Identification of a distinct lipidomic profile in the osteoarthritic synovial membrane by mass spectrometry imaging.

OBJECTIVE: Synovial inflammation is one of the most characteristic events in different types of arthritis, including Osteoarthritis (OA). Emerging evidence also suggests the involvement of lipids in the regulation of inflammatory processes. The aim of this study was to elucidate the heterogeneity and spatial distribution of lipids in the OA synovial membrane and explore their putative involvement in inflammation. METHOD: The abundance and distribution of lipids were examined in human synovial membranes. To this end, histological cuts from this tissue were analysed by matrix-assisted laser desorption ionization - mass spectrometry imaging (MALDI-MSI). The lipidomic profile of OA synovium was characterized and compared with healthy and other forms of inflammatory arthropathies as Rheumatoid Arthritis (RA) and Psoriatic Arthritis (PsA) using principal component analysis and discriminant analysis methods. Lipid identification was undertaken by tandem MS analyses and database queries. RESULTS: Our results reveal differential and characteristic lipidomic profiles between OA and control samples. Specifically, we unveiled that OA synovium presents elevated levels of phosphatidylcholines, fatty acids and lysophosphatidic acids and lower levels of lysophosphatidylcholines compared to control tissues. The spatial distribution of particular glycerophospholipids was also correlated with hypertrophic, inflamed or vascularized synovial areas. Compared with other inflammatory arthritis, the OA tissue showed lower amounts of phosphatidylethanolamine-based plasmalogens. CONCLUSIONS: This study provides a novel insight into the lipid profiles of synovial membrane and differences in abundance between OA and control tissues. The lipidomic alterations improves understanding of the pathogenic mechanisms of OA and may be important for its diagnosis.

Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research.

Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.

Dynamics of Molecules Observed at Crude-Oil-Gas Interfaces by Time-of-Flight Secondary Ion Mass Spectrometry Imaging.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging provides molecular speciation at the micrometer scale, while the penetration depth of the primary ion beam is limited to the top-layers of a sample. These combined properties make TOF-SIMS potentially an ideal technique to study oil-gas interfaces. TOF-SIMS spectra of three crude oils were evaluated, and only low-mass fragment ions could be assigned to molecular structures unambiguously. Films of crude oils were incubated under air, oil vapor, or water vapor for various times. TOF-SIMS images of a polar crude oil revealed feeble structures of ∼10 µm large round patches that grew to ∼30 µm large crystals when incubated under air and oil vapor, respectively. Principal component analysis of the images showed that the continuous phase had typical aromatic signatures, while the patches and crystals had alkane-like characteristics. No features showed up when the oil film was incubated under water vapor, which indicated that saturated water vapor prevented the accumulation of nonpolar alkane-like compounds at the oil-gas interface. These examples showed that crude oils do not behave as dead fluids but that their constituents accumulate at the oil-gas interfaces in a dynamic way.

Spatially resolved proteomics in osteoarthritis: State of the art and new perspectives.

Osteoarthritis (OA) is one of the most common diseases worldwide caused by chronic degeneration of the joints. Its high prevalence and the involvement of several tissues define OA as a highly heterogeneous disease. New biological markers to evaluate the progression of the pathology and improve its prognosis are needed. Among all the different -omic strategies applied to OA, solution phase bottom-up proteomics has made an extensive contribution to the field of biomarker research. However, new technologies for protein analysis should be considered for a better understanding of the disease. This review focuses on complementary proteomic methodologies and new technologies for translational research of OA and other rheumatic pathologies, especially mass spectrometry imaging and protein imaging methods not applied by the OA community yet.

Spatially resolved endogenous improved metabolite detection in human osteoarthritis cartilage by matrix assisted laser desorption ionization mass spectrometry imaging.

Osteoarthritis (OA) is one of the most common musculoskeletal diseases, characterized by the progressive deterioration of articular cartilage. Although the disease has been well studied in the past few years, the endogenous metabolic composition and more importantly the spatial information of these molecules in cartilage is still poorly understood. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has been previously used for the investigation of the bimolecular distribution of proteins and lipids through the in situ analysis of cartilage tissue sections. MALDI-MSI as a tool to detect metabolites remains challenging, as these species have low abundance and degrade rapidly. In this work, we present a complete methodology, from sample preparation to data analysis for the detection of endogenous metabolites on cartilage by MSI. Our results demonstrate for the first time the ability to detect small molecules in fragile, challenging tissues through an optimized protocol, and render MSI as a tool towards a better understanding of OA.

Distinguishing core from penumbra by lipid profiles using Mass Spectrometry Imaging in a transgenic mouse model of ischemic stroke.

Detecting different lipid profiles in early infarct development may give an insight on the fate of compromised tissue. Here we used Mass Spectrometry Imaging to identify lipids at 4, 8 and 24 hours after ischemic stroke in mice, induced by transient middle cerebral artery occlusion (tMCAO). Combining linear transparency overlay, a clustering pipeline and spatial segmentation, we identified three regions: infarct core, penumbra (i.e. comprised tissue that is not yet converted to core), and surrounding healthy tissue. Phosphatidylinositol 4-phosphate (m/z = 965.5) became visible in the penumbra 24 hours after tMCAO. Infarct evolution was shown by 2D-renderings of multiple phosphatidylcholine (PC) and Lyso-PC isoforms. High-resolution Secondary Ion Mass Spectrometry, to evaluate sodium/potassium ratios, revealed a significant increase in sodium and a decrease in potassium species in the ischemic area (core and penumbra) compared to healthy tissue at 24 hours after tMCAO. In a transgenic mouse model with an enhanced susceptibility to ischemic stroke, we found a more pronounced discrimination in sodium/potassium ratios between penumbra and healthy regions. Insight in changes in lipid profiles in the first hours of stroke may guide the development of new prognostic biomarkers and novel therapeutic targets to minimize infarct progression.

Rapid Identification of Ischemic Injury in Renal Tissue by Mass-Spectrometry Imaging.

The increasing analytical speed of mass-spectrometry imaging (MSI) has led to growing interest in the medical field. Acute kidney injury is a severe disease with high morbidity and mortality. No reliable cut-offs are known to estimate the severity of acute kidney injury. Thus, there is a need for new tools to rapidly and accurately assess acute ischemia, which is of clinical importance in intensive care and in kidney transplantation. We investigated the value of MSI to assess acute ischemic kidney tissue in a porcine model. A perfusion model was developed where paired kidneys received warm (severe) or cold (minor) ischemia ( n = 8 per group). First, ischemic tissue damage was systematically assessed by two blinded pathologists. Second, MALDI-MSI of kidney tissues was performed to study the spatial distributions and compositions of lipids in the tissues. Histopathological examination revealed no significant difference between kidneys, whereas MALDI-MSI was capable of a detailed discrimination of severe and mild ischemia by differential expression of characteristic lipid-degradation products throughout the tissue within 2 h. In particular, lysolipids, including lysocardiolipins, lysophosphatidylcholines, and lysophosphatidylinositol, were dramatically elevated after severe ischemia. This study demonstrates the significant potential of MSI to differentiate and identify molecular patterns of early ischemic injury in a clinically acceptable time frame. The observed changes highlight the underlying biochemical processes of acute ischemic kidney injury and provide a molecular classification tool that can be deployed in assessment of acute ischemic kidney injury.

Strategies for managing multi-patient 3D mass spectrometry imaging data.

Mass spectrometry imaging (MSI) has emerged as a powerful tool in biomedical research to reveal the localization of a broad scale of compounds ranging from metabolites to proteins in diseased tissues, such as malignant tumors. MSI is most commonly used for the two-dimensional imaging of tissues from multiple patients or for the three-dimensional (3D) imaging of tissue from a single patient. These applications are potentially introducing a sampling bias on a sample or patient level, respectively. The aim of this study is therefore to investigate the consequences of sampling bias on sample representativeness and on the precision of biomarker discovery for histological grading of human bladder cancers by MSI. We therefore submitted formalin-fixed paraffin-embedded tissues from 14 bladder cancer patients with varying histological grades to 3D analysis by matrix-assisted laser desorption/ionization (MALDI) MSI. We found that, after removing 20% of the data based on novel outlier detection routines for 3D-MSI data based on the evaluation of digestion efficacy and z-directed regression, on average 33% of a sample has to be measured in order to obtain sufficient coverage of the existing biological variance within a tissue sample. SIGNIFICANCE: In this study, 3D MALDI-MSI is applied for the first time on a cohort of bladder cancer patients using formalin-fixed paraffin-embedded (FFPE) tissue of bladder cancer resections. This work portrays the reproducibility that can be achieved when employing an optimized sample preparation and subsequent data evaluation approach. Our data shows the influence of sampling bias on the variability of the results, especially for a small patient cohort. Furthermore, the presented data analysis workflow can be used by others as a 3D FFPE data-analysis pipeline working on multi-patient 3D-MSI studies.

Laser post-ionisation combined with a high resolving power orbitrap mass spectrometer for enhanced MALDI-MS imaging of lipids.

Coupling laser post-ionisation with a high resolving power MALDI Orbitrap mass spectrometer has realised an up to ∼100-fold increase in the sensitivity and enhanced the chemical coverage for MALDI-MS imaging of lipids relative to conventional MALDI. This could constitute a major breakthrough for biomedical research.

Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity.

One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research.

A new imaging method for understanding chemical dynamics: efficient slice imaging using an in-vacuum pixel detector.

The implementation of the Timepix complementary metal oxide semiconductor pixel detector in velocity map slice imaging is presented. This new detector approach eliminates the need for gating the imaging detector. In time-of-flight mode, the detector returns the impact position and the time-of-flight of charged particles with 12.5 ns resolution and a dynamic range of about 100 µs. The implementation of the Timepix detector in combination with a microchannel plate additionally allows for high spatial resolution information via center-of-mass centroiding. Here, the detector was applied to study the photodissociation of NO(2) at 452 nm. The energy resolution observed in the experiment was ΔE/E=0.05 and is limited by the experimental setup rather than by the detector assembly. All together, this new compact detector assembly is well-suited for slice imaging and is a promising tool for imaging studies in atomic and molecular physics research.

Parallel processing of large datasets from NanoLC-FTICR-MS measurements.

A new approach for automatic parallel processing of large mass spectral datasets in a distributed computing environment is demonstrated to significantly decrease the total processing time. The implementation of this novel approach is described and evaluated for large nanoLC-FTICR-MS datasets. The speed benefits are determined by the network speed and file transfer protocols only and allow almost real-time analysis of complex data (e.g., a 3-gigabyte raw dataset is fully processed within 5 min). Key advantages of this approach are not limited to the improved analysis speed, but also include the improved flexibility, reproducibility, and the possibility to share and reuse the pre- and postprocessing strategies. The storage of all raw data combined with the massively parallel processing approach described here allows the scientist to reprocess data with a different set of parameters (e.g., apodization, calibration, noise reduction), as is recommended by the proteomics community. This approach of parallel processing was developed in the Virtual Laboratory for e-Science (VL-e), a science portal that aims at allowing access to users outside the computer research community. As such, this strategy can be applied to all types of serially acquired large mass spectral datasets such as LC-MS, LC-MS/MS, and high-resolution imaging MS results.

Examples of Fourier transform ion cyclotron resonance mass spectrometry developments: from ion physics to remote access biochemical mass spectrometry.

The application of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) for high resolution biomolecular analysis has increased greatly after 30 years of innovation since its conception in 1974. FT- ICR-MS can now routinely be used for the analysis of complex organic mixtures such as biological or petrochemical samples. Many of these new possibilities have been the results of many different instrumental developments. This paper provides a mini review of selected instrumental developments that now allow these measurements. The development of soft ionization techniques such as electrospray ionization and matrix assisted laser desorption and ionisation was crucial for the analysis of biological macromolecules. Improved ion transport optics led to an increase in sensitivity. New ICR cell designs complement the capabilities of FT-ICR-MS by allowing a more thorough study of the mechanism and kinetics of ion reactions in the gas-phase. A selected example of electron capture dissociation (ECD) employs these developments to investigate the role of peptide conformation in ECD. Improved electronics and software allow faster and more flexible experiments. All these improvements led to an increase in speed and sensitivity that are necessary to couple FT-MS to fast separation techniques such as nano-high performance liquid chromatography. The modern FT-ICR-MS instruments can be incorporated in virtual organizations allowing remote access to unique infrastructure. This concept of remote experimentation opens new possibilities for scientific collaborations between expert scientists at different locations and allows the efficient use of this expensive instrumentation.

A mini-review of mass spectrometry using high-performance FTICR-MS methods.

Structural characterization of macromolecules is currently delivering new insights into the behavior of individual molecules or molecular ensembles. Technological advances have made it possible to examine smaller and smaller amounts (down to single molecules) of larger and larger molecular systems. Mass spectrometry in particular is capable of the detailed study of extremely small quantities (down to a single molecule) of very large (biological) molecules. The advent of new ionization techniques such as electrospray and matrix-assisted laser desorption are mainly responsible for these advances. As a result, mass spectrometry has evolved into an enabling discipline that plays an increasingly important role in combinatorial chemistry, polymer science, biochemistry, medicine, environmental and marine science, and archaeology and conservation science. This paper will review a selection of methodological developments in the field of high-performance Fourier transform ion cyclotron resonance mass spectrometry for structural analysis of these macromolecules.