The procoagulant activity of tissue factor expressed on fibroblasts is increased by tissue factor-negative extracellular vesicles

Tissue factor (TF) is critical for the activation of blood coagulation. TF function is regulated by the amount of externalised phosphatidylserine (PS) and phosphatidylethanolamine (PE) on the surface of the cell in which it is expressed. We investigated the role PS and PE in fibroblast TF function. Fibroblasts expressed 6–9 x 104 TF molecules/cell but had low specific activity for FXa generation. We confirmed that this was associated with minimal externalized PS and PE and characterised for the first time the molecular species of PS/PE demonstrating that these differed from those found in platelets. Mechanical damage of fibroblasts, used to simulate vascular injury, increased externalized PS/PE and led to a 7-fold increase in FXa generation that was inhibited by annexin V and an anti-TF antibody. Platelet-derived extracellular vesicles (EVs), that did not express TF, supported minimal FVIIa-dependent FXa generation but substantially increased fibroblast TF activity. This enhancement in fibroblast TF activity could also be achieved using synthetic liposomes comprising 10% PS without TF. In conclusion, despite high levels of surface TF expression, healthy fibroblasts express low levels of external-facing PS and PE limiting their ability to generate FXa. Addition of platelet-derived TF-negative EVs or artificial liposomes enhanced fibroblast TF activity in a PS dependent manner. These findings contribute information about the mechanisms that control TF function in the fibroblast membrane

LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics

Summary We present LipidFinder online, hosted on the LIPID MAPS website, as a liquid chromatography/mass spectrometry (LC/MS) workflow comprising peak filtering, MS searching and statistical analysis components, highly customized for interrogating lipidomic data. The online interface of LipidFinder includes several innovations such as comprehensive parameter tuning, a MS search engine employing in-house customized, curated and computationally generated databases and multiple reporting/display options. A set of integrated statistical analysis tools which enable users to identify those features which are significantly-altered under the selected experimental conditions, thereby greatly reducing the complexity of the peaklist prior to MS searching is included. LipidFinder is presented as a highly flexible, extensible user-friendly online workflow which leverages the lipidomics knowledge base and resources of the LIPID MAPS website, long recognized as a leading global lipidomics portal

LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications

We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate (FDR) method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder’s online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools

Metabolic dysregulation of the lysophospholipid/autotaxin axis in the chromosome 9p21 gene SNP rs10757274

Background - Common chromosome 9p21 SNPs increase coronary heart disease (CHD) risk, independent of 'traditional lipid risk factors'. However, lipids comprise large numbers of structurally related molecules not measured in traditional risk measurements, and many have inflammatory bioactivities. Here we applied lipidomic and genomic approaches to three model systems, to characterize lipid metabolic changes in common Chr9p21 SNPs which confer ~30% elevated CHD risk associated with altered expression of ANRIL, a long ncRNA. Methods - Untargeted and targeted lipidomics was applied to plasma from Northwick Park Heart Study II (NPHSII) homozygotes for AA or GG in rs10757274, followed by correlation and network analysis. To identify candidate genes, transcriptomic data from shRNA downregulation of ANRIL in HEK293 cells was mined. Transcriptional data from vascular smooth muscle cells differentiated from iPSCs of individuals with/without Chr9p21 risk, non-risk alleles, and corresponding knockout isogenic lines were next examined. Last, an in-silico analysis of miRNAs was conducted to identify how ANRIL might control lysoPL/lysoPA genes. Results - Elevated risk GG correlated with reduced lysophosphospholipids (lysoPLs), lysophosphatidic acids (lysoPA) and autotaxin (ATX). Five other risk SNPs did not show this phenotype. LysoPL-lysoPA interconversion was uncoupled from ATX in GG plasma, suggesting metabolic dysregulation. Significantly altered expression of several lysoPL/lysoPA metabolising enzymes was found in HEK cells lacking ANRIL. In the VSMC dataset, the presence of risk alleles associated with altered expression of several lysoPL/lysoPA enzymes. Deletion of the risk locus reversed expression of several lysoPL/lysoPA genes to non-risk haplotype levels. Genes that were altered across both cell datasets were DGKA, MBOAT2, PLPP1 and LPL. The in-silico analysis identified four ANRIL-regulated miRNAs that control lysoPL genes as miR-186-3p, miR-34a-3p, miR-122-5p, miR-34a-5p. Conclusions - A Chr9p21 risk SNP associates with complex alterations in immune-bioactive phospholipids and their metabolism. Lipid metabolites and genomic pathways associated with CHD pathogenesis in Chr9p21 and ANRIL-associated disease are demonstrated

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

The lipid envelope of 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 anti-viral agents, as well as further our understanding of viral-host protein interactions, infectivity, pathogenicity, and innate immune system clearance. Using lipidomics analyses, we revealed that the virus envelope comprised mainly phospholipids (PL), with little cholesterol or sphingolipids, indicating significant differences from the composition of host membranes. Unlike cellular membranes, procoagulant aminophospholipids were present on the external side of the viral envelope at levels exceeding those on activated platelets. As a result, 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 viral infectivity. Products containing PL-disrupting surfactants (such as cetylpyridinium chloride (CPC)) met European virucidal standards in vitro; however, components that altered the critical micelle concentration reduced efficacy, and products containing essential oils, PVP-I, or Chlorhexidine were ineffective. This result was recapitulated in vivo, where a 30-second oral rinse with CPC mouthwash eliminated live virus in the oral cavity of COVID-19 patients for at least one hour, while PVP-Iodine and saline mouthwashes were found ineffective. We conclude the SARS-CoV-2 lipid envelope (i) is distinct from the host plasma membrane, which may enable design of selective anti-viral approaches; (ii) contains exposed PE and PS, which may influence thrombosis, pathogenicity, and inflammation; and (iii) can be selectively targeted in vivo by specific oral rinses

Phospholipid membranes drive abdominal aortic aneurysm development through stimulating coagulation factor activity

Abdominal aortic aneurysm (AAA) is an inflammatory vascular disease with high mortality and limited treatment options. How blood lipids regulate AAA development is unknown. Here lipidomics and genetic models demonstrate a central role for procoagulant enzymatically oxidized phospholipids (eoxPL) in regulating AAA. Specifically, through activating coagulation, eoxPL either promoted or inhibited AAA depending on tissue localization. Ang II administration to ApoE−/− mice increased intravascular coagulation during AAA development. Lipidomics revealed large numbers of eoxPL formed within mouse and human AAA lesions. Deletion of eoxPL-generating enzymes (Alox12 or Alox15) or administration of the factor Xa inhibitor rivaroxaban significantly reduced AAA. Alox-deficient mice displayed constitutively dysregulated hemostasis, including a consumptive coagulopathy, characterized by compensatory increase in prothrombotic aminophospholipids (aPL) in circulating cell membranes. Intravenously administered procoagulant PL caused clotting factor activation and depletion, induced a bleeding defect, and significantly reduced AAA development. These data suggest that Alox deletion reduces AAA through diverting coagulation away from the vessel wall due to eoxPL deficiency, instead activating clotting factor consumption and depletion in the circulation. In mouse whole blood, ∼44 eoxPL molecular species formed within minutes of clot initiation. These were significantly elevated with ApoE−/− deletion, and many were absent in Alox−/− mice, identifying specific eoxPL that modulate AAA. Correlation networks demonstrated eoxPL belonged to subfamilies defined by oxylipin composition. Thus, procoagulant PL regulate AAA development through complex interactions with clotting factors. Modulation of the delicate balance between bleeding and thrombosis within either the vessel wall or circulation was revealed that can either drive or prevent disease development

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023.

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes

Metabolic Dysregulation of the Lysophospholipid/Autotaxin Axis in the Chromosome 9p21 Gene SNP rs10757274.

BackgroundCommon chromosome 9p21 single nucleotide polymorphisms (SNPs) increase coronary heart disease risk, independent of traditional lipid risk factors. However, lipids comprise large numbers of structurally related molecules not measured in traditional risk measurements, and many have inflammatory bioactivities. Here, we applied lipidomic and genomic approaches to 3 model systems to characterize lipid metabolic changes in common Chr9p21 SNPs, which confer ≈30% elevated coronary heart disease risk associated with altered expression of ANRIL, a long ncRNA.MethodsUntargeted and targeted lipidomics was applied to plasma from NPHSII (Northwick Park Heart Study II) homozygotes for AA or GG in rs10757274, followed by correlation and network analysis. To identify candidate genes, transcriptomic data from shRNA downregulation of ANRIL in HEK-293 cells was mined. Transcriptional data from vascular smooth muscle cells differentiated from induced pluripotent stem cells of individuals with/without Chr9p21 risk, nonrisk alleles, and corresponding knockout isogenic lines were next examined. Last, an in-silico analysis of miRNAs was conducted to identify how ANRIL might control lysoPL (lysophosphospholipid)/lysoPA (lysophosphatidic acid) genes.ResultsElevated risk GG correlated with reduced lysoPLs, lysoPA, and ATX (autotaxin). Five other risk SNPs did not show this phenotype. LysoPL-lysoPA interconversion was uncoupled from ATX in GG plasma, suggesting metabolic dysregulation. Significantly altered expression of several lysoPL/lysoPA metabolizing enzymes was found in HEK cells lacking ANRIL. In the vascular smooth muscle cells data set, the presence of risk alleles associated with altered expression of several lysoPL/lysoPA enzymes. Deletion of the risk locus reversed the expression of several lysoPL/lysoPA genes to nonrisk haplotype levels. Genes that were altered across both cell data sets were DGKA, MBOAT2, PLPP1, and LPL. The in-silico analysis identified 4 ANRIL-regulated miRNAs that control lysoPL genes as miR-186-3p, miR-34a-3p, miR-122-5p, and miR-34a-5p.ConclusionsA Chr9p21 risk SNP associates with complex alterations in immune-bioactive phospholipids and their metabolism. Lipid metabolites and genomic pathways associated with coronary heart disease pathogenesis in Chr9p21 and ANRIL-associated disease are demonstrated

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows

Guiding the choice of informatics software and tools for lipidomics research applications

Ni Z, Wolk M, Jukes G, et al. Guiding the choice of informatics software and tools for lipidomics research applications. Nature Methods . 2022.Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows