Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Decoding Distinct Ganglioside Patterns of Native and Differentiated Mesenchymal Stem Cells by a Novel Glycolipidomics Profiling Strategy

Gangliosides are an indispensable glycolipid class concentrated on cell surfaces with a critical role in stem cell differentiation. Nonetheless, owing to the lack of suitable methods for scalable analysis covering the full scope of ganglioside molecular diversity, their mechanistic properties in signaling and differentiation remain undiscovered to a large extent. This work introduces a sensitive and comprehensive ganglioside assay based on liquid chromatography, high-resolution mass spectrometry, and multistage fragmentation. Complemented by an open-source data evaluation workflow, we provide automated in-depth lipid species-level and molecular species-level annotation based on decision rule sets for all major ganglioside classes. Compared to conventional state-of-the-art methods, the presented ganglioside assay offers (1) increased sensitivity, (2) superior structural elucidation, and (3) the possibility to detect novel ganglioside species. A major reason for the highly improved sensitivity is the optimized spectral readout based on the unique capability of two parallelizable mass analyzers for multistage fragmentation. We demonstrated the high-throughput universal capability of our novel analytical strategy by identifying 254 ganglioside species. As a proof of concept, 137 unique gangliosides were annotated in native and differentiated human mesenchymal stem cells including 78 potential cell-state-specific markers and 38 previously unreported gangliosides. A general increase of the ganglioside numbers upon differentiation was observed as well as cell-state-specific clustering based on the ganglioside species patterns. The combination of the developed glycolipidomics assay with the extended automated annotation tool enables comprehensive in-depth ganglioside characterization as shown on biological samples of interest. Our results suggest ganglioside patterns as a promising quality control tool for stem cells and their differentiation products. Additionally, we believe that our analytical workflow paves the way for probing glycolipid-based biochemical processes shedding light on the enigmatic processes of gangliosides and glycolipids in general.

α-Linolenic acid and product octadecanoids in Styrian pumpkin seeds and oils: How processing impacts lipidomes of fatty acid, triacylglycerol and oxylipin molecular structures

Styrian pumpkin seed oil is a conditioned green-colored oil renowned for nutty smell and taste. Due to α-linolenic acid (ALA) contents below 1% of total fatty acids and the prospect of nutritional health claims based on its potential oxidation products, we investigated the fate of ALA and product oxylipins in the course of down-stream processing of seeds and in oils. Lipidomic analyses with Lipid Data Analyzer 2.8.1 revealed: Processing did not change (1) main fatty acid composition in the oils, (2) amounts of triacylglycerol species, (3) structures of triacylglycerol molecular species containing ALA. (4) Minor precursor ALA in fresh Styrian and normal pumpkins produced 6 product phytoprostanes in either cultivar, quantitatively more in the latter. (5) In oil samples 7 phytoprostanes and 2 phytofurans were detected. The latter two are specific for their presence in pumpkin seed oils, of note, quantitatively more in conditioned oils than in cold-pressed native oils.

Nonalcoholic fatty liver disease stratification by liver lipidomics

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

Automated Annotation of Sphingolipids Including Accurate Identification of Hydroxylation Sites Using MSn Data

Sphingolipids constitute a heterogeneous lipid category that is involved in many key cellular functions. For high-throughput analyses of sphingolipids, tandem mass spectrometry (MS/MS) is the method of choice, offering sufficient sensitivity, structural information, and quantitative precision for detecting hundreds to thousands of species simultaneously. While glycerolipids and phospholipids are predominantly non-hydroxylated, sphingolipids are typically dihydroxylated. However, species containing one or three hydroxylation sites can be detected frequently. This variability in the number of hydroxylation sites on the sphingolipid long-chain base and the fatty acyl moiety produces many more isobaric species and fragments than for other lipid categories. Due to this complexity, the automated annotation of sphingolipid species is challenging, and incorrect annotations are common. In this study, we present an extension of the Lipid Data Analyzer (LDA) "decision rule set" concept that considers the structural characteristics that are specific for this lipid category. To address the challenges inherent to automated annotation of sphingolipid structures from MS/MS data, we first developed decision rule sets using spectra from authentic standards and then tested the applicability on biological samples including murine brain and human plasma. A benchmark test based on the murine brain samples revealed a highly improved annotation quality as measured by sensitivity and reliability. The results of this benchmark test combined with the easy extensibility of the software to other (sphingo)lipid classes and the capability to detect and correctly annotate novel sphingolipid species make LDA broadly applicable to automated sphingolipid analysis, especially in high-throughput settings.

Chasing the Major Sphingolipids on Earth: Automated Annotation of Plant Glycosyl Inositol Phospho Ceramides by Glycolipidomics

Glycosyl inositol phospho ceramides (GIPCs) are the major sphingolipids on earth, as they account for a considerable fraction of the total lipids in plants and fungi, which in turn represent a large portion of the biomass on earth. Despite their obvious importance, GIPC analysis remains challenging due to the lack of commercial standards and automated annotation software. In this work, we introduce a novel GIPC glycolipidomics workflow based on reversed-phase ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry. For the first time, automated GIPC assignment was performed using the open-source software Lipid Data Analyzer (LDA), based on platform-independent decision rules. Four different plant samples (salad, spinach, raspberry, and strawberry) were analyzed and the results revealed 64 GIPCs based on accurate mass, characteristic MS2 fragments and matching retention times. Relative quantification using lactosyl ceramide for internal standardization revealed GIPC t18:1/h24:0 as the most abundant species in all plants. Depending on the plant sample, GIPCs contained mainly amine, N-acetylamine or hydroxyl residues. Most GIPCs revealed a Hex-HexA-IPC core and contained a ceramide part with a trihydroxylated t18:0 or a t18:1 long chain base and hydroxylated fatty acid chains ranging from 16 to 26 carbon atoms in length (h16:0-h26:0). Interestingly, four GIPCs containing t18:2 were observed in the raspberry sample, which was not reported so far. The presented workflow supports the characterization of different plant samples by automatic GIPC assignment, potentially leading to the identification of new GIPCs. For the first time, automated high-throughput profiling of these complex glycolipids is possible by liquid chromatography-high-resolution tandem mass spectrometry and subsequent automated glycolipid annotation based on decision rules.

Identification and Quantification of Oxidized Lipids in LC-MS Lipidomics Data

Changes in lipid homeostasis can lead to a plethora of diseases, raising the importance of reliable identification and measurement of lipids enabled by bioinformatics tools. However, due to the enormous diversity of lipids, most contemporary tools cover only a marginal range of lipid classes. To reduce such a shortcoming, this work extends the lipid species covered by Lipid Data Analyzer (LDA) to galactolipids and oxidized lipids. Appropriate mass lists were generated for MS1 identifications and the proprietary decision rule sets were extended for MS2 identifications of the novel lipid classes. Furthermore, LDA was extended to enable identification of oxidatively modified fatty acyl chains. With these extensions, LDA can reliably identify the most important galactolipids as well as oxidatively modified versions of the 22 previously implemented lipid classes. Comparison with other up to date lipidomics tools show that LDA has a better coverage of the newly implemented lipid species. The extended version of LDA provides researchers with a powerful platform to elucidate diseases caused by perturbations in the oxidized lipidome. LDA is freely available from https://genome.tugraz.at/lda.

A Metabolomics Workflow for Analyzing Complex Biological Samples Using a Combined Method of Untargeted and Target-List Based Approaches

In the highly dynamic field of metabolomics, we have developed a method for the analysis of hydrophilic metabolites in various biological samples. Therefore, we used hydrophilic interaction chromatography (HILIC) for separation, combined with a high-resolution mass spectrometer (MS) with the aim of separating and analyzing a wide range of compounds. We used 41 reference standards with different chemical properties to develop an optimal chromatographic separation. MS analysis was performed with a set of pooled biological samples human cerebrospinal fluid (CSF), and human plasma. The raw data was processed in a first step with Compound Discoverer 3.1 (CD), a software tool for untargeted metabolomics with the aim to create a list of unknown compounds. In a second step, we combined the results obtained with our internally analyzed reference standard list to process the data along with the Lipid Data Analyzer 2.6 (LDA), a software tool for a targeted approach. In order to demonstrate the advantages of this combined target-list based and untargeted approach, we not only compared the relative standard deviation (%RSD) of the technical replicas of pooled plasma samples (n = 5) and pooled CSF samples (n = 3) with the results from CD, but also with XCMS Online, a well-known software tool for untargeted metabolomics studies. As a result of this study we could demonstrate with our HILIC-MS method that all standards could be either separated by chromatography, including isobaric leucine and isoleucine or with MS by different mass. We also showed that this combined approach benefits from improved precision compared to well-known metabolomics software tools such as CD and XCMS online. Within the pooled plasma samples processed by LDA 68% of the detected compounds had a %RSD of less than 25%, compared to CD and XCMS online (57% and 55%). The improvements of precision in the pooled CSF samples were even more pronounced, 83% had a %RSD of less than 25% compared to CD and XCMS online (28% and 8% compounds detected). Particularly for low concentration samples, this method showed a more precise peak area integration with its 3D algorithm and with the benefits of the LDAs graphical user interface for fast and easy manual curation of peak integration. The here-described method has the advantage that manual curation for larger batch measurements remains minimal due to the target list containing the information obtained by an untargeted approach.

jmzTab-M: A Reference Parser, Writer, and Validator for the Proteomics Standards Initiative mzTab 2.0 Metabolomics Standard

mzTab 2.0 for metabolomics (mzTab-M) is the most recent standard format developed in collaboration by the Proteomics and Metabolomics Standards Initiatives including contributions by the recently founded Lipidomics Standards Initiative. mzTab-M is a redesign of the original mzTab format which was geared toward reporting of proteomics results and, as such, provided only limited support for metabolites. As a tab-delimited, spreadsheet-like format, mzTab-M captures experimental metadata, summary information on small molecules across assays, MS features as a basis for quantitation, and evidence to support the reporting of individual or feature group identifications. Here, we present the Java reference implementation for reading, writing, and validating mzTab-M files. Furthermore, we provide a web application for conveniently validating mzTab-M files by a graphical user interface, and a command line validator that accompanies the library. The jmzTab-M library, version 1.0.4 ( https://doi.org/10.5281/zenodo.3362151 ), is available at https://github.com/lifs-tools/jmzTab-m and from Maven Central at https://search.maven.org/search?q=jmztabm under the terms of the open source Apache License 2.0. The web application as well as the Python and R implementations are available at https://github.com/lifs-tools . The respective Web sites link to additional API documentation, as well as to usage examples.

mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

Deciphering lipid structures based on platform-independent decision rules

We achieve automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry using decision rule sets embedded in Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2). Using various low- and high-resolution mass spectrometry instruments with several collision energies, we proved the method's platform independence. We propose that the software's reliability, flexibility, and ability to identify novel lipid molecular species may now render current state-of-the-art lipid libraries obsolete.

Proposal for a common nomenclature for fragment ions in mass spectra of lipids

Advances in mass spectrometry-based lipidomics have in recent years prompted efforts to standardize the annotation of the vast number of lipid molecules that can be detected in biological systems. These efforts have focused on cataloguing, naming and drawing chemical structures of intact lipid molecules, but have provided no guidelines for annotation of lipid fragment ions detected using tandem and multi-stage mass spectrometry, albeit these fragment ions are mandatory for structural elucidation and high confidence lipid identification, especially in high throughput lipidomics workflows. Here we propose a nomenclature for the annotation of lipid fragment ions, describe its implementation and present a freely available web application, termed ALEX123 lipid calculator, that can be used to query a comprehensive database featuring curated lipid fragmentation information for more than 430,000 potential lipid molecules from 47 lipid classes covering five lipid categories. We note that the nomenclature is generic, extendable to stable isotope-labeled lipid molecules and applicable to automated annotation of fragment ions detected by most contemporary lipidomics platforms, including LC-MS/MS-based routines.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines multiple selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Calibration showed linearity ranges of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples.

Lipidomics: Prospects from a technological perspective

Over the last two decades, lipidomics has evolved into an 'omics' technology pari passu with benchmarking 'omics' technologies, such as genomics or proteomics. The driving force behind this development was a constant advance in mass spectrometry and related technologies. The aim of this opinion article is to give the interested reader a concise but still comprehensive overview about the technological state of the art in lipidomics, current challenges and perspectives for future development. As such, this article guides through the whole workflow of lipidomics, from sampling to data analysis. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

ATGL and CGI-58 are lipid droplet proteins of the hepatic stellate cell line HSC-T6

Lipid droplets (LDs) of hepatic stellate cells (HSCs) contain large amounts of vitamin A [in the form of retinyl esters (REs)] as well as other neutral lipids such as TGs. During times of insufficient vitamin A availability, RE stores are mobilized to ensure a constant supply to the body. To date, little is known about the enzymes responsible for the hydrolysis of neutral lipid esters, in particular of REs, in HSCs. In this study, we aimed to identify LD-associated neutral lipid hydrolases by a proteomic approach using the rat stellate cell line HSC-T6. First, we loaded cells with retinol and FAs to promote lipid synthesis and deposition within LDs. Then, LDs were isolated and lipid composition and the LD proteome were analyzed. Among other proteins, we found perilipin 2, adipose TG lipase (ATGL), and comparative gene identification-58 (CGI-58), known and established LD proteins. Bioinformatic search of the LD proteome for α/β-hydrolase fold-containing proteins revealed no yet uncharacterized neutral lipid hydrolases. In in vitro activity assays, we show that rat (r)ATGL, coactivated by rat (r)CGI-58, efficiently hydrolyzes TGs and REs. These findings suggest that rATGL and rCGI-58 are LD-resident proteins in HSCs and participate in the mobilization of both REs and TGs.

Determination of oxidized phosphatidylcholines by hydrophilic interaction liquid chromatography coupled to Fourier transform mass spectrometry

A novel liquid chromatography-mass spectrometry (LC-MS) approach for analysis of oxidized phosphatidylcholines by an Orbitrap Fourier Transform mass spectrometer in positive electrospray ionization (ESI) coupled to hydrophilic interaction liquid chromatography (HILIC) was developed. This method depends on three selectivity criteria for separation and identification: retention time, exact mass at a resolution of 100,000 and collision induced dissociation (CID) fragment spectra in a linear ion trap. The process of chromatography development showed the best separation properties with a silica-based Kinetex column. This type of chromatography was able to separate all major lipid classes expected in mammalian samples, yielding increased sensitivity of oxidized phosphatidylcholines over reversed phase chromatography. Identification of molecular species was achieved by exact mass on intact molecular ions and CID tandem mass spectra containing characteristic fragments. Due to a lack of commercially available standards, method development was performed with copper induced oxidation products of palmitoyl-arachidonoyl-phosphatidylcholine, which resulted in a plethora of lipid species oxidized at the arachidonoyl moiety. Validation of the method was done with copper oxidized human low-density lipoprotein (LDL) prepared by ultracentrifugation. In these LDL samples we could identify 46 oxidized molecular phosphatidylcholine species out of 99 possible candidates.

3DSpectra: A 3-dimensional quantification algorithm for LC-MS labeled profile data

Mass spectrometry-based proteomics can generate highly informative datasets, as profile three-dimensional (3D) LC-MS data: LC-MS separates peptides in two dimensions (time, m/z) minimizing their overlap, and profile acquisition enhances quantification. To exploit both data features, we developed 3DSpectra, a 3D approach embedding a statistical method for peptide border recognition. 3DSpectra efficiently accesses profile data by means of mzRTree, and makes use of a priori metadata, provided by search engines, to quantify the identified peptides. An isotopic distribution model, shaped by a bivariate Gaussian Mixture Model (GMM), which includes a noise component, is fitted to the peptide peaks using the expectation-maximization (EM) approach. The EM starting parameters, i.e., the centers and shapes of the Gaussians, are retrieved from the metadata. The borders of the peaks are delimited by the GMM iso-density curves, and noisy or outlying data are discarded from subsequent analysis. The 3DSpectra program was compared to ASAPRatio for a controlled mixture of Isotope-Coded Protein Labels (ICPL) labeled proteins, which were mixed at predefined ratios and acquired in enhanced profile mode, in triplicate. The 3DSpectra software showed significantly higher linearity, quantification accuracy, and precision than did ASAPRatio in this real use case simulation where the true ratios are known, and it also achieved wider peptide coverage and dynamic range.

BIOLOGICAL SIGNIFICANCE

Quantitative proteomics is pivotal for many systems biology related fields, such as biomarker discovery. The quantification quality provided by the adopted software is crucial for the success of protein differential expression studies. To determine the reliability of a quantitative computational method, we suggest evaluating performance parameters like accuracy and precision of the quantifications, robustness to outliers and proteome coverage. A quantitative comparison of these parameters is highly desirable since it enables to benchmark software performance. We applied this strategy to 3DSpectra, a 3-dimensional approach to spectra analysis for MS1 peptide quantification. It distinguishes peptide peaks from spurious peaks interfering in the survey scan. 3DSpectra was compared to ASAPRatio in terms of quantification quality performance parameters and showed an overall improvement.

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.

Quantitation of phosphatidic acid and lysophosphatidic acid molecular species using hydrophilic interaction liquid chromatography coupled to electrospray ionization high resolution mass spectrometry

A method for a highly selective and sensitive identification and quantitation of lysophosphatidic acid (LPA) and phosphatidic acid (PA) molecular species was developed using hydrophilic interaction liquid chromatography (HILIC) followed by negative-ion electrospray ionization high resolution mass spectrometry. Different extraction methods for the polar LPA and PA species were compared and a modified Bligh & Dyer extraction by addition of 0.1M hydrochloric acid resulted in a ≈1.2-fold increase of recovery for the 7 PA and a more than 15-fold increase for the 6 LPA molecular species of a commercially available natural mix compared to conventional Bligh & Dyer extraction. This modified Bligh & Dyer extraction did not show any artifacts resulting from hydrolysis of natural abundant phospholipids. The developed HILIC method is able to separate all PA and LPA species from major polar membrane lipid classes which might have suppressive effects on the minor abundant lipid classes of interest. The elemental compositions of intact lipid species are provided by the high mass resolution of 100,000 and high mass accuracy below 3ppm of the Orbitrap instrument. Additionally, tandem mass spectra were generated in a parallel data dependent acquisition mode in the linear ion trap to provide structural information at molecular level. Limits of quantitation were identified at 45fmol on column and the dynamic range reaches 20pmol on column, covering the range of natural abundance well. By applying the developed method to mouse brain it can be shown that phosphatidic acid contains less unsaturated fatty acids with PA 34:1 and PA 36:1 as the major species. In contrast, for LPA species a high content of polyunsaturated fatty acids (LPA 20:4 and LPA 22:6) was quantified.

The impact of genetic stress by ATGL deficiency on the lipidome of lipid droplets from murine hepatocytes

We showed earlier that nutritional stress like starvation or high-fat diet resulted in phenotypic changes in the lipidomes of hepatocyte lipid droplets (LDs), representative for the pathophysiological status of the mouse model. Here we extend our former study by adding genetic stress due to knockout (KO) of adipocyte triglyceride lipase (ATGL), the rate limiting enzyme in LD lipolysis. An intervention trial for 6 weeks with male wild-type (WT) and ATGL-KO mice was carried out; both genotypes were fed lab chow or were exposed to short-time starvation. Isolated LDs were analyzed by LC-MS/MS. Triacylglycerol, diacylglycerol, and phosphatidylcholine lipidomes, in that order, provided the best phenotypic signatures characteristic for respective stresses applied to the animals. This was evidenced at lipid species level by principal component analysis, calculation of average values for chain-lengths and numbers of double bonds, and by visualization in heat maps. Structural backgrounds for analyses and metabolic relationships were elaborated at lipid molecular species level. Relating our lipidomic data to nonalcoholic fatty liver diseases of nutritional and genetic etiologies with or without accompanying insulin resistance, phenotypic distinction in hepatocyte LDs dependent on insulin status emerged. Taken together, lipidomes of hepatocyte LDs are sensitive responders to nutritional and genetic stress.

A bioinformatics approach for integrated transcriptomic and proteomic comparative analyses of model and non-sequenced anopheline vectors of human malaria parasites

Malaria morbidity and mortality caused by both Plasmodium falciparum and Plasmodium vivax extend well beyond the African continent, and although P. vivax causes between 80 and 300 million severe cases each year, vivax transmission remains poorly understood. Plasmodium parasites are transmitted by Anopheles mosquitoes, and the critical site of interaction between parasite and host is at the mosquito's luminal midgut brush border. Although the genome of the “model” African P. falciparum vector, Anopheles gambiae, has been sequenced, evolutionary divergence limits its utility as a reference across anophelines, especially non-sequenced P. vivax vectors such as Anopheles albimanus. Clearly, technologies and platforms that bridge this substantial scientific gap are required in order to provide public health scientists with key transcriptomic and proteomic information that could spur the development of novel interventions to combat this disease. To our knowledge, no approaches have been published that address this issue. To bolster our understanding of P. vivax–An. albimanus midgut interactions, we developed an integrated bioinformatic-hybrid RNA-Seq-LC-MS/MS approach involving An. albimanus transcriptome (15,764 contigs) and luminal midgut subproteome (9,445 proteins) assembly, which, when used with our custom Diptera protein database (685,078 sequences), facilitated a comparative proteomic analysis of the midgut brush borders of two important malaria vectors, An. gambiae and An. albimanus.

Lipidomic analysis of lipid droplets from murine hepatocytes reveals distinct signatures for nutritional stress

Liver steatosis can be induced by fasting or high-fat diet. We investigated by lipidomic analysis whether such metabolic states are reflected in the lipidome of hepatocyte lipid droplets (LDs) from mice fed normal chow diet (FED), fasted (FAS), or fed a high-fat diet (HFD). LC-MS/MS at levels of lipid species profiles and of lipid molecular species uncovered a FAS phenotype of LD enriched in triacylglycerol (TG) molecular species with very long-chain (VLC)-PUFA residues and an HFD phenotype with less unsaturated TG species in addition to characteristic lipid marker species. Nutritional stress did not result in dramatic structural alterations in diacylglycerol (DG) and phospholipid (PL) classes. Moreover, molecular species of bulk TG and of DG indicated concomitant de novo TG synthesis and lipase-catalyzed degradation to be active in LDs. DG species with VLC-PUFA residues would be preferred precursors for phosphatidylcholine (PC) species, the others for TG molecular species. In addition, molecular species of PL classes fitted the hepatocyte Kennedy and phosphatidylethanolamine methyltransferase pathways. We demonstrate that lipidomic analysis of LDs enables phenotyping of nutritional stress. TG species are best suited for such phenotyping, whereas structural analysis of TG, DG, and PL molecular species provides metabolic insights.

Bioinformatics tools and challenges in structural analysis of lipidomics MS/MS data

Lipidomics, the systematic study of the lipid composition of a cell or tissue, is an invaluable complement to knowledge gained by genomics and proteomics research. Mass spectrometry provides a means to detect hundreds of lipids in parallel, and this includes low abundance species of lipids. Nevertheless, frequently occurring isobaric and isomeric lipid species complicate lipidomics analyses from an analytical and bioinformatics perspective. Various MS/MS strategies have evolved to resolve ambiguous identifications of lipid species, and these strategies have been supported by corresponding bioinformatics analysis tools. This review intends to familiarize readers with available bioinformatics MS/MS analysis tools and databases, the structural information obtainable from these, and their applicability to different MS/MS strategies. Finally, future challenges in detecting double bond positions are investigated from a bioinformatics perspective.

A comprehensive method for lipid profiling by liquid chromatography-ion cyclotron resonance mass spectrometry

This work aims to combine chromatographic retention, high mass resolution and accuracy, MS/MS spectra, and a package for automated identification and quantitation of lipid species in one platform for lipidomic analysis. The instrumental setup elaborated comprises reversed-phase HPLC coupled to a Fourier transform ion cyclotron resonance mass spectrometer (LTQ-FT), and Lipid Data Analyzer (LDA) software. Data analysis for lipid species quantification in this platform is based on retention time, mass resolution of 200,000, and mass accuracy below 2 ppm. In addition, automatically generated MS/MS spectra provide structural information at molecular level. This LC/MS technology allows analyzing complex biological samples in a quantitative manner as shown here paradigmatically for murine lipid droplets having a huge surplus of triacylglycerol species. Chromatographic preseparation of the bulk lipid class alleviates the problem of ion suppression of lipid species from other classes. Extension of 1D to 2D chromatography is possible, yet time consuming. The platform affords unambiguous detection of lipid species as low as 0.1‰ within major lipid classes. Taken together, a novel lipidomic LC/MS platform based on chromatographic retention, high mass resolution and accuracy, MS/MS analysis, and quantitation software enables analysis of complex samples as demonstrated for lipid droplets.

Lipid Data Analyzer: unattended identification and quantitation of lipids in LC-MS data

MOTIVATION

The accurate measurement of the lipidome permits insights into physiological and pathological processes. Of the present high-throughput technologies, LC-MS especially bears potential of monitoring quantitative changes in hundreds of lipids simultaneously. In order to extract valuable information from huge amount of mass spectrometry data, the aid of automated, reliable, highly sensitive and specific analysis algorithms is indispensable.

RESULTS

We present here a novel approach for the quantitation of lipids in LC-MS data. The new algorithm obtains its analytical power by two major innovations: (i) a 3D algorithm that confines the peak borders in m/z and time direction and (ii) the use of the theoretical isotopic distribution of an analyte as selection/exclusion criterion. The algorithm is integrated in the Lipid Data Analyzer (LDA) application which additionally provides standardization, a statistics module for results analysis, a batch mode for unattended analysis of several runs and a 3D viewer for the manual verification. The statistics module offers sample grouping, tests between sample groups and export functionalities, where the results are visualized by heat maps and bar charts. The presented algorithm has been applied to data from a controlled experiment and to biological data, containing analytes distributed over an intensity range of 10(6). Our approach shows improved sensitivity and an extremely high positive predictive value compared with existing methods. Consequently, the novel algorithm, integrated in a user-friendly application, is a valuable improvement in the high-throughput analysis of the lipidome.

IMPLEMENTATION AND AVAILABILITY

The Java application is freely available for non-commercial users at http://genome.tugraz.at/lda. Raw data associated with this manuscript may be downloaded from ProteomeCommons.org Tranche using the following hash: ZBh3nS5bXk6I/Vn32tB5Vh0qnMpVIW71HByFFQqM0RmdF4/4Hcn H3Wggh9kU2teYVOtM1JWwHIeMHqSS/bc2yYNFmyUAAAAAAACl DQ ==

MASPECTRAS 2: An integration and analysis platform for proteomic data

MASPECTRAS 2 is a freely available platform for integrating MS protein identifications with information from the major bioinformatics databases (ontologies, domains, literature, etc.). It assists researchers in understanding their data and publishing through sample comparisons, targeted queries, summaries, and exports in multiple formats such as PRIDE XML (Jones et al., Nucleic Acids Res. 2008, 36, D878-D883). MASPECTRAS 2 also comprises mechanisms to facilitate its integration in a high-throughput infrastructure. We illustrate application of MASPECTRAS 2 with unpublished tyrosine kinase inhibitor drug proteomics profiles in cancerous cells.

PathwayExplorer: web service for visualizing high-throughput expression data on biological pathways

While generation of high-throughput expression data is becoming routine, the fast, easy, and systematic presentation and analysis of these data in a biological context is still an obstacle. To address this need, we have developed PathwayExplorer, which maps expression profiles of genes or proteins simultaneously onto major, currently available regulatory, metabolic and cellular pathways from KEGG, BioCarta and GenMAPP. PathwayExplorer is a platform-independent web server application with an optional standalone Java application using a SOAP (simple object access protocol) interface. Mapped pathways are ranked for the easy selection of the pathway of interest, displaying all available genes of this pathway with their expression profiles in a selectable and intuitive color code. Pathway maps produced can be downloaded as PNG, JPG or as high-resolution vector graphics SVG. The web service is freely available at https://pathwayexplorer.genome.tugraz.at; the standalone client can be downloaded at http://genome.tugraz.at.