A Five-Year Update on Matrix Compounds for MALDI-MS Analysis of Lipids

Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective

Recent advancements in single-cell (sc) resolution analyses, particularly in sc transcriptomics and sc proteomics, have revolutionized our ability to probe and understand cellular heterogeneity. The study of metabolism through small molecules, metabolomics, provides an additional level of information otherwise unattainable by transcriptomics or proteomics by shedding light on the metabolic pathways that translate gene expression into functional outcomes. Metabolic heterogeneity, critical in health and disease, impacts developmental outcomes, disease progression, and treatment responses. However, dedicated approaches probing the sc metabolome have not reached the maturity of other sc omics technologies. Over the past decade, innovations in sc metabolomics have addressed some of the practical limitations, including cell isolation, signal sensitivity, and throughput. To fully exploit their potential in biological research, however, remaining challenges must be thoroughly addressed. Additionally, integrating sc metabolomics with orthogonal sc techniques will be required to validate relevant results and gain systems-level understanding. This perspective offers a broad-stroke overview of recent mass spectrometry (MS)-based sc metabolomics advancements, focusing on ongoing challenges from a biologist's viewpoint, aimed at addressing pertinent and innovative biological questions. Additionally, we emphasize the use of orthogonal approaches and showcase biological systems that these sophisticated methodologies are apt to explore.

Phospholipid-derived lysophospholipids in (patho)physiology

Phospholipids (PL) are major components of cellular membranes and changes in PL metabolism have been associated with the pathogenesis of numerous diseases. Lysophosphatidylcholine (LPC) in particular, is a comparably abundant component of oxidatively damaged tissues. LPC originates from the cleavage of phosphatidylcholine (PC) by phospholipase A2 or the reaction of lipids with reactive oxygen species (ROS) such as HOCl. Another explanation of increased LPC concentration is the decreased re-acylation of LPC into PC. While there are also several other lysophospholipids, LPC is the most abundant lysophospholipid in mammals and will therefore be the focus of this review. LPC is involved in many physiological processes. It induces the migration of lymphocytes, fostering the production of pro-inflammatory compounds by inducing oxidative stress. LPC also "signals" via G protein-coupled and Toll-like receptors and has been implicated in the development of different diseases. However, LPCs are not purely "bad": this is reflected by the fact that the concentration and fatty acyl composition of LPC varies under different conditions, in plasma of healthy and diseased individuals, in tissues and different tumors. Targeting LPC and lipid metabolism and restoring homeostasis might be a potential therapeutic method for inflammation-related diseases.

High-throughput relative quantification of fatty acids by 12-plex isobaric labeling and microchip capillary electrophoresis - Mass spectrometry

BACKGROUND

Fatty acids (FAs) are essential cellular components and play important roles in various biological processes. Importantly, FAs produced by microorganisms from renewable sugars are considered sustainable substrates for biodiesels and oleochemicals. Their complex structures and diverse functional roles in biochemical processes necessitate the development of efficient and accurate methods for their quantitative analysis.

RESULTS

Here, we developed a novel method for relative quantification of FAs by combining 12-plex isobaric N,N-dimethyl leucine-derivatized ethylenediamine (DiLeuEN) labeling and microchip capillary electrophoresis-mass spectrometry (CE-MS). This method enables simultaneous quantification of 12 samples in a single MS analysis. DiLeuEN labeling introduced tertiary amine center structure into FAs, which makes them compatible with the positive mode separation of commercial microchip CE systems and further improves the sensitivity. The CE separation parameters were optimized, and the quantification accuracy was assessed using FA standards. Microchip CE-MS detection exhibited high sensitivity with a femtomole level detection limit and a total analysis time within 8 min. Finally, the applicability of our method to complex biological samples was demonstrated by analyzing FAs produced by four industrially relevant yeast strains (Saccharomyces cerevisiae, Yarrowia lipolytica YB-432, Yarrowia lipolytica Po1f and Rhodotorula glutinis). The analysis time for each sample is less than 1 min.

SIGNIFICANCE

This work addresses the current challenges in the field by introducing a method that combines microchip-based capillary electrophoresis separation with multiplex isobaric labeling. Our method not only offers remarkable sensitivity and rapid analysis speed but also the capability to quantify fatty acids across multiple samples simultaneously, which holds significant potential for extensive application in FA quantitative studies in diverse research areas, promising an enhanced understanding of FA functions and mechanisms.

Mass spectrometry imaging as a promising analytical technique for herbal medicines: an updated review

Herbal medicines (HMs) have long played a pivotal role in preventing and treating various human diseases and have been studied widely. However, the complexities present in HM metabolites and their unclear mechanisms of action have posed significant challenges in the modernization of traditional Chinese medicine (TCM). Over the past two decades, mass spectrometry imaging (MSI) has garnered increasing attention as a robust analytical technique that enables the simultaneous execution of qualitative, quantitative, and localization analyses without complex sample pretreatment. With advances in technical solutions, MSI has been extensively applied in the field of HMs. MSI, a label-free ion imaging technique can comprehensively map the spatial distribution of HM metabolites in plant native tissues, thereby facilitating the effective quality control of HMs. Furthermore, the spatial dimension information of small molecule endogenous metabolites within animal tissues provided by MSI can also serve as a supplement to uncover pharmacological and toxicological mechanisms of HMs. In the review, we provide an overview of the three most common MSI techniques. In addition, representative applications in HM are highlighted. Finally, we discuss the current challenges and propose several potential solutions. We hope that the summary of recent findings will contribute to the application of MSI in exploring metabolites and mechanisms of action of HMs.

Development of benzimidazole derivatives as efficient matrices for the analysis of acidic small-molecule compounds using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry in negative ion mode

RATIONALE

With the development of matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) in spatial localisation omics research on small molecules, the detection sensitivity of the matrix must increase. However, the types of matrices suitable for detecting acidic small molecules in (-) MALDI-MS mode are very limited and are either not sensitive enough or difficult to obtain.

METHODS

More than 10 commercially available benzimidazole and benzothiazole derivatives were selected as MALDI matrices in negative ion mode. MALDI-MS analysis was performed on 38 acidic small molecules and mouse serum, and the matrix effects were compared with those of the common commercial matrices 9-aminoacridine (9AA), 1,5-naphthalenediamine (DAN) and 3-aminoquinoline (3AQ). Moreover, the proton affinity (PA) of the selected potential matrix was calculated, and the relationships among the compound structure, PA value and matrix effect were discussed.

RESULTS

In (-) MALDI-MS mode, a higher PA value generally indicates a better matrix effect. Amino-substituted 2-phenyl-1H-benzo[d]imidazole derivatives had well-defined matrix effects on all analytes and were generally superior to the commonly used matrices 9AA, DAN and 3AQ. Among them, 2-(4-(dimethylamino-phenyl)-1H-benzo[d]imidazole-5-amine (E-4) has the best sensitivity and versatility for detecting different analytes and has the best ability to detect fatty acids in mouse serum; moreover, the limit of detection (LOD) of some analytes can reach as low as ng/L.

CONCLUSIONS

Compared to 9AA, DAN and 3AQ, matrix E-4 is more effective at detecting low-molecular-weight acidic compounds in (-) MALDI-MS mode, with higher sensitivity and better versatility. In addition, there is a clear correlation between compound structure, PA and matrix effects, which provides a basis for designing more efficient matrices.

2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, μm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.

Combining imaging mass spectrometry and immunohistochemistry to analyse the lipidome of spinal cord inflammation

Inflammation is a complex process that accompanies many pathologies. Actually, dysregulation of the inflammatory process is behind many autoimmune diseases. Thus, treatment of such pathologies may benefit from in-depth knowledge of the metabolic changes associated with inflammation. Here, we developed a strategy to characterize the lipid fingerprint of inflammation in a mouse model of spinal cord injury. Using lipid imaging mass spectrometry (LIMS), we scanned spinal cord sections from nine animals injected with lysophosphatidylcholine, a chemical model of demyelination. The lesions were demonstrated to be highly heterogeneous, and therefore, comparison with immunofluorescence experiments carried out in the same section scanned by LIMS was required to accurately identify the morphology of the lesion. Following this protocol, three main areas were defined: the lesion core, the peri-lesion, which is the front of the lesion and is rich in infiltrating cells, and the uninvolved tissue. Segmentation of the LIMS experiments allowed us to isolate the lipid fingerprint of each area in a precise way, as demonstrated by the analysis using classification models. A clear difference in lipid signature was observed between the lesion front and the epicentre, where the damage was maximized. This study is a first step to unravel the changes in the lipidome associated with inflammation in the context of diverse pathologies, such as multiple sclerosis.

Assessment of MALDI matrices for the detection and visualization of phosphatidylinositols and phosphoinositides in mouse kidneys through matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI)

Phosphatidylinositols and their phosphorylated derivatives, known as phosphoinositides, are crucial in cellular processes, with their abnormalities linked to various diseases. Thus, identifying and measuring phosphoinositide levels in tissues are crucial for understanding their contributions to cellular processes and disease development. One powerful technique for mapping the spatial distribution of molecules in biological samples is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). This technique allows for the simultaneous detection and analysis of multiple lipid classes in situ, making it invaluable for unbiased lipidomic studies. However, detecting phosphoinositides with MALDI-MSI is challenging due to their relatively low abundance in tissues and complex matrix effects. Addressing this, our study focused on optimizing matrix selection and thickness for better detection of phosphatidylinositols and their phosphorylated forms in mouse kidney tissues. Various matrices were assessed, including 9AA, DAN, CMBT, and DHA, adjusting their coating to improve ionization efficiency. Our results demonstrate that DAN, DHA, and CMBT matrices produced high-intensity chemical images of phosphatidylinositol distributions within kidney sections. These matrices, particularly DAN, DHA, and CMBT, allowed the identification of even low-abundance phosphoinositides, through tentative identifications. Notably, DAN and DHA served as optimal candidates due to their prominent detection and ability to map a majority of phosphatidylinositol species, while CMBT showed potential detection capability for phosphatidylinositol triphosphate compounds. These findings not only provide valuable insights for future research on the involvement of phosphoinositides in kidney pathophysiology, but also propose the use of the identified optimal matrices, particularly DAN and DHA, as the preferred choices for enhanced detection and mapping of these lipid species in future studies.

Matrix Selection for the Visualization of Small Molecules and Lipids in Brain Tumors Using Untargeted MALDI-TOF Mass Spectrometry Imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging allows for the study of metabolic activity in the tumor microenvironment of brain cancers. The detectable metabolites within these tumors are contingent upon the choice of matrix, deposition technique, and polarity setting. In this study, we compared the performance of three different matrices, two deposition techniques, and the use of positive and negative polarity in two different brain cancer types and across two species. Optimal combinations were confirmed by a comparative analysis of lipid and small-molecule abundance by using liquid chromatography-mass spectrometry and RNA sequencing to assess differential metabolites and enzymes between normal and tumor regions. Our findings indicate that in the tumor-bearing brain, the recrystallized α-cyano-4-hydroxycinnamic acid matrix with positive polarity offered superior performance for both detected metabolites and consistency with other techniques. Beyond these implications for brain cancer, our work establishes a workflow to identify optimal matrices for spatial metabolomics studies.

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.