Ion mobility mass spectrometry for the study of mycobacterial mycolic acids.

Lipids are highly structurally diverse molecules involved in a wide variety of biological processes. The involvement of lipids is even more pronounced in mycobacteria, including the human pathogen Mycobacterium tuberculosis, which produces a highly complex and diverse set of lipids in the cell envelope. These lipids include mycolic acids, which are among the longest fatty acids in nature and can contain up to 90 carbon atoms. Mycolic acids are ubiquitously found in mycobacteria and are alpha branched and beta hydroxylated lipids. Discrete modifications, such as alpha, alpha', epoxy, methoxy, keto, and carboxy, characterize mycolic acids at the species level. Here, we used high precision ion mobility-mass spectrometry to build a database including 206 mass-resolved collision cross sections (CCSs) of mycolic acids originating from the strict human pathogen M. tuberculosis, the opportunistic strains M. abscessus, M. marinum and M. avium, and the nonpathogenic strain M. smegmatis. Primary differences between the mycolic acid profiles could be observed between mycobacterial species. Acyl tail length and modifications were the primary structural descriptors determining CCS magnitude. As a resource for researchers, this work provides a detailed catalogue of the mass-resolved collision cross sections for mycolic acids along with a workflow to generate and analyse the dataset generated.

A Novel Solid Phase Extraction Sample Preparation Method for Lipidomic Analysis of Human Plasma Using Liquid Chromatography/Mass Spectrometry.

Lipidomic approaches are widely used to investigate the relationship between lipids, human health, and disease. Conventional sample preparation techniques for the extraction of lipids from biological matrices like human plasma are based on liquid-liquid extraction (LLE). However, these methods are labor-intensive, time-consuming, and can show poor reproducibility and selectivity on lipid extraction. A novel, solid-phase extraction (SPE) approach was demonstrated to extract lipids from human plasma using a lipid extraction SPE in both cartridge and 96-well-plate formats, followed by analysis using a combination of targeted and untargeted liquid chromatography/mass spectrometry. The Lipid Extraction SPE method was compared to traditional LLE methods for lipid class recovery, lipidome coverage, and reproducibility. The novel SPE method used a simplified protocol with significant time and labor savings and provided equivalent or better qualitative and quantitative results than traditional LLE methods with respect to several critical performance metrics; recovery, reproducibility, and lipidome coverage.

Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using A Rapid and User-Friendly Software.

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.

Enzymes involved in plastid-targeted phosphatidic acid synthesis are essential for Plasmodium yoelii liver-stage development.

Malaria parasites scavenge nutrients from their host but also harbour enzymatic pathways for de novo macromolecule synthesis. One such pathway is apicoplast-targeted type II fatty acid synthesis, which is essential for late liver-stage development in rodent malaria. It is likely that fatty acids synthesized in the apicoplast are ultimately incorporated into membrane phospholipids necessary for exoerythrocytic merozoite formation. We hypothesized that these synthesized fatty acids are being utilized for apicoplast-targeted phosphatidic acid synthesis, the phospholipid precursor. Phosphatidic acid is typically synthesized in a three-step reaction utilizing three enzymes: glycerol 3-phosphate dehydrogenase, glycerol 3-phosphate acyltransferase and lysophosphatidic acid acyltransferase. The Plasmodium genome is predicted to harbour genes for both apicoplast- and cytosol/endoplasmic reticulum-targeted phosphatidic acid synthesis. Our research shows that apicoplast-targeted Plasmodium yoelii glycerol 3-phosphate dehydrogenase and glycerol 3-phosphate acyltransferase are expressed only during liver-stage development and deletion of the encoding genes resulted in late liver-stage growth arrest and lack of merozoite differentiation. However, the predicted apicoplast-targeted lysophosphatidic acid acyltransferase gene was refractory to deletion and was expressed solely in the endoplasmic reticulum throughout the parasite life cycle. Our results suggest that P. yoelii has an incomplete apicoplast-targeted phosphatidic acid synthesis pathway that is essential for liver-stage maturation.

An assessment of current bioinformatic solutions for analyzing LC-MS data acquired by selected reaction monitoring technology.

Selected reaction monitoring (SRM) is an accurate quantitative technique, typically used for small-molecule mass spectrometry (MS). SRM has emerged as an important technique for targeted and hypothesis-driven proteomic research, and is becoming the reference method for protein quantification in complex biological samples. SRM offers high selectivity, a lower limit of detection and improved reproducibility, compared to conventional shot-gun-based tandem MS (LC-MS/MS) methods. Unlike LC-MS/MS, which requires computationally intensive informatic postanalysis, SRM requires preacquisition bioinformatic analysis to determine proteotypic peptides and optimal transitions to uniquely identify and to accurately quantitate proteins of interest. Extensive arrays of bioinformatics software tools, both web-based and stand-alone, have been published to assist researchers to determine optimal peptides and transition sets. The transitions are oftentimes selected based on preferred precursor charge state, peptide molecular weight, hydrophobicity, fragmentation pattern at a given collision energy (CE), and instrumentation chosen. Validation of the selected transitions for each peptide is critical since peptide performance varies depending on the mass spectrometer used. In this review, we provide an overview of open source and commercial bioinformatic tools for analyzing LC-MS data acquired by SRM.

ATF3 protects against atherosclerosis by suppressing 25-hydroxycholesterol-induced lipid body formation.

Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipid-loaded macrophages in the arterial wall. We demonstrate that macrophage lipid body formation can be induced by modified lipoproteins or by inflammatory Toll-like receptor agonists. We used an unbiased approach to study the overlap in these pathways to identify regulators that control foam cell formation and atherogenesis. An analysis method integrating epigenomic and transcriptomic datasets with a transcription factor (TF) binding site prediction algorithm suggested that the TF ATF3 may regulate macrophage foam cell formation. Indeed, we found that deletion of this TF results in increased lipid body accumulation, and that ATF3 directly regulates transcription of the gene encoding cholesterol 25-hydroxylase. We further showed that production of 25-hydroxycholesterol (25-HC) promotes macrophage foam cell formation. Finally, deletion of ATF3 in Apoe(-/-) mice led to in vivo increases in foam cell formation, aortic 25-HC levels, and disease progression. These results define a previously unknown role for ATF3 in controlling macrophage lipid metabolism and demonstrate that ATF3 is a key intersection point for lipid metabolic and inflammatory pathways in these cells.

Lipidomic analyses of Mycobacterium tuberculosis based on accurate mass measurements and the novel "Mtb LipidDB".

The cellular envelope of Mycobacterium tuberculosis is highly distinctive and harbors a wealth of unique lipids possessing diverse structural and biological properties. However, the ability to conduct global analyses on the full complement of M. tuberculosis lipids has been missing from the repertoire of tools applied to the study of this important pathogen. We have established methods to detect and identify lipids from all major M. tuberculosis lipid classes through LC/MS lipid profiling. This methodology is based on efficient chromatographic separation and automated ion identification through accurate mass determination and searching of a newly created database (Mtb LipidDB) that contains 2,512 lipid entities. We demonstrate the sensitive detection of molecules representing all known classes of M. tuberculosis lipids from a single crude extract. We also demonstrate the ability of this methodology to identify changes in lipid content in response to cellular growth phases. This work provides a customizable framework and resource to facilitate future studies on mycobacterial lipid biosynthesis and metabolism.

N-Terminal clustering of the O-glycosylation sites in the Mycobacterium tuberculosis lipoprotein SodC.

SodC is one of two superoxide dismutases produced by Mycobacterium tuberculosis. This protein was previously shown to contribute to virulence and to act as a B-cell antigen. SodC is also a putative lipoprotein, and like other Sec-translocated mycobacterial proteins it was suggested to be modified with glycosyl units. To definitively define the glycosylation of SodC, we applied an approach that combined site-directed mutagenesis, lectin binding, and mass spectrometry. This resulted in identification of six O-glycosylated residues within a 13-amino-acid region near the N-terminus. Each residue was modified with one to three hexose units, and the most dominant SodC glycoform was modified with nine hexose units. In addition to O-glycosylation of threonine residues, this study provides the first evidence of serine O-glycosylation in mycobacteria. When combined with bioinformatic analyses, the clustering of O-glycosylation appeared to occur in a region of SodC with a disordered structure and not in regions important to the enzymatic activity of SodC. The use of recombinant amino acid substitutions to alter glycosylation sites provided further evidence that glycosylation influences proteolytic processing and ultimately positioning of cell wall proteins.

Disease state differentiation and identification of tuberculosis biomarkers via native antigen array profiling.

A critical element of tuberculosis control is early and sensitive diagnosis of infection and disease. Our laboratories recently showed that different stages of disease were distinguishable via two-dimensional Western blot analyses of Mycobacterium tuberculosis culture filtrate proteins. However, this methodology is not suitable for high throughput testing. Advances in protein microarray technology provide a realistic mechanism to screen a large number of serum samples against thousands of proteins to identify biomarkers of disease states. Techniques were established for separation of native M. tuberculosis cytosol and culture filtrate proteins, resulting in 960 unique protein fractions that were used to generate protein microarrays. Evaluation of serological reactivity from 42 patients in three tuberculosis disease states and healthy purified protein derivative-positive individuals demonstrated that human immunodeficiency virus (HIV)-negative cavitary and noncavitary tuberculosis (TB) patients' sera recognized 126 and 59 fractions, respectively. Sera from HIV patients coinfected with TB recognized 20 fractions of which five overlapped with those recognized by non-HIV TB patients' sera and 15 were unique to the HIV+TB+ disease state. Identification of antigens within the reactive fractions yielded 11 products recognized by both cavitary and noncavitary TB patients' sera and four proteins (HspX, MPT64, PstS1, and TrxC) specific to cavitary TB patients. Moreover four novel B cell antigens (BfrB, LppZ, SodC, and TrxC) of human tuberculosis were identified.