Bioinformatics in Lipidomics: Automating Large-Scale LC-MS-Based Untargeted Lipidomics Profiling with SimLipid Software.

Liquid chromatography-mass spectrometry (LC-MS) provides one of the most popular platforms for untargeted plant lipidomics analysis (Shulaev and Chapman, Biochim Biophys Acta 1862(8):786-791, 2017; Rupasinghe and Roessner, Methods Mol Biol 1778:125-135, 2018; Welti et al., Front Biosci 12:2494-506, 2007; Shiva et al., Plant Methods 14:14, 2018). We have developed SimLipid software in order to streamline the analysis of large-volume datasets generated by LC-MS-based untargeted lipidomics methods. SimLipid contains a customizable library of lipid species; graphical user interfaces (GUIs) for visualization of raw data; the identified lipid molecules and their associated mass spectra annotated with fragment ions and parent ions; and detailed information of each identified lipid species all in a single workbench enabling users to rapidly review the results by examining the data for confident identifications of lipid molecular species. In this chapter, we present the functionality of the software and workflow for automating large-scale LC-MS-based untargeted lipidomics profiling.

Comparative Analysis of Milk Triglycerides Profile between Jaffarabadi Buffalo and Holstein Friesian Cow.

Milk lipids are known for a variety of biological functions, however; little is known about compositional variation across breeds, especially for Jaffarabadi buffalo, an indigenous Indian breed. Systematic profiling of extracted milk lipids was performed by mass spectrometry across summer and winter in Holstein Friesian cow and Jaffarabadi buffalo. Extensive MS/MS spectral analysis for the identification (ID) of probable lipid species using software followed by manual verification and grading of each assigned lipid species enabled ID based on (a) parent ion, (b) head group, and (c) partial/full acyl characteristic ions for comparative profiling of triacylglycerols between the breeds. Additionally, new triacylglycerol species with short-chain fatty acids were reported by manual interpretation of MS/MS spectra and comparison with curated repositories. Collectively, 1093 triacylglycerol species belonging to 141 unique sum compositions between the replicates of both the animal groups were identified. Relative quantitation at sum composition level followed by statistical analyses revealed changes in relative abundances of triacylglycerol species due to breed, season, and interaction effect of the two. Significant changes in triacylglycerols were observed between breeds (81%) and seasons (59%). When the interaction effect is statistically significant, a higher number of triacylglycerols species in Jaffarabadi has lesser seasonal variation than Holstein Friesian.

Trapped ion mobility spectrometry and PASEF enable in-depth lipidomics from minimal sample amounts.

A comprehensive characterization of the lipidome from limited starting material remains very challenging. Here we report a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry (TIMS). Taking advantage of parallel accumulation-serial fragmentation (PASEF), we fragment on average 15 precursors in each of 100 ms TIMS scans, while maintaining the full mobility resolution of co-eluting isomers. The acquisition speed of over 100 Hz allows us to obtain MS/MS spectra of the vast majority of isotope patterns. Analyzing 1 µL of human plasma, PASEF increases the number of identified lipids more than three times over standard TIMS-MS/MS, achieving attomole sensitivity. Building on high intra- and inter-laboratory precision and accuracy of TIMS collisional cross sections (CCS), we compile 1856 lipid CCS values from plasma, liver and cancer cells. Our study establishes PASEF in lipid analysis and paves the way for sensitive, ion mobility-enhanced lipidomics in four dimensions.

Automating mass spectrometry-based quantitative glycomics using aminoxy tandem mass tag reagents with SimGlycan.

Protein glycosylation is a common post-translational modification, which serves critical roles in the biological processes of organisms. Monitoring of changes in the abundance and structure of glycans may be necessary to explain the correlations between protein glycosylation and various diseases. Hence, the growing importance of glycoproteomics necessitates in-depth qualitative and quantitative studies of glycans. One of the emerging trends in glycomics research is the innovation related to accurate mass spectrometry based quantitative analysis of glycans. Recently, we have introduced aminoxyTMT reagents, which enable efficient relative quantitation of carbohydrates, improved glycan ionization efficiency and increased analytical throughput. These reagents can be used for quantitative analysis of N-glycans by direct infusion or liquid chromatography (LC)-coupled to electrospray ionization mass spectrometry (ESI-MS). However, unlike in proteomics, one of the major challenges left unaddressed is the lack of informatics tools to automate the qualitative and quantitative analysis of generated data. This analysis typically includes identification/quantitation of glycans using MS/MS data and differential analysis across biological samples. We have developed software modules to streamline such protocols for quantitative analysis of aminoxyTMT labeled-glycans derived from complex mixtures. This article is part of a Special Issue entitled: Proteomics in India.

Bioinformatics in glycomics: glycan characterization with mass spectrometric data using SimGlycan.

Mass spectrometry (MS), with its low sample requirement and high sensitivity, has been the predominantly used methodology for characterization and elucidation of glycan structures. However, manual interpretation of MS data is complex and tedious due to large number of product ions observed and also due to the variation in their m/z values under various experimental conditions. We present an automated tool, SimGlycan, for this purpose, which accepts raw/standard MS data files as input and characterizes the associated glycan structure with high accuracy using database searching and scoring techniques. Not only does it predict the glycan structure using an MS/MS database searching technique, but it also facilitates predicting novel glycans by drawing a glycan and mapping it onto an experimental spectrum to check the degree of proximity between the theoretical and the experimental glycans. It serves as a platform for developing advanced tools that may be used for glycopeptide identification using MS data and 3D structural analysis of glycans with a few improvements in the existing features.

Interpretation support for multistage MS: a mathematical method for theoretical generation of glycan fragments and calculation of their masses.

Glycan fragmentation forms an integral part of the current research in glycomics. Creation of a database of glycan fragments and their masses for known glycan structures is an important step in the interpretation of mass spectra for the identification of unknown glycan structures. This paper introduces the concept of positional nomenclature, gives a systematic representation of glycan structure of any size, and hence develops a method for theoretically generating all possible first and second generation fragments resulting from glycosidic and cross ring cleavages. Matrix equations are developed for the calculation of theoretical masses. Algorithm is presented for iterative generation of all fragments and calculation of their masses. This method is applicable to glycan analytical techniques using MS, MS/MS, and multistage MS (MSn) with different ionization methods, derivatives, or ions used. The method is adaptable to computer program and has been verified for theoretical masses reported in literature. Rules for the theoretical validation of the fragments are presented.