A lipidome atlas in MS-DIAL 4

Nonpolar Lipids Contribute to Midday Fogging During Scleral Lens Wear

Purpose

To determine correlations between lipids in the fluid reservoir (FR) and the severity of midday fogging (MDF) in scleral lens (SL) wear.

Methods

SL neophytes were recruited to wear custom SL for 4 days, examined after 8 hours on days 1 and 4. Lens vault and MDF were quantified from anterior segment optical coherence tomography (AS-OCT), and the FR was collected and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Relative abundance of lipids was compared to MDF scores using nonparametric correlation testing (Spearman rank). Ocular surface and SL fitting characteristics (lens vault, fitting curves) were likewise compared to MDF.

Results

Thirteen participants (26 eyes, 69% female, 28 ± 9 years old) were included in this study. MDF severity after 8 hours of SL wear was 33 ± 29 units on day 1 and 28 ± 24 units on day 4 (r = .94; P < 0.01). Twelve samples were analyzed using LC-MS/MS, and a total of 170 distinct lipid species were detected. The lipid classes with greatest correlation to MDF were the wax esters (r = .73, P = 0.01), cholesteryl esters (r = .59; P = 0.049), and triacylglycerols (r = .64, P = 0.03). Polar lipids were observed abundantly in all samples. None of the measured ocular surface or fitting outcomes were correlated to MDF.

Conclusions

Nonpolar lipids were the greatest contributors to MDF among these normal participants. Polar lipids may be due to cellular debris, although they do not appear contributory to MDF.

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism

Introduction

Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects.

Objectives

To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations.

Methods

Lipids were extracted from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days and analyzed using MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility.

Results

Lipidomics analysis of 6 mouse tissues and plasma using MS/MS combining BRI-DIA and DDA allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that 1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; 2) the impact on lysophosphorylcholine and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations.

Conclusion

The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

LipidA-IDER to Explore the Global Lipid A Repertoire of Drug-Resistant Gram-Negative Bacteria

With the global emergence of drug-resistant bacteria causing difficult-to-treat infections, there is an urgent need for a tool to facilitate studies on key virulence and antimicrobial resistant factors. Mass spectrometry (MS) has contributed substantially to the elucidation of the structure-function relationships of lipid A, the endotoxic component of lipopolysaccharide which also serves as an important protective barrier against antimicrobials. Here, we present LipidA-IDER, an automated structure annotation tool for system-level scale identification of lipid A from high-resolution tandem mass spectrometry (MS²) data. LipidA-IDER was validated against previously reported structures of lipid A in the reference bacteria, Escherichia coli and Pseudomonas aeruginosa. Using MS² data of variable quality, we demonstrated LipidA-IDER annotated lipid A with a performance of 71.2% specificity and 70.9% sensitivity, offering greater accuracy than existing lipidomics software. The organism-independent workflow was further applied to a panel of six bacterial species: E. coli and Gram-negative members of ESKAPE pathogens. A comprehensive atlas comprising 188 distinct lipid A species, including remodeling intermediates, was generated and can be integrated with software including MS-DIAL and Metabokit for identification and semiquantitation. Systematic comparison of a pair of polymyxin-sensitive and polymyxin-resistant Acinetobacter baumannii isolated from a human patient unraveled multiple key lipid A structural features of polymyxin resistance within a single analysis. Probing the lipid A landscape of bacteria using LipidA-IDER thus holds immense potential for advancing our understanding of the vast diversity and structural complexity of a key lipid virulence and antimicrobial-resistant factor. LipidA-IDER is freely available at https://github.com/Systems-Biology-Of-Lipid-Metabolism-Lab/LipidA-IDER.

Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives

Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.

LC-MS-Based Redox Phosphoipidomics Analysis in Ferroptosis

Ferroptosis is a regulated form of cell death characterized by the accumulation of oxidized phospholipids, particularly oxidized phosphatidylethanolamines (PE), which serve as important biomarkers in the progression of various diseases. To facilitate the comprehensive investigation of ferroptosis in biological systems, we present a robust and versatile untargeted redox phospholipidomics method employing normal-phase liquid chromatography-mass spectrometry (LC-MS). This high-throughput technique enables the identification and quantification of dozens of oxidized phospholipid species in a single run, providing valuable insights into the molecular mechanisms underlying ferroptosis. It has been successfully applied to diverse biological samples, including human patients, animals, and cell cultures, and offers a powerful tool for investigating the roles of oxidized phospholipids in the development and progression of various diseases.

Serum metabolites associated with wholegrain consumption using nontargeted metabolic profiling: a discovery and reproducibility study

PURPOSE

To identify fasting serum metabolites associated with WG intake in a free-living population adjusted for potential confounders.

METHODS

We selected fasting serum samples at baseline from a subset (n = 364) of the prospective population-based Kuopio Ischaemic Heart Disease Risk Factor Study (KIHD) cohort. The samples were analyzed using nontargeted metabolomics with liquid chromatography coupled with mass spectrometry (LC-MS). Association with WG intake was investigated using both random forest followed by linear regression adjusted for age, BMI, smoking, physical activity, energy and alcohol consumption, and partial Spearman correlation adjusted for the same covariates. Features selected by any of these models were shortlisted for annotation. We then checked if we could replicate the findings in an independent subset from the same cohort (n = 200).

RESULTS

Direct associations were observed between WG intake and pipecolic acid betaine, tetradecanedioic acid, four glucuronidated alkylresorcinols (ARs), and an unknown metabolite both in discovery and replication cohorts. The associations remained significant (FDR<0.05) even after adjustment for the confounders in both cohorts. Sinapyl alcohol was positively correlated with WG intake in both cohorts after adjustment for the confounders but not in linear models in the replication cohort. Some microbial metabolites, such as indolepropionic acid, were positively correlated with WG intake in the discovery cohort, but the correlations were not replicated in the replication cohort.

CONCLUSIONS

The identified associations between WG intake and the seven metabolites after adjusting for confounders in both discovery and replication cohorts suggest the potential of these metabolites as robust biomarkers of WG consumption.

Chemical derivatization strategy for mass spectrometry-based lipidomics

Lipids, serving as the structural components of cellular membranes, energy storage, and signaling molecules, play the essential and multiple roles in biological functions of mammals. Mass spectrometry (MS) is widely accepted as the first choice for lipid analysis, offering good performance in sensitivity, accuracy, and structural characterization. However, the untargeted qualitative profiling and absolute quantitation of lipids are still challenged by great structural diversity and high structural similarity. In recent decade, chemical derivatization mainly targeting carboxyl group and carbon-carbon double bond of lipids have been developed for lipidomic analysis with diverse advantages: (i) offering more characteristic structural information; (ii) improving the analytical performance, including chromatographic separation and MS sensitivity; (iii) providing one-to-one chemical isotope labeling internal standards based on the isotope derivatization regent in quantitative analysis. Moreover, the chemical derivatization strategy has shown great potential in combination with ion mobility mass spectrometry and ambient mass spectrometry. Herein, we summarized the current states and advances in chemical derivatization-assisted MS techniques for lipidomic analysis, and their strengths and challenges are also given. In summary, the chemical derivatization-based lipidomic approach has become a promising and reliable technique for the analysis of lipidome in complex biological samples.

Human serum lipidomics analysis revealed glyphosate may lead to lipid metabolism disorders and health risks

Glyphosate-based herbicides (GBH) are one of the most widely used pesticides worldwide. Industrial workers in glyphosate-based herbicides manufacture are the populations who experience long-term exposure to high glyphosate levels. The impacts of glyphosate on human health are the important public health problem of great concern. Up to date, the potential adverse effects of glyphosate on humans or other mammals have been reported in multiple studies. However, limited research is available on lipid alternations related to human exposure to glyphosate. In fact, the perturbations in some lipid metabolisms have been found in industrial workers in previous work. This study aims to explore the serum lipidomic characterization and to understand the underlying mechanisms of health risks associated with glyphosate exposure. A nontargeted lipidomics study was conducted to investigate the 391 serum samples from the general population and chemical factory workers. It was demonstrated that glyphosate caused significant perturbations of 115 differentially expressed lipids. The main manifestations were the elevation of circulating diacylglycerols (DG), cholesteryl esters (CE), ceramides (Cer), sphingomyelins (SM), lysophosphatidylethanolamines (LPE) and phosphatidylcholines (PC), and the decrease of ysophosphatidylcholines (LPC), triacylglycerols (TG), fatty acids (FA) and phosphatidylethanolamines (PE). A total of 88 lipids were further screened as potential lipid biomarkers associated closely with glyphosate using partial correlation analysis, and five of which (including PC 16:0/18:2; O, PC 18:0/18:2; O, PC 18:0/20:4; O, PC O-40:9 and CE 18:3) showed excellent superior performance (AUC = 1) to evaluate and monitor health risks due to glyphosate exposure. The present work discovered glyphosate-induced potential health risks, including chronic hepatic and renal dysfunction, atherosclerosis, cardiovascular disease and neurodegenerative diseases from a lipidomic perspective, and could inform the identification of early indicators and interpretation of biological mechanisms to detect health risks of the glyphosate-exposed populations as early as possible.

Circulating extracellular particles from severe COVID-19 patients show altered profiling and innate lymphoid cell-modulating ability

Introduction

Extracellular vesicles (EVs) and particles (EPs) represent reliable biomarkers for disease detection. Their role in the inflammatory microenvironment of severe COVID-19 patients is not well determined. Here, we characterized the immunophenotype, the lipidomic cargo and the functional activity of circulating EPs from severe COVID-19 patients (Co-19-EPs) and healthy controls (HC-EPs) correlating the data with the clinical parameters including the partial pressure of oxygen to fraction of inspired oxygen ratio (PaO2/FiO2) and the sequential organ failure assessment (SOFA) score.

Methods

Peripheral blood (PB) was collected from COVID-19 patients (n=10) and HC (n=10). EPs were purified from platelet-poor plasma by size exclusion chromatography (SEC) and ultrafiltration. Plasma cytokines and EPs were characterized by multiplex bead-based assay. Quantitative lipidomic profiling of EPs was performed by liquid chromatography/mass spectrometry combined with quadrupole time-of-flight (LC/MS Q-TOF). Innate lymphoid cells (ILC) were characterized by flow cytometry after co-cultures with HC-EPs or Co-19-EPs.

Results

We observed that EPs from severe COVID-19 patients: 1) display an altered surface signature as assessed by multiplex protein analysis; 2) are characterized by distinct lipidomic profiling; 3) show correlations between lipidomic profiling and disease aggressiveness scores; 4) fail to dampen type 2 innate lymphoid cells (ILC2) cytokine secretion. As a consequence, ILC2 from severe COVID-19 patients show a more activated phenotype due to the presence of Co-19-EPs.

Discussion

In summary, these data highlight that abnormal circulating EPs promote ILC2-driven inflammatory signals in severe COVID-19 patients and support further exploration to unravel the role of EPs (and EVs) in COVID-19 pathogenesis.

Thermal treatment of magnesium particles in polylactic acid polymer films elicits the expression of osteogenic differentiation markers and lipidome profile remodeling in human adipose stem cells

The efficacy of polylactic acid (PLA)/Magnesium (Mg)-based materials for driving stem cells toward bone tissue engineering applications requires specific Mg surface properties to modulate the interface of stem cells with the film. Here, we have developed novel PLA/Mg-based composites and explored their osteogenic differentiation potential on human adipose stem cells (hASCs). Mg-particles/polymer interface was improved by two treatments: heating in oxidative atmosphere (TT) and surface modification with a compatibilizer (PEI). Different contents of Mg particles were dispersed in PLA and composite surface and bulk properties, protein adsorption, stem cell-PLA/Mg interactions, osteogenic markers expressions, and lipids composition profile were evaluated. Mg particles were uniformly distributed on the surface and in the bulk PLA polymer. Improved and modulated particle-polymer adhesion was observed in Mg particle-treated composites. After 21 days in canonical growth culture conditions, hASCs on PLA/MgTT displayed the highest expression of the general osteogenic markers, RUNX2, SSP1, and BGLAP genes, Alkaline Phosphatase, type I Collagen, Osteopontin, and Calcium deposits. Moreover, by LC/MS QTOF mass-spectrophotometry lipidomic analysis, we found in PLA/MgTT-cells, for the first time, a remodeling of the lipid classes composition associated with the osteogenic differentiation. We ascribed these results to MgTT characteristics, which improve Mg availability and composite osteoinductive performance.

Towards Non-Targeted Screening of Lipid Biomarkers for Improved Equine Anti-Doping

The current approach to equine anti-doping is focused on the targeted detection of prohibited substances. However, as new substances are rapidly being developed, the need for complimentary methods for monitoring is crucial to ensure the integrity of the racing industry is upheld. Lipidomics is a growing field involved in the characterisation of lipids, their function and metabolism in a biological system. Different lipids have various biological effects throughout the equine system including platelet aggregation and inflammation. A certain class of lipids that are being reviewed are the eicosanoids (inflammatory markers). The use of eicosanoids as a complementary method for monitoring has become increasingly popular with various studies completed to highlight their potential. Studies including various corticosteroids, non-steroidal anti-inflammatories and cannabidiol have been reviewed to highlight the progress lipidomics has had in contributing to the equine anti-doping industry. This review has explored the techniques used to prepare and analyse samples for lipidomic investigations in addition to the statistical analysis and potential for lipidomics to be used for a longitudinal assessment in the equine anti-doping industry.

MS-RIDD paves the way toward routine double bond localization in mass spectrometry-based lipidomics

Pinpointing double bond (C=C) positions in native lipid extracts is beyond the capabilities of standard mass spectrometry-based approaches. This article highlights a novel untargeted workflow supported by the open-source software MS-RIDD, that allows for semi-automated annotation of C=C locations with high confidence.

Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics

INTRODUCTION

Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching.

METHODS

This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation.

RESULTS AND DISCUSSION

The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.

Mitochondria directly sense osmotic stress to trigger rapid metabolic remodeling via regulation of pyruvate dehydrogenase phosphorylation

A high-salt diet significantly impacts various diseases, ilncluding cancer and immune diseases. Recent studies suggest that the high-salt/hyperosmotic environment in the body may alter the chronic properties of cancer and immune cells in the disease context. However, little is known about the acute metabolic changes in hyperosmotic stress. Here, we found that hyperosmotic stress for a few minutes induces Warburg-like metabolic remodeling in HeLa and Raw264.7 cells and suppresses fatty acid oxidation. Regarding Warburg-like remodeling, we determined that the pyruvate dehydrogenase phosphorylation status was altered bidirectionally (high in hyperosmolarity and low in hypoosmolarity) to osmotic stress in isolated mitochondria, suggesting that mitochondria themselves have an acute osmosensing mechanism. Additionally, we demonstrate that Warburg-like remodeling is required for HeLa cells to maintain ATP levels and survive under hyperosmotic conditions. Collectively, our findings suggest that cells exhibit acute metabolic remodeling under osmotic stress via the regulation of pyruvate dehydrogenase phosphorylation by direct osmosensing within mitochondria.

Computational mass spectrometry accelerates C = C position-resolved untargeted lipidomics using oxygen attachment dissociation

Mass spectrometry-based untargeted lipidomics has revealed the lipidome atlas of living organisms at the molecular species level. Despite the double bond (C = C) position being a crucial factor in biological system, the C = C defined structures have not yet been characterized comprehensively. Here, we present an approach for C = C position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to increase the annotation rate. We validated the accuracy of our platform as per the authentic standards of 85 lipids and the biogenic standards of 52 molecules containing polyunsaturated fatty acids (PUFAs) from the cultured cells fed with various fatty acid-enriched media. By analyzing human and mice-derived samples, we characterized 648 unique lipids with the C = C position-resolved level encompassing 24 lipid subclasses defined by LIPIDMAPS. Our platform also illuminated the unique profiles of tissue-specific lipids containing n-3 and/or n-6 very long-chain PUFAs (carbon [Formula: see text] 28 and double bonds [Formula: see text] 4) in the eye, testis, and brain of the mouse.

Lysophosphatidylcholines and phosphatidylcholines as biomarkers for stroke recovery

Stroke is a serious global public health issue, associated with severe disability and high mortality rates. Its early detection is challenging, and no effective biomarkers are available. To obtain a better understanding of stroke prevention, management, and recovery, we conducted lipidomic analyses to characterize plasma metabolic features. Lipid species were measured using an untargeted lipidomic analysis with liquid chromatography-tandem mass spectrometry. Sixty participants were recruited in this cohort study, including 20 healthy individuals and 40 patients with stroke. To investigate the association between lipids related to long-term functional recovery in stroke patients. The primary independent variable was activities of daily living (ADL) dependency upon admission to the stroke unit and at the 3-month follow-up appointment. ADL dependency was assessed using the Barthel Index. Eleven significantly altered lipid species between the stroke and healthy groups were detected and displayed in a hierarchically clustered heatmap. Acyl carnitine, triacylglycerol, and ceramides were detected as potential lipid markers. Regarding the association between lipid profiles and functional status of patients with stroke the results indicated, lysophosphatidylcholines (LPC) and phosphatidylcholines were closely associated with stroke recovery. LPC may contribute positively role in patient's rehabilitation process via an anti-inflammatory mechanism. Appropriate management or intervention for lipid levels is expected to lead to better clinical outcomes.

The glutamate receptor-like 3.3 and 3.6 mediate systemic resistance to insect herbivores in Arabidopsis

Herbivory activates responses in local and systemic leaves, and the glutamate receptor-like genes GLR3.3 and GLR3.6 are critical in leaf-to-leaf systemic signalling. However, whether and how these genes mediate plant systemic resistance to insects remain largely unexplored. We show that a piercing-sucking insect Myzus persicae (green peach aphid, GPA) or chewing insect Spodoptera litura (cotton leafworm, CLW) feeding-induced systemic defences were attenuated in the glr3.3 glr3.6 mutants. In response to herbivory from either insect, glr3.3 glr3.6 mutants exhibited reduced accumulation of the hormone jasmonic acid (JA) and defensive metabolites glucosinolates (GSs) in systemic (but not local) leaves. Transcriptome analysis indicated that GLR3.3 and GLR3.6 play an important role in regulating the transcriptional responses to GPA and simulated CLW feeding in both local and systemic leaves, including JA- and GS-related genes. Metabolome analysis also revealed that in response to GPA or simulated CLW feeding, GLR3.3 and GLR3.6 are involved in the regulation of various metabolites locally and systemically, including amino acids, carbohydrates, and organic acids. Taken together, this study provides new insights into the function of GLR3.3 and GLR3.6 in mediating transcripts and metabolites in local and systemic leaves under insect attack, and highlights their role in regulating insect resistance in systemic leaves.

Sterol O-Acyltransferase Inhibition Ameliorates High-Fat Diet-Induced Renal Fibrosis and Tertiary Lymphoid Tissue Maturation after Ischemic Reperfusion Injury

Metabolic syndrome is associated with the development of chronic kidney disease (CKD). We previously demonstrated that aged kidneys are prone to developing tertiary lymphoid tissues (TLTs) and sustain inflammation after injury, leading to CKD progression; however, the relationship between renal TLT and metabolic syndrome is unknown. In this study, we demonstrated that a high-fat diet (HFD) promoted renal TLT formation and inflammation via sterol O-acyltransferase (SOAT) 1-dependent mechanism. Mice fed a HFD prior to ischemic reperfusion injury (IRI) exhibited pronounced renal TLT formation and sustained inflammation compared to the controls. Untargeted lipidomics revealed the increased levels of cholesteryl esters (CEs) in aged kidneys with TLT formation after IRI, and, consistently, the Soat1 gene expression increased. Treatment with avasimibe, a SOAT inhibitor, attenuated TLT maturation and renal inflammation in HFD-fed mice subjected to IRI. Our findings suggest the importance of SOAT1-dependent CE accumulation in the pathophysiology of CKDs associated with TLT.

The RNA-binding protein RBM24 regulates lipid metabolism and SLC7A11 mRNA stability to modulate ferroptosis and inflammatory response

Lipids play a critical role in many cellular processes by serving as structural components of cell membranes or functioning as energy fuel and signaling molecules. The RNA-binding proteins RBM24 and RBM38 share an identical RNA-binding domain and thereby, regulate a group of same targets, such as p21. However, it is not certain whether RBM24 and RBM38 participates in lipid homeostasis. Here, lipidomic analysis showed that a deficiency in RBM24 or RBM38 leads to altered lipid metabolism, with more profound alteration by loss of RBM24 in MCF7 cells. We also showed that mice deficient in RBM24 were prone to chronic inflammation and liver steatosis, but not spontaneous tumors. These data let us speculate whether RBM24 regulates ferroptosis, a programmed cell death that links inflammation and liver steatosis via lipid peroxidation. Indeed, we found that over-expression of RBM24 protected, whereas knockout of RBM24 sensitized, cells to Erastin-induced ferroptosis by modulating the mRNA stability of SLC7A11, a ferroptosis inhibitor. Moreover, we showed that knockdown of SLC7A11 reversed the effect of RBM24 on ferroptosis. Together, our study revealed that RBM24 regulates lipid metabolism and SLC7A11 mRNA stability to modulate ferroptosis and inflammatory response.

Linking research of biomedical datasets

Biomedical data preprocessing and efficient computing can be as important as the statistical methods used to fit the data; data processing needs to consider application scenarios, data acquisition and individual rights and interests. We review common principles, knowledge and methods of integrated research according to the whole-pipeline processing mechanism diverse, coherent, sharing, auditable and ecological. First, neuromorphic and native algorithms integrate diverse datasets, providing linear scalability and high visualization. Second, the choice mechanism of different preprocessing, analysis and transaction methods from raw to neuromorphic was summarized on the node and coordinator platforms. Third, combination of node, network, cloud, edge, swarm and graph builds an ecosystem of cohort integrated research and clinical diagnosis and treatment. Looking forward, it is vital to simultaneously combine deep computing, mass data storage and massively parallel communication.

The critical role that spectral libraries play in capturing the metabolomics community knowledge

BACKGROUND

Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of thousands of compounds, forming an essential knowledge base for the interpretation of metabolomics experiments.

AIM OF REVIEW

We describe existing spectral library resources, highlight different strategies for compiling spectral libraries, and discuss quality considerations that should be taken into account when interpreting spectral library searching results. Finally, we describe how spectral libraries are empowering the next generation of machine learning tools in computational metabolomics, and discuss several opportunities for using increasingly accessible large spectral libraries.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the current state of spectral libraries for untargeted LC-MS/MS based metabolomics. We show how the number of entries in publicly accessible spectral libraries has increased more than 60-fold in the past eight years to aid molecular interpretation and we discuss how the role of spectral libraries in untargeted metabolomics will evolve in the near future.

Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking

Liquid chromatography - mass spectrometry (LC-MS) based untargeted metabolomics allows to measure both known and unknown metabolites in the metabolome. However, unknown metabolite annotation is a major challenge in untargeted metabolomics. Here, we develop an approach, namely, knowledge-guided multi-layer network (KGMN), to enable global metabolite annotation from knowns to unknowns in untargeted metabolomics. The KGMN approach integrates three-layer networks, including knowledge-based metabolic reaction network, knowledge-guided MS/MS similarity network, and global peak correlation network. To demonstrate the principle, we apply KGMN in an in vitro enzymatic reaction system and different biological samples, with ~100-300 putative unknowns annotated in each data set. Among them, >80% unknown metabolites are corroborated with in silico MS/MS tools. Finally, we validate 5 metabolites that are absent in common MS/MS libraries through repository mining and synthesis of chemical standards. Together, the KGMN approach enables efficient unknown annotations, and substantially advances the discovery of recurrent unknown metabolites for common biological samples from model organisms, towards deciphering dark matter in untargeted metabolomics.

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.

Potential cardiotoxicity induced by Euodiae Fructus: In vivo and in vitro experiments and untargeted metabolomics research

Background: Euodiae Fructus, a well-known herbal medicine, is widely used in Asia and has also gained in popularity in Western countries over the last decades. It has known side effects, which have been observed in clinical settings, but few studies have reported on its cardiotoxicity. Methods: In the present study, experiments using techniques of untargeted metabolomics clarify the hazardous effects of Euodiae Fructus on cardiac function and metabolism in rats in situations of overdosage and unsuitable syndrome differentiation. In vitro assays are conducted to observe the toxic effects of evodiamine and rutaecarpine, two main chemical constituents of Euodiae Fructus, in H9c2 and neonatal rat cardiomyocytes (NRCMs), with their signaling mechanisms analyzed accordingly. Results: The cardiac cytotoxicity of evodiamine and rutaecarpine in in vivo experiments is associated with remarkable alterations in lactate dehydrogenase, creatine kinase, and mitochondrial membrane potential; also with increased intensity of calcium fluorescence, decreased protein expression of the cGMP-PKG pathway in H9c2 cells, and frequency of spontaneous beat in NRCMs. Additionally, the results in rats with Yin deficiency receiving a high-dosage of Euodiae Fructus suggest obvious cardiac physiological dysfunction, abnormal electrocardiogram, pathological injuries, and decreased expression of PKG protein. At the level of endogenous metabolites, the cardiac side effects of overdose and irrational usage of Euodiae Fructus relate to 34 differential metabolites and 10 metabolic pathways involving among others, the purine metabolism, the glycerophospholipid metabolism, the glycerolipid metabolism, and the sphingolipid metabolism. Conclusion: These findings shed new light on the cardiotoxicity induced by Euodiae Fructus, which might be associated with overdose and unsuitable syndrome differentiation, that comes from modulating the cGMP-PKG pathway and disturbing the metabolic pathways of purine, lipid, and amino acid. Continuing research is needed to ensure pharmacovigilance for the safe administration of Chinese herbs in the future.

Functional significance of ion channels during macropinosome resolution in immune cells

Macropinocytosis is a unique type of endocytosis accompanied by membrane ruffle formation. Closure of membrane ruffles leads to the uptake of large volumes of fluid phase and, subsequently, the formation of large vacuoles termed macropinosomes. Immune cells, such as dendritic cells, T cells, and macrophages, endocytose the surrounding amino acids and pathogens via macropinocytosis either constitutively or in a stimulus-dependent fashion. This process is critical for cell migration, mammalian target of rapamycin complex 1 (mTORC1) activation, and antigen presentation. Large vacuoles are fragmented into tubules and smaller vesicles during the progression and maturation of macropinosomes in immune cells. This process is called “macropinosome resolution” and requires osmotically driven shrinkage of macropinosomes, which is controlled by ion channels present in them. The crenation of membranes on shrunken macropinosomes is recognized by curvature-sensing proteins and results in intracellular membrane trafficking. In this mini review, we highlight the recent progress in research on macropinosome resolution in macrophages, with a focus on ion channels (TPC1/2 for Na+ and TMEM206 for Cl−) that is required for macropinosome resolution. We also discuss the potential contribution of membrane lipids to this process.

Integrated Lipidomic and Metabolomics Analysis Revealing the Effects of Frozen Storage Duration on Pork Lipids

Frozen storage is an important strategy to maintain meat quality for long-term storage and transportation. Lipid oxidation is one of the predominant causes of the deterioration of meat quality during frozen storage. Untargeted lipidomic and targeted metabolomics were employed to comprehensively evaluate the effect of frozen duration on pork lipid profiles and lipid oxidative products including free fatty acids and fatty aldehydes. A total of 688 lipids, 40 fatty acids and 14 aldehydes were successfully screened in a pork sample. We found that ether-linked glycerophospholipids, the predominant type of lipids, gradually decreased during frozen storage. Of these ether-linked glycerophospholipids, ether-linked phosphatidylethanolamine and phosphatidylcholine containing more than one unsaturated bond were greatly influenced by frozen storage, resulting in an increase in free polyunsaturated fatty acids and fatty aldehydes. Among these lipid oxidative products, decanal, cis-11,14-eicosenoic acid and cis-5,8,11,14,17-dicosapentaenoic acid can be considered as potential indicators to calculate the freezing time of unknown frozen pork samples. Moreover, over the three-month frozen storage, the first month was a rapid oxidation stage while the other two months were a slow oxidation stage.

TLCD1 and TLCD2 regulate cellular phosphatidylethanolamine composition and promote the progression of non-alcoholic steatohepatitis

The fatty acid composition of phosphatidylethanolamine (PE) determines cellular metabolism, oxidative stress, and inflammation. However, our understanding of how cells regulate PE composition is limited. Here, we identify a genetic locus on mouse chromosome 11, containing two poorly characterized genes Tlcd1 and Tlcd2, that strongly influences PE composition. We generated Tlcd1/2 double-knockout (DKO) mice and found that they have reduced levels of hepatic monounsaturated fatty acid (MUFA)-containing PE species. Mechanistically, TLCD1/2 proteins act cell intrinsically to promote the incorporation of MUFAs into PEs. Furthermore, TLCD1/2 interact with the mitochondria in an evolutionarily conserved manner and regulate mitochondrial PE composition. Lastly, we demonstrate the biological relevance of our findings in dietary models of metabolic disease, where Tlcd1/2 DKO mice display attenuated development of non-alcoholic steatohepatitis compared to controls. Overall, we identify TLCD1/2 proteins as key regulators of cellular PE composition, with our findings having broad implications in understanding and treating disease.

The regulation of cellular phosphatidylethanolamine (PE) acyl chain composition is poorly understood. Here, the authors show that TLCD1 and TLCD2 proteins mediate the formation of monounsaturated fatty acid-containing PE species and promote the progression of non-alcoholic steatohepatitis.

Comparability of Steroid Collision Cross Sections Using Three Different IM-HRMS Technologies: An Interplatform Study

Steroids play key roles in various biological processes and are characterized by many isomeric variants, which makes their unambiguous identification challenging. Ion mobility-mass spectrometry (IM-MS) has been proposed as a suitable platform for this application, particularly using collision cross section (CCS) databases obtained from different commercial IM-MS instruments. CCS is seen as an ideal additional identification parameter for steroids as long-term repeatability and interlaboratory reproducibility of this measurand are excellent and matrix effects are negligible. While excellent results were demonstrated for individual IM-MS technologies, a systematic comparison of CCS derived from all major commercial IM-MS technologies has not been performed. To address this gap, a comprehensive interlaboratory comparison of 142 CCS values derived from drift tube (DTIM-MS), traveling wave (TWIM-MS), and trapped ion mobility (TIM-MS) platforms using a set of 87 steroids was undertaken. Besides delivering three instrument-specific CCS databases, systematic comparisons revealed excellent interlaboratory performance for 95% of the ions with CCS biases within ±1% for TIM-MS and within ±2% for TWIM-MS with respect to DTIM-MS values. However, a small fraction of ions (<1.5%) showed larger biases of up to 7% indicating that differences in the ion conformation sampled on different instrument types need to be further investigated. Systematic differences between CCS derived from different IM-MS analyzers and implications on the applicability for nontargeted analysis are critically discussed. To the best of our knowledge, this is the most comprehensive interlaboratory study comparing CCS from three different IM-MS technologies for analysis of steroids and small molecules in general.

Strain-specific impacts of probiotics are a significant driver of gut microbiome development in very preterm infants

The development of the gut microbiome from birth plays important roles in short- and long-term health, but factors influencing preterm gut microbiome development are poorly understood. In the present study, we use metagenomic sequencing to analyse 1,431 longitudinal stool samples from 123 very preterm infants (<32 weeks' gestation) who did not develop intestinal disease or sepsis over a study period of 10 years. During the study period, one cohort had no probiotic exposure whereas two cohorts were given different probiotic products: Infloran (Bifidobacterium bifidum and Lactobacillus acidophilus) or Labinic (B. bifidum, B. longum subsp. infantis and L. acidophilus). Mothers' own milk, breast milk fortifier, antibiotics and probiotics were significantly associated with the gut microbiome, with probiotics being the most significant factor. Probiotics drove microbiome transition into different preterm gut community types (PGCTs), each enriched in a different Bifidobacterium sp. and significantly associated with increased postnatal age. Functional analyses identified stool metabolites associated with PGCTs and, in preterm-derived organoids, sterile faecal supernatants impacted intestinal, organoid monolayer, gene expression in a PGCT-specific manner. The present study identifies specific influencers of gut microbiome development in very preterm infants, some of which overlap with those impacting term infants. The results highlight the importance of strain-specific differences in probiotic products and their impact on host interactions in the preterm gut.

Fluoroacetate distribution, response to fluoridation, and synthesis in juvenile Gastrolobium bilobum plants

Like angiosperms from several other families, the leguminous shrub Gastrolobium bilobum R.Br. produces and accumulates fluoroacetate, indicating that it performs the difficult chemistry needed to make a C-F bond. Bioinformatic analyses indicate that plants lack homologs of the only enzymes known to make a C-F bond, i.e., the Actinomycete flurorinases that form 5'-fluoro-5'-deoxyadenosine from S-adenosylmethionine and fluoride ion. To probe the origin of fluoroacetate in G. bilobum we first showed that fluoroacetate accumulates to millimolar levels in young leaves but not older leaves, stems or roots, that leaf fluoroacetate levels vary >20-fold between individual plants and are not markedly raised by sodium fluoride treatment. Young leaves were fed adenosine-¹³C-ribose, ¹³C-serine, or ¹³C-acetate to test plausible biosynthetic routes to fluoroacetate from S-adenosylmethionine, a C₃-pyridoxal phosphate complex, or acetyl-CoA, respectively. Incorporation of ¹³C into expected metabolites confirmed that all three precursors were taken up and metabolized. Consistent with the bioinformatic evidence against an Actinomycete-type pathway, no adenosine-¹³C-ribose was converted to ¹³C-fluoroacetate; nor was the characteristic 4-fluorothreonine product of the Actinomycete pathway detected. Similarly, no ¹³C from acetate or serine was incorporated into fluoroacetate. While not fully excluding the hypothetical pathways that were tested, these negative labeling data imply that G. bilobum creates the C-F bond by an unprecedented biochemical reaction. Enzyme(s) that mediate such a reaction could be of great value in pharmaceutical and agrochemical manufacturing.

Longitudinal Metabolomics and Lipidomics Analyses Reveal Alterations Associated with Envenoming by Bothrops asper and Daboia russelii in an Experimental Murine Model

Longitudinal metabolomics and lipidomics analyses were carried out on the blood plasma of mice injected intramuscularly with venoms of the viperid species Bothrops asper or Daboia russelii. Blood samples were collected 1, 3, 6, and 24 h after venom injection, and a control group of non-envenomed mice was included. Significant perturbations in metabolomics and lipidomics were observed at 1, 3, and 6 h, while values returned close to those of control mice by 24 h, hence reflecting a transient pattern of metabolic disturbance. Both venoms induced significant changes in amino acids, as well as in several purines and pyrimidines, and in some metabolites of the tricarboxylic acid cycle. KEGG analysis of metabolic pathways that showed those with the greatest change included aminoacyl tRNA synthesis and amino acid biosynthesis and metabolism pathways. With regard to lipid metabolism, there was an increase in triglycerides and some acyl carnitines and a concomitant drop in the levels of some phospholipids. In addition, envenomed mice had higher levels of cortisol, heme, and some oxidative stress markers. The overall pattern of metabolic changes in envenomed mice bears similarities with the patterns described in several traumatic injuries, thus underscoring a metabolic response/adaptation to the injurious action of the venoms.

Probabilistic quotient’s work and pharmacokinetics’ contribution: countering size effect in metabolic time series measurements

Metabolomic time course analyses of biofluids are highly relevant for clinical diagnostics. However, many sampling methods suffer from unknown sample sizes, commonly known as size effects. This prevents absolute quantification of biomarkers. Recently, several mathematical post acquisition normalization methods have been developed to overcome these problems either by exploiting already known pharmacokinetic information or by statistical means. Here we present an improved normalization method, MIX, that combines the advantages of both approaches. It couples two normalization terms, one based on a pharmacokinetic model (PKM) and the other representing a popular statistical approach, probabilistic quotient normalization (PQN), in a single model. To test the performance of MIX, we generated synthetic data closely resembling real finger sweat metabolome measurements. We show that MIX normalization successfully tackles key weaknesses of the individual strategies: it (i) reduces the risk of overfitting with PKM, and (ii), contrary to PQN, it allows to compute sample volumes. Finally, we validate MIX by using real finger sweat as well as blood plasma metabolome data and demonstrate that MIX allows to better and more robustly correct for size effects. In conclusion, the MIX method improves the reliability and robustness of quantitative biomarker detection in finger sweat and other biofluids, paving the way for biomarker discovery and hypothesis generation from metabolomic time course data.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Generating Heterokaryotic Cells via Bacterial Cell-Cell Fusion

Fusion of cells is an important and common biological process that leads to the mixing of cellular contents and the formation of multinuclear cells. Cell fusion occurs when distinct membranes are brought into proximity of one another and merge to become one. Fusion holds promise for biotechnological innovations, for instance, for the discovery of urgently needed new antibiotics. Here, we used antibiotic-producing bacteria that can proliferate without their cell wall as a model to investigate cell-cell fusion. We found that fusion between genetically distinct cells yields heterokaryons that are viable, contain multiple selection markers, and show increased antimicrobial activity. The rate of fusion induced using physical and chemical methods was dependent on membrane fluidity, which is related to lipid composition as a function of cellular age. Finally, by using an innovative system of synthetic membrane-associated lipopeptides, we achieved targeted fusion between distinctly marked cells to further enhance fusion efficiency. These results provide a molecular handle to understand and control cell-cell fusion, which can be used in the future for the discovery of new drugs. IMPORTANCE Cell-cell fusion is instrumental in introducing different sets of genes in the same environment, which subsequently leads to diversity. There is need for new protocols to fuse cells of different types together for biotechnological applications like drug discovery. We present here wall-deficient cells as a platform for the same. We identify the fluidity of the membrane as an important characteristic for the process of fusion. We demonstrate a cell-specific approach for fusion using synthetically designed peptides yielding cells with modified antibiotic production profiles. Overall, wall-deficient cells can be a chassis for innovative metabolite production by providing an alternative method for cell-cell fusion.

Lipidomics Profiles and Lipid Metabolite Biomarkers in Serum of Coal Workers' Pneumoconiosis

As a serious occupational pulmonary fibrosis disease, pneumoconiosis still lacks effective biomarkers. Previous studies suggest that pneumoconiosis may affect the body's lipid metabolism. The purpose of this study was to explore lipidomics profiles and lipid metabolite biomarkers in the serum of coal workers' pneumoconiosis (CWP) by a population case-control study. A total of 150 CWP cases and 120 healthy controls from Beijing, China were included. Blood lipids were detected in serum biochemistry. Lipidomics was performed in serum samples for high-throughput detection of lipophilic metabolites. Serum high density lipoprotein cholesterol (HDL-C) decreased significantly in CWP cases. Lipidomics data found 131 differential lipid metabolites between the CWP case and control groups. Further, the top eight most important differential lipid metabolites were screened. They all belonged to differential metabolites of CWP at different stages. However, adjusting for potential confounding factors, only three of them were significantly related to CWP, including acylhexosylceramide (AHEXCER 43:5), diacylglycerol (DG 34:8) and dimethyl-phosphatidylethanolamine (DMPE 36:0|DMPE 18:0_18:0), of which good sensitivity and specificity were proven. The present study demonstrated that lipidomics profiles could change significantly in the serum of CWP patients and that the lipid metabolites represented by AHEXCER, DG and DMPE may be good biomarkers of CWP.

Critical evaluation of the role of external calibration strategies for IM-MS

The major benefits of integrating ion mobility (IM) into LC-MS methods for small molecules are the additional separation dimension and especially the use of IM-derived collision cross sections (CCS) as an additional ion-specific identification parameter. Several large CCS databases are now available, but outliers in experimental interplatform IM-MS comparisons are identified as a critical issue for routine use of CCS databases for identity confirmation. We postulate that different routine external calibration strategies applied for traveling wave (TWIM-MS) in comparison to drift tube (DTIM-MS) and trapped ion mobility (TIM-MS) instruments is a critical factor affecting interplatform comparability. In this study, different external calibration approaches for IM-MS were experimentally evaluated for 87 steroids, for which ^TWCCS_N2, ^DTCCS_N2 and ^TIMCCS_N2 are available. New reference CCS_N2 values for commercially available and class-specific calibrant sets were established using DTIM-MS and the benefit of using consolidated reference values on comparability of CCS_N2 values assessed. Furthermore, use of a new internal correction strategy based on stable isotope labelled (SIL) internal standards was shown to have potential for reducing systematic error in routine methods. After reducing bias for CCS_N2 between different platforms using new reference values (95% of ^TWCCS_N2 values fell within 1.29% of ^DTCCS_N2 and 1.12% of ^TIMCCS_N2 values, respectively), remaining outliers could be confidently classified and further studied using DFT calculations and CCS_N2 predictions. Despite large uncertainties for in silico CCS_N2 predictions, discrepancies in observed CCS_N2 values across different IM-MS platforms as well as non-uniform arrival time distributions could be partly rationalized.

Pleiotropic Roles of Cholesteryl Sulfate during Entamoeba Encystation: Involvement in Cell Rounding and Development of Membrane Impermeability

Entamoeba histolytica, a protozoan parasite, causes amoebiasis, which is a global public health problem. The major route of infection is oral ingestion of cysts, the only form that is able to transmit to a new host. Cysts are produced by cell differentiation from proliferative trophozoites in a process termed "encystation." During encystation, cell morphology is markedly changed; motile amoeboid cells become rounded, nonmotile cells. Concomitantly, cell components change and significant fluctuations of metabolites occur. Cholesteryl sulfate (CS) is a crucial metabolite for encystation. However, its precise role remains uncertain. To address this issue, we used in vitro culture of Entamoeba invadens as the model system for the E. histolytica encystation study and identified serum-free culture conditions with CS supplementation at concentrations similar to intracellular CS concentrations during natural encystation. Using this culture system, we show that CS exerts pleiotropic effects during Entamoeba encystation, affecting cell rounding and development of membrane impermeability. CS dose dependently induced and maintained encysting cells as spherical maturing cysts with almost no phagocytosis activity. Consequently, the percentage of mature cysts was increased. CS treatment also caused time- and dose-dependent development of membrane impermeability in encysting cells via induction of de novo synthesis of dihydroceramides containing very long N-acyl chains (≥26 carbons). These results indicate that CS-mediated morphological and physiological changes are necessary for the formation of mature cysts and the maintenance of the Entamoeba life cycle. Our findings also reveal important morphological aspects of the process of dormancy and the control of membrane structure. IMPORTANCE Entamoeba histolytica causes a parasitic infectious disease, amoebiasis. Amoebiasis is a global public health problem with a high occurrence of infection and inadequate clinical options. The parasite alternates its form between a proliferative trophozoite and a dormant cyst that enables the parasite to adapt to new environments. The transition stage in which trophozoites differentiate into cysts is termed "encystation." Cholesteryl sulfate is essential for encystation; however, its precise role remains to be determined. Here, we show that cholesteryl sulfate is a multifunctional metabolite exerting pleiotropic roles during Entamoeba encystation, including the rounding of cells and the development of membrane impermeability. Such morphological and physiological changes are required for Entamoeba to produce cysts that are transmissible to a new host, which is essential for maintenance of the Entamoeba life cycle. Our findings are therefore relevant not only to Entamoeba biology but also to general cell and lipid biology.

Comprehensive lipid and lipid-related gene investigations of host immune responses to characterize metabolism-centric biomarkers for pulmonary tuberculosis

Despite remarkable success in the prevention and treatment of tuberculosis (TB), it remains one of the most devastating infectious diseases worldwide. Management of TB requires an efficient and timely diagnostic strategy. In this study, we comprehensively characterized the plasma lipidome of TB patients, then selected candidate lipid and lipid-related gene biomarkers using a data-driven, knowledge-based framework. Among 93 lipids that were identified as potential biomarker candidates, ether-linked phosphatidylcholine (PC O–) and phosphatidylcholine (PC) were generally upregulated, while free fatty acids and triglycerides with longer fatty acyl chains were downregulated in the TB group. Lipid-related gene enrichment analysis revealed significantly altered metabolic pathways (e.g., ether lipid, linolenic acid, and cholesterol) and immune response signaling pathways. Based on these potential biomarkers, TB patients could be differentiated from controls in the internal validation (random forest model, area under the curve [AUC] 0.936, 95% confidence interval [CI] 0.865–0.992). PC(O-40:4), PC(O-42:5), PC(36:0), and PC(34:4) were robust biomarkers able to distinguish TB patients from individuals with latent infection and healthy controls, as shown in the external validation. Small changes in expression were identified for 162 significant lipid-related genes in the comparison of TB patients vs. controls; in the random forest model, their utilities were demonstrated by AUCs that ranged from 0.829 to 0.956 in three cohorts. In conclusion, this study introduced a potential framework that can be used to identify and validate metabolism-centric biomarkers.

Using MetaboAnalyst 5.0 for LC-HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become a workhorse in global metabolomics studies with growing applications across biomedical and environmental sciences. However, outstanding bioinformatics challenges in terms of data processing, statistical analysis and functional interpretation remain critical barriers to the wider adoption of this technology. To help the user community overcome these barriers, we have made major updates to the well-established MetaboAnalyst platform ( www.metaboanalyst.ca ). This protocol extends the previous 2011 Nature Protocol by providing stepwise instructions on how to use MetaboAnalyst 5.0 to: optimize parameters for LC-HRMS spectra processing; obtain functional insights from peak list data; integrate metabolomics data with transcriptomics data or combine multiple metabolomics datasets; conduct exploratory statistical analysis with complex metadata. Parameter optimization may take ~2 h to complete depending on the server load, and the remaining three stages may be executed in ~60 min.

Lipidomic comparison of 2D and 3D colon cancer cell culture models

Altered lipid metabolism is one of the hallmarks of cancer. Cellular proliferation and de novo synthesis of lipids are related to cancer progression. In this study, we evaluated the lipidomic profile of two-dimensional (2D) monolayer and multicellular tumor spheroids from the HCT 116 colon carcinoma cell line. We utilized serial trypsinization on the spheroid samples to generate three cellular populations representing the proliferative, quiescent, and necrotic regions of the spheroid. This analysis enabled a comprehensive identification and quantification of lipids produced in each of the spheroid layer and 2D cultures. We show that lipid subclasses associated with lipid droplets form in oxygen-restricted and acidic regions of spheroids and are produced at higher levels than in 2D cultures. Additionally, sphingolipid production, which is implicated in cell death and survival pathways, is higher in spheroids relative to 2D cells. Finally, we show that increased numbers of lipids composed of polyunsaturated fatty acids (PUFAs) are produced in the quiescent and necrotic regions of the spheroid. The lipidomic signature for each region and cell culture type highlights the importance of understanding the spatial aspects of cancer biology. These results provide additional lipid biomarkers in colon cancer cells that can be further studied to target pivotal lipid production pathways.

MAVEN2: An Updated Open-Source Mass Spectrometry Exploration Platform

MAVEN, an open-source software program for analysis of LC-MS metabolomics data, was originally released in 2010. As mass spectrometry has advanced in the intervening years, MAVEN has been periodically updated to reflect this advancement. This manuscript describes a major update to the program, MAVEN2, which supports LC-MS/MS analysis of metabolomics and lipidomics samples. We have developed algorithms to support MS/MS spectral matching and efficient search of large-scale fragmentation libraries. We explore the ability of our approach to separate authentic from spurious metabolite identifications using a set of standards spiked into water and yeast backgrounds. To support our improved lipid identification workflow, we introduce a novel in-silico lipidomics library covering major lipid classes and compare searches using our novel library to searches with existing in-silico lipidomics libraries. MAVEN2 source code and cross-platform application installers are freely available for download from GitHub under a GNU permissive license [ver 3], as are the in silico lipidomics libraries and corresponding code repository.

Natural fish oil improves the differentiation and maturation of oligodendrocyte precursor cells to oligodendrocytes in vitro after interaction with the blood–brain barrier

The blood–brain barrier (BBB) tightly controls the microenvironment of the central nervous system (CNS) to allow neurons to function properly. Additionally, emerging studies point to the beneficial effect of natural oils affecting a wide variety of physiological and pathological processes in the human body. In this study, using an in vitro model of the BBB, we tested the influence of natural fish oil mixture (FOM) vs. borage oil (BO), both rich in long-chain polyunsaturated fatty acids (LC-PUFAs) and monounsaturated fatty acids (MUFAs) such as oleic acid (C18:1n9c) or nervonic acid (NA), on human oligodendrocyte precursor cells (hOPCs) during their maturation to oligodendrocytes (OLs) regarding their ability to synthesize myelin peptides and NA. We demonstrated that FOM, opposite to BO, supplemented endothelial cells (ECs) and astrocytes forming the BBB, affecting the function of hOPCs during their maturation. This resulted in improved synthesis of myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), proteolipid protein (PLP), and NA in mature OLs. This effect is probably the result of BBB cell and hOPC stimulation via free fatty acid receptors (FFARs), which increases insulin growth factor-1 (IGF-1), ciliary neurotrophic factor (CNTF), and brain-derived neurotrophic factor (BDNF) and inhibits fibroblast growth factor 2 (FGF-2) synthesis. The unique formula of fish oil, characterized by much more varied components compared to those of BOs, also improved the enhancement of the tight junction by increasing the expression of claudin-5 and VE-cadherin on ECs. The obtained data justify consideration of naturally derived fish oil intake in human diet as affecting during remyelination.

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis

INTRODUCTION

Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.

OBJECTIVES

To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.

METHODS

Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.

RESULTS

DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.

CONCLUSION

The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

Isotope Calculation Gadgets: A Series of Software for Isotope-Tracing Experiments in Garuda Platform

Isotope tracing is a powerful technique for elucidating intracellular metabolism. Experiments utilizing this technique involve various processes, such as the correction of natural isotopes. Although some previously developed software are available for these procedures, there are still time-consuming steps in isotope tracing including the creation of an isotope measurement method in mass spectrometry (MS) and the interpretation of obtained labeling data. Additionally, these multi-step tasks often require data format conversion, which is also time-consuming. In this study, the Isotope Calculation Gadgets, a series of software that supports an entire workflow of isotope-tracing experiments, was developed in the Garuda platform, an open community. Garuda is a graphical user interface-based platform that allows individual operations to be sequentially performed, without data format conversion, which significantly reduces the required time and effort. The developed software includes new features that construct channels for isotopomer measurements, as well as conventional functions such as natural isotope correction, the calculation of fractional labeling and split ratio, and data mapping, thus facilitating an overall workflow of isotope-tracing experiments through smooth functional integration.