Systems level analysis of lipidome

Lipids, once thought to be mainly for energy-storage and structural purpose, have now gained immense recognition as a class of critical metabolites with versatile functions. The diversity and complexity of the cellular lipids are the main challenge for the comprehensive analysis of a lipidome. Lipidomics, which aims at mapping all of the lipids in a cell, is expanded rapidly in recent years, mainly attributed to recent advances in mass spectrometry (MS). MS-based lipidomic approaches developed recently allow the quick profiling of hundreds of lipids in a crude lipid extract. With the aid of latest computational tools/software (chemometrics), aberrant lipid metabolites or important signaling lipid(s) could be easily identified using unbiased lipid profiling approaches. Further tandem MS (MS/MS)-based lipidomic approaches, known as targeted approaches and able to convey structural information, hold the promise for high-throughput lipidome analysis. In this review, I discussed the basic strategy for systems level analysis of lipidome in biomedical study.     

The LUX Score: A Metric for Lipidome Homology

A lipidome is the set of lipids in a given organism, cell or cell compartment and this set reflects the organism’s synthetic pathways and interactions with its environment. Recently, lipidomes of biological model organisms and cell lines were published and the number of functional studies of lipids is increasing. In this study we propose a homology metric that can quantify systematic differences in the composition of a lipidome. Algorithms were developed to 1. consistently convert lipids structure into SMILES, 2. determine structural similarity between molecular species and 3. describe a lipidome in a chemical space model. We tested lipid structure conversion and structure similarity metrics, in detail, using sets of isomeric ceramide molecules and chemically related phosphatidylinositols. Template-based SMILES showed the best properties for representing lipid-specific structural diversity. We also show that sequence analysis algorithms are best suited to calculate distances between such template-based SMILES and we adjudged the Levenshtein distance as best choice for quantifying structural changes. When all lipid molecules of the LIPIDMAPS structure database were mapped in chemical space, they automatically formed clusters corresponding to conventional chemical families. Accordingly, we mapped a pair of lipidomes into the same chemical space and determined the degree of overlap by calculating the Hausdorff distance. We named this metric the ‘Lipidome jUXtaposition (LUX) score’. First, we tested this approach for estimating the lipidome similarity on four yeast strains with known genetic alteration in fatty acid synthesis. We show that the LUX score reflects the genetic relationship and growth temperature better than conventional methods although the score is based solely on lipid structures. Next, we applied this metric to high-throughput data of larval tissue lipidomes of Drosophila. This showed that the LUX score is sufficient to cluster tissues and determine the impact of nutritional changes in an unbiased manner, despite the limited information on the underlying structural diversity of each lipidome. This study is the first effort to define a lipidome homology metric based on structures that will enrich functional association of lipids in a similar manner to measures used in genetics. Finally, we discuss the significance of the LUX score to perform comparative lipidome studies across species borders.     

Simultaneous extraction and rapid visualization of peptidomic and lipidomic body fluids fingerprints using mesoporous aluminosilicate and MALDI‐TOF MS

Herein we report the use of mesoporous aluminosilicate (MPAS) for the simultaneous extraction of peptides and lipids from complex body fluids such as human plasma and synovial fluid. We show that MPAS particles, given their mesostructural features with nanometric pore size and high surface area, are an efficient device for simultaneous extraction of peptidome and lipidome from as little as a few microliters of body fluids. The peptides and the lipids, selected and enriched by MPAS particles and rapidly visualized by MALDI‐TOF MS, could form part of a diagnostic profile of the “peptidome” and the “lipidome” of healthy versus diseased subjects in comparative studies. The ability of this approach to rapidly reveal the overall pattern of changes in both lipidome and peptidome signatures of complex biofluids could be of valuable interest for handling large numbers of samples required in ‐omics studies for the purpose of finding novel biomarkers.     

Data-dependent electron capture dissociation FT-ICR mass spectrometry for proteomic analyses

Electron capture dissociation (ECD) offers many benefits for the analysis of peptides and proteins, and consequently shows great potential for the field of proteomics. Recent developments have reduced the time scale required for ECD to milliseconds resulting in the technique's compatibility with on-line separation techniques, e.g., HPLC. Here, we demonstrate incorporation of ECD into a high-throughput data-dependent LC-MS/MS approach for the analysis of proteomic samples. The approach is applied to analysis of the protein Fc-ROR2 isolated from chondrocytes and is the first example of LC-ECD-MS/MS of such a sample. Protein sequence coverage was 29%. Within that coverage, fifteen peptides were isolated and subjected to ECD. In most cases, the sequence tag generated by ECD was over 70% (in terms of the number of peptide backbone cleavages). The ECD data were searched against the nonredundant human NCBI database using the SEQUEST algorithm. Protein ROR2 was assigned, as was IgG (Fc domain). The results demonstrate the suitability of ECD as an integral technique in high-throughput proteomic strategies.     

High-throughput quantification of phosphatidylcholine and sphingomyelin by electrospray ionization tandem mass spectrometry coupled with isotope correction algorithm

The choline head group containing phosphatidylcholine (PC) and sphingomyelin (SPM) are major eukaryotic lipid components playing an important role in forming membrane microdomains and serve as precursor of signaling molecules. Both lipids can be monitored by positive ion mode electrospray tandem mass spectrometry using a parent ion scan of m/z 184. Although PC species appear at even m/z and SPM species at odd m/z, there may be a significant overlap of their isotopes. In order to separate PC and SPM species, an isotope correction algorithm was established, which utilizes calculated isotope percentages to correct the measured peak intensities for their isotopic overlap. We could demonstrate that this approach was applicable to correct the isotope overlap resulting from spiked PC and SPM species. Quantification was achieved by addition of different PC and SPM species prior to lipid extraction. The developed assay showed a precision, detection limit and robustness sufficient for routine analysis. Furthermore, an analysis time of only 1.3 min combined with automated data analysis using self-programmed Excel Macros allows high-throughput analysis. In summary, this assay may be a valuable tool for detailed lipid analysis of PC and SPM species in a variety of sample materials.     

The emergence of yeast lipidomics

The emerging field of lipidomics, driven by technological advances in lipid analysis, provides greatly enhanced opportunities to characterize, on a quantitative or semi-quantitative level, the entire spectrum of lipids, or lipidome, in specific cell types. When combined with advances in other high throughput technologies in genomics and proteomics, lipidomics offers the opportunity to analyze the unique roles of specific lipids in complex cellular processes such as signaling and membrane trafficking. The yeast system offers many advantages for such studies, including the relative simplicity of its lipidome as compared to mammalian cells, the relatively high proportion of structural and regulatory genes of lipid metabolism which have been assigned and the excellent tools for molecular genetic analysis that yeast affords. The current state of application of lipidomic approaches in yeast and the advantages and disadvantages of yeast for such studies are discussed in this report.     

Human tear fluid lipidome: from composition to function

We have explored human aqueous tear fluid lipidome with an emphasis to identify the major lipids. We also address the physiological significance of the lipidome. The tears were analysed using thin layer chromatographic, enzymatic and mass spectrometric techniques. To emphasize the physiological aspect of the lipidome, we modelled the spreading of the non-polar tear fluid lipids at air-water interface in macroscopic scale with olive oil and egg yolk phosphatidylcholine. Based on enzymatic analysis the respective concentrations of choline-containing lipids, triglycerides, and cholesteryl esters were 48±14, 10±0, and 21±18 μM. Ultra performance liquid chromatography quadrupole time of flight mass spectrometry analysis showed that phosphatidylcholine and phosphatidylethanolamine were the two most common polar lipids comprising 88±6% of all identified lipids. Triglycerides were the only non-polar lipids detected in mass spectrometric analysis i.e. no cholesteryl or wax esters were identified. The spreading experiments show that the presence of polar lipids is an absolute necessity for a proper spreading of non-polar tear fluid lipids. We provide evidence that polar lipids are the most common lipid species. Furthermore, we provide a physiological rationale for the observed lipid composition. The results open insights into the functional role of lipids in the tear fluid and also aids in providing new means to understand and treat diseases of the ocular surface.     

The lipidome as a composite biomarker of the modifiable part of the risk of breast cancer

The potential for dietary fat to prevent breast cancer makes identification of defined molecules a mandatory step. In order to circumvent the limitations and/or bias of dietary exposure assessment tools, we have used the fatty acid composition of white adipose tissue as biomarker of past lipid intake. When considered separately, candidate fatty acids identified as favourable on the basis of their association with breast cancer risk have usually led to inconsistent results in dietary intervention studies carried out in rats. This inconsistency indicates that any approach based on a single fatty acid should be abandoned for an integrated view over the complex lipid interactions, which finally determines the lipidome, the lipid profile that is found in individuals. We reappraised the role of the complete lipid profile through a comprehensive study of adipose tissue fatty acids obtained in patients with benign or malignant breast tumors. Rather than a single fatty acid, a composite indicator combining elevated monounsaturates and low n-6/n-3 fatty acid ratio was associated with decreased breast cancer risk. The lipidome may provide the opportunity to quantify the modifiable part of the risk of breast cancer. The lipidome may be used as a template for designing proper dietary modifications in order to delay the occurrence of breast cancer. Which dietary modifications should be undertaken in order to bring a pertinent change to the lipidome with respect to the risk of breast cancer is currently unknown. The lipidome may allow the individualization of a high risk population of women, who may be targeted for a dietary prevention of breast cancer. The setting and validation of a high-throughput lipidomic station with analytical capabilities fitted to the need of mass screening is required. These two locks must be resolved before a primary prevention of breast cancer by diet could be contemplated.     

Application of the accurate mass and time tag approach in studies of the human blood lipidome

We report a preliminary demonstration of the accurate mass and time (AMT) tag approach for lipidomics. Initial data-dependent LC-MS/MS analyses of human plasma, erythrocyte, and lymphocyte lipids were performed in order to identify lipid molecular species in conjunction with complementary accurate mass and isotopic distribution information. Identified lipids were used to populate initial lipid AMT tag databases containing 250 and 45 entries for those species detected in positive and negative electrospray ionization (ESI) modes, respectively. The positive ESI database was then utilized to identify human plasma, erythrocyte, and lymphocyte lipids in high-throughput LC-MS analyses based on the AMT tag approach. We were able to define the lipid profiles of human plasma, erythrocytes, and lymphocytes based on qualitative and quantitative differences in lipid abundance.     

Shotgun cross-linking analysis for studying quaternary and tertiary protein structures

We developed a new approach that employs a novel computer algorithm for the sensitive and high-throughput analysis of tertiary and quaternary interaction sites from chemically cross-linked proteins or multi-protein complexes. First, we directly analyze the digests of the chemically cross-linked proteins using only high-accuracy LC-MS/MS data. We analyze these data using a computer algorithm, we term X!Link, to find cross-links between two peptides. Our algorithm is rapid, taking only a few seconds to analyze approximately 5000 MS/MS spectra. We applied this algorithm to analyze cross-linked sites generated chemically using the amino specific reagent, BS3, in both cytochrome c and the mitochondrial division dynamin mutant, Dnm1G385D, which exists as a stable homodimer. From cytochrome c, a well-established test protein, we identified a total of 31 cross-links, 21 interpeptide and 10 intrapeptide cross-links, in 257 MS/MS spectra from a single LC-MS/MS data set. The high sensitivity of this technique is indicated by the fact that all 19 lysines in cytochrome c were detected as a cross-link product and 33% of all the Lys pairs within 20 A were also observed as a cross-link. Analysis of the cross-linked dimeric form of Dnm1G385D identified a total of 46 cross-links, 38 interpeptide and 8 intrapeptide cross-links, in 98 MS/MS spectra in a single LC-MS/MS data set. These results represent the most abundant cross-links identified in a single protein or protein dimer to date. Statistical analysis suggests a 1% false discovery rate after optimization of filtering parameters. Further analysis of the cross-links identified using our approach indicates that careful manual inspection is important for the correct assignment of cross-linking sites when multiple cross-linkable sites or several similar sequences exist. In summary, we have developed a sensitive MS-based approach to identify peptide-peptide cross-links that does not require isotopic labeling or comparison with non-cross-linked controls, making it faster and simpler than current methodologies.     

Dyslipidemia,but not hyperglycemia and insulin resistance,is associated with marked alterations in the HDL lipidome in type 2 diabetic subjects in the DIWA cohort: Impact on small HDL particles

In this study we have used mass spectrometry in order to characterize the HDL lipidome in three groups of women from the DIWA cohort; one control group, plus two groups with type 2 diabetes with insulin resistance; one dyslipidemic and one normolipidemic. The aim was to investigate whether dyslipidemia is required in addition to insulin resistance for the occurrence of an altered HDL lipidome, which in turn might impact HDL functionality. The dyslipidemic type 2 diabetic subjects were distinguished by obesity, hypertriglyceridemia with elevated apoC3, low HDL-cholesterol and chronic low grade inflammation. In a stepwise multivariate linear regression analysis, including biomarkers of dyslipidemia and insulin resistance as independent variables, only dyslipidemia showed a significant correlation with HDL lipid classes. Small HDL-particles predominated in dyslipidemic subjects in contrast to the normolipidemic diabetic and control groups, and were enriched in lysophosphatidylcholine (+ 13%), a product of proinflammatory phospholipases, and equally in two core lipids, palmitate-rich triacylglycerols and diacylglycerols (+ 77 %), thereby reflecting elevated CETP activity. Dyslipidemic small HDL particles were further distinguished not only as the primary carrier of ceramides, which promote inflammation and insulin resistance, but also by a subnormal plasmalogen/apoAI ratio, consistent with elevated oxidative stress typical of type 2 diabetes. From these data we conclude that in type 2 diabetes, dyslipidemia predominates relative to hyperglycemia for the occurrence of an altered HDL lipidome. Furthermore, dyslipidemia alters the cargo of bioactive lipids, with implications for HDL function.     

Plant lipidomics based on hydrophilic interaction chromatography coupled to ion trap time-of-flight mass spectrometry

Plants synthesize a wide range of hydrophobic compounds, generally known as lipids. Here, we report an application of liquid chromatography ion trap time-of-flight mass spectrometry (LC-IT-TOF-MS) for plant lipidomics. Using hydrophilic interaction chromatography (HILIC) for class separation, typical membrane lipids including glycerolipids, steryl glucosides and glucosylceramides, and hydrophobic plant secondary metabolites such as saponins were analyzed simultaneously. By this method, we annotated approximately 100 molecules from Arabidopsis thaliana. To demonstrate the application of this method to biological study, we analyzed Arabidopsis mutant trigalactosyldiacylglycerol3 (tgd3), which has a complex metabolic phenotype including the accumulation of unusual forms of galactolipids. Lipid profiling by LC-MS revealed that tgd3 accumulated an unusual form of digalactosyldiacylglycerol, annotated as Gal(β1 → 6)βGalDG. The compositional difference between normal and unusual forms of digalactosyldiacylglycerol was detected by this method. In addition, we analyzed well-known Arabidopsis mutants ats1-1, fad6-1, and fad7-2, which are also disrupted in lipid metabolic genes. Untargeted lipidome analysis coupled with multivariate analysis clearly discriminated the mutants and their distinctive metabolites. These results indicated that HILIC-MS is an efficient method for plant lipidomics.

     

Lipidomics as a Principal Tool for Advancing Biomedical Research

Lipidomics,which targets at the construction of a comprehensive map of lipidome comprising the entire lipid pool within a cell or tissue,is currently emerging as an independent discipline at the interf...     

Optimization for peptide sample preparation for urine peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.     

Linear discriminant analysis-based estimation of the false discovery rate for phosphopeptide identifications

The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to reanalyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the peptide scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides. The Phosphopeptide FDR Estimator software is freely available for download at http://ncrr.pnl.gov/software/.     

A protein processing filter method for bacterial identification by mass spectrometry-based proteomics

A "one-pot" alternative method for processing proteins and isolating peptide mixtures from bacterial samples is presented for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and data reduction. The conventional in-solution digestion of the protein contents of bacteria is compared to a small disposable filter unit placed inside a centrifuge vial for processing and digestion of bacterial proteins. Each processing stage allows filtration of excess reactants and unwanted byproduct while retaining the proteins. Upon addition of trypsin, the peptide mixture solution is passed through the filter while retaining the trypsin enzyme. The peptide mixture is then analyzed by LC-MS/MS with an in-house BACid algorithm for a comparison of the experimental unique peptides to a constructed proteome database of bacterial genus, specie, and strain entries. The concentration of bacteria was varied from 10 × 10(7) to 3.3 × 10(3) cfu/mL for analysis of the effect of concentration on the ability of the sample processing, LC-MS/MS, and data analysis methods to identify bacteria. The protein processing method and dilution procedure result in reliable identification of pure suspensions and mixtures at high and low bacterial concentrations.     

High-throughput phospholipid quantitation in mammalian cells using matrix-assisted laser desorption ionization-time of flight mass spectrometry with N-trifluoroacetyl-phosphatidylethanolamine as internal standard

A high-throughput method is described for quantitative analysis of phospholipids. The method comprises extraction of lipids, addition of the internal standard N-trifluoroacetyl-phosphatidylethanolamine, and final analysis using matrix-assisted laser desorption ionization mass spectrometry. Quantitative data are obtained by calibration directly in the sample matrix. Calibration with one phosphatidylcholine was found sufficient for quantification of all major phosphatidylcholines tested. The method is very sensitive, has broad application, and is easily applicable to any biological sample. The detection limit for phosphatidylcholines was clearly below 2 μg on the spot, requiring less than 4000 cells corresponding to about 1.6 μg cell dry mass.