Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in ...particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.
Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic ...and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue,
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0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97–112% accuracy. Other MS modes resulted in LOD 6.7–569.4 and 2.6–119.1 μg/g tissue,
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0.86–0.98 and 0.86–0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70–356% and 64–398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.
Graphical abstract
Mass spectrometry imaging (MSI) has evolved into a valuable tool across many fields of chemistry, biology, and medicine. However, arguably its greatest disadvantage is the difficulty in acquiring ...quantitative data regarding the surface concentration of the analyte(s) of interest. These difficulties largely arise from the high dependence of the ion signal on the localized chemical and morphological environment and the difficulties associated with calibrating such signals. The development of quantitative MSI approaches would correspond to a giant leap forward for the field, particularly for the biomedical and pharmaceutical fields, and is thus a highly active area of current research. In this review, we outline the current progress being made in the development and application of quantitative MSI workflows with a focus on biomedical applications. Particular emphasis is placed on the various strategies used for both signal calibration and correcting for various ion suppression effects that are invariably present in any MSI study. In addition, the difficulties in validating quantitative-MSI data on a pixel-by-pixel basis are highlighted.
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Determining localised surface concentrations with quantitative imaging mass spectrometry
Matrix-assisted laser desorption/ionisation-mass spectrometry imaging (MALDI-MSI) is a powerful technique for visualising the spatial locations of lipids in biological tissues. However, a major ...challenge in interpreting the biological significance of local lipid compositions and distributions detected using MALDI-MSI is the difficulty in associating spectra with cellular lipid metabolism within the tissue. By-and-large this is due to the typically limited spatial resolution of MALDI-MSI (30–100 μm) meaning individual spectra represent the average spectrum acquired from multiple adjacent cells, each potentially possessing a unique lipid composition and biological function. The use of oversampling is one promising approach to decrease the sampling area and improve the spatial resolution in MALDI-MSI, but it can suffer from a dramatically decreased sensitivity. In this work we overcome these challenges through the coupling of oversampling MALDI-MSI with laser post-ionisation (MALDI-2). We demonstrate the ability to acquire rich lipid spectra from pixels as small as 6 μm, equivalent to or smaller than the size of typical mammalian cells. Coupled with an approach for automated lipid identification, it is shown that MALDI-2 combined with oversampling at 6 μm pixel size can detect up to three times more lipids and many more lipid classes than even conventional MALDI at 20 μm resolution in the positive-ion mode. Applying this to mouse kidney and human brain tissue containing active multiple sclerosis lesions, where 74 and 147 unique lipids are identified, respectively, the localisation of lipid signals to individual tubuli within the kidney and lipid droplets with lesion-specific macrophages is demonstrated.
Graphical abstract
Mass spectrometry imaging has become a popular tool for probing the chemical complexity of biological surfaces. This led to the development of a wide range of instrumentation and preparation ...protocols. It is thus desirable to evaluate and compare the data output from different methodologies and mass spectrometers. Here, we present an approach for the comparison of mass spectrometry imaging data from different laboratories (often referred to as multicenter studies). This is exemplified by the analysis of mouse brain sections in five laboratories in Europe and the USA. The instrumentation includes matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF), MALDI-QTOF, MALDI-Fourier transform ion cyclotron resonance (FTICR), atmospheric-pressure (AP)-MALDI-Orbitrap, and cluster TOF-secondary ion mass spectrometry (SIMS). Experimental parameters such as measurement speed, imaging bin width, and mass spectrometric parameters are discussed. All datasets were converted to the standard data format imzML and displayed in a common open-source software with identical parameters for visualization, which facilitates direct comparison of MS images. The imzML conversion also allowed exchange of fully functional MS imaging datasets between the different laboratories. The experiments ranged from overview measurements of the full mouse brain to detailed analysis of smaller features (depending on spatial resolution settings), but common histological features such as the corpus callosum were visible in all measurements. High spatial resolution measurements of AP-MALDI-Orbitrap and TOF-SIMS showed comparable structures in the low-micrometer range. We discuss general considerations for planning and performing multicenter studies in mass spectrometry imaging. This includes details on the selection, distribution, and preparation of tissue samples as well as on data handling. Such multicenter studies in combination with ongoing activities for reporting guidelines, a common data format (imzML) and a public data repository can contribute to more reliability and transparency of MS imaging studies.
Comparison of MS imaging platforms in international multicenter study
MALDI imaging mass spectrometry (MALDI-IMS) has become a powerful tool for the detection and localization of drugs, proteins, and lipids on-tissue. Nevertheless, this approach can only perform ...identification of low mass molecules as lipids, pharmaceuticals, and peptides. In this article, a combination of approaches for the detection and imaging of proteins and their identification directly on-tissue is described after tryptic digestion. Enzymatic digestion protocols for different kinds of tissues—formalin fixed paraffin embedded (FFPE) and frozen tissues—are combined with MALDI-ion mobility mass spectrometry (IM-MS). This combination enables localization and identification of proteins via their related digested peptides. In a number of cases, ion mobility separates isobaric ions that cannot be identified by conventional MALDI time-of-flight (TOF) mass spectrometry. The amount of detected peaks per measurement increases (versus conventional MALDI-TOF), which enables mass and time selected ion images and the identification of separated ions. These experiments demonstrate the feasibility of direct proteins identification by ion-mobility-TOF IMS from tissue. The tissue digestion combined with MALDI-IM-TOF-IMS approach allows a proteomics “bottom-up” strategy with different kinds of tissue samples, especially FFPE tissues conserved for a long time in hospital sample banks. The combination of IM with IMS marks the development of IMS approaches as real proteomic tools, which brings new perspectives to biological studies.
Ion mobility separation reveals new details on the distribution of nominally isobaric tryptic peptides on FFPE brain tissue sections in imaging mass spectrometry.
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