A framework for the statistical analysis of mass spectrometry imaging experiments

Mass spectrometry (MS) imaging is a powerful investigation technique for a wide range of biological applications such as molecular histology of tissue, whole body sections, and bacterial films , and biomedical applications such as cancer diagnosis. MS imaging visualizes the spatial distribution of molecular ions in a sample by repeatedly collecting mass spectra across its surface, resulting in complex, high-dimensional imaging datasets. Two of the primary goals of statistical analysis of MS imaging experiments are classification (for supervised experiments), i.e. assigning pixels to pre-defined classes based on their spectral profiles, and segmentation (for unsupervised experiments), i.e. assigning pixels to newly discovered segments with relatively homogenous and distinct spectral profiles. To accomplish these goals, this research provides both statistical methods and statistical computing tools. First, we propose a novel spatial shrunken centroids framework for performing classification and segmentation of MS imaging experiments with feature selection. Spatial shrunken centroids combines spatial smoothing with statistical regularization in a model-based framework appropriate for both supervised and unsupervised settings. Second, we provide Cardinal, a free and open-source R package for processing, visualization, and statistical analysis of MS imaging experiments. Cardinal is the first R package designed specifically for MS imaging, and the first software for MS imaging that focuses specifically on experiments and statistical analysis. In addition to providing tools for statistical analysis, it also provides infrastructure to enable other statisticians to more easily develop new methods for MS imaging experiments. Lastly, to enable scalability of Cardinal to larger-than-memory datasets, we provide matter, a free and open-source R package for statistical computing with structured datasets-on-disk, such as MS imaging data files. Together, spatial shrunken centroids, Cardinal, and matter aim to allow scalable statistical analysis for high-resolution, high-throughput MS imaging experiments

3D DESI-MS lipid imaging in a xenograft model of glioblastoma : a proof of principle

Desorption electrospray ionisation mass spectrometry (DESI-MS) can image hundreds of molecules in a 2D tissue section, making it an ideal tool for mapping tumour heterogeneity. Tumour lipid metabolism has gained increasing attention over the past decade; and here, lipid heterogeneity has been visualised in a glioblastoma xenograft tumour using 3D DESI-MS imaging. The use of an automatic slide loader automates 3D imaging for high sample-throughput. Glioblastomas are highly aggressive primary brain tumours, which display heterogeneous characteristics and are resistant to chemotherapy and radiotherapy. It is therefore important to understand biochemical contributions to their heterogeneity, which may be contributing to treatment resistance. Adjacent sections to those used for DESI-MS imaging were used for H&E staining and immunofluorescence to identify different histological regions, and areas of hypoxia. Comparing DESI-MS imaging with biological staining allowed association of different lipid species with hypoxic and viable tissue within the tumour, and hence mapping of molecularly different tumour regions in 3D space. This work highlights that lipids are playing an important role in the heterogeneity of this xenograft tumour model, and DESI-MS imaging can be used for lipid 3D imaging in an automated fashion to reveal heterogeneity, which is not apparent in H&E stains alone

Development of high-spatial and high-mass resolution mass spectrometric imaging (MSI) and its application to the study of small metabolites and endogenous molecules of plants

High-spatial and high-mass resolution laser desorption ionization (LDI) mass spectrometric (MS) imaging technology was developed for the attainment of MS images of higher quality containing more information on the relevant cellular and molecular biology in unprecedented depth. The distribution of plant metabolites is asymmetric throughout the cells and tissues, and therefore the increase in the spatial resolution was pursued to reveal the localization of plant metabolites at the cellular level by MS imaging. For achieving high-spatial resolution, the laser beam size was reduced by utilizing an optical fiber with small core diameter (25 μm) in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer. Matrix application was greatly improved using oscillating capillary nebulizer. As a result, single cell level spatial resolution of ~ 12 μm was achieved. MS imaging at this high spatial resolution was directly applied to a whole Arabidopsis flower and the substructures of an anther and single pollen grains at the stigma and anther were successfully visualized. MS imaging of high spatial resolution was also demonstrated to the secondary roots of Arabidopsis thaliana and a high degree of localization of detected metabolites was successfully unveiled. This was the first MS imaging on the root for molecular species. MS imaging with high mass resolution was also achieved by utilizing the LTQ-Orbitrap mass spectrometer for the direct identification of the surface metabolites on the Arabidopsis stem and root and differentiation of isobaric ions having the same nominal mass with no need of tandem mass spectrometry (MS/MS). MS imaging at high-spatial and high-mass resolution was also applied to cer1 mutant of the model system Arabidopsis thaliana to demonstrate its usefulness in biological studies and reveal associated metabolite changes in terms of spatial distribution and/or abundances compared to those of wild-type. The spatial distribution of targeted metabolites, mainly waxes and flavonoids, was systematically explored on various organs, including flowers, leaves, stems, and roots at high spatial resolution of ~ 12-50 μm and the changes in the abundance level of these metabolites were monitored on the cer1 mutant with respect to the wild-type. This study revealed the metabolic biology of CER1 gene on each individual organ level with very detailed high spatial resolution. The separate MS images of isobaric metabolites, i.e. C29 alkane vs. C28 aldehyde could be constructed on both genotypes from MS imaging at high mass resolution. This allows tracking of abundance changes for those compounds along with the genetic mutation, which is not achievable with low mass resolution mass spectrometry. This study supported previous hypothesis of molecular function of CER1 gene as aldehyde decarbonylase, especially by displaying hyper accumulation of aldehydes and C30 fatty acid and decrease in abundance of alkanes and ketones in several plant organs of cer1 mutant. The scope of analytes was further directed toward internal cell metabolites from the surface metabolites of the plant. MS profiling and imaging of internal cell metabolites were performed on the vibratome section of Arabidopsis leaf. Vibratome sectioning of the leaf was first conducted to remove the surface cuticle layer and it was followed by enzymatic treatment of the section to induce the digestion of primary cell walls, middle lamella, and expose the internal cells underneath to the surface for detection with the laser by LDI-MS. The subsequent MS imaging onto the enzymatically treated vibratome section allowed us to map the distribution of the metabolites in the internal cell layers, linolenic acid (C18:3 FA) and linoleic acid (C18:2 FA). The development of an assay for relative quantification of analytes at the single subcellular/organelle level by LDI-MS imaging was attempted and both plausibility and significant obstacles were seen. As a test system, native plant organelle, chloroplasts isolated from the spinach leaves were used and the localization of isolated chloroplasts dispersed on the target plate in low density was monitored by detecting the ion signal of chlorophyll a (Chl a) degradation products such as pheophytin a and pheophobide a by LDI-MS imaging in combination with fluorescence microscopy. The number of chloroplasts and their localization visualized in the MS image exactly matched those in the fluorescence image especially at low density, which first shows the plausibility of single-organelle level quantification of analytes by LDI-MS. The accumulation level of Chl a within a single chloroplast detected by LDI-MS was compared to the fluorescence signal on a pixel-to-pixel basis to further confirm the correlations of the accumulation levels measured by two methods. The proportional correlation was observed only for the chloroplasts which do not show the significant leakage of chlorophyll indicated by MS ion signal of Chl a degradation products and fluorescence signal, which was presumably caused by the prior fluorescence measurement before MS imaging. Further investigation is necessary to make this method more complete and develop LDI-MS imaging as an effective analytical tool to evaluate a relative accumulation of analytes of interest at the single subcellular/organelle level

MS imaging of small metabolites in fruits

MS Imaging of large molecules, e.g. proteins and lipids, have been reported with MALDI. On the other hand, few works have been done on mapping the small molecules by MALDI imaging. This is mainly due to the high chemical noise background interference in the low mass region caused by chemical matrices. DESI Imaging, however, could be complementary to MALDI in that sample can be analyzed directly without matrices. A large group of small metabolites are of considerable physiological and morphological importance in plants, e.g. flavonols involve in plant defense against environmental stresses and organic acids are one of important factors for fruit quality, but knowledge of their precise functions is limited due to insufficient characterization of their spatial responses. In this communication we will discuss methodological details about MS imaging of small metabolites in apple and grape in terms of sample preparation, imaging methods, and other experimental concerns by using MALDI [1] and DESI source coupled with a high resolution/accurate LTQ-Orbitrap mass spectrometer. Finally, we will describe the spatial distributions of flavonols and organic acids in apple and grape, respectively

Mass Spectral Imaging for Analysis of Pharmaceutical Ingredients

Mass spectral imaging (MS-imaging) is a modern technique used for the analysis and characterization and distribution of pharmaceutical ingredients , drugs, peptidies, lipids, and other bioactive species in tissue section/ Tissue prints. Although now widely accepted, there remains a host of competing and complementary techniques including DESI, MALDI, SIMS, and DART ionization techniques that allow the researchers to obtain appreciable ion intensities for mapping purposes. Instrumentation further is, rapidly advancing with significant progress in TOF, ion trap, and quadrupole instrumentation for mapping. In this review, I will examine the current status and role of MS-imaging with emphasis on analysis of pharmaceutical ingredients

High-resolution 3D and (sub-)cellular level LA-ICP-MS imaging approaches : accumulation of toxic metals in biological material

C

Lipid changes within the epidermis of living skin equivalents observed across a time-course by MALDI-MS imaging and profiling

© 2015 Mitchell et al. Abstract Background: Mass spectrometry imaging (MSI) is a powerful tool for the study of intact tissue sections. Here, its application to the study of the distribution of lipids in sections of reconstructed living skin equivalents during their development and maturation is described. Methods: Living skin equivalent (LSE) samples were obtained at 14 days development, re-suspended in maintenance medium and incubated for 24 h after delivery. The medium was then changed, the LSE re-incubated and samples taken at 4, 6 and 24 h time points. Mass spectra and mass spectral images were recorded from 12 μm sections of the LSE taken at each time point for comparison using matrix assisted laser desorption ionisation mass spectrometry. Results: A large number of lipid species were identified in the LSE via accurate mass-measurement MS and MSMS experiments carried out directly on the tissue sections. MS images acquired at a spatial resolution of 50 μm × 50 μm showed the distribution of identified lipids within the developing LSE and changes in their distribution with time. In particular development of an epidermal layer was observable as a compaction of the distribution of phosphatidylcholine species. Conclusions: MSI can be used to study changes in lipid composition in LSE. Determination of the changes in lipid distribution during the maturation of the LSE will assist in the identification of treatment responses in future investigations