Compression strategies for the chemometric analysis of mass spectrometry imaging data

Application of chemometric methods to mass spectrometry imaging (MSI) data faces a bottleneck concerning the vast size of the experimental data sets. This drawback is critical when considering high‐resolution mass spectrometry data, which provide several thousand points for each considered pixel. In this work, different approaches have been tested to reduce the size of the analyzed data with the aim to allow the subsequent application of typical chemometric methods for image analysis. The standard approach for MSI data compression consists in binning mass spectra for each pixel to reduce the number of m/z values. In this work, a method is proposed to handle the huge size of MSI data based on the adaptation of a liquid chromatography‐mass spectrometry data compression method by the detection of regions of interest. Results showed that both approaches achieved high compression rates, although the proposed regions of interest–based method attains this reduction requiring lower computational requirements and keeping utter spectral information. For instance, typical compression rate reached values higher than 90% without loss of information in images and spectra.     

Comparative imaging of P,S, Fe,Cu, Zn and C in thin sections of rat brain tumor as well as control tissues by laser ablation inductively coupled plasma mass spectrometry

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used for quantitative imaging of selected elements (P, S, Fe, Cu, Zn and C) in thin sections of rat brain samples (thickness 20 μm). The sample surface was scanned (raster area ~ 2 cm²) with a focused laser beam (wavelength 266 nm, diameter of laser crater 50 μm, and irradiance 1 × 10⁹ W cm^− 2). The laser ablation system was coupled to a double-focusing sector field. The possibility was evaluated of using carbon (via measurement of ¹³C⁺) as an internal standard element for imaging element distribution as part of this method. The LA-ICP-MS images obtained for P, S, Fe Cu and Zn were quantified using synthetically prepared matrix-matched laboratory standards. Depending on the sample analyzed, concentrations of Cu and Zn in the control tissue were found to be in the range of 8–10 μg g^− 1 and 10–12 μg g^− 1, while in the tumor tissue these concentrations were in the range of 12–15 μg g^− 1 and 15–17 μg g^− 1, respectively. The measurements of P, S and Fe distribution revealed the depletion of these elements in tumor tissue. In all the samples, the shape of the tumor could be clearly distinguished from the surrounding healthy tissue by the depletion in carbon. Additional experiments were performed in order to study the influence of the water content of the analyzed tissue on the intensity signal of the analyte. The results of these measurements show the linear correlation (R² = 0.9604) between the intensity of analyte and amount of water in the sample. The growth of a brain tumor was thus studied for the first time by imaging mass spectrometry.     

Summary of ISO/TC 201 standard: XXII. ISO 22048:2004—Surface chemical analysis—Information format for static secondary ion mass spectrometry

This International Standard provides a digital format to store and transfer between computers, in a compact way, important calibration and instrumental parameter data necessary to make effective use of spectral data files from static SIMS instruments. This format is designed to supplement the data transfer format specified in ISO 14976. Copyright © 2004 John Wiley & Sons, Ltd.     

Profiling monoterpenol glycoconjugation in Vitis vinifera L. cv. Muscat of Alexandria using a novel putative compound database approach,high resolution mass spectrometry and collision induced dissociation fragmentation analysis

In this work we present a novel approach for the identification of plant metabolites using ultrahigh performance liquid chromatography coupled to accurate mass time-of-flight mass spectrometry. The workflow involves developing an in-house compound database consisting of exact masses of previously identified as well as putative compounds. The database is used to screen accurate mass spectrometry (MS) data to identify possible compound matches. Subsequent tandem MS data is acquired for possible matches and used for structural elucidation. The methodology is applied to profile monoterpene glycosides in Vitis vinifera cv. Muscat of Alexandria grape berries over three developmental stages. Monoterpenes are a subclass of terpenes, the largest class of plant secondary metabolites, and are found in two major forms in the plant, “bound” to one or more sugar moieties or “free” of said sugar moieties. In the free form, monoterpenes are noted for their fragrance and play important roles in plant defense and as attractants for pollinators. However, glycoconjugation renders these compounds odorless, and it is this form that the plant uses for monoterpene storage. In order to gain insight into monoterpene biochemistry and their fate in the plant an analysis of intact glycosides is essential. Eighteen monoterpene glycosides were identified including a monoterpene trisaccharide glycoside, which is tentatively identified here for this first time in any plant. Additionally, while previous studies have identified monoterpene malonylated glucosides in other grapevine tissue, we tentatively identify them for the first time in grape berries. This analytical approach can be readily applied to other plants and the workflow approach can also be used for other classes of compounds. This approach, in general, provides researchers with data to support the identification of putative compounds, which is especially useful when no standard is available.