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).

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.

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.

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.

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.

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.