LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications

Integrative processing of untargeted metabolomic and lipidomic data using MultiABLER

Mass spectrometry (MS)-based untargeted metabolomic and lipidomic approaches are being used increasingly in biomedical research. The adoption and integration of these data are critical to the overall multi-omic toolkit. Recently, a sample extraction method called Multi-ABLE has been developed, which enables concurrent generation of proteomic and untargeted metabolomic and lipidomic data from a small amount of tissue. The proteomics field has a well-established set of software for processing of acquired data; however, there is a lack of a unified, off-the-shelf, ready-to-use bioinformatics pipeline that can take advantage of and prepare concurrently generated metabolomic and lipidomic data for joint downstream analyses. Here we present an R pipeline called MultiABLER as a unified and simple upstream processing and analysis pipeline for both metabolomics and lipidomics datasets acquired using liquid chromatography-tandem mass spectrometry. The code is available via an open-source license at https://github.com/holab-hku/MultiABLER.

ADViSELipidomics: a workflow for analyzing lipidomics data

SUMMARY

ADViSELipidomics is a novel Shiny app for preprocessing, analyzing and visualizing lipidomics data. It handles the outputs from LipidSearch and LIQUID for lipid identification and quantification and the data from the Metabolomics Workbench. ADViSELipidomics extracts information by parsing lipid species (using LIPID MAPS classification) and, together with information available on the samples, performs several exploratory and statistical analyses. When the experiment includes internal lipid standards, ADViSELipidomics can normalize the data matrix, providing normalized concentration values per lipids and samples. Moreover, it identifies differentially abundant lipids in simple and complex experimental designs, dealing with batch effect correction. Finally, ADViSELipidomics has a user-friendly graphical user interface and supports an extensive series of interactive graphics.

AVAILABILITY AND IMPLEMENTATION

ADViSELipidomics is freely available at https://github.com/ShinyFabio/ADViSELipidomics.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

The SARS-CoV2 envelope differs from host cells, exposes procoagulant lipids, and is disrupted in vivo by oral rinses

The lipid envelope of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an essential component of the virus; however, its molecular composition is undetermined. Addressing this knowledge gap could support the design of antiviral agents as well as further our understanding of viral-host protein interactions, infectivity, pathogenicity, and innate immune system clearance. Lipidomics revealed that the virus envelope comprised mainly phospholipids (PLs), with some cholesterol and sphingolipids, and with cholesterol/phospholipid ratio similar to lysosomes. Unlike cellular membranes, procoagulant amino-PLs were present on the external side of the viral envelope at levels exceeding those on activated platelets. Accordingly, virions directly promoted blood coagulation. To investigate whether these differences could enable selective targeting of the viral envelope in vivo, we tested whether oral rinses containing lipid-disrupting chemicals could reduce infectivity. Products containing PL-disrupting surfactants (such as cetylpyridinium chloride) met European virucidal standards in vitro; however, components that altered the critical micelle concentration reduced efficacy, and products containing essential oils, povidone-iodine, or chlorhexidine were ineffective. This result was recapitulated in vivo, where a 30-s oral rinse with cetylpyridinium chloride mouthwash eliminated live virus in the oral cavity of patients with coronavirus disease 19 for at least 1 h, whereas povidone-iodine and saline mouthwashes were ineffective. We conclude that the SARS-CoV-2 lipid envelope i) is distinct from the host plasma membrane, which may enable design of selective antiviral approaches; ii) contains exposed phosphatidylethanolamine and phosphatidylserine, which may influence thrombosis, pathogenicity, and inflammation; and iii) can be selectively targeted in vivo by specific oral rinses.