Michler's ethylketone as a novel negative-ion matrix for the enhancement of lipid MALDI tissue imaging

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.

Nitro Indole Derivatives as Novel Dual-Polarity Matrices for MALDI Mass Spectrometry and Imaging with Broad Applications

A new matrix framework is presented in this study for the improved ionization efficiency of complex mixtures by matrix-assisted laser desorption ionization (MALDI) mass spectrometry/imaging. Five nitro indole (NI) derivatives [3-methyl-4-nitro-1H-indole (3,4-MNI), 3-methyl-6-nitro-1H-indole (3,6-MNI), 2,3-dimethyl-4-nitro-1H-indole (2,3,4-DMNI), 2,3-dimethyl-6-nitro-1H-indole (2,3,6-DMNI), and 4-nitro-1H-indole (4-NI)] were synthesized and shown to produce both positive and negative ions with a broad class of analytes as MALDI matrices. NI matrices were compared to several common matrices, such as 2,5-dihydroxybenzoic acid (DHB), alpha-cyano-4-hydroxylcinnamic acid (CHCA), sinapinic acid (SA), 1,5-diaminonaphthelene (1,5-DAN), and 9-aminoacridine (9-AA), for the analysis of lipid, peptide, protein, glycan, and perfluorooctanesulfonic acid (PFOS) compounds. 3,4-MNI demonstrated the best performance among the NI matrices. This matrix resulted in reduced ion suppression and better detection sensitivity for complex mixtures, for example, egg lipids/milk proteins/PFOS in tap water, while 2,3,6-DMNI was the best matrix for blueberry tissue imaging. Several important aspects of this work are reported: (1) dual-polarity ion production with NI matrices and complex mixtures; (2) quantitative analysis of PFOS with a LOQ of 0.5 ppb in tap water and 0.05 ppb in MQ water (without solid phase extraction enrichment), with accuracy and precision within 5%; (3) MALDI imaging with 2,3,6-DMNI as a matrix for plant metabolite/lipid identification with ionization enhancement in the negative ion mode m/z 600-900 region; and (4) development of a thin film deposition under/above tissue method for MALDI imaging with a vacuum sublimation matrix on a high-vacuum MALDI instrument.

2,5-Dihydroxyterephthalic Acid: A Matrix for Improved Detection and Imaging of Amino Acids

Amino acids (AAs), which are low-molecular-weight (low-MW) metabolites, serve as essential building blocks not only for protein synthesis but also for maintaining the nitrogen balance in living systems. In situ detection and imaging of AAs are crucial for understanding more complex biological processes. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a label-free mass spectrometric imaging technique that enables the simultaneous detection and imaging of the spatial distribution and relative abundance of different endogenous/exogenous compounds in biological samples. The excellent efficiency of MALDI-MSI is attributed to the choice of the MALDI matrix. However, to the best of our knowledge, no matrix has been specifically developed for AAs. Herein, we report a MALDI matrix, 2,5-dihydroxyterephthalic acid (DHT), which can improve the detection and imaging of AAs in biological samples by MALDI-MS. Our results indicated that DHT exhibited strong ultraviolet-visible (UV-vis) absorption, uniform matrix deposition, and high vacuum stability. Moreover, the matrix-related ion signals produced from DHT were reduced by 50 and 71.8% at m/z < 500 compared to the commonly used matrices of 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA), respectively, in their respective organic solvents. In terms of quantitative performance, arginine, glutamic acid, glutamine, and proline can be detected with limits of detection of 6, 4, 6, and 4 ng/mL, respectively, using the DHT as the matrix. Using DHT as the matrix, all 20 protein AAs were successfully detected in human serum by MALDI-MS, whereas only 7 and 10 AAs were detected when DHB and CHCA matrices were used, respectively. Furthermore, 20 protein AAs and taurine were successfully detected and imaged in a section of edible Crassostrea gigas (oyster) tissue for the first time. Our study demonstrates that using DHT as a matrix can improve the detection and imaging of AAs in biological samples by MALDI-MS.

Desorption electrospray ionization and matrix-assisted laser desorption/ionization as imaging approaches for biological samples analysis

The imaging of biological tissues can offer valuable information about the sample composition, which improves the understanding of analyte distribution in such complex samples. Different approaches using mass spectrometry imaging (MSI), also known as imaging mass spectrometry (IMS), enabled the visualization of the distribution of numerous metabolites, drugs, lipids, and glycans in biological samples. The high sensitivity and multiple analyte evaluation/visualization in a single sample provided by MSI methods lead to various advantages and overcome drawbacks of classical microscopy techniques. In this context, the application of MSI methods, such as desorption electrospray ionization-MSI (DESI-MSI) and matrix-assisted laser desorption/ionization-MSI (MALDI-MSI), has significantly contributed to this field. This review discusses the evaluation of exogenous and endogenous molecules in biological samples using DESI and MALDI imaging. It offers rare technical insights not commonly found in the literature (scanning speed and geometric parameters), making it a comprehensive guide for applying these techniques step-by-step. Furthermore, we provide an in-depth discussion of recent research findings on using these methods to study biological tissues.

Polyacrylamide gel as a new embedding medium for the enhancement of metabolite MALDI imaging

In this study, polyacrylamide gel (PAAG) was successfully used as a new embedding medium to provide the more effective maintenance of biological tissues during the sectioning process, enhancing the tissue imaging of metabolites via matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Herein, PAAG, agarose, gelatin, optimal cutting temperature compound (OCT), and ice media were used to embed rat liver and Atlantic salmon (Salmo salar) eyeball samples. These embedded tissues were then sectioned into thin slices and thaw-mounted on conductive microscope glass slides for MALDI-MSI detection to evaluate the embedding effects. The results showed that PAAG embedding has characteristics superior to those of commonly-used embedding media (e.g., agarose, gelatin, OCT, and ice) with the advantages of one-step operation without heating, a better performance of morphology maintenance, the absence of PAAG polymer-ion-related interference below m/z 2000, and the more efficient in situ ionization of metabolites, providing a significant enhancement of both the numbers and intensities of the metabolite ion signals. Our study demonstrates the potential of PAAG embedding as a standard practice for metabolite MALDI tissue imaging, which will lead to an expanded application scope of MALDI-MSI.

Visualizing the distribution of flavonoids in litchi (Litchi chinenis) seeds through matrix-assisted laser desorption/ionization mass spectrometry imaging

Flavonoids are one of the most important bioactive components in litchi (Litchi chinensis Sonn.) seeds and have broad-spectrum antiviral and antitumor activities. Litchi seeds have been shown to inhibit the proliferation of cancer cells and induce apoptosis, particularly effective against breast and liver cancers. Elucidating the distribution of flavonoids is important for understanding their physiological and biochemical functions and facilitating their efficient extraction and utilization. However, the spatial distribution patterns and expression states of flavonoids in litchi seeds remain unclear. Herein, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was used for in situ detection and imaging of the distribution of flavonoids in litchi seed tissue sections for the first time. Fifteen flavonoid ion signals, including liquiritigenin, apigenin, naringenin, luteolin, dihydrokaempferol, daidzein, quercetin, taxifolin, kaempferol, isorhamnetin, myricetin, catechin, quercetin 3-β-d-glucoside, baicalin, and rutin, were successfully detected and imaged in situ through MALDI-MSI in the positive ion mode using 2-mercaptobenzothiazole as a matrix. The results clearly showed the heterogeneous distribution of flavonoids, indicating the potential of litchi seeds for flavonoid compound extraction. MALDI-MS-based multi-imaging enhanced the visualization of spatial distribution and expression states of flavonoids. Thus, apart from improving our understanding of the spatial distribution of flavonoids in litchi seeds, our findings also facilitate the development of MALDI-MSI-based metabolomics as a novel effective molecular imaging tool for evaluating the spatial distribution of endogenous compounds.

Dual-Mechanism-Driven Strategy for High-Coverage Detection of Serum Lipids on a Novel SALDI-MS Target

Serum lipid metabolites have been emerging as ideal biomarkers for disease diagnosis and prediction. In the current stage, nontargeted or targeted lipidomic research mainly relies on a liquid chromatography-mass spectrometry (LC-MS) platform, but future clinical applications need more robust and high-speed platforms. Surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) has shown excellent advantages in the high-speed analysis of lipid metabolites. However, the platform in the positive ion mode is more inclined to target a certain class of lipids, leading to the low coverage of lipid detection and limiting its practical translation to clinical applications. Herein, we proposed a dual-mechanism-driven strategy for high-coverage detection of serum lipids on a novel SALDI-MS target, which is a composite nanostructure comprising vertical silicon nanowires (VSiNWs) decorated with AuNPs and polydopamine (VSiNW-Au-PDA). The performance of laser desorption and ionization on the target can be enhanced by charge-driven desorption coupled with thermal-driven desorption. Simultaneous detection of 236 serum lipids (S/N ≥ 5) including neutral and polar lipids can be achieved in the positive ion mode. Among these, 107 lipid peaks were successfully identified. When combined with VSiNW-Au-PDA and VSiNW chips, 479 lipid peaks can be detected in serum samples in positive and negative ion modes, respectively. Based on the platform, serum samples from 57 hepatocellular carcinoma (HCC) patients and 76 healthy controls were analyzed. After data mining, 14 lipids containing different lipid types (TAG, CE, PC) were selected as potential lipidomic biomarkers. With the assistance of an artificial neural network, a diagnostic model with a sensitivity of 92.7% and a specificity of 96% was constructed for HCC diagnosis.