explore the therapeutic/toxic mechanisms of TCMs.

CONCLUSIONS

As a new type of analysis method, MSI has unique advantages to metabolic analysis, quality control, and mechanisms of action explorations of TCMs, and contributes to the establishment of quality standards to explore the safety and toxicology of TCMs.

Accumulation and Transformation of Biogenic Amines and Gamma-Aminobutyric Acid (GABA) in Chickpea Sourdough

In general, sourdough fermentation leads to an improvement in the technological, nutritional, and sensory properties of bakery products. The use of non-conventional flours with a specific autochthonous microbiota may lead to the formation of secondary metabolites, which may even have undesirable physiological and toxicological effects. Chickpea flours from different suppliers have been used to produce sourdoughs by spontaneous and inoculated fermentations. The content of nutritionally undesirable biogenic amines (BA) and beneficial gamma-aminobutyric acid (GABA) was determined by chromatography. Fenugreek sprouts, which are a rich source of amine oxidases, were used to reduce the BA content in the sourdoughs. Spontaneous fermentation resulted in a high accumulation of cadaverine, putrescine, and tyramine for certain flours. The use of commercial starter cultures was not effective in reducing the accumulation of BA in all sourdoughs. The addition of fenugreek sprouts to the suspension of sourdough with pH raised to 6.5 resulted in a significant reduction in BA contents. Enzymatic oxidation was less efficient during kneading. Baking resulted in only a partial degradation of BA and GABA in the crust and not in the crumb. Therefore, it could be suggested to give more importance to the control of sourdough fermentation with regard to the formation of nutritionally undesirable BA and to exploit the possibilities of their degradation.

Mass spectrometry imaging for direct visualization of components in plants tissues

Mass spectrometry is considered the most informative technique for components identification and has been widely adopted in plant sciences. However, the spatial distribution of compounds in the plant, which is vital for the exploration of plant physiological mechanisms, is missed in MS analysis. In recent years, mass spectrometry imaging has brought a great breakthrough in plant analysis because it can determine both the molecular compositions and spatial distributions, which is conducive to understand functions and regulation pathways of specific components in plants. Mass spectrometry imaging analysis of plant tissue is toward high sensitivity, high spatial resolution, and even single-cell analysis. Despite many challenges and technical barriers, such as difficulties of sample pretreatment caused by morphological diversity of plant tissues, obstacles for high spatial resolution imaging, and so on, lots of researches have contributed to remarkable progress, including improvement in tissue preparation, matrix innovation, and ionization mode development. This review focuses on the advances of mass spectrometry imaging analysis of plants in the last 5 years, including commonly used ionization techniques, technical advances, and recent applications of mass spectrometry imaging in plants.

MALDI-TOF/TOF tandem mass spectrometry imaging reveals non-uniform distribution of disaccharide isomers in plant tissues

Mass spectrometry imaging (MSI) is a powerful technique for investigating the biomolecular locations within tissues. However, the isomeric compounds are rarely distinguished due to inability of MSI to differentiate isomers in the probing area. Coupling tandem mass spectrometry with MSI can facilitate differentiating isomeric compounds. Here MALDI-TOF/TOF tandem mass spectrometry imaging approach was applied to probing the spatial distributions of isomeric disaccharides in plant tissues. First, MS/MS imaging analysis of disaccharide-matrix droplet spots demonstrated the feasibility of distinguishing isomeric species in tissues, by measuring the relative intensity of specific fragments. Then, tandem MS imaging of disaccharides in onion bulb tissues indicated that sucrose and other unknown non-sucrose disaccharides exhibit heterogeneous locations throughout the tissues. This method enables us to image disaccharide isomers differentially in biological tissues, and to discover new saccharide species in plant. This work also emphasizes the necessity of considering isobaric compounds when interpreting MSI results.

Application of Mass Spectrometry Imaging for Visualizing Food Components

Consuming food is essential for survival, maintaining health, and triggering positive emotions like pleasure. One of the factors that drive us toward such behavior is the presence of various compounds in foods. There are many methods to analyze these molecules in foods; however, it is difficult to analyze the spatial distribution of these compounds using conventional techniques, such as mass spectrometry combined with high-performance liquid chromatography or gas chromatography. Mass spectrometry imaging (MSI) is a two-dimensional ionization technology that enables detection of compounds in tissue sections without extraction, purification, separation, or labeling. There are many methods for ionization of analytes, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization, and desorption electrospray ionization. Such MSI technologies can provide spatial information on the location of a specific analyte in food. The number of studies utilizing MSI technologies in food science has been increasing in the past decade. This review provides an overview of some of the recent applications of MSI in food science and related fields. In the future, MSI will become one of the most promising technologies for visualizing the distribution of food components and for identifying food-related factors by their molecular weights to improve quality, quality assurance, food safety, nutritional analysis, and to locate administered food factors.