A lipidome atlas in MS-DIAL 4

Lipidomics reveals the serum profiles of pediatric allergic rhinitis and its severity

Allergic rhinitis (AR) is a prevalent upper airway chronic inflammatory disease in children worldwide. The role of bioactive lipids in the regulation of AR has been recognized, but the underlying serum lipidomic basis of its pathology remains unclear. We utilized ultra-performance liquid chromatography (UPLC)-Q-Exactive Orbitrap/mass spectrometry (MS) to investigate the serum lipidomic profiles of children with AR. The lipidomic analysis identified 42 lipids that were differentially expressed (p < 0.05, fold change > 2) between the AR (n = 75) and normal control groups (n = 44). Specifically, the serum levels of diacylglycerol (DG), triacylglycerol (TG), fatty acid (FA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine, phosphatidyl-ethanolamine, and cardiolipins were significantly higher in the AR group. The diagnostic potential of the identified lipids was further evaluated using receiver operating characteristic curve analysis. The analysis revealed that five lipids, including FA 30:7, LPC O-18:1, LPC 18:0, LPC 16:0, and DG 34:0, had area under the curve values greater than 0.9 (p < 0.05). Furthermore, serum levels of IgE and IL-33, markers of AR severity, were found to have a significant positive correlation (p < 0.05) with DGs, LPCs, TGs, and FAs in AR patients. This study revealed the lipid disorders associated with AR and its severity, providing new insights into the pathological process of AR.

Adverse effects of the 5-alpha-reductase inhibitor finasteride on Daphnia magna: Endocrine system and lipid metabolism disruption

Finasteride, a steroid 5-alpha reductase inhibitor, is commonly used for the treatment of benign prostatic hyperplasia and hair loss. However, despite continued use, its environmental implications have not been thoroughly investigated. Thus, we investigated the acute and chronic adverse impacts of finasteride on Daphnia magna, a crucial planktonic crustacean in freshwater ecosystems selected as bioindicator organism for understanding the ecotoxicological effects. Chronic exposure (for 23 days) to finasteride negatively affected development and reproduction, leading to reduced fecundity, delayed first brood, reduced growth, and reduced neonate size. Additionally, acute exposure (< 24 h) caused decreased expression levels of genes crucial for reproduction and development, especially EcR-A/B (ecdysone receptors), Jhe (juvenile hormone esterase), and Vtg2 (vitellogenin), with oxidative stress-related genes. Untargeted lipidomics/metabolomic analyses revealed lipidomic alteration, including 19 upregulated and 4 downregulated enriched lipid ontology categories, and confirmed downregulation of metabolites. Pathway analysis implicated significant effects on metabolic pathways, including the pentose phosphate pathway, histidine metabolism, beta-alanine metabolism, as well as alanine, aspartate, and glutamate metabolism. This comprehensive study unravels the intricate molecular and metabolic responses of D. magna to finasteride exposure, underscoring the multifaceted impacts of this anti-androgenic compound on a keystone species of freshwater ecosystems. The findings emphasize the importance of understanding the environmental repercussions of widely used pharmaceuticals to protect biodiversity in aquatic ecosystems.

Improving the intestinal lipidome coverage in a gnotobiotic mouse model using UHPLC-MS-based approach through optimization of mobile phase modifiers and column selection

Lipidomics is focusing on the screening of lipid species in complex mixtures using mass spectrometry-based approaches. In this work, we aim to enhance the intestinal lipidome coverage within the Oligo-Mouse-Microbiota (OMM12) colonized mouse model by testing eight mobile phase conditions on five reversed-phase columns. Our selected mobile phase modifiers included two ammonium salts, two concentrations, and the addition of respective acids at 0.1 %. We compared two columns with hybrid surface technology, two with ethylene bridged hybrid technology and one with core-shell particles. Best performance was attained for standards and intestinal lipidome, using either ammonium formate or acetate in ESI(+) or ammonium acetate in ESI(-) for all column technologies. Notably, a concentration of 5 mM ammonium salt showed optimal results for both modes, while the addition of acids had a negligible effect on lipid ionization efficiency. The HST BEH C18 column improved peak width and tailing factor parameters compared to other technologies. We achieved the highest lipid count in colon and ileum content, including ceramides, phosphatidylethanolamines and phosphatidylcholines, when using 5 mM ammonium acetate in ESI(-). Conversely, in ESI(+) 5 mM ammonium formate demonstrated superior coverage for diacylglycerols and triacylglycerols.

Hazard assessment of hexagonal boron nitride and hexagonal boron nitride reinforced thermoplastic polyurethane composites using human skin and lung cells

Hexagonal boron nitride (hBN) is an emerging two-dimensional material attracting considerable attention in the industrial sector given its innovative physicochemical properties. Potential risks are associated mainly with occupational exposure where inhalation and skin contact are the most relevant exposure routes for workers. Here we aimed at characterizing the effects induced by composites of thermoplastic polyurethane (TPU) and hBN, using immortalized HaCaT skin keratinocytes and BEAS-2B bronchial epithelial cells. The composite was abraded using a Taber® rotary abraser and abraded TPU and TPU-hBN were also subjected to photo-Fenton-mediated degradation mimicking potential weathering across the product life cycle. Cells were exposed to the materials for 24 h (acute exposure) or twice per week for 4 weeks (chronic exposure) and evaluated with respect to material internalization, cytotoxicity, and proinflammatory cytokine secretion. Additionally, comprehensive mass spectrometry-based proteomics and metabolomics (secretomics) analyses were performed. Overall, despite evidence of cellular uptake of the material, no significant cellular and/or protein expression profiles alterations were observed after acute or chronic exposure of HaCaT or BEAS-2B cells, identifying only few pro-inflammatory proteins. Similar results were obtained for the degraded materials. These results support the determination of hazard profiles associated with cutaneous and pulmonary hBN-reinforced polymer composites exposure.

MS based foodomics: An edge tool integrated metabolomics and proteomics for food science

Foodomics has become a popular methodology in food science studies. Mass spectrometry (MS) based metabolomics and proteomics analysis played indispensable roles in foodomics research. So far, several methodologies have been developed to detect the metabolites and proteins in diets and consumers, including sample preparation, MS data acquisition, annotation and interpretation. Moreover, multiomics analysis integrated metabolomics and proteomics have received considerable attentions in the field of food safety and nutrition, because of more comprehensive and deeply. In this context, we intended to review the emerging strategies and their applications in MS-based foodomics, as well as future challenges and trends. The principle and application of multiomics were also discussed, such as the optimization of data acquisition, development of analysis algorithm and exploration of systems biology.

Glucose-6-phosphate dehydrogenase maintains redox homeostasis and biosynthesis in LKB1-deficient KRAS-driven lung cancer

Cancer cells depend on nicotinamide adenine dinucleotide phosphate (NADPH) to combat oxidative stress and support reductive biosynthesis. One major NADPH production route is the oxidative pentose phosphate pathway (committed step: glucose-6-phosphate dehydrogenase, G6PD). Alternatives exist and can compensate in some tumors. Here, using genetically-engineered lung cancer mouse models, we show that G6PD ablation significantly suppresses KrasG12D/+;Lkb1-/- (KL) but not KrasG12D/+;P53-/- (KP) lung tumorigenesis. In vivo isotope tracing and metabolomics reveal that G6PD ablation significantly impairs NADPH generation, redox balance, and de novo lipogenesis in KL but not KP lung tumors. Mechanistically, in KL tumors, G6PD ablation activates p53, suppressing tumor growth. As tumors progress, G6PD-deficient KL tumors increase an alternative NADPH source from serine-driven one carbon metabolism, rendering associated tumor-derived cell lines sensitive to serine/glycine depletion. Thus, oncogenic driver mutations determine lung cancer dependence on G6PD, whose targeting is a potential therapeutic strategy for tumors harboring KRAS and LKB1 co-mutations.

Long-term impacts of egg quiescence and Wolbachia infection on lipid profiles in Aedes aegypti: Ovarian roles in lipid synthesis during reproduction

Wolbachia, an endosymbiotic bacterium, relies on nutrients from its host to complete its life cycle. The presence of Wolbachia strain wAlbB in the mosquito Aedes aegypti during egg or larval stages affects the host's development, leading to the absence of developed and visible ovaries in adult mosquito females. In this study, we investigated the impacts of egg quiescence and Wolbachia infection on lipid profiles of adult Ae. aegypti females, and discerned the role of ovaries in lipid synthesis in the reproductive process. The lipidomes of Wolbachia infected and uninfected female individuals at various developmental stages were quantitatively analyzed by LC-MS/MS. Lipidomic change patterns were systematically further investigated in wAlbB-infected fertile females and infertile females following blood feeding. Prolonged egg quiescence induced a shortage of acyl-carnitine (CAR) and potentially impacted some molecules of diacyl-phospholipid (diacyl-PL) and sphingolipid (SL) in young adult mosquitoes. After the first gonotrophic cycle, infertile females accumulated more CAR and lyso-phospholipid (lyso-PL) than fertile females. Then in the second gonotrophic cycle, the patterns of different lipid groups remained similar between fertile and infertile females. Only a small proportion of molecules of triglyceride (TG), phospholipid (lyso-PL and diacyl-PL) and ceramide (Cer) increased exclusively in fertile females from 0 h to 16 h post blood meal, suggesting that the generation or prescence of these lipids rely on ovaries. In addition, we found cardiolipins (CL) might be impacted by Wolbachia infection at the egg stage, and infected mosquitoes also showed distinct patterns between fertile and infertile females at their second gonotrophic cycle. Our study provides new insights into the long-term influence of Wolbachia on lipid profiles throughout various life stages of mosquitoes. Additionally, it suggests a role played by ovaries in lipid synthesis during mosquito reproduction.

MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation

We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.

Hyphenation of Liquid Chromatography and Trapped Ion Mobility - Mass Spectrometry for Characterization of Isomeric Phosphatidylethanolamines with Focus on N-Acylated Species

In prior research, hydrophilic interaction liquid chromatography coupled to tandem mass spectrometry (HILIC-MS/MS) has demonstrated applicability for characterizing regioisomers in lipidomics studies, including phosphatidylglycerols (PG) and bis(monoacyl)glycerophosphates (BMP). However, there are other lipid regioisomers, such as phosphatidylethanolamines (PE) and lyso-N-acyl-PE (LNAPE), that have not been studied as extensively. Therefore, hyphenated mass spectrometric methods are needed to investigate PE and LNAPE regioisomers individually. The asymmetric structure of LNAPE favors isomeric species, which can result in coelution and chimeric MS/MS spectra. One way to address the challenge of chimeric MS/MS spectra is through mobility-resolved fragmentation using trapped ion mobility spectrometry (TIMS). Therefore, we developed a multidimensional HILIC-TIMS-MS/MS approach for the structural characterization of isomeric phosphatidylethanolamines in both negative and positive ionization modes. The study revealed the complementary fragmentation pattern and ion mobility behavior of LNAPE in both ionization modes, which was confirmed by a self-synthesized LNAPE standard. With this knowledge, a distinction of regioisomeric PE and LNAPE was achieved in human plasma samples. Furthermore, regioisomeric LNAPE species containing at least one unsaturated fatty acid were noted to exhibit a change in collision cross-section in positive ionization mode, leading to a lipid characterization with respect to fatty acyl positional level. Similar mobility behavior was also observed for the biological LNAPE precursor N-acyl-PE (NAPE). Application of this approach to plasma and cereal samples demonstrated its effectiveness in regioisomeric LNAPE and NAPE species' elucidation.

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Arabidopsis seeds altered in the circadian clock protein TOC1 are characterized by higher level of linolenic acid

The circadian clock plays a critical role in regulating plant physiology and metabolism. However, the way in which the clock impacts the regulation of lipid biosynthesis in seeds is partially understood. In the present study, we characterized the seed fatty acid (FA) and glycerolipid (GL) compositions of pseudo-response regulator mutants. Among these mutants, toc1 (timing of cab expression 1) exhibited the most significant differences compared to control plants. These included an increase in total FA content, characterized by elevated levels of linolenic acid (18:3) along with a reduction in linoleic acid (18:2). Furthermore, our findings revealed that toc1 developing seeds showed increased expression of genes related to FA metabolism. Our results show a connection between TOC1 and lipid metabolism in Arabidopsis seeds.

Non-targeted mass spectrometry and feature-based molecular networking for determination of branched fatty acid esters of hydroxy fatty acids in milk

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) represent trace lipids with significant natural biological functions. While exogenous FAHFAs have been extensively studied, research on FAHFAs in milk remains limited, constraining our grasp of their nutritional roles. This study introduces a non-targeted mass spectrometry approach combined with chemical networking of spectral fragmentation patterns to uncover FAHFAs. Through meticulous sample handling and comparisons of various data acquisition and processing modes, we validate the method's superiority, identifying twice as many FAHFAs compared to alternative techniques. This validated method was then applied to different milk samples, revealing 45 chemical signals associated with known and potential FAHFAs, alongside findings of 66 ceramide/hexosylceramide (Cer/HexCer), 48 phosphatidyl ethanolamine/lyso phosphatidyl ethanolamine (PE/LPE), 21 phosphatidylcholine/lysophosphatidylcholine (PC/LPC), 16 phosphatidylinositol (PI), 7 phosphatidylserine (PS), and 11 sphingomyelin (SM) compounds. This study expands our understanding of the FAHFA family in milk and provides a fast and convenient method for identifying FAHFAs.

Investigating the effects of dexamethasone on pulmonary surfactant lipids based on lipidomics studies

Dexamethasone, a glucocorticoid commonly used in pediatric patients, has potent anti-inflammatory and immunosuppressive properties. However, it is associated with side effects such as reduced lung function and decreased immunity. Pulmonary surfactant lipids are closely linked to lung disease and play a role in reducing surface tension, immune response and antiviral activity. The dysregulation of lipid metabolism is closely associated with lung disease. Hence, untargeted lipidomics may be instrumental in elucidating the effects of dexamethasone on pulmonary surfactant lipids. We obtained surfactant lipid samples from the bronchoalveolar lavage fluid of young mice injected subcutaneously with dexamethasone and conducted a comprehensive lipidomic analysis, comparing them with a control group. We observed a decrease in lipids, such as phosphatidylcholine, phosphatidylglycerol and phosphatidylethanolamine, and an increase in ceramide, fatty acid, diacylglycerol and monoglyceride, which may impact lung health. This study revealed the influence of dexamethasone on pulmonary surfactant lipids, offering new insights into adverse reactions in clinical settings.

Liver tissue lipids in metabolic dysfunction-associated steatotic liver disease with diabetes and obesity

BACKGROUND

Diabetes and obesity are associated with altered lipid metabolism and hepatic steatosis. Studies suggest that increases in lipid accumulation in these patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are not uniform for all lipid components. This study evaluates this variation.

METHODS

A comprehensive lipidomic analysis of different lipid groups, were performed on liver tissue and plasma samples obtained at the time of histology from a well-defined cohort of 72 MASLD participants. The lipid profiles of controls were compared to those of MASLD patients with obesity, diabetes, or a combination of both.

RESULTS

MASLD patients without obesity or diabetes exhibited distinct changes in the lipid profile of their liver tissue. The presence of diabetes or obesity further modified these lipid profiles (e.g., ceramide 47:7;4O), with positive or negative correlation (p < 0.05). A step-wise increase (long-chain fatty acids, triglycerides, and ceramides) or decrease (ultra-long fatty acids, diglycerides, and phospholipids) for lipid groups was observed compared to control among patients with MASLD without obesity or diabetes to MASLD patients with obesity as a single risk factor, and MASLD patients with obesity and diabetes. Changes in lipids observed in the plasma did not align with their corresponding liver tissue findings.

CONCLUSION

The changes observed in the composition of lipids are not similar in patients with obesity and diabetes among those with MASLD. This highlights the different metabolic processes at play. The presence of obesity or diabetes in patients with MASLD exacerbates these lipid derangements, underscoring the potential for targeted intervention in MASLD patients.

Exploring the broad-spectrum pharmacological activity of two less studied Australian native fruits: chemical characterisation using LCMS-driven metabolomics

Australian fruits such as native currant (Acrotriche depressa) and lemon aspen (Acronychia acidula) are under-examined in terms of their therapeutic potential. In this study, the in vitro antiproliferative activity of native currant and lemon aspen extracts (water and ethanol) against MCF7 breast adenocarcinoma cells was determined using the Alamar blue assay. The most potent extracts (native currant water, NC-W; native currant ethanol, NC-Et; lemon aspen ethanol, LA-Et) were further evaluated using flow cytometry to detect the potential induction of apoptosis in MCF7 cells whereas 2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA) assay was implemented to understand the impact of the extracts on the intracellular reactive oxygen species (ROS) levels in MCF7 cells. Furthermore, the antioxidant activity of the extracts was assessed using ABTS [2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonate)], and CUPRAC (cupric reducing antioxidant capacity) assays. The antimicrobial susceptibility testing of NC-W, NC-Et, and LA-Et was carried out against Gram-positive (Staphylococcus aureus), Gram-negative (Escherichia coli), and yeast (Candida albicans) strains using a resazurin-based assay. Additionally, potential metabolites in the NC-W and NC-Et extracts were analysed with liquid chromatography-mass spectrometry (LC-MS) driven metabolomics and chemometrics to spot differential and major metabolites. A dose-dependent antiproliferative activity was conferred by the NC extracts against MCF7 cells. Of the two LA extracts, only LA-Et showed a dose-dependent antiproliferative activity at higher concentrations. Both NC extracts and LA-Et induced apoptosis in MCF7 cells. None of the extracts increased the production of ROS significantly in MCF7 cells compared to the untreated control. A dose-dependent antioxidant activity was observed in both antioxidant assays. Both NC and LA extracts showed a similar minimum inhibitory concentration (MIC) value against S. aureus. Only LA-Et showed activity against E. coli, while NC-W and NC-Et were less active. All extracts showed MIC values of >1500 μg mL-1 against C. albicans. The metabolomics analysis revealed an abundance of flavonoids, fatty acyl derivatives, carbohydrates, carboxylic acids and their derivatives, and alkaloid compounds as potential bioactive metabolites in the NC extracts. In conclusion, both NC and LA showed antiproliferative (against MCF7 breast adenocarcinoma cells through the induction of apoptosis), strong antioxidant and minimal antimicrobial properties.

Dopamine‑iron homeostasis interaction rescues mitochondrial fitness in Parkinson's disease

Imbalances of iron and dopamine metabolism along with mitochondrial dysfunction have been linked to the pathogenesis of Parkinson's disease (PD). We have previously suggested a direct link between iron homeostasis and dopamine metabolism, as dopamine can increase cellular uptake of iron into macrophages thereby promoting oxidative stress responses. In this study, we investigated the interplay between iron, dopamine, and mitochondrial activity in neuroblastoma SH-SY5Y cells and human induced pluripotent stem cell (hiPSC)-derived dopaminergic neurons differentiated from a healthy control and a PD patient with a mutation in the α-synuclein (SNCA) gene. In SH-SY5Y cells, dopamine treatment resulted in increased expression of the transmembrane iron transporters transferrin receptor 1 (TFR1), ferroportin (FPN), and mitoferrin2 (MFRN2) and intracellular iron accumulation, suggesting that dopamine may promote iron uptake. Furthermore, dopamine supplementation led to reduced mitochondrial fitness including decreased mitochondrial respiration, increased cytochrome c control efficiency, reduced mtDNA copy number and citrate synthase activity, increased oxidative stress and impaired aconitase activity. In dopaminergic neurons derived from a healthy control individual, dopamine showed comparable effects as observed in SH-SY5Y cells. The hiPSC-derived PD neurons harboring an endogenous SNCA mutation demonstrated altered mitochondrial iron homeostasis, reduced mitochondrial capacity along with increased oxidative stress and alterations of tricarboxylic acid cycle linked metabolic pathways compared with control neurons. Importantly, dopamine treatment of PD neurons promoted a rescue effect by increasing mitochondrial respiration, activating antioxidant stress response, and normalizing altered metabolite levels linked to mitochondrial function. These observations provide evidence that dopamine affects iron homeostasis, intracellular stress responses and mitochondrial function in healthy cells, while dopamine supplementation can restore the disturbed regulatory network in PD cells.

AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.

Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments

Direct-to-Mass Spectrometry and ambient ionization techniques can be used for biochemical fingerprinting in a fast way. Data processing is typically accomplished with vendor-provided software tools. Here, a novel, open-source functionality, entitled Tidy-Direct-to-MS, was developed for data processing of direct-to-MS data sets. It allows for fast and user-friendly processing using different modules for optional sample position detection and separation, mass-to-charge ratio drift detection and correction, consensus spectra calculation, and bracketing across sample positions as well as feature abundance calculation. The tool also provides functionality for the automated comparison of different sets of parameters, thereby assisting the user in the complex task of finding an optimal combination to maximize the total number of detected features while also checking for the detection of user-provided reference features. In addition, Tidy-Direct-to-MS has the capability for data quality review and subsequent data analysis, thereby simplifying the workflow of untargeted ambient MS-based metabolomics studies. Tidy-Direct-to-MS is implemented in the Python programming language as part of the TidyMS library and can thus be easily extended. Capabilities of Tidy-Direct-to-MS are showcased in a data set acquired in a marine metabolomics study reported in MetaboLights (MTBLS1198) using a transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS)-based method.

MetaboReport: from metabolomics data analysis to comprehensive reporting

MOTIVATION

Metabolomics, as an essential tool in systems biology, is now widely accessible to researchers of all levels. Yet challenges remain in data analysis and result interpretation. To address these challenges, we introduced MetaboReport, a versatile and interactive web app that simplifies metabolomics experiment design, data preprocessing, exploration, statistical analysis, visualization, and reporting.

RESULTS

MetaboReport produces a comprehensive HTML report, including project details, an introduction, interactive plots and tables, statistical results and an in-depth explanations and interpretation of the results. MetaboReport is particularly tailored for research labs and metabolomics core facilities that provide metabolomics services, allowing them to efficiently manage and document different metabolomics projects, and effectively report the metabolomics results to users.

AVAILABILITY AND IMPLEMENTATION

MetaboReport is freely accessible on https://metaboreport.com, with source code available on GitHub (https://github.com/YonghuiDong/MetReport). Alternatively, users can install MetaboReport as a standalone desktop app (https://metaboreport.sourceforge.io).

Structure Revision of a Widespread Marine Sulfonolipid Class Based on Isolation and Total Synthesis

The cosmopolitan marine Roseobacter clade is of global biogeochemical importance. Members of this clade produce sulfur-containing amino lipids (SALs) involved in biofilm formation and marine surface colonization processes. Despite their physiological relevance and abundance, SALs have only been explored through genomic mining approaches and lipidomic studies based on mass spectrometry, which left the relative and absolute structures of SALs unresolved, hindering progress in biochemical and functional investigations. Herein, we report the structural revision of a new group of SALs, which we named cysteinolides, using a combination of analytical techniques, isolation and degradation experiments and total synthetic efforts. Contrary to the previously proposed homotaurine-based structures, cysteinolides are composed of an N,O-acylated cysteinolic acid-containing head group carrying various different (α-hydroxy)carboxylic acids. We also performed the first validated targeted-network based analysis, which allowed us to map the distribution and structural diversity of cysteinolides across bacterial lineages. Beyond offering structural insight, our research provides SAL standards and validated analytical data. This information holds significance for forthcoming investigations into bacterial sulfonolipid metabolism and biogeochemical nutrient cycling within marine environments.

A ternary correlation multi-symptom network strategy based on in vivo chemical profile identification and metabolomics to explore the molecular basis of Ephedra herb against viral pneumonia

Ephedra herb (EH), an important medicine prescribed in herbal formulas by Traditional Chinese Medicine practitioners, has been widely used in the treatment of viral pneumonia in China. However, the molecular basis of EH in viral pneumonia remains unclear. In this study, a ternary correlation multi-symptom network strategy was established based on in vivo chemical profile identification and metabolomics to explore the molecular basis of EH against viral pneumonia. Results showed that 143 compounds of EH and 70 prototype components were identified in vivo. EH could reduce alveolar-capillary barrier disruption in rats with viral pneumonia and significantly downregulate the expression of inflammatory factors and bronchoalveolar lavage fluid. Plasma metabolomics revealed that EH may be involved in the regulation of arachidonic acid, tryptophan, tyrosine, nicotinate, and nicotinamide metabolism. The multi-symptom network showed that 12 compounds have an integral function in the treatment of viral pneumonia by intervening in many pathways related to viruses, immunity and inflammation, and lung injury. Further verification demonstrated that sinapic acid and frambinone can regulate the expression of related genes. It has been shown to be a promising representative of the pharmacological constituents of ephedra.

Exploring contrast-enhancing staining agents for studying adipose tissue through contrast-enhanced computed tomography

Contrast-enhanced computed tomography offers a nondestructive approach to studying adipose tissue in 3D. Several contrast-enhancing staining agents (CESAs) have been explored, whereof osmium tetroxide (OsO4) is the most popular nowadays. However, due to the toxicity and volatility of the conventional OsO4, alternative CESAs with similar staining properties were desired. Hf-WD 1:2 POM and Hexabrix have proven effective for structural analysis of adipocytes using contrast-enhanced computed tomography but fail to provide chemical information. This study introduces isotonic Lugol's iodine (IL) as an alternative CESA for adipose tissue analysis, comparing its staining potential with Hf-WD 1:2 POM and Hexabrix in murine caudal vertebrae and bovine muscle tissue strips. Single and sequential staining protocols were compared to assess the maximization of information extraction from each sample. The study investigated interactions, distribution, and reactivity of iodine species towards biomolecules using simplified model systems and assesses the potential of the CESA to provide chemical information. (Bio)chemical analyses on whole tissues revealed that differences in adipocyte gray values post-IL staining were associated with chemical distinctions between bovine muscle tissue and murine caudal vertebrae. More specific, a difference in the degree of unsaturation of fatty acids was identified as a likely contributor, though not the sole determinant of gray value differences. This research sheds light on the potential of IL as a CESA, offering both structural and chemical insights into adipose tissue composition.

Investigation of the Effects of Labware Contamination on Mass Spectrometry-Based Human Serum Lipidome Analysis

Polypropylene microcentrifuge tubes (MCTs) are increasingly used in lipidome sample preparation. In the absence of a comprehensive study evaluating ramifications of plasticware utilization in mass spectrometry-based lipidomic analyses, we conducted a systematic analysis to elucidate potential negative effects ascribable to labware contamination in serum lipidomics. During serum lipid extractions, tested glassware introduced 24 labware contaminants. In contrast, Eppendorf polypropylene MCTs contributed 485 contaminant features, many of which could be erroneously putatively identified as lipids via their m/z values. Eppendorf MCTs contamination engendered severe ion-suppression of 40 low abundance serum lipids, while generating mild to modest lipid ion-suppression across a multitude of higher abundance coeluting lipids. Less compatible polypropylene MCTs from an alternative manufacturer introduced a staggering 2,949 contaminant m/z values, severely affecting 75 coeluting serum lipids and causing more frequent and pronounced ion-suppression instances. Furthermore, by performing serum extractions with varied initial volumes, it was ascertained that labware-induced lipid ion-suppression is a dynamic phenomenon, contingent on both lipid and labware contaminant concentrations where low-abundance lipids are disproportionately impacted by coelutes of suppressive contaminants. In addition to lipid ion-suppression, the identification and quantification of 7 fatty acid endogenous serum lipids were compromised by the leaching of structurally identical surfactants from MCTs. MCTs artificially introduced 10 additional primary amides extraneous to serum samples. Utmost caution is imperative in interpreting data concerning primary amides and fatty acids when employing plastic labware. Through this investigation, we aspire to elevate awareness regarding the pernicious impact of labware contamination on lipidome analysis.

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies

Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

The integration of metabolic and proteomic data uncovers an augmentation of the sphingolipid biosynthesis pathway during T-cell differentiation

Recent studies have highlighted the significance of cellular metabolism in the initiation of clonal expansion and effector differentiation of T cells. Upon exposure to antigens, naïve CD4+ T cells undergo metabolic reprogramming to meet their metabolic requirements. However, only few studies have simultaneously evaluated the changes in protein and metabolite levels during T cell differentiation. Our research seeks to fill the gap by conducting a comprehensive analysis of changes in levels of metabolites, including sugars, amino acids, intermediates of the TCA cycle, fatty acids, and lipids. By integrating metabolomics and proteomics data, we discovered that the quantity and composition of cellular lipids underwent significant changes in different effector Th cell subsets. Especially, we found that the sphingolipid biosynthesis pathway was commonly activated in Th1, Th2, Th17, and iTreg cells and that inhibition of this pathway led to the suppression of Th17 and iTreg cells differentiation. Additionally, we discovered that Th17 and iTreg cells enhance glycosphingolipid metabolism, and inhibition of this pathway also results in the suppression of Th17 and iTreg cell generation. These findings demonstrate that the utility of our combined metabolomics and proteomics analysis in furthering the understanding of metabolic transition during Th cell differentiation.

Interplatform comparison between three ion mobility techniques for human plasma lipid collision cross sections

The implementation of ion mobility spectrometry (IMS) in liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflows has become a valuable tool for improving compound annotation in metabolomics analyses by increasing peak capacity and by adding a new molecular descriptor, the collision cross section (CCS). Although some studies reported high repeatability and reproducibility of CCS determination and only few studies reported good interplatform agreement for small molecules, standardized protocols are still missing due to the lack of reference CCS values and reference materials. We present a comparison of CCS values of approximatively one hundred lipid species either commercially available or extracted from human plasma. We used three different commercial ion mobility technologies from different laboratories, drift tube IMS (DTIMS), travelling wave IMS (TWIMS) and trapped IMS (TIMS), to evaluate both instrument repeatability and interlaboratory reproducibility. We showed that CCS discrepancies of 0.3% (average) could occur depending on the data processing software tools. Moreover, eleven CCS calibrants were evaluated yielding mean RSD below 2% for eight calibrants, ESI Low concentration tuning mix (Tune Mix) showing the lowest RSD (< 0.5%) in both ion modes. Tune Mix calibrated CCS from the three different IMS instruments proved to be well correlated and highly reproducible (R2 > 0.995 and mean RSD ≤ 1%). More than 90% of the lipid CCS had deviations of less than 1%, demonstrating high comparability between techniques, and the possibility to use the CCS as molecular descriptor. We highlighted the need of standardized procedures for calibration, data acquisition, and data processing. This work demonstrates that using harmonized analytical conditions are required for interplatform reproducibility for CCS determination of human plasma lipids.

Concomitant investigation of crustacean amphipods lipidome and metabolome during the molting cycle by Zeno SWATH data-independent acquisition coupled with electron activated dissociation and machine learning

BACKGROUND

DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) initially developed for proteomics studies and recently emerging in metabolomics and lipidomics. It provides a comprehensive and unbiased coverage of molecules with improved reproducibility and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field.

RESULTS

DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to characterize molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified significant features. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra database annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness.

SIGNIFICANCE

Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing enhances detection sensitivity and targeted fragmentation with EAD in positive polarity provides orthogonal fragmentation information. In our study, Zeno-DIA and EAD thereby facilitated a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying informative biomarkers on the health status of an environmental sentinel species.

Viral Infection Leads to a Unique Suite of Allelopathic Chemical Signals in Three Diatom Host-Virus Pairs

Ecophysiological stress and the grazing of diatoms are known to elicit the production of chemical defense compounds called oxylipins, which are toxic to a wide range of marine organisms. Here we show that (1) the viral infection and lysis of diatoms resulted in oxylipin production; (2) the suite of compounds produced depended on the diatom host and the infecting virus; and (3) the virus-mediated oxylipidome was distinct, in both magnitude and diversity, from oxylipins produced due to stress associated with the growth phase. We used high-resolution accurate-mass mass spectrometry to observe changes in the dissolved lipidome of diatom cells infected with viruses over 3 to 4 days, compared to diatom cells in exponential, stationary, and decline phases of growth. Three host virus pairs were used as model systems: Chaetoceros tenuissimus infected with CtenDNAV; C. tenuissimus infected with CtenRNAV; and Chaetoceros socialis infected with CsfrRNAV. Several of the compounds that were significantly overproduced during viral infection are known to decrease the reproductive success of copepods and interfere with microzooplankton grazing. Specifically, oxylipins associated with allelopathy towards zooplankton from the 6-, 9-, 11-, and 15-lipogenase (LOX) pathways were significantly more abundant during viral lysis. 9-hydroperoxy hexadecatetraenoic acid was identified as the strongest biomarker for the infection of Chaetoceros diatoms. C. tenuissimus produced longer, more oxidized oxylipins when lysed by CtenRNAV compared to CtenDNAV. However, CtenDNAV caused a more statistically significant response in the lipidome, producing more oxylipins from known diatom LOX pathways than CtenRNAV. A smaller set of compounds was significantly more abundant in stationary and declining C. tenuissimus and C. socialis controls. Two allelopathic oxylipins in the 15-LOX pathway and essential fatty acids, arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) were more abundant in the stationary phase than during the lysis of C. socialis. The host-virus pair comparisons underscore the species-level differences in oxylipin production and the value of screening more host-virus systems. We propose that the viral infection of diatoms elicits chemical defense via oxylipins which deters grazing with downstream trophic and biogeochemical effects.

A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys

The growing disparity between the demand for transplants and the available donor supply, coupled with an aging donor population and increasing prevalence of chronic diseases, highlights the urgent need for the development of platforms enabling reconditioning, repair, and regeneration of deceased donor organs. This necessitates the ability to preserve metabolically active kidneys ex vivo for days. However, current kidney normothermic machine perfusion (NMP) approaches allow metabolic preservation only for hours. Here we show that human kidneys discarded for transplantation can be preserved in a metabolically active state up to 4 days when perfused with a cell-free perfusate supplemented with TCA cycle intermediates at subnormothermia (25 °C). Using spatially resolved isotope tracing we demonstrate preserved metabolic fluxes in the kidney microenvironment up to Day 4 of perfusion. Beyond Day 4, significant changes were observed in renal cell populations through spatial lipidomics, and increases in injury markers such as LDH, NGAL and oxidized lipids. Finally, we demonstrate that perfused kidneys maintain functional parameters up to Day 4. Collectively, these findings provide evidence that this approach enables metabolic and functional preservation of human kidneys over multiple days, establishing a solid foundation for future clinical investigations.

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

A dual extraction method involving 80% methanol followed by MTBE (methyl tert-butyl ether) extraction enables the analysis of free fatty acids, polar metabolites, and lipids. Extracts from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days were analyzed using HILIC chromatography coupled to Q Exactive Plus mass spectrometer or reversed-phase liquid chromatography coupled to 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 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 lysophosphatidylcholine (lysoPC) 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; (3) increase of intestinal tricarboxylic acid (TCA) cycle intermediates after metformin treatment.

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).

The longitudinal microbial and metabolic landscape of infant cystic fibrosis: the gut-lung axis

BACKGROUND AND AIM

In cystic fibrosis, gastrointestinal dysfunction and lower airway infection occur early and are independently associated with poorer outcomes in childhood. This study aimed to define the relationship between the microbiota at each niche during the first 2 years of life, its association with growth and airway inflammation, and explanatory features in the metabolome.

MATERIALS AND METHODS

67 bronchoalveolar lavage fluid (BALF), 62 plasma and 105 stool samples were collected from 39 infants with cystic fibrosis between 0 and 24 months who were treated with prophylactic antibiotics. 16S rRNA amplicon and shotgun metagenomic sequencing were performed on BALF and stool samples, respectively; metabolomic analyses were performed on all sample types. Sequencing data from healthy age-matched infants were used as controls.

RESULTS

Bacterial diversity increased over the first 2 years in both BALF and stool, and microbial maturation was delayed in comparison to healthy controls from the RESONANCE cohort. Correlations between their respective abundance in both sites suggest stool may serve as a noninvasive alternative for detecting BALF Pseudomonas and Veillonella. Multisite metabolomic analyses revealed age- and growth-related changes, associations with neutrophilic airway inflammation, and a set of core systemic metabolites. BALF Pseudomonas abundance was correlated with altered stool microbiome composition and systemic metabolite alterations, highlighting a complex gut-plasma-lung interplay and new targets with therapeutic potential.

CONCLUSION

Exploration of the gut-lung microbiome and metabolome reveals diverse multisite interactions in cystic fibrosis that emerge in early life. Gut-lung metabolomic links with airway inflammation and Pseudomonas abundance warrant further investigation for clinical utility, particularly in non-expectorating patients.

A lipidome landscape of aging in mice

Understanding the molecular mechanisms of aging is crucial for enhancing healthy longevity. We conducted untargeted lipidomics across 13 biological samples from mice at various life stages (2, 12, 19 and 24 months) to explore the potential link between aging and lipid metabolism, considering sex (male or female) and microbiome (specific pathogen-free or germ-free) dependencies. By analyzing 2,704 molecules from 109 lipid subclasses, we characterized common and tissue-specific lipidome alterations associated with aging. For example, the levels of bis(monoacylglycero)phosphate containing polyunsaturated fatty acids increased in various organs during aging, whereas the levels of other phospholipids containing saturated and monounsaturated fatty acids decreased. In addition, we discovered age-dependent sulfonolipid accumulation, absent in germ-free mice, correlating with Alistipes abundance determined by 16S ribosomal RNA gene amplicon sequencing. In the male kidney, glycolipids such as galactosylceramides, galabiosylceramides (Gal2Cer), trihexosylceramides (Hex3Cer), and mono- and digalactosyldiacylglycerols were detected, with two lipid classes-Gal2Cer and Hex3Cer-being significantly enriched in aged mice. Integrated analysis of the kidney transcriptome revealed uridine diphosphate galactosyltransferase 8A (UGT8a), alkylglycerone phosphate synthase and fatty acyl-coenzyme A reductase 1 as potential enzymes responsible for the male-specific glycolipid biosynthesis in vivo, which would be relevant to sex dependency in kidney diseases. Inhibiting UGT8 reduced the levels of these glycolipids and the expression of inflammatory cytokines in the kidney. Our study provides a valuable resource for clarifying potential links between lipid metabolism and aging.

MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics

The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.

Computational methods for processing and interpreting mass spectrometry-based metabolomics

Metabolomics has emerged as an indispensable tool for exploring complex biological questions, providing the ability to investigate a substantial portion of the metabolome. However, the vast complexity and structural diversity intrinsic to metabolites imposes a great challenge for data analysis and interpretation. Liquid chromatography mass spectrometry (LC-MS) stands out as a versatile technique offering extensive metabolite coverage. In this mini-review, we address some of the hurdles posed by the complex nature of LC-MS data, providing a brief overview of computational tools designed to help tackling these challenges. Our focus centers on two major steps that are essential to most metabolomics investigations: the translation of raw data into quantifiable features, and the extraction of structural insights from mass spectra to facilitate metabolite identification. By exploring current computational solutions, we aim at providing a critical overview of the capabilities and constraints of mass spectrometry-based metabolomics, while introduce some of the most recent trends in data processing and analysis within the field.

Biomarker Candidates of Habitual Food Intake in a Swedish Cohort of Pregnant and Lactating Women and Their Infants

Circulating food metabolites could improve dietary assessments by complementing traditional methods. Here, biomarker candidates of food intake were identified in plasma samples from pregnancy (gestational week 29, N = 579), delivery (mothers, N = 532; infants, N = 348), and four months postpartum (mothers, N = 477; breastfed infants, N = 193) and associated to food intake assessed with semi-quantitative food frequency questionnaires. Families from the Swedish birth cohort Nutritional impact on Immunological maturation during Childhood in relation to the Environment (NICE) were included. Samples were analyzed using untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. Both exposure and outcome were standardized, and relationships were investigated using a linear regression analysis. The intake of fruits and berries and fruit juice were both positively related to proline betaine levels during pregnancy (fruits and berries, β = 0.23, FDR < 0.001; fruit juice, β = 0.27, FDR < 0.001), at delivery (fruit juice, infants: β = 0.19, FDR = 0.028), and postpartum (fruits and berries, mothers: β = 0.27, FDR < 0.001, infants: β = 0.29, FDR < 0.001; fruit juice, mothers: β = 0.37, FDR < 0.001). Lutein levels were positively related to vegetable intake during pregnancy (β = 0.23, FDR < 0.001) and delivery (mothers: β = 0.24, FDR < 0.001; newborns: β = 0.18, FDR = 0.014) and CMPF with fatty fish intake postpartum (mothers: β = 0.20, FDR < 0.001). No clear relationships were observed with the expected food sources of the remaining metabolites (acetylcarnitine, choline, indole-3-lactic acid, pipecolic acid). Our study suggests that plasma lutein could be useful as a more general food group intake biomarker for vegetables and fruits during pregnancy and delivery. Also, our results suggest the application of proline betaine as an intake biomarker of citrus fruit during gestation and lactation.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study

Background

Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms.

Methods

Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software.

Results

A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.

Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

Metabolomic profiling of serum and tongue coating of pregnant women with intrahepatic cholestasis in pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is associated with an increased risk of cesarean section and adverse fetal outcomes. Currently, ICP diagnosis depends largely on serum levels of bile acids and lacks sensitivity and specificity for accurate diagnosis. Tongue diagnosis is an important diagnostic tool in traditional Chinese medicine (TCM) and is used in our clinic as complementary treatment and personalized medicine for ICP. However, the molecular basis of the manifestation of greasy white tongue coatings in ICP remains unknown. In this study, we performed untargeted metabolomic profiling of the serum, tongue coating, and saliva of 66 pregnant women, including 22 with ICP. The metabolomic profiles of the serum and tongue coatings showed marked differences between the two clinical groups. Forty-six differentially abundant metabolites were identified, and their relative concentrations correlated with total bile acid levels. These differential metabolites included bile acids, lipids, microbiota- and diet-related metabolites, and exposomes. Conventional biochemical markers, including serum aminotransferases and bilirubin, were not significantly increased in the ICP group, whereas the total cholesterol and triglyceride levels were significantly increased as early as the first trimester. Our data provide insights into the pathophysiology of ICP and implicate the gut-liver axis and environmental exposure. Tongue coating has the potential to be a non-invasive diagnostic approach. Further studies are required to validate the clinical utility of these findings.

Single-cell and spatial RNA sequencing reveal the spatiotemporal trajectories of fruit senescence

The senescence of fruit is a complex physiological process, with various cell types within the pericarp, making it highly challenging to elucidate their individual roles in fruit senescence. In this study, a single-cell expression atlas of the pericarp of pitaya (Hylocereus undatus) is constructed, revealing exocarp and mesocarp cells undergoing the most significant changes during the fruit senescence process. Pseudotime analysis establishes cellular differentiation and gene expression trajectories during senescence. Early-stage oxidative stress imbalance is followed by the activation of resistance in exocarp cells, subsequently senescence-associated proteins accumulate in the mesocarp cells at late-stage senescence. The central role of the early response factor HuCMB1 is unveiled in the senescence regulatory network. This study provides a spatiotemporal perspective for a deeper understanding of the dynamic senescence process in plants.

Advancing Natural Product Discovery: A Structure-Oriented Fractions Screening Platform for Compound Annotation and Isolation

Natural product discovery is hindered by the lack of tools that integrate untargeted nuclear magnetic resonance and mass spectrometry data on a library scale. This article describes the first application of the innovative NMR/MS-based machine learning tool, the "Structure-Oriented Fractions Screening Platform (SFSP)", enabling functional-group-guided fractionation and accelerating the discovery and characterization of undescribed natural products. The concept was applied to the extract of a marine fungus known to be a prolific producer of diverse natural products. With the assistance of SFSP, we isolated 24 flavipidin derivatives and five phenalenone analogues from Aspergillus sp. GE2-6, revealing 27 undescribed compounds. Compounds 7-22 were proposed as isomeric derivatives featuring a 5/6-ring fusion, formed by the dimerization of flavipidin E (5). Compounds 23 and 24 were envisaged as isomeric derivatives with a 6/5/6-ring fusion, generated through the degradation of two flavipidin E molecules. Furthermore, flavipidin A (1) and asperphenalenone E (28) exhibited potent anti-influenza (PR8) activities, with IC50 values of 21.9 ± 0.2 and 12.9 ± 0.1 μM, respectively. Meanwhile, asperphenalenone (26) and asperphenalenone P (27) treatments exhibited significant inhibition of HIV pseudovirus infection in 293FT cells, boasting IC50 values of 6.1 ± 0.9 and 4.6 ± 1.1 μM, respectively. Overall, SFSP streamlines natural product isolation through NMR and MS data integration, as showcased by the discovery of numerous undescribed flavipidins and phenalenones based on NMR olefinic signals and low-field hydroxy signals.

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

Resource competition predicts assembly of gut bacterial communities in vitro

Microbial community dynamics arise through interspecies interactions, including resource competition, cross-feeding and pH modulation. The individual contributions of these mechanisms to community structure are challenging to untangle. Here we develop a framework to estimate multispecies niche overlaps by combining metabolomics data of individual species, growth measurements in spent media and mathematical models. We applied our framework to an in vitro model system comprising 15 human gut commensals in complex media and showed that a simple model of resource competition accounted for most pairwise interactions. Next, we built a coarse-grained consumer-resource model by grouping metabolomic features depleted by the same set of species and showed that this model predicted the composition of 2-member to 15-member communities with reasonable accuracy. Furthermore, we found that incorporation of cross-feeding and pH-mediated interactions improved model predictions of species coexistence. Our theoretical model and experimental framework can be applied to characterize interspecies interactions in bacterial communities in vitro.

Combinatory data-independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities

Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra-performance liquid chromatography-high-resolution mass spectrometry in data-independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high-throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.

Metabolic phenotyping and global functional analysis facilitate metabolic signature discovery for tuberculosis treatment monitoring

Tracking alterations in polar metabolite and lipid levels during anti-tuberculosis (TB) interventions is an emerging biomarker discovery and validation approach due to its sensitivity in capturing changes and reflecting on the host status. Here, we employed deep plasma metabolic phenotyping to explore the TB patient metabolome during three phases of treatment: at baseline, during intensive phase treatment, and upon treatment completion. Differential metabolites (DMs) in each period were determined, and the pathway-level biological alterations were explored by untargeted metabolomics-guided functional interpretations that bypassed identification. We identified 41 DMs and 39 pathways that changed during intensive phase completion. Notably, levels of certain amino acids including histidine, bile acids, and metabolites of purine metabolism were dramatically increased. The altered pathways included those involved in the metabolism of amino acids, glycerophospholipids, and purine. At the end of treatment, 44 DMs were discovered. The levels of glutamine, bile acids, and lysophosphatidylinositol significantly increased compared to baseline; the levels of carboxylates and hypotaurine declined. In addition, 37 pathways principally associated with the metabolism of amino acids, carbohydrates, and glycan altered at treatment completion. The potential of each DM for diagnosing TB was examined using a cohort consisting of TB patients, those with latent infections, and controls. Logistic regression revealed four biomarkers (taurine, methionine, glutamine, and acetyl-carnitine) that exhibited excellent performance in differential diagnosis. In conclusion, we identified metabolites that could serve as useful metabolic signatures for TB management and elucidated underlying biological processes affected by the crosstalk between host and TB pathogen during treatment.

Identify organic contaminants of high-concern based on non-targeted toxicity testing and non-targeted LC-HRMS analysis in tap water and source water along the Yangtze River

Many organic pollutants were detected in tap water (TW) and source water (SW) along the Yangtze River. However, the potential toxic effects and the high-concern organics (HCOs) which drive the effect are still unknown. Here, a non-targeted toxicity testing method based on the concentration-dependent transcriptome and non-targeted LC-HRMS analysis combining tiered filtering were used to reveal the overall biological effects and chemical information. Subsequently, we developed a qualitative pathway-structure relationship (QPSR) model to effectively match the biological and chemical information and successfully identified HCOs in TW and SW along the Yangtze River by potential substructures of HCOs. Non-targeted toxicity testing found that the biological potency of both TW and SW was stronger in the downstream of the Yangtze River, and disruption of the endocrine system and cancer were the main drivers of the effect. In addition, non-targeted LC-HRMS analysis combined with retention time prediction results identified 3220 and 631 high-confidence compound structures in positive and negative ion modes, respectively. Then, QPSR model was further implied and identified a total of 103 HCOs, containing 35 industrial chemicals, 30 PPCPs, 26 pesticides, and 12 hormones in TW and SW, respectively. Among them, the neuroactive and hormonal compounds oxoamide, 8-iso-16-cyclohexyl-tetranor prostaglandin E2, E Keppra, and Tocris-0788 showed the highest frequency of detection, which were identified in more than 1/3 of the samples. The strategy of combining non-targeted toxicity testing and non-targeted LC-HRMS analysis will support comprehensive biological effect assessment, identification of HCOs, and risk control of mixtures.

Novel class of peptides disintegrating biological membranes to aid in the characterization of membrane proteins

Styrene-maleic acid (SMA) and similar amphiphilic copolymers are known to cut biological membranes into lipid nanoparticles/nanodiscs containing membrane proteins apparently in their relatively native membrane lipid environment. Our previous work demonstrated that membrane raft microdomains resist such disintegration by SMA. The use of SMA in studying membrane proteins is limited by its heterogeneity and the inability to prepare defined derivatives. In the present paper, we demonstrate that some amphiphilic peptides structurally mimicking SMA also similarly disintegrate cell membranes. In contrast to the previously used copolymers, the simple peptides are structurally homogeneous. We found that their membrane-disintegrating activity increases with their length (reaching optimum at 24 amino acids) and requires a basic primary structure, that is, (XXD)n, where X represents a hydrophobic amino acid (optimally phenylalanine), D aspartic acid, and n is the number of repeats of these triplets. These peptides may provide opportunities for various well-defined potentially useful modifications in the study of membrane protein biochemistry. Our present results confirm a specific character of membrane raft microdomains.

Metabolic Profiling as an Approach to Differentiate T-Cell Acute Lymphoblastic Leukemia Cell Lines Belonging to the Same Genetic Subgroup

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30-45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.

LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case

We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.