Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics

Unveiling Lipidomic Alterations in Metabolic Syndrome: A Study of Plasma, Liver, and Adipose Tissues in a Dietary-Induced Rat Model

Metabolic syndrome (MetS) is a complex condition characterized by fat accumulation, dyslipidemia, impaired glucose control and hypertension. In this study, rats were fed a high-fat high-fructose (HFF) diet in order to develop MetS. After ten weeks, the dietary-induced MetS was confirmed by higher body fat percentage, lower HDL-cholesterol and increased blood pressure in the HFF-fed rats compared to the normal-fed control animals. However, the effect of MetS development on the lipidomic signature of the dietary-challenged rats remains to be investigated. To reveal the contribution of specific lipids to the development of MetS, the lipid profiling of rat tissues particularly susceptible to MetS was performed using untargeted UHPLC-QTOF-MS/MS lipidomic analysis. A total of 37 lipid species (mainly phospholipids, triglycerides, sphingolipids, cholesterol esters, and diglycerides) in plasma, 43 lipid species in liver, and 11 lipid species in adipose tissue were identified as dysregulated between the control and MetS groups. Changes in the lipid signature of selected tissues additionally revealed systemic changes in the dietary-induced rat model of MetS.

Spatial lipidomic profiles of atherosclerotic plaques: A mass spectrometry imaging study

Lipids contribute to atherosclerotic cardiovascular disease but their roles are not fully understood. Spatial lipid composition of atherosclerotic plaques was compared between species focusing on aortic plaques from New Zealand White rabbits and carotid plaques from humans (n = 3), using matrix-assisted laser desorption/ionization mass spectrometry imaging. Histologically discriminant lipids within plaque features (neointima and media in rabbits, and lipid-necrotic core and fibrous cap/tissue in humans) included sphingomyelins, phosphatidylcholines, and cholesteryl esters. There were 67 differential lipids between rabbit plaque features and 199 differential lipids in human, each with variable importance in projection score ≥1.0 and p < 0.05. The lipid profile of plaques in the rabbit model closely mimicked that of human plaques and two key pathways (impact value ≥ 0.1), sphingolipid and glycerophospholipid metabolism, were disrupted by atherosclerosis in both species. Thus, mass spectrometry imaging of spatial biomarkers offers valuable insights into atherosclerosis.

Untargeted Blood Lipidomics Analysis in Critically Ill Pediatric Patients with Ventilator-Associated Pneumonia: A Pilot Study

This study aims to explore the diagnostic potential of blood lipid profiles in suspected ventilator-associated pneumonia (VAP). Early detection of VAP remains challenging for clinicians due to subjective clinical criteria and the limited effectiveness of current diagnostic tests. Blood samples from 20 patients, with ages between 6 months and 15 years, were collected at days 1, 3, 6, and 12, and an untargeted lipidomics analysis was performed using a Ultra high Pressure Liquid Chromatography hyphenated with High Resolution Mass Spectrometry UPLC-HRMS (TIMS-TOF/MS) platform. Patients were stratified based on modified pediatric clinical pulmonary index score (mCPIS) into high (mCPIS ≥ 6, n = 12) and low (mCPIS < 6, n = 8) VAP suspicion groups. With the untargeted lipid profiling, we were able to identify 144 lipid species from different lipid groups such as glycerophospholipids, glycerolipids, and sphingolipids, in the blood of children with VAP. Multivariate and univariate statistical analyses revealed a distinct distribution of blood lipid profiles between the studied groups, indicating the potential utility of lipid biomarkers in discriminating VAP presence. Additionally, specific lipids were associated with pharyngeal culture results, notably the presence of Klebsiella pneumoniae and Staphylococcus aureus, underscoring the importance of lipid profiling in identifying the microbial etiology of VAP.

Challenges in Lipidomics Biomarker Identification: Avoiding the Pitfalls and Improving Reproducibility

Identification of features with high levels of confidence in liquid chromatography-mass spectrometry (LC-MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in biomarker identification. In this work, we illustrate the reproducibility gap for two open-access lipidomics platforms, MS DIAL and Lipostar, finding just 14.0% identification agreement when analyzing identical LC-MS spectra using default settings. Whilst the software platforms performed more consistently using fragmentation data, agreement was still only 36.1% for MS2 spectra. This highlights the critical importance of validation across positive and negative LC-MS modes, as well as the manual curation of spectra and lipidomics software outputs, in order to reduce identification errors caused by closely related lipids and co-elution issues. This curation process can be supplemented by data-driven outlier detection in assessing spectral outputs, which is demonstrated here using a novel machine learning approach based on support vector machine regression combined with leave-one-out cross-validation. These steps are essential to reduce the frequency of false positive identifications and close the reproducibility gap, including between software platforms, which, for downstream users such as bioinformaticians and clinicians, can be an underappreciated source of biomarker identification errors.

Lipidomic-Based Algorithms Can Enhance Prediction of Obstructive Coronary Artery Disease

Lipidomics emerges as a promising research field with the potential to help in personalized risk stratification and improve our understanding on the functional role of individual lipid species in the metabolic perturbations occurring in coronary artery disease (CAD). This study aimed to utilize a machine learning approach to provide a lipid panel able to identify patients with obstructive CAD. In this posthoc analysis of the prospective CorLipid trial, we investigated the lipid profiles of 146 patients with suspected CAD, divided into two categories based on the existence of obstructive CAD. In total, 517 lipid species were identified, from which 288 lipid species were finally quantified, including glycerophospholipids, glycerolipids, and sphingolipids. Univariate and multivariate statistical analyses have shown significant discrimination between the serum lipidomes of patients with obstructive CAD. Finally, the XGBoost algorithm identified a panel of 17 serum biomarkers (5 sphingolipids, 7 glycerophospholipids, a triacylglycerol, galectin-3, glucose, LDL, and LDH) as totally sensitive (100% sensitivity, 62.1% specificity, 100% negative predictive value) for the prediction of obstructive CAD. Our findings shed light on dysregulated lipid metabolism's role in CAD, validating existing evidence and suggesting promise for novel therapies and improved risk stratification.

Amniotic fluid stem cell-derived extracellular vesicles educate type 2 conventional dendritic cells to rescue autoimmune disorders in a multiple sclerosis mouse model

Dendritic cells (DCs) are essential orchestrators of immune responses and represent potential targets for immunomodulation in autoimmune diseases. Human amniotic fluid secretome is abundant in immunoregulatory factors, with extracellular vesicles (EVs) being a significant component. However, the impact of these EVs on dendritic cells subsets remain unexplored. In this study, we investigated the interaction between highly purified dendritic cell subsets and EVs derived from amniotic fluid stem cell lines (HAFSC-EVs). Our results suggest that HAFSC-EVs are preferentially taken up by conventional dendritic cell type 2 (cDC2) through CD29 receptor-mediated internalization, resulting in a tolerogenic DC phenotype characterized by reduced expression and production of pro-inflammatory mediators. Furthermore, treatment of cDC2 cells with HAFSC-EVs in coculture systems resulted in a higher proportion of T cells expressing the regulatory T cell marker Foxp3 compared to vehicle-treated control cells. Moreover, transfer of HAFSC-EV-treated cDC2s into an EAE mouse model resulted in the suppression of autoimmune responses and clinical improvement. These results suggest that HAFSC-EVs may serve as a promising tool for reprogramming inflammatory cDC2s towards a tolerogenic phenotype and for controlling autoimmune responses in the central nervous system, representing a potential platform for the study of the effects of EVs in DC subsets.

Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach

Nonalcoholic fatty liver disease (NAFLD), nowadays the most prevalent chronic liver disease in Western countries, is characterized by a variable phenotype ranging from steatosis to nonalcoholic steatohepatitis (NASH). Intracellular lipid accumulation is considered the hallmark of NAFLD and is associated with lipotoxicity and inflammation, as well as increased oxidative stress levels. In this study, a lipidomic approach was used to investigate the plasma lipidome of 12 NASH patients, 10 Nonalcoholic Fatty Liver (NAFL) patients, and 15 healthy controls, revealing significant alterations in lipid classes, such as glycerolipids and glycerophospholipids, as well as fatty acid compositions in the context of steatosis and steatohepatitis. A machine learning XGBoost algorithm identified a panel of 15 plasma biomarkers, including HOMA-IR, BMI, platelets count, LDL-c, ferritin, AST, FA 12:0, FA 18:3 ω3, FA 20:4 ω6/FA 20:5 ω3, CAR 4:0, LPC 20:4, LPC O-16:1, LPE 18:0, DG 18:1_18:2, and CE 20:4 for predicting steatohepatitis. This research offers insights into the connection between imbalanced lipid metabolism and the formation and progression of NAFL D, while also supporting previous research findings. Future studies on lipid metabolism could lead to new therapeutic approaches and enhanced risk assessment methods, as the shift from isolated steatosis to NASH is currently poorly understood.

Lipidomic Analysis of Liver and Adipose Tissue in a High-Fat Diet-Induced Non-Alcoholic Fatty Liver Disease Mice Model Reveals Alterations in Lipid Metabolism by Weight Loss and Aerobic Exercise

Detailed investigation of the lipidome remodeling upon normal weight conditions, obesity, or weight loss, as well as the influence of physical activity, can help to understand the mechanisms underlying dyslipidemia in metabolic conditions correlated to the emergence and progression of non-alcoholic fatty liver disease (NAFLD). C57BL/6 male mice were fed a normal diet (ND) or a high-fat diet (HFD) for 20 weeks. Subgroups within the high-fat diet (HFD) group underwent different interventions: some engaged in exercise (HFDex), others were subjected to weight loss (WL) by changing from the HFD to ND, and some underwent a combination of weight loss and exercise (WLex) during the final 8 weeks of the 20-week feeding period. To support our understanding, not only tissue-specific lipid remodeling mechanisms but also the cross-talk between different tissues and their impact on the systemic regulation of lipid metabolism are essential. Exercise and weight loss-induced specific adaptations in the liver and visceral adipose tissue lipidomes of mice were explored by the UPLC-TOF-MS/MS untargeted lipidomics methodology. Lipidomic signatures of ND and HFD-fed mice undergoing weight loss were compared with animals with and without physical exercise. Several lipid classes were identified as contributing factors in the discrimination of the groups by multivariate analysis models, such as glycerolipids, glycerophospholipids, sphingolipids, and fatty acids, with respect to liver samples, whereas triglycerides were the only lipid class identified in visceral adipose tissue. Lipids found to be dysregulated in HFD animals are related to well-established pathways involved in the biosynthesis of PC, PE, and TG metabolism. These show a reversing trend back to basic levels of ND when animals change to a normal diet after 12 weeks, whereas the impact of exercise, though in some cases it slightly enhances the reversing trend, is not clear.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

In Silico-Predicted Dynamic Oxlipidomics MS/MS Library: High-Throughput Discovery and Characterization of Unknown Oxidized Lipids

Nontargeted lipidomics using liquid chromatography-tandem mass spectrometry can detect thousands of molecules in biological samples. However, the annotation of unknown oxidized lipids is limited to the structures present in libraries, restricting the analysis and interpretation of experimental data. Here, we describe Doxlipid, a computational tool for oxidized lipid annotation that predicts a dynamic MS/MS library for every experiment. Doxlipid integrates three key simulation algorithms to predict libraries and covers 32 subclasses of oxidized lipids from the three main classes. In the evaluation, Doxlipid achieves very high prediction and characterization performance and outperforms the current oxidized lipid annotation methods. Doxlipid, combined with a molecular network, further annotates unknown chemical analogs in the same reaction or pathway. We demonstrate the broad utility of Doxlipid by analyzing oxidized lipids in ferroptosis hepatocellular carcinoma, tissue samples, and other biological samples, substantially advancing the discovery of biological pathways at the trace oxidized lipid level.

MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics

Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.

Dual species sphingosine-1-phosphate lyase inhibitors to combine antifungal and anti-inflammatory activities in cystic fibrosis: a feasibility study

Cystic fibrosis (CF) is an autosomal recessive disorder characterized by respiratory failure due to a vicious cycle of defective Cystic Fibrosis Transmembrane conductance Regulator (CFTR) function, chronic inflammation and recurrent bacterial and fungal infections. Although the recent introduction of CFTR correctors/potentiators has revolutionized the clinical management of CF patients, resurgence of inflammation and persistence of pathogens still posit a major concern and should be targeted contextually. On the background of a network-based selectivity that allows to target the same enzyme in the host and microbes with different outcomes, we focused on sphingosine-1-phosphate (S1P) lyase (SPL) of the sphingolipid metabolism as a potential candidate to uniquely induce anti-inflammatory and antifungal activities in CF. As a feasibility study, herein we show that interfering with S1P metabolism improved the immune response in a murine model of CF with aspergillosis while preventing germination of Aspergillus fumigatus conidia. In addition, in an early drug discovery process, we purified human and A. fumigatus SPL, characterized their biochemical and structural properties, and performed an in silico screening to identify potential dual species SPL inhibitors. We identified two hits behaving as competitive inhibitors of pathogen and host SPL, thus paving the way for hit-to-lead and translational studies for the development of drug candidates capable of restraining fungal growth and increasing antifungal resistance.

A platelet lipidomics signature in patients with COVID-19

Ischemic cardiovascular and venous thromboembolic events are a frequent cause of death in severe COVID-19 patients. Platelet activation plays a key role in these complications, however platelet lipidomics have not been studied yet. The aim of our pilot investigation was to perform a preliminary study of platelet lipidomics in COVID-19 patients compared to healthy subjects. Lipid extraction and identification of ultrapurified platelets from eight hospitalized COVID-19 patients and eight age- and sex-matched healthy controls showed a lipidomic pattern almost completely separating COVID-19 patients from healthy controls. In particular, a significant decrease of ether phospholipids and increased levels of ganglioside GM3 were observed in platelets from COVID-19 patients. In conclusion, our study shows for the first time that platelets from COVID-19 patients display a different lipidomics signature distinguishing them from healthy controls, and suggests that altered platelet lipid metabolism may play a role in viral spreading and in the thrombotic complications of COVID-19.

Chiral high-performance liquid chromatography analysis of mono-, di-, and triacylglycerols with amylose- and cellulose-phenylcarbamate-based stationary phases

The ever-increasing technological advancement in the (ultra)high-performance liquid chromatography tandem (high-resolution) mass spectrometry platforms have largely contributed to steeply intensify the interest towards lipidomics research. However, mass spectrometers alone are unable to distinguish between enantiomers. This obstacle is especially evident in the case of glycerolipids analysis due the prochiral nature of glycerol. Until a couple of decades ago, the stereoselective analysis of triacylglycerols (TAGs) was performed on the end products generated either from their enzymatic or chemical hydrolysis, namely on mono- or diacyl-sn-glycerols (MAGs and DAGs, respectively). These were then mostly analyzed with Pirkle-type chiral stationary phases (CSPs) after dedicated multi-step derivatization procedures. One of the most significant drawbacks of these traditional methods for enantioselective TAGs analysis (actually of the produced MAGs and DAGs, often investigated as target species per se) was the difficulty to totally abolish the migration of fatty acyls between glycerol positions. This made difficult to control and keep unaltered the stereochemistry of the original molecules. Over the last two decades, it has been widely demonstrated that the enantioselective analysis of intact TAGs as well as of non-derivatized MAGs and DAGs can be efficiently obtained using polysaccharide-based CSPs incorporating either amylose- or cellulose-phenylcarbamate derivatives chiral selectors. In this paper, the enantioselective methods developed with these CSPs for the enantioselective direct LC analysis of MAGs, DAGs and TAGs embedding different types of fatty acid residues are comprehensively reviewed.

Q-RAI data-independent acquisition for lipidomic quantitative profiling

Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC-MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies.

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.

IsoMatchMS: Open-Source Software for Automated Annotation and Visualization of High Resolution MALDI-MS Spectra

Due to its speed, accuracy, and adaptability to various sample types, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a popular method to identify molecular isotope profiles from biological samples. Often MALDI-MS data do not include tandem MS fragmentation data, and thus the identification of compounds in samples requires external databases so that the accurate mass of detected signals can be matched to known molecular compounds. Most relevant MALDI-MS software tools developed to confirm compound identifications are focused on small molecules (e.g., metabolites, lipids) and cannot be easily adapted to protein data due to their more complex isotopic distributions. Here, we present an R package called IsoMatchMS for the automated annotation of MALDI-MS data for multiple datatypes: intact proteins, peptides, and glycans. This tool accepts already derived molecular formulas or, for proteomics applications, can derive molecular formulas from a list of input peptides or proteins including proteins with post-translational modifications. Visualization of all matched isotopic profiles is provided in a highly accessible HTML format called a trelliscope display, which allows users to filter and sort by several parameters such as match scores and the number of peaks matched. IsoMatchMS simplifies the annotation and visualization of MALDI-MS data for downstream analyses.

Whole Blood and Plasma-Based Lipid Profiling Reveals Distinctive Metabolic Changes in Systemic Lupus Erythematosus and Systemic Sclerosis

Autoimmune diseases (AID), such as systemic lupus erythematosus (SLE) and systemic sclerosis (SS), are complex conditions involving immune system dysregulation. Diagnosis is challenging, requiring biomarkers for improved detection and prediction of relapses. Lipids have emerged as potential biomarkers due to their role in inflammation and immune response. This study uses an untargeted C18 RP-LC-MS lipidomics approach to comprehensively assess changes in lipid profiles in patients with SLE and SS. By analyzing whole blood and plasma, the study aims to simplify the lipidomic analysis, explore cellular-level lipids, and compare lipid signatures of SLE and SS with healthy controls. Our findings showed variations in the lipid profile of SLE and SS. Sphingomyelin and ceramide molecular species showed significant increases in plasma samples from SS patients, suggesting an atherosclerotic profile and potentially serving as lipid biomarkers. Phosphatidylserine species in whole blood from SLE patients exhibited elevated levels supporting previously reported dysregulated processes of cell death and defective clearance of dying cells in this AID. Moreover, decreased phospholipids bearing PUFA were observed, potentially attributed to the degradation of these species through lipid peroxidation processes. Further studies are needed to better understand the role of lipids in the pathological mechanisms underlying SLE and SS.

Enhancing metabolite coverage in MALDI-MSI using laser post-ionisation (MALDI-2)

Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) of metabolites can reveal how metabolism is altered throughout heterogeneous tissues. Here negative ion mode MALDI-MSI has been coupled with laser post-ionisation (MALDI-2) and applied to the MSI of low molecular weight (LMW) metabolites ( Collapse

Key Words Collapse

MESH Headings

• Animals
• Mice
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
• Molecular Weight
• Drama
• Glutamic Acid
• Lasers
• Thinness

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Grants Collapse

Affiliation(s)

J C McKinnon Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.
H H Milioli Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
C A Purcell Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
C L Chaffer Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
B Wadie Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
T Alexandrov Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
T W Mitchell Molecular Horizons, School of Medical, Indigenous and Health Science, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
S R Ellis Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.

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Fatty acid desaturase 2 determines the lipidomic landscape and steroidogenic function of the adrenal gland

Corticosteroids regulate vital processes, including stress responses, systemic metabolism, and blood pressure. Here, we show that corticosteroid synthesis is related to the polyunsaturated fatty acid (PUFA) content of mitochondrial phospholipids in adrenocortical cells. Inhibition of the rate-limiting enzyme of PUFA synthesis, fatty acid desaturase 2 (FADS2), leads to perturbations in the mitochondrial lipidome and diminishes steroidogenesis. Consistently, the adrenocortical mitochondria of Fads2-/- mice fed a diet with low PUFA concentration are structurally impaired and corticoid levels are decreased. On the contrary, FADS2 expression is elevated in the adrenal cortex of obese mice, and plasma corticosterone is increased, which can be counteracted by dietary supplementation with the FADS2 inhibitor SC-26192 or icosapent ethyl, an eicosapentaenoic acid ethyl ester. In humans, FADS2 expression is elevated in aldosterone-producing adenomas compared to non-active adenomas or nontumorous adrenocortical tissue and correlates with expression of steroidogenic genes. Our data demonstrate that FADS2-mediated PUFA synthesis determines adrenocortical steroidogenesis in health and disease.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

Metabolic signature of HepaRG cells exposed to ethanol and tumor necrosis factor alpha to study alcoholic steatohepatitis by LC-MS-based untargeted metabolomics

Despite the high prevalence of alcoholic liver disease, its identification and characterization remain poor, especially in early stages such as alcoholic fatty liver disease and alcoholic steatohepatitis. This latter implies diagnostic difficulties, few therapeutic options and unclear mechanisms of action. To elucidate the metabolic alterations and pinpoint affected biochemical pathways, alcoholic steatohepatitis was simulated in vitro by exposing HepaRG cells to ethanol (IC₁₀, 368 mM) and tumor necrosis factor alpha (TNF-α, 50 ng/mL) for 24 h. This combined exposure was compared to solely ethanol-exposed as well as -nonexposed cells. Four different metabolomics platforms were used combining liquid chromatography, high-resolution mass spectrometry and drift tube ion mobility to elucidate both intracellular and extracellular metabolic alterations. Some of the key findings include the influence of TNF-α in the upregulation of hepatic triglycerides and the downregulation of hepatic phosphatidylethanolamines and phosphatidylcholines. S-Adenosylmethionine showed to play a central role in the progression of alcoholic steatohepatitis. In addition, fatty acyl esters of hydroxy fatty acid (FAHFA)-containing triglycerides were detected for the first time in human hepatocytes and their alterations showed a potentially important role during the progression of alcoholic steatohepatitis. Ethoxylated phosphorylcholine was identified as a potential new biomarker of ethanol exposure.

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.

Retinoic acid-induced 1 gene haploinsufficiency alters lipid metabolism and causes autophagy defects in Smith-Magenis syndrome

Smith-Magenis syndrome (SMS) is a neurodevelopmental disorder characterized by cognitive and behavioral symptoms, obesity, and sleep disturbance, and no therapy has been developed to alleviate its symptoms or delay disease onset. SMS occurs due to haploinsufficiency of the retinoic acid-induced-1 (RAI1) gene caused by either chromosomal deletion (SMS-del) or RAI1 missense/nonsense mutation. The molecular mechanisms underlying SMS are unknown. Here, we generated and characterized primary cells derived from four SMS patients (two with SMS-del and two carrying RAI1 point mutations) and four control subjects to investigate the pathogenetic processes underlying SMS. By combining transcriptomic and lipidomic analyses, we found altered expression of lipid and lysosomal genes, deregulation of lipid metabolism, accumulation of lipid droplets, and blocked autophagic flux. We also found that SMS cells exhibited increased cell death associated with the mitochondrial pathology and the production of reactive oxygen species. Treatment with N-acetylcysteine reduced cell death and lipid accumulation, which suggests a causative link between metabolic dyshomeostasis and cell viability. Our results highlight the pathological processes in human SMS cells involving lipid metabolism, autophagy defects and mitochondrial dysfunction and suggest new potential therapeutic targets for patient treatment.

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.

Single‐Photon‐Induced Post‐Ionization to Boost Ion Yields in MALDI Mass Spectrometry Imaging**

Matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI) is a rapidly growing method in the life sciences. However, for many analyte classes, its sensitivity is limited due to poor ionization efficiencies. To mitigate this problem, we here introduce a novel post‐ionization scheme based on single‐photon induced chemical ionization using pulsed RF‐Kr lamps. The fine‐vacuum conditions of a dual ion‐funnel ion source effectively thermalize the evolving MALDI plume and enable ample gas‐phase reactions. Injected chemical dopants crucially support fragment‐less ionization to [M+H]⁺/[M−H]⁻ species. Based on this interplay, numerous glycerophospho‐, sphingo‐, and further lipids, registered from mammalian tissue sections, were boosted by up to three orders of magnitude, similar to results obtained with laser‐based post‐ionization (MALDI‐2). Experiments with deuterated matrix and dopant, however, indicated complex chemical ionization pathways different from MALDI‐2.

Mass spectrometry imaging identifies altered hepatic lipid signatures during experimental Leishmania donovani infection

Introduction

Spatial analysis of lipids in inflammatory microenvironments is key to understand the pathogenesis of infectious disease. Granulomatous inflammation is a hallmark of leishmaniasis and changes in host and parasite lipid metabolism have been observed at the bulk tissue level in various infection models. Here, mass spectrometry imaging (MSI) is applied to spatially map hepatic lipid composition following infection with Leishmania donovani, an experimental mouse model of visceral leishmaniasis.

Methods

Livers from naïve and L. donovani-infected C57BL/6 mice were harvested at 14- and 20-days post-infection (n=5 per time point). 12 µm transverse sections were cut and covered with norhamane, prior to lipid analysis using MALDI-MSI. MALDI-MSI was performed in negative mode on a Rapiflex (Bruker Daltonics) at 5 and 50 µm spatial resolution and data-dependent analysis (DDA) on an Orbitrap-Elite (Thermo-Scientific) at 50 µm spatial resolution for structural identification analysis of lipids.

Results

Aberrant lipid abundances were observed in a heterogeneous distribution across infected mouse livers compared to naïve mouse liver. Distinctive localized correlated lipid masses were found in granulomas and surrounding parenchymal tissue. Structural identification revealed 40 different lipids common to naïve and d14/d20 infected mouse livers, whereas 15 identified lipids were only detected in infected mouse livers. For pathology-guided MSI imaging, we deduced lipids from manually annotated granulomatous and parenchyma regions of interests (ROIs), identifying 34 lipids that showed significantly different intensities between parenchyma and granulomas across all infected livers.

Discussion

Our results identify specific lipids that spatially correlate to the major histopathological feature of Leishmania donovani infection in the liver, viz. hepatic granulomas. In addition, we identified a three-fold increase in the number of unique phosphatidylglycerols (PGs) in infected liver tissue and provide direct evidence that arachidonic acid-containing phospholipids are localized with hepatic granulomas. These phospholipids may serve as important precursors for downstream oxylipin generation with consequences for the regulation of the inflammatory cascade. This study provides the first description of the use of MSI to define spatial-temporal lipid changes at local sites of infection induced by Leishmania donovani in mice.

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.

Lipidomics profiling of zebrafish liver through untargeted liquid chromatography-high resolution mass spectrometry

Lipidomics analysis of zebrafish tissues has shown promising results to understand disease-related outcomes of exposure to toxic substances at molecular level. However, knowledge about their lipidome is limited, as most untargeted studies only identify the lipids that are statistically significant in their setup. In this work, liquid chromatography-high resolution mass spectrometry was used to study different aspects of the analytical workflow, i.e., extraction solvents (methanol/chloroform/water (3/2/2, v/v/v), methanol/dichloromethane/water (2/3/2, v/v/v) and methanol/methyl-tert-butyl ether/water (3/10/2.5, v/v/v), instrumental response, and strategies used for lipid annotation. The number of high-quality features (relative standard deviation of the intensity values ≤ 10% in the range 10³ -10⁷ counts) was affected by the dilution of lipid extracts, indicating that it is an important parameter for developing untargeted methods. The workflows used allowed the selection of a dilution factor to annotate 712 lipid species (507 bulk lipids) in zebrafish liver using four software (LipidMatch, LipidHunter, MS-DIAL and Lipostar). Retention time mapping was a valuable tool to filter lipid annotations obtained from automatic software annotations. The lipid profiling of zebrafish livers will help in a better understanding of the true constitution of their lipidome at the species level, as well as in the use of zebrafish in toxicological studies. This article is protected by copyright. All rights reserved.

Murine Falcor/LL35 lncRNA Contributes to Glucose and Lipid Metabolism In Vitro and In Vivo

Glucose and lipid metabolism are crucial functional systems in eukaryotes. A large number of experimental studies both in animal models and humans have shown that long non-coding RNAs (lncRNAs) play an important role in glucose and lipid metabolism. Previously, human lncRNA DEANR1/linc00261 was described as a tumor suppressor that regulates a variety of biological processes such as cell proliferation, apoptosis, glucose metabolism and tumorigenesis. Here we report that murine lncRNA Falcor/LL35, a proposed functional analog of human DEANR1/linc00261, is predominantly expressed in murine normal hepatocytes and downregulated in HCC and after partial hepatectomy. The application of high-throughput approaches such as RNA-seq, LC-MS proteomics, lipidomics and metabolomics analysis allowed changes to be found in the transcriptome, proteome, lipidome and metabolome of hepatocytes after LL35 depletion. We revealed that LL35 is involved in the regulation of glycolysis and lipid biosynthesis in vitro and in vivo. Moreover, LL35 affects Notch and NF-κB signaling pathways in normal hepatocytes. All observed changes result in the decrease in the proliferation and migration of hepatocytes. We demonstrated similar phenotype changes between murine LL35 and human linc00261 depletion in vitro and in vivo that opens the opportunity to translate results for LL35 from a liver murine model to possible functions of human lncRNA linc00261.

Lipid metabolism analysis in liver of different chicken genotypes and impact on nutritionally relevant polyunsaturated fatty acids of meat

Humans and mammalian species are unable to synthesize significant amounts of polyunsaturated fatty acids (PUFA), which therefore must be introduced with the diet. In birds, lipogenesis takes place primarily in the liver, whereas adipose tissue serves as the storage site for triacylglycerols (TG, composed by 80-85% esterified fatty acids). However, both the nature (unsaturation level, n-3, or n-6 series) and the allocation (such as constituents of complexed lipids) of PUFA are very important to evaluate their function in lipid metabolism. The objective of the present investigation was to study the liver lipid metabolism, with particular attention to non-esterified fatty acids (NEFA), TG, phospholipids (PL), FADS2 gene expression, and Δ6-desaturase activity of three chicken genotypes, Leghorn (Leg), Ross 308 (Ross), and their crossbreed (LxR), by LC/MS analysis. The concentration of single fatty acids in muscle was quantified by GC-FID. The results showed that the Ross has a lipid metabolism related mainly to storage and structural roles, exhibiting higher levels of TG, phosphatidylethanolamine (PE) and phosphatidylcholine (PC) that are largely unsaturated. Meanwhile Leg showed a relevant amount of n-3 NEFA characterized by a higher phosphatidylserine (PS) unsaturation level, FADS2 gene expression and enzyme activity. The LxR seem to have a moderate trend: n-6 and n-3 NEFA showed intermediate values compared with that of the Ross and Leg and the TG trend was similar to that of the Ross, while PE and PC were largely unsaturated (mainly 6 and 7 UNS most of the metabolic energy for storage fatty acids in their tissues (TG) whereas, the Leg birds were characterized by different lipid metabolism showing in their liver a higher content of n-3 NEFA and higher unsaturation level in PS. Furthers details are needed to better attribute the lipid energy to the different metabolic portion.

Role of cardiolipins, mitochondria, and autophagy in the differentiation process activated by all-trans retinoic acid in acute promyelocytic leukemia

The role played by lipids in the process of granulocytic differentiation activated by all-trans retinoic acid (ATRA) in Acute-Promyelocytic-Leukemia (APL) blasts is unknown. The process of granulocytic differentiation activated by ATRA in APL blasts is recapitulated in the NB4 cell-line, which is characterized by expression of the pathogenic PML-RARα fusion protein. In the present study, we used the NB4 model to define the effects exerted by ATRA on lipid homeostasis. Using a high-throughput lipidomic approach, we demonstrate that exposure of the APL-derived NB4 cell-line to ATRA causes an early reduction in the amounts of cardiolipins, a major lipid component of the mitochondrial membranes. The decrease in the levels of cardiolipins results in a concomitant inhibition of mitochondrial activity. These ATRA-dependent effects are causally involved in the granulocytic maturation process. In fact, the ATRA-induced decrease of cardiolipins and the concomitant dysfunction of mitochondria precede the differentiation of retinoid-sensitive NB4 cells and the two phenomena are not observed in the retinoid-resistant NB4.306 counterparts. In addition, ethanolamine induced rescue of the mitochondrial dysfunction activated by cardiolipin deficiency inhibits ATRA-dependent granulocytic differentiation and induction of the associated autophagic process. The RNA-seq studies performed in parental NB4 cells and a NB4-derived cell population, characterized by silencing of the autophagy mediator, ATG5, provide insights into the mechanisms underlying the differentiating action of ATRA. The results indicate that ATRA causes a significant down-regulation of CRLS1 (Cardiolipin-synthase-1) and LPCAT1 (Lysophosphatidylcholine-Acyltransferase-1) mRNAs which code for two enzymes catalyzing the last steps of cardiolipin synthesis. ATRA-dependent down-regulation of CRLS1 and LPCAT1 mRNAs is functionally relevant, as it is accompanied by a significant decrease in the amounts of the corresponding proteins. Furthermore, the decrease in CRLS1 and LPCAT1 levels requires activation of the autophagic process, as down-regulation of the two proteins is blocked in ATG5-silenced NB4-shATG5 cells.

Fully Automatized Detection of Phosphocholine-Containing Lipids through an Isotopically Labeled Buffer Modification Workflow

High-resolution mass spectrometry is the foremost technique for qualitative and quantitative lipidomics analyses. Glycerophospholipids and sphingolipids, collectively termed polar lipids, are commonly investigated by hyphenated liquid chromatography-mass spectrometry (LC-MS) techniques that reduce aggregation effects and provide a greater dynamic range of detection sensitivity compared to shotgun lipidomics. However, automatic polar lipid identification is hindered by several isobaric and isomer mass overlaps, which cause software programs to often fail to correctly annotate the lipid species. In the present paper, a buffer modification workflow based on the use of labeled and unlabeled acetate ions in the chromatographic buffers was optimized by Box-Behnken design of the experiments and applied to the characterization of phosphocholine-containing lipids in human plasma samples. The contemporary generation of [M + CH₃COO]^-, [M + CD₃COO]^-, and [M - CH₃]^- coupled with a dedicated data processing workflow, which was specifically set up on Compound Discoverer software, allowed us to correctly determine adduct composition, molecular formulas, and grouping, as well as granting a lower false-positive rate and streamlining the manual validation step compared to commonly employed lipidomics platforms. The proposed workflow represents a robust yet easier alternative to the existing approaches for improving lipid annotation, as it does not require extensive sample pretreatment or prior isotopic enrichment or derivatization.

AdipoAtlas: A reference lipidome for human white adipose tissue

Obesity, characterized by expansion and metabolic dysregulation of white adipose tissue (WAT), has reached pandemic proportions and acts as a primer for a wide range of metabolic disorders. Remodeling of WAT lipidome in obesity and associated comorbidities can explain disease etiology and provide valuable diagnostic and prognostic markers. To support understanding of WAT lipidome remodeling at the molecular level, we provide in-depth lipidomics profiling of human subcutaneous and visceral WAT of lean and obese individuals. We generate a human WAT reference lipidome by performing tissue-tailored preanalytical and analytical workflows, which allow accurate identification and semi-absolute quantification of 1,636 and 737 lipid molecular species, respectively. Deep lipidomic profiling allows identification of main lipid (sub)classes undergoing depot-/phenotype-specific remodeling. Previously unanticipated diversity of WAT ceramides is now uncovered. AdipoAtlas reference lipidome serves as a data-rich resource for the development of WAT-specific high-throughput methods and as a scaffold for systems medicine data integration.

Integratomics of Human Dermal Fibroblasts Treated with Low Molecular Weight Hyaluronic Acid

Hyaluronic acid (HA) is a glycosaminoglycan very common in commercial products from pharmaceuticals to cosmetics due to its widespread distribution in humans and its diversified physico-chemical proprieties. Despite its extended use and preliminary evidence showing even also opposite activities to the native form, the precise cellular effects of HA at low-molecular-weight (LWM-HA) are currently unclear. The ‘omics sciences currently in development offer a new and combined perspective on the cellular and organismal environment. This work aims to integrate lipidomics analyses to our previous quantitative proteomics one for a multi-omics vision of intra- and extra-cellular impact of different concentrations (0.125, 0.25, and 0.50%) of LMW-HA (20–50 kDa) on normal human dermal fibroblasts by LC-high resolution mass spectrometry (LC-HRMS). Untargeted lipidomics allowed us to identify 903 unique lipids mostly represented by triacylglycerols, ceramides, and phosphatidylcholines. According to proteomics analyses, LMW-HA 0.50% was the most effective concentration also in the lipidome rearrangement especially stimulating the synthesis of ceramides involved in skin hydration and reparation, cell signaling, and energy balance. Finally, integrative analyses showed 25 nodes covering several intra- and extra-cellular functions. The more complete comprehension of intra- and extra-cellular effects of LMW-HA here pointed out will be useful to further exploit its features and improve current formulations even though further studies on lipids biosynthesis and degradation are necessary.

Analytical Methodologies for Lipidomics in Hemp Plant

The chemical composition of Cannabis sativa L. has been extensively studied for tens of years, but little is known about its lipidome. This chapter describes an analytical workflow for polar lipid determination in hemp. After extraction, lipids are enriched and isolated by graphitized carbon black sorbent, and the isolated lipid is analyzed by liquid chromatography (LC) coupled with high resolution mass spectrometry, leading to identification of many lipid species. We have developed a semi-automated platform using commercially available Lipostar software for lipid identification. Our approach affords the identification of 189 polar lipids in hemp extract, including sulfolipids and phospholipids. The number of the identified lipid species is by far the highest ever reported for Cannabis sativa.

Aircraft noise exposure drives the activation of white blood cells and induces microvascular dysfunction in mice

Epidemiological studies showed that traffic noise has a dose-dependent association with increased cardiovascular morbidity and mortality. Whether microvascular dysfunction contributes significantly to the cardiovascular health effects by noise exposure remains to be established. The connection of inflammation and immune cell interaction with microvascular damage and functional impairment is also not well characterized. Male C57BL/6J mice or gp91phox^−/y mice with genetic deletion of the phagocytic NADPH oxidase catalytic subunit (gp91phox or NOX-2) were used at the age of 8 weeks, randomly instrumented with dorsal skinfold chambers and exposed or not exposed to aircraft noise for 4 days. Proteomic analysis (using mass spectrometry) revealed a pro-inflammatory phenotype induced by noise exposure that was less pronounced in noise-exposed gp91phox^−/y mice. Using in vivo fluorescence microscopy, we found a higher number of adhesive leukocytes in noise-exposed wild type mice. Dorsal microvascular diameter (by trend), red blood cell velocity, and segmental blood flow were also decreased by noise exposure indicating microvascular constriction. All adverse effects on functional parameters were normalized or improved at least by trend in noise-exposed gp91phox^−/y mice. Noise exposure also induced endothelial dysfunction in cerebral microvessels, which was associated with higher oxidative stress burden and inflammation, as measured using video microscopy. We here establish a link between a pro-inflammatory phenotype of plasma, activation of circulating leukocytes and microvascular dysfunction in mice exposed to aircraft noise. The phagocytic NADPH oxidase was identified as a central player in the underlying pathophysiological mechanisms.

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Noise exposure induces a pro-thrombo-inflammatory phenotype in mouse plasma.

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Aircraft noise increases leukocyte-endothelium interactions in dorsal microvessels.

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Noise decreases segmental blood flow/red blood cell velocity in dorsal microvessels.

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Noise increases cerebral microvascular dysfunction and oxidative stress.

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Nox2 deficiency (gp91phox^-/y) improves noise-induced adverse effects.

Mass Spectrometry-based Biomarkers for Knee Osteoarthritis: A Systematic Review

Introduction: Knee osteoarthritis (OA) is a joint disease, affecting multiple tissues in the joint. Early detection and intervention may delay OA development and avoid total knee arthroplasty. Specific biomarker profiles for early detection and guiding clinical decision-making of OA have not yet been identified. One technique that can contribute to the finding of this "OA biomarker" is mass spectrometry (MS), which offers the possibility to analyze different molecules in tissues or fluids. Several proteomic, lipidomic, metabolomic and other -omic approaches aim to identify these molecular profiles; however, variation in methods and techniques complicate the finding of promising candidate biomarkers.Areas covered: In this systematic review, we aim to provide an overview of molecules in OA knee patients. Possible biomarkers in several tissue types of OA and non-OA patients, as well as current limitations and possible future suggestions will be discussed.Expert opinion: According to this review, we do not believe one specific biomarker will function as predictive molecule for OA. Likely, a group of molecules will give insight in OA development and possible therapeutic targets. For clinical implementation of MS-analysis in clinical decision-making, standardized procedures, large cohort studies and sharing protocols and data is necessary.

Enhanced triacylglycerol catabolism by carboxylesterase 1 promotes aggressive colorectal carcinoma

The ability to adapt to low-nutrient microenvironments is essential for tumor cell survival and progression in solid cancers, such as colorectal carcinoma (CRC). Signaling by the NF-κB transcription factor pathway associates with advanced disease stages and shorter survival in patients with CRC. NF-κB has been shown to drive tumor-promoting inflammation, cancer cell survival, and intestinal epithelial cell (IEC) dedifferentiation in mouse models of CRC. However, whether NF-κB affects the metabolic adaptations that fuel aggressive disease in patients with CRC is unknown. Here, we identified carboxylesterase 1 (CES1) as an essential NF-κB-regulated lipase linking obesity-associated inflammation with fat metabolism and adaptation to energy stress in aggressive CRC. CES1 promoted CRC cell survival via cell-autonomous mechanisms that fuel fatty acid oxidation (FAO) and prevent the toxic build-up of triacylglycerols. We found that elevated CES1 expression correlated with worse outcomes in overweight patients with CRC. Accordingly, NF-κB drove CES1 expression in CRC consensus molecular subtype 4 (CMS4), which is associated with obesity, stemness, and inflammation. CES1 was also upregulated by gene amplifications of its transcriptional regulator HNF4A in CMS2 tumors, reinforcing its clinical relevance as a driver of CRC. This subtype-based distribution and unfavorable prognostic correlation distinguished CES1 from other intracellular triacylglycerol lipases and suggest CES1 could provide a route to treat aggressive CRC.

Automatic Identification of Lansoprazole Degradants under Stress Conditions by LC-HRMS with MassChemSite and WebChembase

Stress testing is one of the most important parts of the drug development process, helping to foresee stability problems and to identify degradation products. One of the processes involving stress testing is represented by forced degradation studies, which can predict the impact of certain conditions of pH, moisture, heat, or other negative effects due to transportation or packaging issues on drug potency and purity, ensuring patient safety. Regulatory agencies have been working on a standardization of laboratory procedures since the past two decades. One of the results of those years of intensive research is the International Conference on Harmonization (ICH) guidelines, which clearly define which forced degradation studies should be performed on new drugs, which become a routine work in pharmaceutical laboratories. Since used techniques based on high-performance liquid chromatography coupled with high-resolution mass spectrometry have been developed years ago and are now mastered by pharmaceutical scientists, automation of data analysis, and thus data processing, is becoming a hot topic nowadays. In this work, we present MassChemSite and WebChembase as a tandem to automatize the routine analysis studies without missing information quality, using as a case study the degradation of lansoprazole under acidic, oxidative, basic, and neutral stress conditions.

Functional and Material Properties in Nanocatalyst Design: A Data Handling and Sharing Problem

(1) Background: Properties and descriptors are two forms of molecular in silico representations. Properties can be further divided into functional, e.g., catalyst or drug activity, and material, e.g., X-ray crystal data. Millions of real measured functional property records are available for drugs or drug candidates in online databases. In contrast, there is not a single database that registers a real conversion, TON or TOF data for catalysts. All of the data are molecular descriptors or material properties, which are mainly of a calculation origin. (2) Results: Here, we explain the reason for this. We reviewed the data handling and sharing problems in the design and discovery of catalyst candidates particularly, material informatics and catalyst design, structural coding, data collection and validation, infrastructure for catalyst design and the online databases for catalyst design. (3) Conclusions: Material design requires a property prediction step. This can only be achieved based on the registered real property measurement. In reality, in catalyst design and discovery, we can observe either a severe functional property deficit or even property famine.

Towards Physiologic Culture Approaches to Improve Standard Cultivation of Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are of great interest for their use in cell-based therapies due to their multipotent differentiation and immunomodulatory capacities. In consequence of limited numbers following their isolation from the donor tissue, MSCs require extensive expansion performed in traditional 2D cell culture setups to reach adequate amounts for therapeutic use. However, prolonged culture of MSCs in vitro has been shown to decrease their differentiation potential and alter their immunomodulatory properties. For that reason, preservation of these physiological characteristics of MSCs throughout their in vitro culture is essential for improving the efficiency of therapeutic and in vitro modeling applications. With this objective in mind, many studies already investigated certain parameters for enhancing current standard MSC culture protocols with regard to the effects of specific culture media components or culture conditions. Although there is a lot of diversity in the final therapeutic uses of the cells, the primary stage of standard isolation and expansion is imperative. Therefore, we want to review on approaches for optimizing standard MSC culture protocols during this essential primary step of in vitro expansion. The reviewed studies investigate and suggest improvements focused on culture media components (amino acids, ascorbic acid, glucose level, growth factors, lipids, platelet lysate, trace elements, serum, and xenogeneic components) as well as culture conditions and processes (hypoxia, cell seeding, and dissociation during passaging), in order to preserve the MSC phenotype and functionality during the primary phase of in vitro culture.

Degradation of the polar lipid and fatty acid molecular species in extra virgin olive oil during storage based on shotgun lipidomics

Among the bioactive compounds present in extra-virgin olive oil, polar lipids and free fatty acids are minor compounds with well-known nutritional values and have been studied for traceability and adulteration investigations as well. In the present paper, the simultaneous characterization of polar lipids and free fatty acids in a pool of fifteen EVOO samples was achieved by means of reversed phase C18 analysis coupled to negative polarity high-resolution mass spectrometry. A total of 24 polar lipids, comprising 19 phospholipids and 5 sulfolipids, and 27 free fatty acids were tentatively identified, including several odd-chain and very long-chain fatty acids at trace levels. Moreover, a one-month study of lipid degradation on simulated storage conditions was carried out thanks to the set-up of a dedicated approach for degradation product analysis which was implemented of Compound Discoverer software. By virtue of the customized data processing workflow, more than forty compounds were tentatively identified, including compounds deriving from hydrolysis and oxidation reactions. Finally, by analysis of peak area trends, phosphoester hydrolyses of polar heads of phospholipids emerged as the fastest reactions, followed by glycerol ester hydrolyses and oxidative processes.

Volumetric Absorptive Microsampling of Blood for Untargeted Lipidomics

In the present, proof-of-concept paper, we explore the potential of one common solid support for blood microsampling (dried blood spot, DBS) and a device (volumetric absorptive microsampling, VAMS) developed for the untargeted lipidomic profiling of human whole blood, performed by high-resolution LC-MS/MS. Dried blood microsamples obtained by means of DBS and VAMS were extracted with different solvent compositions and compared with fluid blood to evaluate their efficiency in profiling the lipid chemical space in the most broad way. Although more effort is needed to better characterize this approach, our results indicate that VAMS is a viable option for untargeted studies and its use will bring all the corresponding known advantages in the field of lipidomics, such as haematocrit independence.

Interactive Visual Analysis of Mass Spectrometry Imaging Data Using Linear and Non-Linear Embeddings

Mass spectrometry imaging (MSI) is an imaging technique used in analytical chemistry to study the molecular distribution of various compounds at a micro-scale level. For each pixel, MSI stores a mass spectrum obtained by measuring signal intensities of thousands of mass-to-charge ratios (m/z-ratios), each linked to an individual molecular ion species. Traditional analysis tools focus on few individual m/z-ratios, which neglects most of the data. Recently, clustering methods of the spectral information have emerged, but faithful detection of all relevant image regions is not always possible. We propose an interactive visual analysis approach that considers all available information in coordinated views of image and spectral space visualizations, where the spectral space is treated as a multi-dimensional space. We use non-linear embeddings of the spectral information to interactively define clusters and respective image regions. Of particular interest is, then, which of the molecular ion species cause the formation of the clusters. We propose to use linear embeddings of the clustered data, as they allow for relating the projected views to the given dimensions. We document the effectiveness of our approach in analyzing matrix-assisted laser desorption/ionization (MALDI-2) imaging data with ground truth obtained from histological images.

CycloBranch 2: Molecular Formula Annotations Applied to imzML Data Sets in Bimodal Fusion and LC-MS Data Files

Natural product chemistry, microbiology, and food, human, and plant metabolomics represent a few sources of complex metabolomics data generated by mass spectrometry. Among the medley of software tools used to handle these data sets, no universal tool can qualitatively, quantitatively, or statistically address major biological questions or tasks. CycloBranch 2, an open and platform-free software, at least now provides the de novo generation of molecular formulas of unknown compounds in both liquid chromatography/mass spectrometry and mass spectrometry imaging datafiles. For imaging files, this database-free approach was documented in the bimodal image fusion and characterization of three small molecules, including metallophores. The fine isotope ratio data filtering step distinguished ³⁴S/¹³C₂ and ⁴¹K/¹³C₂ features. The standalone software package is implemented in C++ and can be downloaded from https://ms.biomed.cas.cz/cyclobranch/ and used under GNU General Public License.

Sphingomyelins Prevent Propagation of Lipid Peroxidation-LC-MS/MS Evaluation of Inhibition Mechanisms

Free radical driven lipid peroxidation is a chain reaction which can lead to oxidative degradation of biological membranes. Propagation vs. termination rates of peroxidation in biological membranes are determined by a variety of factors including fatty acyl chain composition, presence of antioxidants, as well as biophysical properties of mono- or bilayers. Sphingomyelins (SMs), a class of sphingophospholipids, were previously described to inhibit lipid oxidation most probably via the formation of H-bond network within membranes. To address the “antioxidant” potential of SMs, we performed LC-MS/MS analysis of model SM/glycerophosphatidylcholine (PC) liposomes with different SM fraction after induction of radical driven lipid peroxidation. Increasing SM fraction led to a strong suppression of lipid peroxidation. Electrochemical oxidation of non-liposomal SMs eliminated the observed effect, indicating the importance of membrane structure for inhibition of peroxidation propagation. High resolution MS analysis of lipid peroxidation products (LPPs) observed in in vitro oxidized SM/PC liposomes allowed to identify and relatively quantify SM- and PC-derived LPPs. Moreover, mapping quantified LPPs to the known pathways of lipid peroxidation allowed to demonstrate significant decrease in mono-hydroxy(epoxy) LPPs relative to mono-keto derivatives in SM-rich liposomes. The results presented here illustrate an important property of SMs in biological membranes, acting as “biophysical antioxidant”. Furthermore, a ratio between mono-keto/mono-hydroxy(epoxy) oxidized species can be used as a marker of lipid peroxidation propagation in the presence of different antioxidants.