Lipidomics for translational skin research: A primer for the uninitiated.

Healthy skin depends on a unique lipid profile to form a barrier that confers protection and prevents excessive water loss, aids cell-cell communication and regulates cutaneous homoeostasis and inflammation. Alterations in the cutaneous lipid profile can have severe consequences for skin health and have been implicated in numerous inflammatory skin conditions. Thus, skin lipidomics is increasingly of interest, and recent developments in mass spectrometry-based analytical technologies can deliver in-depth investigation of cutaneous lipids, providing insight into their role and mechanism of action. The choice of tissue sampling technique and analytical approach depends on the location and chemistry of the lipid of interest. Lipidomics can be conducted by various mass spectrometry approaches, including different chromatography and ionisation techniques. Targeted mass spectrometry is a sensitive approach for measuring low-abundance signalling lipids, such as eicosanoids, endocannabinoids and ceramides. This approach requires specific extraction, chromatography and mass spectrometry protocols to quantitate the lipid targets. Untargeted mass spectrometry reveals global changes and allows analysis of hundreds of complex lipids across a range of lipid classes, including phospholipids, glycerophospholipids, cholesteryl esters and sphingolipids. Mass spectrometry lipid imaging, including matrix-assisted laser desorption ionisation mass spectrometry and desorption electrospray ionisation mass spectrometry, can reveal information about abundance and anatomical distribution of lipids within a single skin sample. Skin lipidomics can provide qualitative and quantitative data on hundreds of biologically relevant lipid species with different properties and activities, all found within a single skin sample, and support translational studies exploring the involvement of lipids in skin health and disease.

Enhanced capabilities for imaging gangliosides in murine brain with matrix-assisted laser desorption/ionization and desorption electrospray ionization mass spectrometry coupled to ion mobility separation.

The increased interest in lipidomics calls for improved yet simplified methods of lipid analysis. Over the past two decades, mass spectrometry imaging (MSI) has been established as a powerful technique for the analysis of molecular distribution of a variety of compounds across tissue surfaces. Matrix-assisted laser desorption/ionization (MALDI) MSI is widely used to study the spatial distribution of common lipids. However, a thorough sample preparation and necessity of vacuum for efficient ionization might hamper its use for high-throughput lipid analysis. Desorption electrospray ionization (DESI) is a relatively young MS technique. In DESI, ionization of molecules occurs under ambient conditions, which alleviates sample preparation. Moreover, DESI does not require the application of an external matrix, making the detection of low mass species more feasible due to the lack of chemical matrix background. However, irrespective of the ionization method, the final information obtained during an MSI experiment is very complex and its analysis becomes challenging. It was shown that coupling MSI to ion mobility separation (IMS) simplifies imaging data interpretation. Here we employed DESI and MALDI MSI for a lipidomic analysis of the murine brain using the same IMS-enabled instrument. We report for the first time on the DESI IMS-MSI of multiply sialylated ganglioside species, as well as their acetylated versions, which we detected directly from the murine brain tissue. We show that poly-sialylated gangliosides can be imaged as multiply charged ions using DESI, while they are clearly separated from the rest of the lipid classes based on their charge state using ion mobility. This represents a major improvement in MSI of intact fragile lipid species. We additionally show that complementary lipid information is reached under particular conditions when DESI is compared to MALDI MSI.

In vivo isotopically labeled atherosclerotic aorta plaques in ApoE KO mice and molecular profiling by matrix-assisted laser desorption/ionization mass spectrometric imaging.

RATIONALE: The ability to quantify rates of formation, regression and/or remodeling of atherosclerotic plaque should facilitate a better understanding of the pathogenesis and management of cardiovascular disease. In the current study, we coupled a stable isotope labeled tracer protocol with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to examine spatial and temporal lipid dynamics in atherosclerotic plaque. METHODS: To promote plaque formation in the aorta region, ApoE KO mice were fed a high cholesterol diet (0.15% cholesterol) and orally dosed with (2,2,3,4,4,6-d(6))-cholesterol over several weeks. Tissue sections of ~10 µm thickness were analyzed by MALDI-MSI using matrix deposition by either chemical sublimation or acoustic droplet ejection. RESULTS: MALDI-MSI yielded distinct spatial distribution information for a variety of lipid classes including specific lysophosphatidylcholines typically associated with atherosclerosis-related tissue damage such as phospholipase 2 (Lp-PLA(2)) that mediate chemotactic responses to inflammation (e.g. LPC 16:0, LPC 18:0 and LPC 18:1) as well as free cholesterol and cholesteryl esters that contribute to atheroma formation. MALDI mass spectra acquired from aorta tissue sections clearly distinguished non-esterified and esterified versions of (2,2,3,4,4,6-d(6))-cholesterol within aortic plaque regions and showed distinct spatial accumulation of the cholesterol tracer. CONCLUSIONS: The ability to couple stable isotope based protocols with MALDI-MSI enables a novel strategy to characterize the effects of therapeutic treatments on atherosclerotic plaque formation, regression and potential remodeling of the complex lipid components with high chemical specificity and spatiotemporal information.

Update DESI Mass Spectrometry Imaging (MSI).

Desorption electrospray ionization (DESI) is an ambient technique that allows chemical information to be obtained directly from a wide range of surfaces, without pretreatment. Here we describe the improvements that have been developed to be able to achieve low tens of microns pixel size MSI experiments with high sensitivity for metabolites and lipids from biological tissue sections.In the last decade, DESI mass spectrometry has undergone developmental improvements, with regard to the method of desorption and ionization as well as the mass spectrometer to which the DESI source has been coupled to. DESI is becoming a mass spectrometry imaging technique, which can match and complement the currently most widely adopted ionization technique, the matrix-assisted laser desorption/ionization (MALDI).

Identifying lipid traces of atherogenic mechanisms in human carotid plaque.

BACKGROUND AND AIMS: Lipids play an important role in atherosclerotic plaque development and are interesting candidate predictive biomarkers. However, the link between circulating lipids, accumulating lipids in the vessel wall, and plaque destabilization processes in humans remains largely unknown. This study aims to provide new insights into the role of lipids in atherosclerosis using lipidomics and mass spectrometry imaging to investigate lipid signatures in advanced human carotid plaque and plasma samples. METHODS: We used lipidomics and desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to investigate lipid signatures of advanced human carotid plaque and plasma obtained from patients who underwent carotid endarterectomy (n = 14 out of 17 whose plaque samples were analyzed by DESI-MSI). Multivariate data analysis and unsupervised clustering were applied to identify lipids that were the most discriminative species between different patterns in plaque and plasma. These patterns were interpreted by quantitative comparison with conventional histology. RESULTS: Lipidomics detected more than 300 lipid species in plasma and plaque, with markedly different relative abundances. DESI-MSI visualized the spatial distribution of 611 lipid-related m/z features in plaques, of which 330 m/z features could be assigned based on exact mass, comparison to the lipidomic data, and high mass resolution MSI. Matching spatial lipid patterns to histological areas of interest revealed several molecular species that were colocalized with pertinent disease processes in plaque including specific sphingomyelin and ceramide species with calcification, phospholipids and free fatty acids with inflammation, and triacylglycerols and phosphatidylinositols with fibrin-rich areas. CONCLUSIONS: By comparing lipid species in plaque and plasma, we identified those circulating species that were also prominently present in plaque. Quantitative comparison of lipid spectral patterns with histology revealed the presence of specific lipid species in destabilized plaque areas, corroborating previous in vitro and animal studies.

Phosphorylation site localization in peptides by MALDI MS/MS and the Mascot Delta Score.

Owing to its broad biological significance, the large-scale analysis of protein phosphorylation is more and more getting into the focus of proteomic research. Thousands of phosphopeptides can nowadays be identified using state-of-the-art tandem mass spectrometers in conjunction with sequence database searching, but localizing the phosphate group to a particular amino acid in the peptide sequence is often still difficult. Using 180 individually synthesized phosphopeptides with precisely known phosphorylation sites (p-sites), we have assessed the merits of the Mascot Delta Score (MD score) for the assignment of phosphorylation sites from tandem mass spectra (MS/MS) generated on four different matrix-assisted laser desorption ionization (MALDI) mass spectrometers including tandem time-of-flight (TOF/TOF), quadrupole time-of-flight, and ion trap mass analyzers. The results show that phosphorylation site identification is generally possible with false localization rates of about 10%. However, a comparison to previous work also revealed that phosphorylation site determination by MALDI MS/MS is less accurate than by ESI-MS/MS particularly if several and/or adjacent possible phosphorylation acceptor sites exist in a peptide sequence. We are making the tandem MS spectra and phosphopeptide collection available to the community so that scientists may adapt the MD scores reported here to their analytical environment and so that informatics developers may integrate the MD score into proteomic data analysis pipelines.

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset.

BACKGROUND: Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics. RESULTS: We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods. CONCLUSIONS: The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author.

Introduction of 4-chloro-alpha-cyanocinnamic acid liquid matrices for high sensitivity UV-MALDI MS.

Matrix-assisted laser desorption/ionization (MALDI) is a key ionization technique in mass spectrometry (MS) for the analysis of labile macromolecules. An important area of study and improvements in relation to MALDI and its application in high-sensitivity MS is that of matrix design and sample preparation. Recently, 4-chloro-alpha-cyanocinnamic acid (ClCCA) has been introduced as a new rationally designed matrix and reported to provide an improved analytical performance as demonstrated by an increase in sequence coverage of protein digests obtained by peptide mass mapping (PMM) (Jaskolla, T. W.; et al. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 12200-12205). This new matrix shows the potential to be a superior alternative to the commonly used and highly successful alpha-cyano-4-hydroxycinnamic acid (CHCA). We have taken this design one step further by developing and optimizing an ionic liquid matrix (ILM) and liquid support matrix (LSM) using ClCCA as the principle chromophore and MALDI matrix compound. These new liquid matrices possess greater sample homogeneity and a simpler morphology. The data obtained from our studies show improved sequence coverage for BSA digests compared to the traditional CHCA crystalline matrix and for the ClCCA-containing ILM a similar performance to the ClCCA crystalline matrix down to 1 fmol of BSA digest prepared in a single MALDI sample droplet with current sensitivity levels in the attomole range. The LSMs show a high tolerance to contamination such as ammonium bicarbonate, a commonly used buffering agent.

Optimised Desorption Electrospray Ionisation Mass Spectrometry Imaging (DESI-MSI) for the Analysis of Proteins/Peptides Directly from Tissue Sections on a Travelling Wave Ion Mobility Q-ToF.

Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) is typically known for the ionisation of small molecules such as lipids and metabolites, in singly charged form. Here we present a method that allows the direct detection of proteins and peptides in multiply charged forms directly from tissue sections by DESI. Utilising a heated mass spectrometer inlet capillary, combined with ion mobility separation (IMS), the conditions with regard to solvent composition, nebulising gas flow, and solvent flow rate have been explored and optimised. Without the use of ion mobility separation prior to mass spectrometry analysis, only the most abundant charge series were observed. In addition to the dominant haemoglobin subunit(s) related trend line in the m/z vs drift time (DT) 2D plot, trend lines were found relating to background solvent peaks, residual lipids and, more importantly, small proteins/large peptides of lower abundance. These small proteins/peptides were observed with charge states from 1+ to 12+, the majority of which could only be resolved from the background when using IMS. By extracting charge series from the 2D m/z vs DT plot, a number of proteins could be tentatively assigned by accurate mass. Tissue images were acquired with a pixel size of 150 µm showing a marked improvement in protein image resolution compared to other liquid-based ambient imaging techniques such as liquid extraction surface analysis (LESA) and continuous-flow liquid microjunction surface sampling probe (LMJ-SSP) imaging. Graphical Abstract ᅟ.

BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology.

Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI.

Spinal diastematomyelia: a means of identification of charred remains.

The purpose of medico legal autopsy examination is the positive identification of the deceased in addition to the determination of the cause of death in most jurisdictions and additionally the manner of death in many jurisdictions. Notwithstanding the established and recognised value of DNA analysis in human identification, in the case of significant and extensive thermal injury in victims of fire, DNA analysis may prove difficult. Fire fatality identification can be assisted by alternative methods in this situation, including correlation between ante mortem and post mortem radiological investigations, identification of rare medical disease and or dental record examinations, where available. We describe a case where identification of charred human remains from a car fire was securely determined by demonstration of the presence of a rare congenital abnormality of the spinal cord, Diastematomyelia.

Mass spectrometry imaging of glucosinolates in Arabidopsis flowers and siliques.

Glucosinolates are multi-functional plant secondary metabolites which play a vital role in plant defence and are, as dietary compounds, important to human health and livestock well-being. Knowledge of the tissue-specific regulation of their biosynthesis and accumulation is essential for plant breeding programs. Here, we report that in Arabidopsis thaliana, glucosinolates are accumulated differentially in specific cells of reproductive organs. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), distribution patterns of three selected compounds, 4-methylsulfinylbutyl (glucoraphanin), indol-3-ylmethyl (glucobrassicin), and 4-benzoyloxybutyl glucosinolates, were mapped in the tissues of whole flower buds, sepals and siliques. The results show that tissue localization patterns of aliphatic glucosinolate glucoraphanin and 4-benzoyloxybutyl glucosinolate were similar, but indole glucosinolate glucobrassicin had different localisation, indicating a possible difference in function. The high resolution images obtained by a complementary approach, cryo-SEM Energy Dispersive X-ray analysis (cryo-SEM-EDX), confirmed increased concentration of sulphur in areas with elevated amounts of glucosinolates, and allowed identifying the cell types implicated in accumulation of glucosinolates. High concentration of sulphur was found in S-cells adjacent to the phloem in pedicels and siliques, indicating the presence of glucosinolates. Moreover, both MALDI MSI and cryo-SEM-EDX analyses indicated accumulation of glucosinolates in cells on the outer surface of the sepals, suggesting that a layer of glucosinolate-accumulating epidermal cells protects the whole of the developing flower, in addition to the S-cells, which protect the phloem. This research demonstrates the high potential of MALDI MSI for understanding the cell-specific compartmentation of plant metabolites and its regulation.