Plasma and platelet lipidome changes in Fabry disease.

BACKGROUND: Fabry disease (FD) is an X-linked lysosomal storage disorder characterized by the progressive accumulation of globotriaosylceramide (Gb3) leading to systemic manifestations such as chronic kidney disease, cardiomyopathy, and stroke. There is still a need for novel markers for improved FD screening and prognosis. Moreover, the pathological mechanisms in FD, which also include systemic inflammation and fibrosis, are not yet fully understood. METHODS: Plasma and platelets were obtained from 11 ERT (enzyme-replacement therapy)-treated symptomatic, 4 asymptomatic FD patients, and 13 healthy participants. A comprehensive targeted lipidomics analysis was conducted quantitating more than 550 lipid species. RESULTS: Sphingadiene (18:2;O2)-containing sphingolipid species, including Gb3 and galabiosylceramide (Ga2), were significantly increased in FD patients. Plasma levels of lyso-dihexosylceramides, sphingoid base 1-phosphates (S1P), and GM3 ganglioside were also altered in FD patients, as well as specific plasma ceramide ratios used in cardiovascular disease risk prediction. Gb3 did not increase in patients' platelets but displayed a high inter-individual variability in patients and healthy participants. Platelets accumulated, however, lyso-Gb3, acylcarnitines, C16:0-sphingolipids, and S1P. CONCLUSIONS: This study identified lipidome changes in plasma and platelets from FD patients, a possible involvement of platelets in FD, and potential new markers for screening and monitoring of this disease.

Effects of wolfberry (Lycium barbarum) consumption on the human plasma lipidome and its association with cardiovascular disease risk factors: a randomized controlled trial of middle-aged and older adults.

Background: Long-term wolfberry intake as part of a healthy dietary pattern was recognized to have beneficial vascular outcomes. Characterization of the plasma lipidome may further provide comprehensive insights into pathways underlying these cardiovascular protective effects. Objective: We analyzed the plasma lipidome of subjects who adhered to a healthy dietary pattern either with or without wolfberry and investigated the associations between the plasma lipidomic profile and cardiovascular health-related indicators. Methods: In this 16-week, parallel design, randomized controlled trial, middle-aged and older adults (n = 41) were provided dietary counseling and assigned to either consume or not consume 15 g of wolfberry daily. At baseline and post-intervention, plasma lipidomics was assayed, and its relationships with classical CVD risk factors, vascular health, oxidant burden, carotenoids status, body composition, and anthropometry were examined. Results: From the plasma lipidome, 427 lipid species from 26 sub-classes were quantified. In the wolfberry and control groups, significant changes were prominent for 27 and 42 lipid species, respectively (P < 0.05 with > 0.2-fold change). Fold changes for seven lipid species were also markedly different between the two groups. Examining the relationships between the plasma lipidome and CVD-related risk factors, total cholesterol revealed a marked positive correlation with 13 ceramide species, while HDL-cholesterol which was notably increased with wolfberry consumption showed a positive correlation with 10 phosphatidylcholine species. Oxidant burden, as represented by plasma 8-isoprostanes, was also inversely associated with lipidomic triglycerides and ether-triglycerides (41 species) and directly associated with hexosylceramides (eight species) and sphingomyelins (six species). There were no differential associations with CVD risk detected between groups. Conclusion: Characteristic alterations to the plasma lipidome were observed with healthy dietary pattern adherence and wolfberry consumption. An examination of these fluctuations suggests potential biochemical mechanisms that may mediate the antioxidant and cardiovascular protective effects of healthy dietary pattern adherence and wolfberry intake. This study was registered at clinicaltrials.gov as NCT0353584.

An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes.

Background: Patients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes. Materials and methods: In a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190). Results: The post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF. Conclusion: Post-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.

Evaluation of Normalization Approaches for Quantitative Analysis of Bile Acids in Human Feces.

Quantitative analysis of bile acids in human feces can potentially help to better understand the influence of the gut microbiome and diet on human health. Feces is a highly heterogeneous sample matrix, mainly consisting of water and indigestible solid material (as plant fibers) that show high inter-individual variability. To compare bile acid concentrations among different individuals, a reliable normalization approach is needed. Here, we compared the impact of three normalization approaches, namely sample wet weight, dry weight, and protein concentration, on the absolute concentrations of fecal bile acids. Bile acid concentrations were determined in 70 feces samples from healthy humans. Our data show that bile acid concentrations normalized by the three different approaches are substantially different for each individual sample. Fecal bile acid concentrations normalized by wet weight show the narrowest distribution. Therefore, our analysis will provide the basis for the selection of a suitable normalization approach for the quantitative analysis of bile acids in feces.

Immunolipidomics Reveals a Globoside Network During the Resolution of Pro-Inflammatory Response in Human Macrophages.

Toll-like receptor 4 (TLR4)-mediated changes in macrophages reshape intracellular lipid pools to coordinate an effective innate immune response. Although this has been previously well-studied in different model systems, it remains incompletely understood in primary human macrophages. Here we report time-dependent lipidomic and transcriptomic responses to lipopolysaccharide (LPS) in primary human macrophages from healthy donors. We grouped the variation of ~200 individual lipid species measured by LC-MS/MS into eight temporal clusters. Among all other lipids, glycosphingolipids (glycoSP) and cholesteryl esters (CE) showed a sharp increase during the resolution phase (between 8h or 16h post LPS). GlycoSP, belonging to the globoside family (Gb3 and Gb4), showed the greatest inter-individual variability among all lipids quantified. Integrative network analysis between GlycoSP/CE levels and genome-wide transcripts, identified Gb4 d18:1/16:0 and CE 20:4 association with subnetworks enriched for T cell receptor signaling (PDCD1, CD86, PTPRC, CD247, IFNG) and DC-SIGN signaling (RAF1, CD209), respectively. Our findings reveal Gb3 and Gb4 globosides as sphingolipids associated with the resolution phase of inflammatory response in human macrophages.

Population-based plasma lipidomics reveals developmental changes in metabolism and signatures of obesity risk: a mother-offspring cohort study.

BACKGROUND: Lipids play a vital role in health and disease, but changes to their circulating levels and the link with obesity remain poorly characterized in expecting mothers and their offspring in early childhood. METHODS: LC-MS/MS-based quantitation of 480 lipid species was performed on 2491 plasma samples collected at 4 time points in the mother-offspring Asian cohort GUSTO (Growing Up in Singapore Towards healthy Outcomes). These 4 time points constituted samples collected from mothers at 26-28 weeks of gestation (n=752) and 4-5 years postpartum (n=650), and their offspring at birth (n=751) and 6 years of age (n=338). Linear regression models were used to identify the pregnancy and developmental age-specific variations in the plasma lipidomic profiles, and their association with obesity risk. An independent birth cohort (n=1935), the Barwon Infant Study (BIS), comprising mother-offspring dyads of Caucasian origin was used for validation. RESULTS: Levels of 36% of the profiled lipids were significantly higher (absolute fold change > 1.5 and Padj < 0.05) in antenatal maternal circulation as compared to the postnatal phase, with phosphatidylethanolamine levels changing the most. Compared to antenatal maternal lipids, cord blood showed lower concentrations of most lipid species (79%) except lysophospholipids and acylcarnitines. Changes in lipid concentrations from birth to 6 years of age were much higher in magnitude (log2FC=-2.10 to 6.25) than the changes observed between a 6-year-old child and an adult (postnatal mother) (log2FC=-0.68 to 1.18). Associations of cord blood lipidomic profiles with birth weight displayed distinct trends compared to the lipidomic profiles associated with child BMI at 6 years. Comparison of the results between the child and adult BMI identified similarities in association with consistent trends (R2=0.75). However, large number of lipids were associated with BMI in adults (67%) compared to the children (29%). Pre-pregnancy BMI was specifically associated with decrease in the levels of phospholipids, sphingomyelin, and several triacylglycerol species in pregnancy. CONCLUSIONS: In summary, our study provides a detailed landscape of the in utero lipid environment provided by the gestating mother to the growing fetus, and the magnitude of changes in plasma lipidomic profiles from birth to early childhood. We identified the effects of adiposity on the circulating lipid levels in pregnant and non-pregnant women as well as offspring at birth and at 6 years of age. Additionally, the pediatric vs maternal overlap of the circulating lipid phenotype of obesity risk provides intergenerational insights and early opportunities to track and intervene the onset of metabolic adversities. CLINICAL TRIAL REGISTRATION: This birth cohort is a prospective observational study, which was registered on 1 July 2010 under the identifier NCT01174875 .

Serum Lipidome Signatures of Dogs with Different Endocrinopathies Associated with Hyperlipidemia.

Hyperlipidemia (hypertriglyceridemia, hypercholesterolemia) is a common finding in human and veterinary patients with endocrinopathies (e.g., hypothyroidism and hypercortisolism (Cushing's syndrome; CS)). Despite emerging use of lipidomics technology in medicine, the lipid profiles of these endocrinopathies have not been evaluated and characterized in dogs. The aim of this study was to compare the serum lipidomes of dogs with naturally occurring CS or hypothyroidism with those of healthy dogs. Serum samples from 39 dogs with CS, 45 dogs with hypothyroidism, and 10 healthy beagle dogs were analyzed using a targeted lipidomics approach with liquid chromatography-mass spectrometry. There were significant differences between the lipidomes of dogs with CS, hypothyroidism, and the healthy dogs. The most significant changes were found in the lysophosphatidylcholines, lysophosphatidylethanolamines, lysophosphatidylinositols, phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerols, ceramides, and sphingosine 1-phosphates. Lipid alterations were especially pronounced in dogs with hypothyroidism. Several changes suggested a more atherogenic lipid profile in dogs with HT than in dogs with CS. In this study, we found so far unknown effects of naturally occurring hypothyroidism and CS on lipid metabolism in dogs. Our findings provide starting points to further examine differences in occurrence of atherosclerotic lesion formation between the two diseases.

Variability of the Plasma Lipidome and Subclinical Coronary Atherosclerosis.

OBJECTIVE: While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis. Approach and Results: Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41-75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CVg) and within-subject (CVw) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CVg than CVw. Among the lipids (n=145) with 1.2-fold higher CVg than CVw, 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume. CONCLUSIONS: High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.

Lipidomic Analysis of Archival Pathology Specimens Identifies Altered Lipid Signatures in Ovarian Clear Cell Carcinoma.

Cancer metabolism is associated with the enhanced lipogenesis required for rapid growth and proliferation. However, the magnitude of dysregulation of diverse lipid species still requires significant characterization, particularly in ovarian clear cell carcinoma (OCCC). Here, we have implemented a robust sample preparation workflow together with targeted LC-MS/MS to identify the lipidomic changes in formalin-fixed paraffin-embedded specimens from OCCC compared to tumor-free ovarian tissue. We quantitated 340 lipid species, representing 28 lipid classes. We observed differential regulation of diverse lipid species belonging to several glycerophospholipid classes and trihexosylceramide. A number of unsaturated lipid species were increased in OCCC, whereas saturated lipid species showed a decrease in OCCC compared to the controls. We also carried out total fatty acid analysis and observed an increase in the levels of several unsaturated fatty acids with a concomitant increase in the index of stearoyl-CoA desaturase (SCD) in OCCC. We confirmed the upregulation of SCD (the rate-limiting enzyme for the synthesis of monounsaturated fatty acids) by immunohistochemistry (IHC) assays. Hence, by carrying out a mass spectrometry analysis of archival tissue samples, we were able to provide insights into lipidomic alterations in OCCC.

A reference map of sphingolipids in murine tissues.

Sphingolipids (SPs) have both a structural role in the cell membranes and a signaling function that regulates many cellular processes. The enormous structural diversity and low abundance of many SPs pose a challenge for their identification and quantification. Recent advances in lipidomics, in particular liquid chromatography (LC) coupled with mass spectrometry (MS), provide methods to detect and quantify many low-abundant SP species reliably. Here we use LC-MS to compile a "murine sphingolipid atlas," containing the qualitative and quantitative distribution of 114 SPs in 21 tissues of a widely utilized wild-type laboratory mouse strain (C57BL/6). We report tissue-specific SP fingerprints, as well as sex-specific differences in the same tissue. This is a comprehensive, quantitative sphingolipidomic map of mammalian tissues collected in a systematic fashion. It will complement other tissue compendia for interrogation into the role of SP in mammalian health and disease.

LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring.

Lipidomics is developing as an important area in biomedical and clinical research. Reliable quantification of lipid species is required for clinical translation of lipidomic studies. Hydrophilic interaction chromatography (HILIC), normal-phase liquid chromatography (NPLC), and supercritical fluid chromatography (SFC) are commonly used techniques in lipidomics and provide class-based separation of lipids. While co-elution of lipid species and their internal standards is an advantage for accurate quantification, it leads to isotopic overlap between species of the same lipid class. In shotgun lipidomics, isotopic correction is typically done based on elemental formulas of precursor ions. In multiple reaction monitoring (MRM) analyses, however, this approach should not be used, as the overall contribution of heavy isotopes to the MRM transitions' intensities depends on their location in the molecule with respect to the fragmentation pattern. We present an algorithm, provided in the R programming language, for isotopic correction in class-based separation using MRM, extracting relevant structural information from MRM transitions to apply adequate isotopic correction factors. Using standards, we show that our algorithm accurately estimates the isotopic contribution of isotopologues to MRM transitions' measured intensities. Using human plasma as an example, we demonstrate the necessity of adequate isotopic correction for accurate quantitation of lipids measured by MRM with class-based chromatographic separation. We show that over a third of the measured phosphatidylcholine species had their intensity corrected by more than 10%. This isotopic correction algorithm and R-implemented application enable a more accurate quantification of lipids in class-based separation-MRM, a prerequisite for successful translation of lipidomic applications.

SmartPeak Automates Targeted and Quantitative Metabolomics Data Processing.

Technological advances in high-resolution mass spectrometry (MS) vastly increased the number of samples that can be processed in a life science experiment, as well as volume and complexity of the generated data. To address the bottleneck of high-throughput data processing, we present SmartPeak (https://github.com/AutoFlowResearch/SmartPeak), an application that encapsulates advanced algorithms to enable fast, accurate, and automated processing of capillary electrophoresis-, gas chromatography-, and liquid chromatography (LC)-MS(/MS) data and high-pressure LC data for targeted and semitargeted metabolomics, lipidomics, and fluxomics experiments. The application allows for an approximate 100-fold reduction in the data processing time compared to manual processing while enhancing quality and reproducibility of the results.

Impact of ion suppression by sample cap liners in lipidomics.

Contamination from the polymeric material released by vial caps used for sample introduction in liquid chromatography can significantly affect the signal of the analyte of interest. In particular, repeated injections from the same sample vial can enhance this suppressing effect. Multiple injections of the same sample are often used in metabolomics and lipidomics during routine analyses. Here we demonstrate how the presence of contaminant polymers, originating from the vial closures, significantly influences the estimation of the relative amount of endogenous lipids in human plasma. Furthermore, this can negatively impact other operations in mass spectrometric analysis, such as instrument equilibration and tuning or the common use of technical replicates to improve confidence in data interpretation. Our observations provide critical information on how to improve future analyses through the use of appropriate vial caps, solvents, chromatographic separations and equipment.

Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics.

We introduce STAMPS, a pathway-centric web service for the development of targeted proteomics assays. STAMPS guides the user by providing several intuitive interfaces for a rapid and simplified method design. Applying our curated framework to signaling and metabolic pathways, we reduced the average assay development time by a factor of ∼150 and revealed that the insulin signaling is actively controlled by protein abundance changes in insulin-sensitive and -resistance states. Although at the current state STAMPS primarily contains mouse data, it was designed for easy extension with additional organisms.

MRMkit: Automated Data Processing for Large-Scale Targeted Metabolomics Analysis.

MRMkit is an open-source software package designed for automated processing of large-scale targeted mass spectrometry-based metabolomics data. With improvements in the automation of sample preparation for LC-MS analysis, a challenging next step is to fully automate the workflow to process raw data and ensure the quality of measurements in large-scale analysis settings. MRMkit capitalizes on the richness of large-sample data in capturing peak shapes and interference patterns of transitions across many samples and delivers fully automated, reproducible peak integration results in a scalable and time-efficient manner. In addition to fast and accurate peak integration, the tool also provides reliable data normalization functions and quality metrics along with visualizations for fast data quality evaluation. In addition, MRMkit learns retention time offset patterns by user-specified compound classes and makes recommendations for peak picking in multimodal ion chromatograms. In summary, MRMkit offers highly consistent and scalable data processing capacity for targeted metabolomics, substantially curtailing the time required to produce the final quantification results after LC-MS analysis.

Dual mass spectrometry as a tool to improve annotation and quantification in targeted plasma lipidomics.

INTRODUCTION: High quality data, based on reliable quantification and clear identification of the reported lipid species, are required for the clinical translation of human plasma lipidomic studies. OBJECTIVE: Lipid quantification can be efficiently performed on triple quadrupole (QqQ) mass spectrometers in targeted multiple reaction monitoring (MRM) mode. However, a series of issues can be encountered when aiming at unambiguous identification and accurate quantification, including (i) resolving peaks of polyunsaturated species, (ii) discriminating between plasmanyl-, plasmenyl- and odd chain species and (iii) resolving the isotopic overlap between co-eluting lipid species. METHODS: As a practical tool to improve the quality of targeted lipidomics studies, we applied a Dual MS platform by simultaneously coupling a reversed-phase liquid chromatography separation to a QqQ and a quadrupole-time of flight (Q-ToF) mass spectrometers. In one single experiment, this platform allows to correctly identify, by high-resolution MS and MS/MS, the peaks that are quantified by MRM. RESULTS: As proof of concept, we applied the platform on glycerophosphocholines (GPCs) and sphingomyelins (SMs), which are highly abundant in human plasma and play crucial roles in various physiological functions. Our results demonstrated that Dual MS could provide a higher level of confidence in the identification and quantification of GPCs and SMs in human plasma. The same approach can also be applied to improve the study of other lipid classes and expanded for the identification of novel lipid molecular species. CONCLUSIONS: This methodology might have a great potential to achieve a better specificity in the quantification of lipids by targeted lipidomics in high-throughput studies.

LipidCreator workbench to probe the lipidomic landscape.

Mass spectrometry (MS)-based targeted lipidomics enables the robust quantification of selected lipids under various biological conditions but comprehensive software tools to support such analyses are lacking. Here we present LipidCreator, a software that fully supports targeted lipidomics assay development. LipidCreator offers a comprehensive framework to compute MS/MS fragment masses for over 60 lipid classes. LipidCreator provides all functionalities needed to define fragments, manage stable isotope labeling, optimize collision energy and generate in silico spectral libraries. We validate LipidCreator assays computationally and analytically and prove that it is capable to generate large targeted experiments to analyze blood and to dissect lipid-signaling pathways such as in human platelets.

Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories.

Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., "shared references") can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma.

Serum lipidome analysis of healthy beagle dogs receiving different diets.

INTRODUCTION: Food and dietary ingredients have significant effects on metabolism and health. OBJECTIVE: To evaluate whether and how different diets affected the serum lipidomic profile of dogs. METHODS: Sixteen healthy beagles were fed a commercial dry diet for 3 months (control diet). After an overnight fasting period, a blood sample was taken for serum lipidomic profile analysis, and each dog was then randomly assigned to one of two groups. Group 1 was fed a commercial diet (Diet 1) and group 2 was fed a self-made, balanced diet supplemented with linseed oil and salmon oil (Diet 2) for 3 months. After an overnight fasting period, a blood sample was taken from each dog. Serum cholesterol and triacylglycerol analyses were performed and the serum lipidomic profiles were analyzed using targeted liquid chromatography-mass spectrometry. RESULTS: Dogs fed the supplemented self-made diet (Diet 2) had significantly higher omega-3 fatty acid-containing lipids species and significantly lower saturated and mono- and di-unsaturated lipid species. Concentrations of sphingosine 1-phosphate species S1P d16:1 and S1P d17:1 were significantly increased after feeding Diet 2. CONCLUSION: This study found that different diets had significant effects on the dog's serum lipidomic profile. Therefore, in studies that include lipidomic analyses, diet should be included as a confounding factor.

A T164S mutation in the dengue virus NS1 protein is associated with greater disease severity in mice.

Dengue viruses cause severe and sudden human epidemics worldwide. The secreted form of the nonstructural protein 1 (sNS1) of dengue virus causes vascular leakage, a hallmark of severe dengue disease. Here, we reverse engineered the T164S mutation of NS1, associated with the severity of dengue epidemics in the Americas, into a dengue virus serotype 2 mildly infectious strain. The T164S mutant virus decreased infectious virus production and increased sNS1 production in mammalian cell lines and human peripheral blood mononuclear cells (PBMCs) without affecting viral RNA replication. Gene expression profiling of 268 inflammation-associated human genes revealed up-regulation of genes induced in response to vascular leakage. Infection of the mosquito vector Aedes aegypti with the T164S mutant virus resulted in increased viral load in the mosquito midgut and higher sNS1 production compared to wild-type virus infection. Infection of type 1 and 2 interferon receptor-deficient AG129 mice with the T164S mutant virus resulted in severe disease coupled with increased complement activation, tissue inflammation, and more rapid mortality compared to AG129 mice infected with wild-type virus. Molecular dynamics simulations predicted that mutant sNS1 formed stable dimers similar to the wild-type protein, whereas the hexameric mutant sNS1 was predicted to be unstable. Immunoaffinity-purified sNS1 from T164S mutant virus-infected mammalian cells was associated with different lipid classes compared to wild-type sNS1. Treatment of human PBMCs with sNS1 purified from T164S mutant virus resulted in a twofold higher production of proinflammatory cytokines, suggesting a mechanism for how mutant sNS1 may cause more severe dengue disease.