LA-ICP-MS and MALDI-MS image registration for correlating nanomaterial biodistributions and their biochemical effects

Quantitative imaging of the sub-organ distributions of nanomaterials in biological tissues via laser ablation inductively coupled plasma mass spectrometry

Nanomaterials have been employed in many biomedical applications, and their distributions in biological systems can provide an understanding of their behavior in vivo. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) can be used to determine the distributions of metal-based NMs in biological systems. However, LA-ICP-MS has not commonly been used to quantitatively measure the cell-specific or sub-organ distributions of nanomaterials in tissues. Here, we describe a new platform that uses spiked gelatin standards with control tissues on top to obtain an almost perfect tissue mimic for quantitative imaging purposes. In our approach, gelatin is spiked with both nanomaterial standards and an internal standard to improve quantitation and image quality. The value of the developed approach is illustrated by determining the sub-organ distributions of different metal-based and metal-tagged polymeric nanomaterials in mice organs. The LA-ICP-MS images reveal that the chemical and physical properties of the nanomaterials cause them to distribute in quantitatively different extents in spleens, kidneys, and tumors, providing new insight into the fate of nanomaterials in vivo. Furthermore, we demonstrate that this approach enables quantitative co-localization of nanomaterials and their cargo. We envision this method being a valuable tool in the development of nanomaterial drug delivery systems.

BioQuant: Data Processing Software for Simultaneous Imaging Analysis for Elements and Molecules Using Two Mass Spectrometers

Simultaneous imaging analysis for both elements and molecules was conducted by introducing laser-induced sample particles into two separate mass spectrometers (i.e., an inorganic spectrometer and an organic mass spectrometer) through the split-flow protocol. The timing of ion detections for elements and molecules can be different, reflecting the differences in mass scan rates, lengths for transport tubing, and flow rates of carrier gases, and thus, the timing of ion detections must be carefully aligned to discuss abundance correlations between elements and molecules. To achieve this, a new data processing software "BioQuant" was developed to correct the time difference of the signal intensities for components obtained by the two mass spectrometers. With the BioQuant software, signal intensity data obtained from several unit cells were merged into a newly defined unit cell, calculated by the common time intervals from both mass spectrometers. With the newly defined unit cells, correlation analysis between the elements and molecules can be conducted. Combination of the BioQuant software and laser ablation system connected to two separated mass spectrometers can become a benchmark technique for simultaneous imaging analysis for both the elements and molecules from single sample material.

Emerging Computational Methods in Mass Spectrometry Imaging

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.

MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives

Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.