Multimodal high-resolution nano-DESI MSI and immunofluorescence imaging reveal molecular signatures of skeletal muscle fiber types

Spatial metabolomics platform combining mass spectrometry imaging and in-depth chemical characterization with capillary electrophoresis

Spatial metabolomics offers the combination of molecular identification and localization. As a tool for spatial metabolomics, mass spectrometry imaging (MSI) can provide detailed information on localization. However, molecular annotation with MSI is challenging due to the lack of separation prior to mass spectrometric analysis. Contrarily, surface sampling capillary electrophoresis mass spectrometry (SS-CE-MS) provides detailed molecular information, although the size of the sampling sites is modest. Here, we describe a platform for spatial metabolomics where MSI using pneumatically assisted nanospray desorption electrospray ionization (PA-nano-DESI) is combined with SS-CE-MS to gain both in-depth chemical information and spatial localization from thin tissue sections. We present the workflow, including the user-friendly setup and switching between the techniques, compare the obtained data, and demonstrate a quantitative approach when using the platform for spatial metabolomics of ischemic stroke.

Spatial multi-omics in whole skeletal muscle reveals complex tissue architecture

Myofibers are large multinucleated cells that have long thought to have a rather simple organization. Single-nucleus transcriptomics, spatial transcriptomics and spatial metabolomics analysis have revealed distinct transcription profiles in myonuclei related to myofiber type. However, the use of local tissue collection or dissociation methods have obscured the spatial organization. To elucidate the full tissue architecture, we combine two spatial omics, RNA tomography and mass spectrometry imaging. This enables us to map the spatial transcriptomic, metabolomic and lipidomic organization of the whole murine tibialis anterior muscle. Our findings on heterogeneity in fiber type proportions are validated with multiplexed immunofluorescence staining in tibialis anterior, extensor digitorum longus and soleus. Our results demonstrate unexpectedly strong regionalization of gene expression, metabolic differences and variable myofiber type proportion along the proximal-distal axis. These new insights in whole-tissue level organization reconcile sometimes conflicting results coming from previous studies relying on local sampling methods.

MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data

Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.

Direct Three-Dimensional Mass Spectrometry Imaging with Laser Ablation Remote Atmospheric Pressure Photoionization/Chemical Ionization

The laser ablation remote atmospheric pressure photoionization/chemical ionization (LARAPPI/CI) platform coupled to an ultrahigh resolution quadrupole-time-of-flight (QToF) mass spectrometer was developed and employed for the first direct three-dimensional (3D) mass spectrometry imaging (MSI) of metabolites in human and plant tissues. Our solution for 3D MSI does not require sample modification or cutting into thin slices. Ablation characteristics of an optical system based on a diffraction optical element are studied and used for voxel stacking to directly remove layers of tissues. Agar gel, red radish, kiwi, human kidney cancer, and normal tissue samples were used for the tests of this new system. The 2D and 3D ion images vividly illustrate differences in the abundances of selected metabolites between cancerous and noncancerous regions of the kidney tissue and also between different parts of plant tissues. The LARAPPI/CI MSI setup is also the first example of the successful use of combined dopant-assisted atmospheric pressure photoionization (DA-APPI) and atmospheric pressure chemical ionization (APCI) ion source for mass spectrometry imaging.

Multi-modal mass spectrometry imaging of a single tissue section

Mass spectrometry imaging (MSI) was developed to visualize spatial chemical information within tissues, thereby facilitating spatial multi-omic analysis. However, due to the limited spatial information provided by individual modal MSI, correlating various chemical data within tissues remains a significant challenge. In recent years, multimodal MSI has garnered considerable attention due to its ability to visualize the spatial distributions of multiple biomolecules within tissues. Among the strategies employed in this field, multimodal imaging on a single tissue section circumvents multiple issues introduced by integration of images of consecutive tissue sections. In this minireview, we provide an overview of multimodal MSI on a single tissue section, with a particular focus on the use of Matrix-Assisted Laser Desorption/Ionization-MSI for spatial multi-omic investigations that offer a comprehensive and in-depth elucidation of the biological state and activities, aiming to inspire the development of new approaches in this field.

Hardware and software solutions for implementing nanospray desorption electrospray ionization (nano-DESI) sources on commercial mass spectrometers

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.

AI-assisted mass spectrometry imaging with in situ image segmentation for subcellular metabolomics analysis

Subcellular metabolomics analysis is crucial for understanding intracellular heterogeneity and accurate drug-cell interactions. Unfortunately, the ultra-small size and complex microenvironment inside the cell pose a great challenge to achieving this goal. To address this challenge, we propose an artificial intelligence-assisted subcellular mass spectrometry imaging (AI-SMSI) strategy with in situ image segmentation. Based on the nanometer-resolution MSI technique, the protonated guanine and threonine ions were respectively employed as the nucleus and cytoplasmic markers to complete image segmentation at the subcellular level, avoiding mutual interference of signals from various compartments in the cell. With advanced AI models, the metabolites within the different regions could be further integrated and profiled. Through this method, we decrypted the distinct action mechanism of isomeric drugs, doxorubicin (DOX) and epirubicin (EPI), only with a stereochemical inversion at C-4'. Within the cytoplasmic region, fifteen specific metabolites were discovered as biomarkers for distinguishing the drug action difference between DOX and EPI. Moreover, we identified that the downregulations of glutamate and aspartate in the malate-aspartate shuttle pathway may contribute to the higher paratoxicity of DOX. Our current AI-SMSI approach has promising applications for subcellular metabolomics analysis and thus opens new opportunities to further explore drug-cell specific interactions for the long-term pursuit of precision medicine.

Microfluidic Sampling of Undissolved Components from Subcellular Regions of Living Single Cells for Mass Spectrometry Analysis

Precise sampling of undissolved chemical components from subcellular regions of living single cells is a prerequisite for their in-depth analysis, which could promote understanding of subtle early stage physiological or pathological processes. Here we report a microfluidic method to extract undissolved components from subcellular regions for MS analysis. The target single cell was isolated by the microchamber beneath the microfluidic probe and washed by the injected biocompatible isotonic glucose aqueous solution (IGAS). Then, the sampling solvent was injected to extract undissolved components from the expected subcellular region of the living single cell, where the position and size of the sampling region could be controlled. The components immobilized by undissolved cellular structures were proven to be successfully extracted. Since unextracted subcellular regions were protected by IGAS, the single cell could survive after a tiny part was extracted, providing the possibility of repetitive sampling of the same living cell. Phospholipids extracted from the subcellular regions were successfully identified. The results demonstrated the feasibility of our method for subcellular sampling and analysis.

Nanospray Desorption Electrospray Ionization (Nano-DESI) Mass Spectrometry Imaging with High Ion Mobility Resolution

Untargeted separation of isomeric and isobaric species in mass spectrometry imaging (MSI) is challenging. The combination of ion mobility spectrometry (IMS) with MSI has emerged as an effective strategy for differentiating isomeric and isobaric species, which substantially enhances the molecular coverage and specificity of MSI experiments. In this study, we have implemented nanospray desorption electrospray ionization (nano-DESI) MSI on a trapped ion mobility spectrometry (TIMS) mass spectrometer. A new nano-DESI source was constructed, and a specially designed inlet extension was fabricated to accommodate the new source. The nano-DESI-TIMS-MSI platform was evaluated by imaging mouse brain tissue sections. We achieved high ion mobility resolution by utilizing three narrow mobility scan windows that covered the majority of the lipid molecules. Notably, the mobility resolution reaching up to 300 in this study is much higher than the resolution obtained in our previous study using drift tube IMS. High-resolution TIMS successfully separated lipid isomers and isobars, revealing their distinct localizations in tissue samples. Our results further demonstrate the power of high-mobility-resolution IMS for unraveling the complexity of biomolecular mixtures analyzed in MSI experiments.