Tuberculostearic Acid-Containing Phosphatidylinositols as Markers of Bacterial Burden in Tuberculosis
One-fourth of the global human population is estimated to be infected with strains of the Mycobacterium tuberculosis complex (MTBC), the causative agent of tuberculosis (TB). Using lipidomic approaches, we show that tuberculostearic acid (TSA)-containing phosphatidylinositols (PIs) are molecular markers for infection with clinically relevant MTBC strains and signify bacterial burden. For the most abundant lipid marker, detection limits of ∼102 colony forming units (CFUs) and ∼103 CFUs for bacterial and cell culture systems were determined, respectively. We developed a targeted lipid assay, which can be performed within a day including sample preparation─roughly 30-fold faster than in conventional methods based on bacterial culture. This indirect and culture-free detection approach allowed us to determine pathogen loads in infected murine macrophages, human neutrophils, and murine lung tissue. These marker lipids inferred from mycobacterial PIs were found in higher levels in peripheral blood mononuclear cells of TB patients compared to healthy individuals. Moreover, in a small cohort of drug-susceptible TB patients, elevated levels of these molecular markers were detected at the start of therapy and declined upon successful anti-TB treatment. Thus, the concentration of TSA-containing PIs can be used as a correlate for the mycobacterial burden in experimental models and in vitro systems and may prospectively also provide a clinically relevant tool to monitor TB severity.
Brandenburg, J. et al., Tuberculostearic Acid-Containing Phosphatidylinositols as Markers of Bacterial Burden in Tuberculosis, ACS Infectious Diseases (2022)doi:10.1021/acsinfecdis.2c00075
A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics
Mass spectrometry is a widely used technology to identify and quantify biomolecules such as lipids, metabolites and proteins necessary for biomedical research. In this study, we catalogued freely available software tools, libraries, databases, repositories and resources that support lipidomics data analysis and determined the scope of currently used analytical technologies. Because of the tremendous importance of data interoperability, we assessed the support of standardized data formats in mass spectrometric (MS)-based lipidomics workflows. We included tools in our comparison that support targeted as well as untargeted analysis using direct infusion/shotgun (DI-MS), liquid chromatography-mass spectrometry, ion mobility or MS imaging approaches on MS1 and potentially higher MS levels. As a result, we determined that the Human Proteome Organization-Proteomics Standards Initiative standard data formats, mzML and mzTab-M, are already supported by a substantial number of recent software tools. We further discuss how mzTab-M can serve as a bridge between data acquisition and lipid bioinformatics tools for interpretation, capturing their output and transmitting rich annotated data for downstream processing. However, we identified several challenges of currently available tools and standards. Potential areas for improvement were: adaptation of common nomenclature and standardized reporting to enable high throughput lipidomics and improve its data handling. Finally, we suggest specific areas where tools and repositories need to improve to become FAIRer.
Dannenberger, D. et al., A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics, Metabolites (2022)doi:10.3390/metabo12070584
Goslin is the first grammar-based computational library for the recognition/parsing and normalization of lipid names following the hierarchical lipid shorthand nomenclature. The new version Goslin 2.0 implements the latest nomenclature and adds an additional grammar to recognize systematic IUPAC-IUB fatty acyl names as stored, e.g., in the LIPID MAPS database and is perfectly suited to update lipid names in LIPID MAPS or HMDB databases to the latest nomenclature. Goslin 2.0 is available as a standalone web application with a REST API as well as C++, C#, Java, Python 3, and R libraries. Importantly, it can be easily included in lipidomics tools and scripts providing direct access to translation functions. All implementations are open source.
Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment
Membrane lipids and their metabolism have key functions in neurotransmission. Here we provide a quantitative lipid inventory of mouse and rat synaptic junctions. To this end, we developed a multiomics extraction and analysis workflow to probe the interplay of proteins and lipids in synaptic signal transduction from the same sample. Based on this workflow, we generate hypotheses about novel mechanisms underlying complex changes in synaptic connectivity elicited by environmental stimuli. As a proof of principle, this approach reveals that in mice exposed to an enriched environment, reduced endocannabinoid synthesis and signaling is linked to increased surface expression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) in a subset of Cannabinoid-receptor 1 positive synapses. This mechanism regulates synaptic strength in an input-specific manner. Thus, we establish a compartment-specific multiomics workflow that is suitable to extract information from complex lipid and protein networks involved in synaptic function and plasticity.