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Abstract Nanospray desorption electrospray ionization (nano‐DESI) is an ambient ionization mass spectrometry imaging (MSI) approach that enables spatial mapping of biological and environmental samples with high spatial resolution and throughput. Because nano‐DESI has not yet been commercialized, researchers develop their own sources and interface them with different commercial mass spectrometers. Previously, several protocols focusing on the fabrication of nano‐DESI probes have been reported. In this tutorial, we discuss different hardware requirements for coupling the nano‐DESI source to commercial mass spectrometers, such as the safety interlock, inlet extension, and contact closure. In addition, we describe the structure of our custom software for controlling the nano‐DESI MSI platform and provide detailed instructions for its usage. With this tutorial, interested researchers should be able to implement nano‐DESI experiments in their labs. 

Abstract Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high‐spatial resolution and high‐throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation‐driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods. 

Spatial lipidomics is a powerful technique for understanding the complexity of the lipidome in biological systems through mass spectrometry imaging (MSI). Recent advancements have enabled isomer-selected MSI (iMSI) of lipids in biological samples using both online and off-line derivatization strategies. Despite these impressive developments, most iMSI techniques are limited to either positive or negative ion mode analysis, restricting the molecular coverage achievable in a single experiment. Additionally, derivatization efficiency often varies across lipid classes, presenting challenges for comprehensive lipid analysis. In this study, we introduce tetrakis(4-carboxyphenyl)porphyrin (TCPP) as a universal photosensitizer that facilitates online lipid derivatization in both positive and negative ionization modes via singlet oxygen (1O2) reaction. This method enables the identification and localization of both acyl chain compositions and lipid carbon-carbon (C=C) isomers in liquid extraction-based ambient ionization techniques. We have also employed sodium fluoride (NaF) as a solvent dopant to enhance the analysis of low-abundance and poorly ionizable biomolecules. By integrating these online derivatization and signal enhancement strategies with nanospray desorption electrospray ionization (nano-DESI), we achieved dual polarity iMSI within the same sample. We demonstrate imaging of low-abundance isomeric lipids, which were otherwise below the noise level. Notably, TCPP significantly enhances the efficiency of the online derivatization of unsaturated fatty acids, for which other photosensitizers are inefficient. This novel approach allows for the imaging of isomeric fatty acids and phospholipids from multiple classes in the same experiment, revealing their distinct spatial localization within biological tissues. 

Mass spectrometry is a powerful analytical technique used at every stage of the pharmaceutical research process. A specialized subset of this technique, mass spectrometry imaging (MSI) has emerged as an important technique for determining the spatial distribution of drugs in biological samples. Despite the importance of MSI, its quantitative capabilities are still limited due to the complexity of biological samples and the lack of separation prior to analysis. This makes the simultaneous quantification and visualization of analytes challenging. Several techniques have been developed to address this challenge and enable quantitative MSI. One of these techniques is the mimetic tissue model, which involves the incorporation of an analyte of interest into tissue homogenates at several concentrations. A calibration curve that accounts for signal suppression by the complex biological matrix is then created by measuring the signal of the analyte in the series of tissue homogenates. Herein, we use the mimetic tissue model on a triple quadrupole mass spectrometer (QqQ) in multiple reaction monitoring (MRM) mode to demonstrate the quantitative abilities of nanospray desorption electrospray ionization (nano-DESI) and compare these results with those obtained using atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI). For the tested compounds, our findings indicate that nano-DESI achieves lower standard deviations than AP-MALDI which contributes to nano-DESI also achieving lower limits of detection (LOD) for the analytes studied. Additionally, we discuss the limitations of the mimetic tissue model in the quantification of certain analytes and the challenges involved with the implementation of the model. 

Novel laser-assisted etching of a fused silica microfluidic probe for liquid extraction-based ambient mass spectrometry imaging.