Cellular and Subcellular Level Localization of Maize Lipids and Metabolites Using High-Spatial Resolution MALDI Mass Spectrometry Imaging.

Recent technological advances have pushed the achievable spatial resolution for mass spectrometry imaging (MSI) to cellular and subcellular levels. Direct visualization of maize tissues by this tool has provided key insights into the localization of metabolites and lipids. This chapter outlines methodology for sample preparation, data acquisition, and data analysis of maize tissue sections using high-spatial resolution matrix-assisted laser desorption ionization (MALDI)-MSI, as well as the incorporation of a multi-resolution optical system, which allows for simple inter-conversion between different resolution setups (5, 10, and 50 µm imaging).

Spatial Mapping and Profiling of Metabolite Distributions during Germination.

Germination is a highly complex process by which seeds begin to develop and establish themselves as viable organisms. In this study, we utilize a combination of gas chromatography-mass spectrometry, liquid chromatography-fluorescence, and mass spectrometry imaging approaches to profile and visualize the metabolic distributions of germinating seeds from two different inbreds of maize (Zea mays) seeds, B73 and Mo17. Gas chromatography and liquid chromatography analyses demonstrate that the two inbreds are highly differentiated in their metabolite profiles throughout the course of germination, especially with regard to amino acids, sugar alcohols, and small organic acids. Crude dissection of the seed followed by gas chromatography-mass spectrometry analysis of polar metabolites also revealed that many compounds were highly sequestered among the various seed tissue types. To further localize compounds, matrix-assisted laser desorption/ionization mass spectrometry imaging was utilized to visualize compounds in fine detail in their native environments over the course of germination. Most notably, the fatty acyl chain-dependent differential localization of phospholipids and triacylglycerols was observed within the embryo and radicle, showing correlation with the heterogeneous distribution of fatty acids. Other interesting observations include unusual localization of ceramides on the endosperm/scutellum boundary and subcellular localization of ferulate in the aleurone.

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System.

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. In this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 µm practical laser spot size to a practical laser spot size of ~4 µm, thereby allowing for 5 µm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging of the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 µm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 µm and compared the differences in imaging quality and signal sensitivity. We also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders. Graphical Abstract ᅟ.

Multi-matrix, dual polarity, tandem mass spectrometry imaging strategy applied to a germinated maize seed: toward mass spectrometry imaging of an untargeted metabolome.

Mass spectrometry imaging (MSI) provides high spatial resolution information that is unprecedented in traditional metabolomics analyses; however, the molecular coverage is often limited to a handful of compounds and is insufficient to understand overall metabolomic changes of a biological system. Here, we propose an MSI methodology to increase the diversity of chemical compounds that can be imaged and identified, in order to eventually perform untargeted metabolomic analysis using MSI. In this approach, we use the desorption/ionization bias of various matrixes for different metabolite classes along with dual polarities and a tandem MSI strategy. The use of multiple matrixes and dual polarities allows us to visualize various classes of compounds, while data-dependent MS/MS spectra acquired in the same MSI scans allow us to identify the compounds directly on the tissue. In a proof of concept application to a germinated corn seed, a total of 166 unique ions were determined to have high-quality MS/MS spectra, without counting structural isomers, of which 52 were identified as unique compounds. According to an estimation based on precursor MSI datasets, we expect over five hundred metabolites could be potentially identified and visualized once all experimental conditions are optimized and an MS/MS library is available. Lastly, metabolites involved in the glycolysis pathway and tricarboxylic acid cycle were imaged to demonstrate the potential of this technology to better understand metabolic biology.

Multiplex MALDI-MS imaging of plant metabolites using a hybrid MS system.

Plant tissues present intriguing systems for study by mass spectrometry imaging, as they exhibit a complex metabolism and a high degree of spatial localization. This chapter presents a methodology for preparation of plant tissue sections for matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) analysis and the use of a hybrid mass spectrometer for "multiplex" imaging. The multiplex method described here provides a wide range of analytical information, including high-resolution, accurate mass imaging and tandem MS scans for structural information, all within a single experiment. While this procedure was developed for plant tissues, it can be readily adapted for analysis of other sample types.