Improved spatial resolution of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging using a reflective objective

Incorporation of Three Different Optical Trains into the IR-MALDESI Mass Spectrometry Imaging Platform to Characterize Artemisia annua

Artemisinin is the leading medication for the treatment of malaria and is only produced naturally in Artemisia annua. The localization of artemisinin in both the glandular and non-glandular trichomes of the plant makes it an ideal candidate for mass spectrometry imaging (MSI) as a model system for method development. Infrared matrix-assisted laser desorption electrospray ionization MSI (IR-MALDESI-MSI) has the capability to detect hundreds to thousands of analytes simultaneously, providing abundance information in conjunction with species localization throughout a sample. The development of several new optical trains and their application to the IR-MALDESI-MSI platform has improved data quality in previous proof-of-concept experiments but has not yet been applied to analysis of native biological samples, especially the MSI analysis of plants. This study aimed to develop a workflow and optimize MSI parameters, specifically the laser optical train, for the analysis of Artemisia annua with the NextGen IR-MALDESI platform coupled to an Orbitrap Exploris 240 mass spectrometer. Two laser optics were compared to the conventional set up, of which include a Schwarzschild-like reflective objective and a diffractive optical element (DOE). These optics, respectively, enhance the spatial resolution of imaging experiments or create a square spot shape for top-hat imaging. Ultimately, we incorporated and characterized three different optical trains into our analysis of Artemisia annua to study metabolites in the artemisinin pathway. These improvements in our workflow, resulted in high spatial resolution and improved ion abundance from previous work, which will allow us to address many different questions in plant biology beyond this model system.

Prototyping an ionization source for non-engineers

Novel mass spectrometry (MS) based analytical platforms have enabled scientists to detect and quantify molecules within biological and environmental samples more accurately. Novel MS instrumentation starts as a prototype and, after years of development, can become a commercial product to be used by the larger MS community. Without the initial prototype, many MS-based instruments today would not be produced. Additionally, biotechnology companies are the main drivers for research, development, and production of novel instruments, but the tools for prototyping instrumentation have never been more accessible. Here, we present a tutorial on prototyping instrumentation through the case study of developing the Next Generation IR-MALDESI source to show that an engineering degree is not required to design and construct a prototype instrument with modern hardware and software. We discuss the prototyping process, the necessary skills required for efficient prototyping, and information about common hardware and software used within initial prototypes.

Advances in Imaging Mass Spectrometry for Biomedical and Clinical Research

Imaging mass spectrometry (IMS) allows for the untargeted mapping of biomolecules directly from tissue sections. This technology is increasingly integrated into biomedical and clinical research environments to supplement traditional microscopy and provide molecular context for tissue imaging. IMS has widespread clinical applicability in the fields of oncology, dermatology, microbiology, and others. This review summarizes the two most widely employed IMS technologies, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), and covers technological advancements, including efforts to increase spatial resolution, specificity, and throughput. We also highlight recent biomedical applications of IMS, primarily focusing on disease diagnosis, classification, and subtyping.

Evaluating the optimal tissue thickness for mass spectrometry imaging using infrared matrix-assisted laser desorption electrospray ionization

RATIONALE

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) utilizes a 2970 nm mid-IR laser to desorb samples with depth resolutions (Z) on the order of micrometers. Conventionally, 5-20 μm thick tissue sections are used to characterize different applications of the IR-MALDESI source, but an optimal thickness has not been systematically investigated.

METHODS

Mouse liver was sectioned to various thicknesses and analyzed using IR-MALDESI mass spectrometry imaging (MSI). Height profiles of tissue sections of various cryosectioned thicknesses were acquired to affirm tissue thickness. Tissue sections of each thickness were measured using a Keyence microscope. Paraffin wax was cryosectioned, mounted on microscope slides, and measured using a chromatic confocal sensor system to determine the cryostat sectioning accuracy.

RESULTS

Analyzing sectioned tissues at higher thickness (>10 μm) leads to lower ion abundance, a decrease in signal over long analysis times, and more frequent instrument cleaning. Additionally, increasing tissue thickness above the optimum (7 μm) does not result in a significant increase in lipid annotations.

CONCLUSIONS

This work defines an optimal sample thickness for IR-MALDESI-MSI and demonstrates the utility of optimizing tissue thickness for MSI platforms of comparable Z resolution.

Maximized Spatial Information and Minimized Acquisition Time of Top-Hat IR-MALDESI-MSI of Zebrafish Using Nested Regions of Interest (nROIs)

Increasing the spatial resolution of a mass spectrometry imaging (MSI) method results in a more defined heatmap of the spatial distribution of molecules across a sample, but it is also associated with the disadvantage of increased acquisition time. Decreasing the area of the region of interest to achieve shorter durations results in the loss of potentially valuable information in larger specimens. This work presents a novel MSI method to reduce the time of MSI data acquisition with variable step size imaging: nested regions of interest (nROIs). Using nROIs, a small ROI may be imaged at a higher spatial resolution while nested inside a lower-spatial-resolution peripheral ROI. This conserves the maximal spatial and chemical information generated from target regions while also decreasing the necessary acquisition time. In this work, the nROI method was characterized on mouse liver and applied to top-hat MSI of zebrafish using a novel optical train, which resulted in a significant improvement in both acquisition time and spatial detail of the zebrafish. The nROI method can be employed with any step size pairing and adapted to any method in which the acquisition time of larger high-resolution ROIs poses a practical challenge.