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On-tissue chemical derivatization is a valuable tool for expanding compound coverage in untargeted metabolomic studies with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Applying multiple derivatization agents in parallel increases metabolite coverage even further but results in large and more complex datasets that can be challenging to analyze. In this work, we present a pipeline to provide rigorous annotations for on-tissue derivatized MSI data using Metaspace. To test and validate the pipeline, maize roots were used as a model system to obtain MSI datasets after chemical derivatization with four different reagents, Girard's T and P for carbonyl groups, coniferyl aldehyde for primary amines, and 2-picolylamine for carboxylic acids. Using this pipeline helped us annotate 631 unique metabolites from the CornCyc/BraChem database compared to 256 in the underivatized dataset, yet, at the same time, shortening the processing time compared to manual processing and providing robust and systematic scoring and annotation. We have also developed a method to remove false derivatized annotations, which can clean 5-25% of false derivatized annotations from the derivatized data, depending on the reagent. Taken together, our pipeline facilitates the use of broadly targeted spatial metabolomics using multiple derivatization reagents.

Organic light emitting devices (OLEDs), especially in a screen display format, present unique and interesting substrates for laser desorption/ionization-mass spectrometry imaging (LDI-MSI) analysis. These devices contain many compounds that inherently absorb light energy and do not require an additional matrix to induce desorption and ionization. OLED screens have lateral features with dimensions that are tens of microns in magnitude and depth features that are tens to hundreds of nanometers thick. Monitoring the chemical composition of these features is essential, as contamination and degradation can impact device lifetime. This work demonstrates the capability of LDI-MSI to obtain lateral and partial depth resolved information on multicolored OLED displays and suggests the application to other mixed organic electronics with minimal sample preparation. This was realized when analyzing two different manufactured OLEDs, in an active-matrix display format, without the need to remove the cathode. By utilizing low laser energy and high lateral spatial resolution imaging (10 μm), depth profiling can be observed while maintaining laterally resolved information, resulting in a three-dimensional MSI approach that would complement existing OLED characterization methods.

The ability to study and visualize metabolites on a cellular and sub-cellular level is important for gaining insights into biological pathways and metabolism of multicellular organisms. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool for metabolomics experiments due to its high sensitivity and small sampling size. The spatial resolution in MALDI-MSI is mainly limited by the number of molecules available in a small sampling size. When the sampling size is low enough to achieve cellular or subcellular spatial resolution, signal intensity is sacrificed making poorly ionized metabolites difficult to detect. To overcome this limitation, on-tissue chemical derivatization reactions have been used to enhance the desorption/ionization efficiency of selected classes of compounds by adding a functional group with a permanent positive charge or one that can be easily ionized. By utilizing several chemical derivatizations in parallel, metabolite coverage can be drastically improved. This chapter outlines methodology for sample preparation and data analysis for on-tissue chemical derivatization using various derivatization reagents.

Derivatization reactions are commonly used in mass spectrometry to improve analyte signals, specifically by enhancing the ionization efficiency of those compounds. Vicinal diols are one group of biologically important compounds that have been commonly derivatized using boronic acid. In this study, a boronic acid with a tertiary amine was adapted for the derivatization of vicinal diol metabolites in B73 maize tissue cross-sections for mass spectrometry imaging analysis. Using this method, dozens of vicinal diol metabolites were derivatized, effectively improving the signal of those metabolites. Many of these metabolites were tentatively assigned using high-resolution accurate mass measurements. In addition, reaction interference and cross-reactivity with various other functional groups were systematically studied to verify data interpretation.