MassPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics.
ABSTRACT: INTRODUCTION:Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. OBJECTIVES:We have developed massPix-an R package for analysing and interpreting data from MSI of lipids in tissue. METHODS:massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. RESULTS:Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. CONCLUSION:massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.
Project description:Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. Here we have developed massPix - an R package for analysing and interpreting data from MSI of lipids in tissue. MassPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications. MassPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. Mouse cerebellum was analysed using matrix assisted laser desorption ionisation (MALDI) MSI. The resulting MSI dataset forms the test data for massPix.
Project description:Hepatocellular lipid accumulation characterizes nonalcoholic fatty liver disease (NAFLD). However, the types of lipids associated with disease progression are debated, as is the impact of their localization. Traditional lipidomics analysis using liver homogenates or plasma dilutes and averages lipid concentrations, and does not provide spatial information about lipid distribution. We aimed to characterize the distribution of specific lipid species related to NAFLD severity by performing label-free molecular analysis by mass spectrometry imaging (MSI). Fresh frozen liver biopsies from obese subjects undergoing bariatric surgery ( n = 23) with various degrees of NAFLD were cryosectioned and analyzed by matrix-assisted laser desorption/ionization (MALDI)-MSI. Molecular identification was verified by tandem MS. Tissue sections were histopathologically stained, annotated according to the Kleiner classification, and coregistered with the MSI data set. Lipid pathway analysis was performed and linked to local proteome networks. Spatially resolved lipid profiles showed pronounced differences between nonsteatotic and steatotic tissues. Lipid identification and network analyses revealed phosphatidylinositols and arachidonic acid metabolism in nonsteatotic regions, whereas low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) metabolism was associated with steatotic tissue. Supervised and unsupervised discriminant analysis using lipid based classifiers outperformed simulated analysis of liver tissue homogenates in predicting steatosis severity. We conclude that lipid composition of steatotic and nonsteatotic tissue is highly distinct, implying that spatial context is important for understanding the mechanisms of lipid accumulation in NAFLD. MSI combined with principal component-linear discriminant analysis linking lipid and protein pathways represents a novel tool enabling detailed, comprehensive studies of the heterogeneity of NAFLD.
Project description:Lipidomics has great promise in various applications; however, a major bottleneck in lipidomics is the accurate and comprehensive annotation of high-resolution tandem mass spectral data. While the number of available lipidomics software has drastically increased over the past five years, the reduction of false positives and the realization of obtaining structurally accurate annotations remains a significant challenge. We introduce Lipid Annotator, which is a user-friendly software for lipidomic analysis of data collected by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). We validate annotation accuracy against lipid standards and other lipidomics software. Lipid Annotator was integrated into a workflow applying an iterative exclusion MS/MS acquisition strategy to National Institute of Standards and Technology (NIST) SRM 1950 Metabolites in Frozen Human Plasma using reverse phase LC-HRMS/MS. Lipid Annotator, LipidMatch, and MS-DIAL produced consensus annotations at the level of lipid class for 98% and 96% of features detected in positive and negative mode, respectively. Lipid Annotator provides percentages of fatty acyl constituent species and employs scoring algorithms based on probability theory, which is less subjective than the tolerance and weighted match scores commonly used by available software. Lipid Annotator enables analysis of large sample cohorts and improves data-processing throughput as compared to previous lipidomics software.
Project description:Myocardial infarction (MI) and subsequent progressive heart failure pathology is the major cause of death worldwide; however, the mechanism of this pathology remains unclear. The present work aimed at testing the hypothesis whether the inflammatory response is superimposed with the formation of bioactive lipid resolving molecules at the site of the injured myocardium in acute heart failure pathology post-MI. In this view, we used a robust permanent coronary ligation model to induce MI, leading to decreased contractility index with marked wall thinning and necrosis of the infarcted left ventricle. Then, we applied mass spectrometry imaging (MSI) in positive and negative ionization modes to characterize the spatial distribution of left ventricle lipids in the infarcted myocardium post-MI. After micro-extraction, liquid chromatography coupled to tandem mass spectrometry was used to confirm the structures of the imaged lipids. Statistical tools such as principal component analysis were used to establish a comprehensive visualization of lipid profile changes in MI and no-MI hearts. Resolving bioactive molecules such as resolvin (Rv) D1, RvD5, RvE3, 17-HDHA, LXA<sub>4</sub>, and 18-HEPE were detected in negative ion mode MSI, whereas phosphatidyl cholines (PC) and oxidized derivatives thereof were detected in positive ion mode. MSI-based analysis demonstrated a significant increase in resolvin bioactive lipids with comprehensive lipid remodeling at the site of infarction. These results clearly indicate that infarcted myocardium is the primary location of inflammation-resolution pathomechanics which is critical for resolution of inflammation and heart failure pathophysiology. Graphical abstract Applied scheme to determine comprehensive lipidomics in failing and non-failing heart.
Project description:Lipid coverage is crucial in comprehensive lipidomics studies challenged by high diversity in lipid structures and wide dynamic range in lipid levels. Current state-of-the-art lipidomics technologies are mostly based on mass spectrometry (MS), including direct-infusion MS, chromatography-MS, and matrix-assisted laser desorption ionization (MALDI) imaging MS, each with its pros and cons. Due to the need or favorability for measurement of isomers and isobars, chromatography-MS is preferable for lipid profiling. The ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based nontargeted lipidomics approach and UHPLC-tandem MS (UHPLC-MS/MS)-based targeted approach are two representative methodological platforms for chromatography-MS. In the present study, we developed a high coverage pseudotargeted lipidomics method combining the advantages of nontargeted and targeted lipidomics approaches. The high coverage of lipids was achieved by integration of the detected lipids derived from nontargeted UHPLC-HRMS lipidomics analysis of multiple matrices (e.g., plasma, cell, and tissue) and the predicted lipids speculated on the basis of the structure and chromatographic retention behavior of the known lipids. A total of 3377 targeted lipid ion pairs with over 7000 lipid molecular structures were defined. The pseudotargeted lipidomics method was well validated with satisfactory analytical characteristics in terms of linearity, precision, reproducibility, and recovery for lipidomics profiling. Importantly, it showed better repeatability and higher coverage of lipids than the nontargeted lipidomics method. The applicability of the developed pseudotargeted lipidomics method was testified in defining differential lipids related to diabetes. We believe that comprehensive lipidomics studies will benefit from the developed high coverage pseudotargeted lipidomics approach.
Project description:We describe a simple method for the detection of low intensity lipid signals in complex tissue samples, based on a combination of liquid chromatography/mass spectrometry and ion mobility mass spectrometry. The method relies on visual and software-assisted analysis of overlapped mobilograms (diagrams of mass-to-charge ratio, m/z, vs drift time, DT) and was successfully applied in untargeted lipidomics analyses of mouse brain tissue to detect relatively small variations in a scarce class of phospholipids (N-acyl phosphatidylethanolamines) generated during neural tissue damage, against a background of hundreds of lipid species. Standard analytical tools, including Principal Component Analysis, failed to detect such changes.
Project description:Lipid species possess very different structures, leading to their very diversified cellular functions in biological systems. Lipidomics represents a powerful technology for deep analysis of hundreds to thousands of intact lipid molecular species. In the current study, a cluster of unknown ion peaks was displayed when we profiled cerebroside species in rat spinal cord samples by neutral loss scan of 162 Da in the positive ion mode using a multi-dimensional mass spectrometry-based shotgun lipidomics strategy. In order to identify the structural identities of these unknown ion peaks, MS<sup>2</sup> and MS<sup>3</sup> analyses of these ions were performed by high mass resolution mass spectrometry. Extensive lines of evidence allowed us to identify that these unknown ion peaks were monohexosyl alkyl-acyl glycerol (HAAG) species, including their sn-positional isomers and alkyl-acyl compositional isomers. We also applied the developed method to identify and quantify HAAG species present in a variety of mouse nerve tissues. We believe that the first kind of lipidomics study on HAAG species present in mammalian nerve tissue samples provided the foundation for future biological research in this unknown area.
Project description:Lipidomics, which focuses on the global study of molecular lipids in biological systems, could provide valuable insights about disease mechanisms. In this study, we present a nontargeted lipidomics strategy to determine cellular lipid alterations after scoparone exposure in primary hepatocytes. Lipid metabolic profiles were analyzed by high-performance liquid chromatography coupled with time-of-flight mass spectrometry, and a novel imaging TransOmics tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. Chemometric and statistical analyses of the obtained lipid fingerprints revealed the global lipidomic alterations and tested the therapeutic effects of scoparone. Identification of ten proposed lipids contributed to the better understanding of the effects of scoparone on lipid metabolism in hepatocytes. The most striking finding was that scoparone caused comprehensive lipid changes, as represented by significant changes of the identificated lipids. The levels of identified PG(19:1(9Z)/14:0), PE(17:1(9Z)/0:0), PE(19:1(9Z)/0:0) were found to be upregulated in ethanol-induced group, whereas the levels in scoparone group were downregulated. Lipid metabolism in primary hepatocytes was changed significantly by scoparone treatment. We believe that this novel approach could substantially broaden the applications of high mass resolution mass spectrometry for cellular lipidomics.
Project description:Detailed studies of lipids in biological systems, including their role in cellular structure, metabolism, and disease development, comprise an increasingly prominent discipline called lipidomics. However, the conventional lipidomics tools, such as mass spectrometry, cannot investigate lipidomes until they are extracted, and thus they cannot be used for probing the lipid distribution nor for studying in live cells. Furthermore, conventional techniques rely on the lipid extraction from relatively large samples, which averages the data across the cellular populations and masks essential cell-to-cell variations. Further advancement of the discipline of lipidomics critically depends on the capability of high-resolution lipid profiling in live cells and, potentially, in single organelles. Here we report a micro-Raman assay designed for single-organelle lipidomics. We demonstrate how Raman microscopy can be used to measure the local intracellular biochemical composition and lipidome hallmarks-lipid concentration and unsaturation level, cis/trans isomer ratio, sphingolipids and cholesterol levels in live cells-with a sub-micrometer resolution, which is sufficient for profiling of subcellular structures. These lipidome data were generated by a newly developed biomolecular component analysis software, which provides a shared platform for data analysis among different research groups. We outline a robust, reliable, and user-friendly protocol for quantitative analysis of lipid profiles in subcellular structures. This method expands the capabilities of Raman-based lipidomics toward the analysis of single organelles within either live or fixed cells, thus allowing an unprecedented measure of organellar lipid heterogeneity and opening new quantitative ways to study the phenotypic variability in normal and diseased cells.
Project description:Human brain lipidomics have elucidated structural lipids and lipid signal transduction pathways in neurologic diseases. Such studies have traditionally sourced tissue exclusively from brain bank biorepositories, however, limited inventories signal that these facilities may not be able to keep pace with this growing research domain. Formalin fixed, whole body donors willed to academic institutions offer a potential supplemental tissue source, the lipid profiles of which have yet to be described. To determine the potential of these subjects in lipid analysis, the lipid levels of fresh and fixed frontal cortical gray matter of human donors were compared using high resolution electrospray ionization mass spectrometry. Results revealed commensurate levels of specific triacylglycerols, diacylglycerols, hexosyl ceramides, and hydroxy hexosyl ceramides. Baseline levels of these lipid families in human fixed tissue were identified <i>via</i> a broader survey study covering six brain regions: cerebellar gray matter, superior cerebellar peduncle, gray and subcortical white matter of the precentral gyrus, periventricular white matter, and internal capsule. Whole body donors may therefore serve as supplemental tissue sources for lipid analysis in a variety of clinical contexts, including Parkinson's disease, Alzheimer's disease, Lewy body dementia, multiple sclerosis, and Gaucher's disease.