Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling

Comprehensive untargeted polar metabolite analysis using solvent switching liquid chromatography tandem mass spectrometry

Metabolomics analyses enable the examination and identification of endogenous biochemical reaction products, revealing information on the metabolic pathways and processes active within a living cell or organism. Determination of metabolic shifts can provide important information on a treatment or disease. Unlike other omics fields that typically have analytes of the same chemical class with common building blocks, those that fall under the nomenclature of metabolites encompass a wide array of different compounds with very diverse physiochemical properties. Development of a comprehensive metabolomic pipeline therefore can be a troublesome and complicated process for the analyst. Often single liquid chromatography-mass spectrometry methods on unfractionated samples are carried out in order to be time-efficient, however this could potentially produce data with a low number of identifiable metabolites. In the present studies, we developed a comprehensive polar metabolomics pipeline for cell-based metabolomics. SH-SY5Y neuroblastoma cells were selected as the sample matrix for method development since they are one of the most widely used cell lines for human neurotoxicity studies. This was accomplished by investigating and optimising different mass spectrometry source and chromatographic conditions to enhance the signal of polar metabolites. Optimised hydrophilic interaction liquid chromatography (HILIC) based metabolomic methods at different pH values were examined in positive, negative, and polarity switching modes to determine which combination yielded the highest number of confidently identified metabolites. Additionally, the use of sequentially running two methods was also compared to determine the degree of overlap and whether there is merit in running two separate methods on one sample. It was determined that solvent switching between two optimised methods, acidic chromatographic conditions in positive mode and basic chromatographic conditions in negative mode, yielded the highest number of unique identifiable metabolites. This could be run in a single analytical batch due to the large pH range of the column. A quick switch method in-between each method allowed both conditioning the column and preparation of the MS source conditions for the sequential method.

Metabolic dysregulation in amyotrophic lateral sclerosis: insights from 1H NMR-based metabolomics in a tertiary care center in India

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by motor neuron loss, leading to severe physical impairment and mortality. Despite available treatments like Riluzole and Edaravone, their limited efficacy highlights the need for improved understanding of ALS pathology. This study has explored metabolic alterations in North Indian ALS patients using 1H Nuclear Magnetic Resonance (NMR)-based metabolomics. A case-control study, involving 45 ALS patients and 30 healthy controls (HCs) was performed. Serum samples were analyzed using 600-MHz NMR spectrometer, revealing significant metabolic differences between ALS and HC groups. Multivariate analyses identified nine dysregulated metabolites-pyruvate, glutamine, histidine, isoleucine, leucine, imidazole, arginine, creatinine, and choline-with ROC analysis showing isoleucine as a promising biomarker (AUC 83%). Pathway enrichment analysis highlighted disruptions in key metabolic pathways, including the Glucose-Alanine Cycle, Urea Cycle, Ammonia Recycling, and the Warburg Effect, suggesting potential links to neuroinflammatory and mitochondrial dysfunction in ALS pathogenesis. This pilot study provides insight into ALS-specific metabolic alterations in Indian cohort and demonstrates the potential of these metabolites as diagnostic biomarkers. Our findings identify potential biomarkers that require validation in larger, multi-centric cohorts to support diagnosis, prognosis, and improved management of ALS.

Bacterial pathogen deploys the iminosugar glycosyrin to manipulate plant glycobiology

The extracellular space (apoplast) in plants is a key battleground during microbial infections. To avoid recognition, the bacterial model phytopathogen Pseudomonas syringae pv. tomato DC3000 produces glycosyrin. Glycosyrin inhibits the plant-secreted β-galactosidase BGAL1, which would otherwise initiate the release of immunogenic peptides from bacterial flagellin. Here, we report the structure, biosynthesis, and multifunctional roles of glycosyrin. High-resolution cryo-electron microscopy and chemical synthesis revealed that glycosyrin is an iminosugar with a five-membered pyrrolidine ring and a hydrated aldehyde that mimics monosaccharides. Glycosyrin biosynthesis was controlled by virulence regulators, and its production is common in bacteria and prevents flagellin recognition and alters the extracellular glycoproteome and metabolome of infected plants. These findings highlight a potentially wider role for glycobiology manipulation by plant pathogens across the plant kingdom.

Untargeted LC-HRMS analyses reveal metabolomic specificities between wine yeast strains selected for their malic acid production

The alcoholic fermentation of wine is mostly achieved by the species Saccharomyces cerevisiae that display a large variability for their ability to consume or produce malic acid. To better characterize the metabolism of such group of strains we explored their non-volatile metabolome using an untargeted LC-HRMS approach. The chemical classes and the putative structures of several hundred compounds where annotated using MS2 spectra using the SIRIUS software. By using both supervised and univariate statistical analyses, several metabolic features able to discriminate the two group of strains in several wines were listed. Quantitative enrichment analyses pointed out drastic differences in pantothenic acid metabolism between the two group of strains. In addition, the produced showed important change in their nitrogen composition that might be due to the pH difference in the resulting wines. Altogether this work paves the avenue for better characterizing the biochemical impact of yeast strains that modulate wine acidity.

Bromine-Based Derivatization of Carboxyl-Containing Metabolites for Liquid Chromatography-Trapped Ion Mobility Spectrometry-Mass Spectrometry

The analysis of small carboxyl-containing metabolites (CCMs), such as tricarboxylic acid (TCA) cycle intermediates, provides highly useful information about the metabolic state of cells. However, their detection using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) methods can face sensitivity and specificity challenges given their low ionization efficiency and the presence of isomers. Ion mobility spectrometry (IMS), such as trapped ion mobility spectrometry (TIMS), provides additional specificity, but further signal loss can occur during the mobility separation process. We, therefore, developed a solution to boost CCM ionization and chromatographic separation as well as leverage specificity of IMS. Inspired by carbodiimide-mediated coupling of carboxylic acids with 4-bromo-N-methylbenzylamine (4-BNMA) for quantitative analysis, we newly report the benefits of this reagent for TIMS-based measurement. We observed a pronounced (orders of magnitude) increase in signal and enhanced isomer separations, particularly by LC. We found that utilization of a brominated reagent, such as 4-BNMA, offered unique benefits for untargeted CCM measurement. Derivatized CCMs displayed shifted mobility out of the metabolite and lipid region of the TIMS-MS space as well as characteristic isotope patterns, which were leveraged for data mining with Mass Spectrometry Query Language (MassQL) and indication of the number of carboxyl groups. The utility of our LC-ESI-TIMS-MS/MS method with 4-BMA derivatization was demonstrated via the characterization of alterations in CCM expression in bone marrow-derived macrophages upon activation with lipopolysaccharide. While metabolic reprogramming in activated macrophages has been characterized previously, especially with respect to TCA cycle intermediates, we report a novel finding that isomeric itaconic, mesaconic, and citraconic acid increase after 24 h, indicating possible roles in the inflammatory response.

Prediction of postoperative delirium by blood metabolome analysis

No established blood markers can preoperatively predict postoperative delirium. Blood concentrations of amino acid catabolites and dipeptides, including those secreted extracellularly during T-lymphocyte activation, were investigated as predictors of postoperative delirium using metabolomic analyses to ascertain whether preoperative blood metabolites could predict postoperative delirium. Eighteen and 24 participants were included in the delirium and non-delirium groups, respectively. Higher preoperative levels of amino acid (tryptophan) catabolites, via the indoleamine 2,3-dioxygenase pathway, were observed in the delirium group and identified as potential predictors of postoperative delirium in this study. The delirium group had preoperatively elevated levels of tryptophan catabolites and only a limited increase postoperatively, suggesting that the tryptophan catabolic pathway may be activated preoperatively in patients at high risk of delirium. Non-targeted metabolomic analysis found a set of preoperatively elevated γ-glutamyl dipeptides as potential predictors of postoperative delirium. In vitro experiments showed that T-cell-receptor stimulation increases tryptophan metabolism and specific γ-glutamyl dipeptide secretion, offering a possible explanation for the increased levels of metabolites in postoperative delirium. This study showed that levels of amino acid metabolites associated with blood immune activity may have the potential to predict postoperative delirium.

High-viscosity dietary fibers modulate gut microbiota and liver metabolism to prevent obesity in high-fat diet-fed mice

Obesity and metabolic disorders are rising global health concerns, emphasizing the need for effective dietary interventions. High-viscosity dietary fibers such as bacterial cellulose (BC) and guar gum (GG) have unique properties that may complement each other in modulating gut microbiota and metabolic health. This study investigates their effects in high-fat diet-fed mice. BC and GG increase Bacteroides, which degrade polysaccharides and produce short-chain fatty acids (SCFAs), supporting metabolic health. BC enhances bile acid excretion and enriches Faecalibaculum, Duncaniella, and Paramuribaculum, promoting gut barrier integrity and reducing inflammation, potentially improving bile acid turnover and lipid metabolism. GG more effectively increases butyrate production by enhancing butyrate-producing bacteria, such as Clostridium XIVa and Kineothrix, and promotes Bifidobacterium, strengthening anti-inflammatory effects and gut barrier function. Both fibers upregulate bile acid biosynthesis, but BC's non-fermentable nature leads to higher bile acid excretion, while GG's fermentation causes lower excretion and broader liver metabolic changes. Both fibers reduce body weight, fat accumulation, and cholesterol levels, highlighting their potential in managing obesity and metabolic disorders. The complementary effects of BC and GG underscore the importance of fiber diversity for targeted dietary strategies to improve metabolic health.

Analytical workflow for comprehensive blood metabolomics analysis by GC-MS. Application to children with ventilator associated pneumonia

Metabolomics is a widely used approach for analyzing a vast array of low molecular weight compounds such as amino acids, organic acids, vitamins, biogenic amines and carbohydrates in biological samples, with the aim of investigating biomarkers in personalized medicine studies. Advancements in gas chromatography- mass spectrometry (GC-MS) instrumentation, along with the availability of commercial and public spectral libraries, have highlighted the relevance of GC-MS analysis as a valuable tool for metabolomics applications. Stability assessment in derivatisation and GC-MS analysis is a crucial yet often overlooked aspect of metabolomics studies. In this study, an untargeted GC-MS method workflow for large scale metabolomics studies is presented after assessment and optimization of whole blood sample's stability. The method consists of a common two-step derivatisation procedure including methoximation using methoxyamine hydrochloride, followed by silylation with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA). To ensure the stability of the studied metabolites, extensive stability experiments were performed. The stability of the derivatives was evaluated over 24 h in the autosampler at room temperature, as well as after storage for 24 and 48 h at -20 °C for both derivatized and dried extracts. While derivatised samples remained stable for 24-48 h in the freezer, dried extracts exhibited variability after 48 h. Findings support the storage of derivatised samples over dried extracts, ensuring greater stability. To increase condidence in metabolite identification data from the analysis of 120 standard compounds were utilized. The developed method was applied to analyze blood samples from 32 children with ventilator-associated pneumonia (VAP), collected at four different time points during ICU hospitalization. This analysis led to the identification of 43 metabolites. The results of multivariate and univariate statistical analyses demonstrated several statistically significant metabolites, including aspartic acid, alanine, and pyroglutamic acid, which showed a strong correlation with the disease's manifestation and may potentially serve as biomarkers in the diagnosis of ventilator-associated pneumonia VAP at the stage of clinical suspicion.

Analysis of salinity-induced metabolome changes in Indian mustard (Brassica juncea) roots and shoots: hydroponic versus microplot cultivation

BACKGROUND

Brassica juncea L. (family Brassicaceae) or Indian mustard is a fast-growing oilseed crop. Climate changes mean that it is very important to evaluate the effects of salinity stress on B. juncea. The aim of this study was therefore to show the metabolic effect of salinity stress on shoots and roots using two cultivation models - hydroponic and microplot - in different cultivars, including RH-725 and RH-761. Salinity levels of 5, 7.5, and 10 dS m⁻¹ were investigated, and compared with a control of 0 dS m⁻¹, using untargeted metabolomics with gas chromatography-mass spectrometry (GC-MS) post-silylation, focusing on metabolic markers such as proline and glycine-betaine.

RESULTS

A total of 56 metabolites were identified, with the most prevalent classes belonging to sugars (8), followed by organic acids (13), amino acids (11), and fatty acids/esters (11). Shoots were found to have a higher sugar content than roots. Increases in unsaturated fatty acids were also associated with salinity stress, compared with a decrease in saturated fatty acids. Absolute levels of proline and glycine-betaine correlated with salinity stress, with the largest increases detected in shoots grown under hydroponic conditions, particularly for the RH-761 cultivar. Multivariate data analyses revealed that roots were more affected than shoots, regardless of cultivation model.

CONCLUSION

These findings might explain the different metabolic behavior of B. juncea's roots and shoots under various levels of salinity, associated with higher levels of free sugars in shoots and lipids in roots. © 2024 Society of Chemical Industry.

Exploring the anti-diabetic potential of barnyard millet: insights from virtual screening, MD simulation and MM-PBSA

Barnyard millet (Echinochloa frumentacea) is a nutritionally superior grain and a rich source of dietary fiber, and protein. It helps in managing health and dietary issues such as malnutrition, diabetes, obesity, and celiac disease. Its low content of slowly digestible carbohydrates promotes a gradual release of glucose, helping to maintain stable blood glucose levels. The present study aims to identify and screen phytochemicals in the barnyard millet and explore its anti-diabetic activity through an in-silico study. Gas chromatography-mass spectrometry (GC-MS) analyses of the seed extract revealed the occurrence of 73 bioactive compounds that are known to possess a variety of pharmacological activities. Based on the virtual screening analysis, phytochemicals interacted with five different diabetic targets, with diosgenin demonstrating the lowest binding affinity across four receptors. Specifically, diosgenin showed a binding affinity of -9.2 kcal/mol with the Insulin receptor (PDB ID: 1IR3), -8.7 kcal/mol with Peroxisome proliferator-activated receptors (PDB ID: 3G9E), -7.5 kcal/mol with Tyrosine phosphatase 1-beta (2F70), and -6.5 kcal/mol with the Glucagon receptor (PDB ID: 5EE7). For Aldose reductase (PDB ID: 4XZH), Docosahexaenoic acid exhibited the lowest binding affinity of -9.9 kcal/mol. The dynamic behavior of 2F70-Diosgenin docked complexes throughout a 500 ns trajectory run was investigated further. The RMSD and RMSF analyses reveal that the complex remains structurally stable. The binding free energies were computed using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology. The calculation results show that the predicted free energies of the complex are stable. These results suggest that the 2F70-Diosgenin complex is stable, highlighting its potential for further wet lab validation.

Omics advancements towards exploring arsenic toxicity and tolerance in plants: a review

MAIN CONCLUSION

Omics approaches provide comprehensive insights into plant arsenic stress responses, setting the stage for engineering arsenic-tolerant crops. Understanding arsenic (As) toxicity in plants is crucial for environmental and agricultural sustainability, considering the implications of As in impacting soil productivity and environmental health. Although some articles already examined the detailed molecular mechanisms behind As toxicity and tolerance, a comprehensive review of recent omics advancements in studying plant responses to As exposure is needed. The present review highlights the valuable contribution of omics approaches (genomics, transcriptomics, proteomics, and metabolomics) to characterize the intricate response to As overall, which could empower As-tolerant plant development. Genomic techniques, such as QTL mapping, GWAS, RAPD, and SSH, hold the potential to provide valuable insights into the genetic diversity and expression patterns associated with the plant response to As stress, highlighting also the power of new advanced technology such as CRISPR-Cas9. Transcriptomics approaches (e.g., microarrays and RNA sequencing) revealed gene expression patterns in plants under As stress, emphasizing the role of sulfur metabolism in As tolerance. Proteomics, using 2-DE combined with MALDI-ToF MS or ESI-MS/MS, offers insights into the stress-inducible proteins and their involvement in As toxicity mitigation, while iTRAQ-based proteomics enabled an understanding of cultivar-specific responses under high As concentration. Metabolomics, with LC-MS, GC-MS, (U)HPLC, and NMR, elucidated small molecule alterations and complex metabolic activities occurring under As plant exposure. Compendium of data and evidence-related tools offers a foundation for advancing As-tolerant plant development and promoting environmental and agricultural resilience.

Polydatin combined with hawthorn flavonoids alleviate high fat diet induced atherosclerosis by remodeling the gut microbiota and glycolipid metabolism

Background

Atherosclerosis is a widely studied pathophysiological foundation of cardiovascular diseases. Inflammation and dyslipidemia are risk factors that promote the formation of atherosclerotic plaques. The gut microbiota and their metabolites are considered independent risk factors for atherosclerosis. Polydatin combined with hawthorn flavonoids, as the extracts of Polygonum cuspidatum Sieb. et Zucc. and Crataegus pinnatifida Bunge, have shown excellent cardiovascular protective effects. However, the underlying mechanism requires further investigation. Our study aimed to explore the anti-atherosclerotic mechanism through gut microbiota and their metabolites.

Methods

ApoE-/- mice were fed either a normal-chow diet or a high-fat diet. The polydatin combined with hawthorn flavonoids group received varied doses of polydatin and hawthorn flavonoids: a high dose (polydatin 200 mg/kg daily; hawthorn flavonoids 100 mg/kg daily), a medium dose (polydatin 100 mg/kg daily; hawthorn flavonoids 50 mg/kg daily), and a low dose (polydatin 50 mg/kg daily; hawthorn flavonoids 25 mg/kg daily). The control and model groups were administered distilled water (0.2 mL daily). The experiment lasted for 24 weeks.

Results

Polydatin combined with hawthorn flavonoids administration significantly reduced lipid and inflammatory cytokine levels, meanwhile, the atherosclerotic lesions in a high-fat diet-induced ApoE-/- mice were significantly decreased. Additionally, polydatin combined with hawthorn flavonoids also inhibited the enhancement of trimethylamine N-oxide (TMAO), trimethylamine (TMA) levels of HFD-induced ApoE-/- mice by regulating the expression of hepatic flavin-containing enzyme monooxygenase 3 (FMO3). 16S rRNA sequencing results demonstrated that high-dose polydatin combined with hawthorn flavonoids treatment increased the abundance of Actinobacteriota, Atopobiaceae and Coriobacteriaea_UCG-002, and decreased the abundance of Desulfobacterota. Norank_f_Muribaculaceae was enriched in the medium-dose polydatin combined with hawthorn flavonoids and simvastatin groups, and Lactobacillus was mainly increased in the simvastatin and the low-dose polydatin combined with hawthorn flavonoids groups. According to the metagenetic results, functional annotations also suggested that the biological processes of each group mainly focused on metabolism-related processes. Specifically, polydatin combined with hawthorn flavonoids may regulate the abundance of TMA-producing bacteria (Coriobacteriaceae, Desulfovibrio, Muribaculum, and Clostridium) and related enzymes in glycolipid metabolic pathways to exert an important effect on the prevention of atherosclerosis.

Conclusion

Our results suggested that polydatin combined with hawthorn flavonoids could regulate the glucolipid metabolism-related pathway, attenuate inflammatory cytokine levels, and reduce atherosclerotic plaques by remodeling gut microbiota.

Aspergillus Mycotoxins: The Major Food Contaminants

Mycotoxins, a category of fungal secondary metabolites, frequently contaminate food products and pose a severe threat to human health. Aspergillus, a genus of fungi, is capable of producing mycotoxins, with aflatoxins (AFs) and ochratoxins being its principal types. Aspergillus mycotoxins can contaminate a wide range of crops and their derivatives, such as maize, wheat, rice, minor cereals, and peanuts, thereby threatening food and feed safety. In the paper, the related biosynthesis genes and multifaceted biosynthesis pathways of these mycotoxins are first discussed in detail, and elucidated several global regulators, including growth conditions, oxidative stress, and cell signal. Furthermore, how global shifts in temperature and water availability, driven by climate change (including rising temperatures, increased heavy rainfall frequency, prolonged droughts, and elevated carbon dioxide levels), are key determinants of Aspergillus proliferation and mycotoxin production are explored. Finally, to safeguard animal and human health from the detrimental impacts of Aspergillus mycotoxins, the effective and convenient analytical techniques and management strategies for the detection and prevention of contamination are analyzed. Overall, this review provides effective detection techniques and promising solutions to the global contamination of food with Aspergillus mycotoxins, which is of great significance to ensuring food security and protecting people's lives and health.

Strain-Specific Features of Primary Metabolome Characteristic for Extremotolerant/Extremophilic Cyanobacteria Under Long-Term Storage

Cyanobacteria isolated from extreme habitats are promising in biotechnology due to their high adaptability to unfavorable environments and their specific natural products. Therefore, these organisms are stored under a reduced light supply in multiple collections worldwide. However, it remains unclear whether these strains maintain constitutively expressed primary metabolome features associated with their unique adaptations. To address this question, a comparative analysis of primary metabolomes of twelve cyanobacterial strains from diverse extreme habitats was performed by a combined GC-MS/LC-MS approach. The results revealed that all these cyanobacterial strains exhibited clear differences in their patterns of primary metabolites. These metabolic differences were more pronounced for the strains originating from ecologically different extreme environments. Extremotolerant terrestrial and freshwater strains contained lower strain-specifically accumulated primary metabolites than extremophilic species from habitats with high salinity and alkalinity. The latter group of strains was highly diverse in amounts of specific primary metabolites. This might indicate essentially different molecular mechanisms and metabolic pathways behind the survival of the microorganisms in saline and alkaline environments. The identified strain-specific metabolites are discussed with respect to the metabolic processes that might impact maintaining the viability of cyanobacteria during their storage and indicate unique adaptations formed in their original extreme habitats.

Metabolomic profiling of plasma from glioma and meningioma patients based on two complementary mass spectrometry techniques

INTRODUCTION

Extracranial and intracranial tumors are a diverse group of malignant and benign neoplasms, influenced by multiple factors. Given the complex nature of these tumors and usually late or accidental diagnosis, minimally invasive, rapid, early, and accurate diagnostic methods are urgently required. Metabolomics offers promising insights into central nervous system tumors by uncovering distinctive metabolic changes linked to tumor development.

OBJECTIVES

This study aimed to elucidate the role of altered metabolites and the associated biological pathways implicated in the development of gliomas and meningiomas.

METHODS

The study was conducted on 95 patients with gliomas, 68 patients with meningiomas, and 71 subjects as a control group. The metabolic profiling of gliomas and meningiomas achieved by integrating untargeted metabolomic analysis based on GC-MS and targeted analysis performed using LC-MS/MS represents the first comprehensive study. Three comparisons (gliomas or meningiomas vs. controls as well as gliomas vs. meningiomas) were performed to reveal statistically significant metabolites.

RESULTS

Comparative analysis revealed 97, 56, and 27 significant metabolites for gliomas vs. controls, meningiomas vs. controls and gliomas vs. meningiomas comparison, respectively. Moreover, among above mentioned comparisons unique metabolites involved in arginine biosynthesis and metabolism, the Krebs cycle, and lysine degradation pathways were found. Notably, 2-aminoadipic acid has been identified as a metabolite that can be used in distinguishing two tumor types.

CONCLUSIONS

Our results provide a deeper understanding of the metabolic changes associated with brain tumor development and progression.

Caenorhabditis nematodes influence microbiome and metabolome characteristics of their natural apple substrates over time

The microbiomes of host organisms and their direct source environments are closely linked and key for shaping microbial community dynamics. The relationship between these linked dynamics is largely unexplored because source substrates are usually unavailable. To address this current knowledge gap, we employed bacteriovorous Caenorhabditis nematodes as a unique model system, for which source substrates like rotting apples can be easily collected. We compared single host microbiomes with their corresponding apple source substrates, as well as nematode-free substrates, over a 2-year sampling period in the botanical garden in Kiel, Germany. We found that single worms have unique microbiomes, which overlap most strongly with nematodes from the same source apple. A comparison to previous, related work revealed that variation in microbiome composition of natural Caenorhabditis isolates is significantly influenced by the substrate type, from which worms were obtained (e.g., fruits or compost). Our current sampling further showed that microbiome assembly is mostly driven by dispersal limitation. Importantly, two independent analysis approaches consistently suggest that worm microbiomes significantly influence characteristics of the apple microbiomes, possibly indicating niche construction by nematodes. Moreover, combining apple microbiome and metabolome data, we identified individual microbes and specific compounds indicative of fruit ripening that are significantly associated with nematode presence. In conclusion, our study elucidates the complex relationship between host microbiomes and their directly connected substrate microbiomes. Our analyses underscore the significant influence of nematode microbiomes on shaping the apple microbiome and, consequently, the fruit's metabolic capacity, thereby enhancing our general understanding of host-microbiome interactions in their natural habitat.IMPORTANCEAlmost all complex organisms are host to a microbial community, the microbiome. This microbiome can influence diverse host functions, such as food processing, protection against parasites, or development. The relationship between host and microbiome critically depends on the assembly of the microbial community, which may be shaped by microbes in the directly linked environment, the source microbiome. This assembly process is often not well understood because of the unavailability of source substrates. Here, we used Caenorhabditis nematodes as a model system that facilitates a direct comparison of host and source microbiomes. Based on a 2-year sampling period, we identified (i) a clear link between assembly dynamics of host and source microbiomes, (ii) a significant influence of nematode microbiomes on apple microbiomes, and (iii) specific microbes and compounds that are associated with the presence of nematodes in the sampled substrates. Overall, our study enhances our understanding of microbiome assembly dynamics and resulting functions.

Harnessing multi-omics approaches to elucidate the role of Chinese herbal compounds in chemotherapy-induced gastrointestinal damage

In this editorial, we discuss the findings reported by Wang et al in the latest issue of the World Journal of Gastrointestinal Oncology. Various research methodologies, including microbiome analysis, assert that the Tzu-Chi Cancer-Antagonizing and Life-Protecting II Decoction of Chinese herbal compounds mitigates inflammatory responses by inhibiting the NF-κB signaling pathway. This action helps maintain the dynamic equilibrium of the intestinal microecology and lessens chemotherapy-induced gastrointestinal damage. The efficacy of these compounds is intimately linked to the composition of intestinal microbes. These compounds regulate intestinal microecology by virtue of their specific compatibility and effectiveness, thereby enhancing the overall therapeutic outcomes of cancer chemotherapy. Nonetheless, the exact mechanisms underlying these effects warrant further investigation. Multi-omics technologies offer a systematic approach to elucidate the mechanisms and effectiveness of Chinese herbal compounds in vivo. This manuscript reviews the application of multi-omics technologies to Chinese herbal compounds and explores their potential role in modulating the gastrointestinal microenvironment following cancer chemotherapy, thus providing a theoretical foundation for their continued use in adjunct cancer treatment.

Applying newly suggested simultaneous analysis of metabolomics and lipidomics into perfluorooctanesulfonate-derived neurotoxicity mechanism in zebrafish embryos

Developing methodologies for performing multi-omics with one sample has been challenging in zebrafish toxicology; however, related studies are lacking. A new strategy for the simultaneous analysis of metabolomics and lipidomics in zebrafish embryos was proposed and applied to explore the neurotoxicity mechanisms of perfluorooctanesulfonate (PFOS). Metabolite and lipid profiled simultaneously with methyl tert-butyl ether (MTBE) were compared with individual results from other extraction solvents. Behavioral alterations were measured after the zebrafish embryos were exposed to 0.1-20 μM PFOS for 5 days. The metabolite-lipid profiles of the MTBE-based strategy analyzed with optimized larval pooling size of 30 were comparable to those of other extraction solvents, indicating the feasibility and efficiency of MTBE-based multi-omics analysis. Many metabolites and lipids, which were enriched more than those previously reported, completed the toxicity pathways involved in energy metabolism and sphingolipids, improving our understanding of PFOS-induced neurotoxicity mechanism manifested by increased movement under dark conditions. Our novel MTBE-based strategy enabled the multi-omics analysis of one sample with minimal use of zebrafish embryos, thereby improving data reliability on changes in multi-layered biomolecules. This study will advance multi-omics technologies that are critical to elucidating the toxicity mechanisms of toxic chemicals including per- and polyfluoroalkyl substances.

Bacterial pathogen deploys iminosugar galactosyrin to manipulate plant glycobiology

The extracellular space (apoplast) of plants is an important molecular battleground during infection by many pathogens. We previously found that a plant-secreted β-galactosidase BGAL1 acts in immunity by facilitating the release of immunogenic peptides from bacterial flagellin and that Pseudomonas syringae suppresses this enzyme by producing a small molecule inhibitor called galactosyrin. Here, we elucidated the structure and biosynthesis of galactosyrin and uncovered its multifunctional roles during infection. Structural elucidation by cryo-EM and chemical synthesis revealed that galactosyrin is an iminosugar featuring a unique geminal diol attached to the pyrrolidine moiety that mimics galactose binding to the β-galactosidase active site. Galactosyrin biosynthesis branches off from purine biosynthesis and involves three enzymes of which the first is a reductase that is unique in iminosugar biosynthesis. Besides inhibiting BGAL1 to avoid detection, galactosyrin also changes the glycoproteome and metabolome of the apoplast. The manipulation of host glycobiology may be common to plant-associated bacteria that carry putative iminosugar biosynthesis clusters.

The Mucilage From the Opuntia ficus-indica (L.) Mill. Cladodes Plays an Anti-Inflammatory Role in the LPS-Stimulated HepG2 Cells: A Combined In Vitro and In Silico Approach

The effect of a mucilage extracted from Opuntia ficus-indica (L.) Mill (OFI) cladodes was tested in lipopolysaccharide (LPS)-challenged HepG2 hepatocarcinoma cells, through a combined in vitro-in silico approach. The OFI mucilage was characterized by gas chromatography-mass spectrometry and liquid chromatography-high resolution mass spectrometry. In cells treated with OFI (5-10 µg/mL) prior to LPS (1 µg/mL, 24 h), the gene expression profile of pro-inflammatory mediators, namely tumor necrosis factor alpha, interleukin-1 beta, interleukin-8, and cyclo-oxygenase-2, was significantly (p < 0.01) reduced if compared to single LPS-challenged cells. The OFI-mediated cytokines reduction was also validated in polystyrene scaffold-grown 3D HepG2 cultures, undergoing treatment with the OFI mucilage (50 µg/mL, 24 h) and LPS stimulation (50 µg/mL, 24 h). We further demonstrated that OFI suppresses the LPS-triggered inflammatory response via impairment of the Toll-like receptor 4 (TLR4)/Myeloid differentiation protein-88/Nuclear factor-kappa B (NF-kB) pathway, by interfering with NF-kB phosphorylation at Serine 536. By molecular docking approach, we provided in silico demonstration of the direct molecular interaction between the mucilage monosaccharides and the TLR4 that interferes with the LPS receptor binding and down-stream inflammatory cascade activation. We also demonstrated that OFI cladodes mucilage downregulates the TLR4 pathway, showing an anti-inflammatory potential in HepG2 cells.

Impact of Limited Irrigation on Fruit Quality and Ethylene Biosynthesis in Tomato: A Comprehensive Analysis of Physical, Biochemical, and Metabolomic Traits

Water scarcity and climate change pose significant challenges to sustainable agriculture, emphasizing the need for optimized irrigation practices. This study evaluates the impact of limited irrigation (0.45 L/day per plant) compared to a control (0.87 L/day per plant) on tomato fruit quality and metabolic responses. Limited irrigation enhanced fruit flavor by reducing the pH from 4.2 to 3.4 and improved cellular integrity, with electrolyte leakage decreasing from 50% to 26%. Antioxidant levels increased, with the vitamin C content rising from 49 to 64 mg 100 g-1 FW, while glucose and fructose accumulation contributed to improved sweetness. Notably, limited irrigation suppressed ethylene biosynthesis, reducing methionine, ACC, ACO activity, and ethylene production, which are key regulators of ripening and senescence. This suppression suggests the potential for extending shelf life and delaying over-ripening. These findings underscore the dual benefits of limited irrigation: enhancing fruit quality and supporting sustainable water use. This research provides a viable strategy for optimizing tomato production and postharvest quality in water-limited regions.

Metabolomics-Driven Insights into Biomarkers for Poor Ovarian Response: A Narrative Review

Poor ovarian response (POR) remains a significant challenge in the field of assisted reproductive technology (ART), as the quantity and quality of oocytes retrieved directly influence embryo implantation, clinical pregnancy, and live birth rates. Metabolomics has become a valuable tool for elucidating the molecular mechanisms underlying diminished ovarian reserve (DOR) and POR. This review aims to synthesize findings from metabolomic studies examining metabolite expression patterns in serum and follicular fluid samples from women with POR. A literature search was performed using the Medline/PubMed and Scopus databases, employing keywords related to metabolomics and POR. In total, nine studies met the inclusion criteria for this review. These studies identified several metabolites with differential expression in serum and follicular fluid samples between women with normal ovarian response and those with POR. Although the metabolomic profiles varied significantly among studies, consistent alterations in prostaglandin related metabolites were observed in two of the nine studies reviewed. These findings suggest that, pending further validation, these metabolites may serve as potential biomarkers for ovarian response. Metabolomics has significantly advanced our understanding of the mechanisms underlying ovarian function and holds promise for identifying effective biomarkers that could improve the prediction and management of POR.

Urine organic acid metabolomic profiling by gas chromatography mass spectrometry: Assessment of solvent extract evaporation parameters on the recovery of key diagnostic metabolites

BACKGROUND

Analysis of urinary organic acids (UOAs) by gas chromatography mass-spectrometry (GC-MS) is widely used in metabolomic studies. It is a complex test with many limitations and pitfalls yet there is limited evidence in the literature to support best practice. This study investigated the impact of drying down time and temperature on the recovery of 16 key analytes from solvent extracts.

METHODS

Pooled urine specimens were enriched with organic acids. Urine aliquots (n = 3) were acidified and extracted into diethyl ether and ethyl acetate. Extracts were dried under nitrogen at ambient temperature (25 °C); 40 °C; 60 °C then left for 0; +5; +15 min. Dried extracts were derivatised with N,O,-bis-(trimethylsilyl)trifluoroacetamide prior to analysis by GC-MS. Urine specimens from individuals with biotinidase deficiency, maple syrup urine disease (MSUD) and ketotic hypoglycemia were analysed to demonstrate the potential clinical impact.

RESULTS

Recovery of shorter chain hydroxycarboxylic acids decreased significantly when extracts were dried above 25 °C (mean recovery 89 % at 60 °C, p < 0.01) or left under nitrogen post-drying (mean recovery at ambient + 15 min, 40 °C + 15mins and 60 °C + 15mins was 56 %, 12 % and 2 %, respectively, p < 0.01). Whilst dicarboxylic acids/medium chain fatty acids were unaffected by temperature (mean recovery 100 %), prolonged drying reduced recovery (mean recovery 85 % at 60 °C + 15mins, p < 0.01).

CONCLUSIONS

Evaporation of solvent extracts with heat and/or prolonged drying under nitrogen results in significant losses of the shorter chain hydroxycarboxylic acids. The evaporation protocol must be carefully controlled to ensure accurate and reproducible results, preventing misdiagnoses and/or misinterpretation of results.

Underlying Mechanisms of Chromatographic H/D, H/F, cis/trans and Isomerism Effects in GC-MS

Charge-free gaseous molecules labeled with deuterium 2H (D) atoms elute earlier than their protium-analogs 1H (H) from most stationary GC phases. This effect is known as the chromatographic H/D isotope effect (hdIEC) and can be calculated by dividing the retention times (tR) of the protiated (tR(H) ) to those of the deuterated (tR(D)) analytes: hdIEC = tR(H)/tR(D). Analytes labeled with 13C, 15N or 18O have almost identical retention times and lack a chromatographic isotope effect. Derivatives of cis- and trans-analytes such as cis- and trans-fatty acids also differ in their retention times. Analytes that contain trans-C=C-double bonds elute earlier in gas chromatography-mass spectrometry (GC-MS) than their cis-C=C-double bonds containing congeners. The chromatographic cis/trans-effect (ctEC) can be calculated by dividing the retention times of the cis- by those of the trans-analytes: ctEC = tR(c)/tR(t). In the present work, the hdIEC and ctEC values of endogenous and exogenous substances were calculated from previously reported GC-MS analyses and found to range each between 1.0009 and 1.0400. The examination suggests that the H/D-isotope effects and the cis/trans-effects observed in GC-MS are based on differences in the inter-molecular interaction strengths of the analyte derivatives with the stationary phase of GC columns. The deuterium atoms, being larger than the H atoms of the analytes, attenuate the interaction of the skeleton of the molecules with the GC stationary phase. The angulation of trans-analytes decreases the interaction of the skeleton of the molecules with the GC stationary phase, as only parts of the molecules are close enough to the GC stationary phase to interact. Other chromatographic effects caused by hydrogen (H) and fluorine (F) atoms and by stereo-isomerism are considered to be based on a similar mechanism due to the different orientation of the side chains.

The triterpenoid curcumene mediates the relative hydrophilicity of Bacillus subtilis spores

Spores of Bacillus subtilis are surrounded and protected by the coat and the crust, multi-layered structures mainly made of proteins and polysaccharides. These polysaccharides are covalently linked to some of the coat and crust proteins and influence some spore properties, such as surface adhesion and hydrophilicity. This study reports that a mutant strain lacking the spsA-L operon, encoding 11 enzymes involved in the synthesis of spore surface polysaccharides, produced spores exposing on their surface hydrophobic molecules that were responsible for the drastic reduction of hydrophilicity of the mutant spores. Biochemical and genetic data support the identification of the C35-terpenoid curcumene, a precursor of the spore-associated lipid sporulene, as the highly hydrophobic molecule present on the surface of mutant spores.IMPORTANCEBacterial spores are the most resistant cell forms on Earth. The metabolically quiescent spores withstand conditions that would be lethal for other cells, maintaining the capacity to sense the environment and respond to the presence of favorable conditions by germinating. Such remarkable resistance is also due to the complex layers that surround the spore cytoplasm and protect it against damaging factors. Altogether, the spore surface layers form a complex cell structure composed of proteins, polysaccharides, and, as highlighted by this study, also of lipids. Understanding the complexity of the spore surface and the specific molecules involved in its structure is an essential step for unraveling the mechanisms underlying the spore's resistance to environmental assaults.

Optimized high-throughput protocols for comprehensive metabolomic and lipidomic profiling of brain sample

Establishing direct causal and functional links between genotype and phenotype requires thoroughly analyzing metabolites and lipids in systems biology. Tissue samples, which provide localized and direct information and contain unique compounds, play a significant role in objectively classifying diseases, predicting prognosis, and deciding personalized therapeutic strategies. Comprehensive metabolomic and lipidomic analyses in tissue samples need efficient sample preparation steps, optimized analysis conditions, and the integration of orthogonal analytical platforms because of the physicochemical diversities of biomolecules. Here, we propose simple, rapid, and robust high-throughput analytical protocols based on the design of experiment (DoE) strategies, with the various parameters systematically tested for comprehensively analyzing the heterogeneous brain samples. The suggested protocols present a systematically DoE-based strategy for performing the most comprehensive analysis for integrated GC-MS and LC-qTOF-MS from brain samples. The five different DoE models, including D-optimal, full factorial, fractional, and Box-Behnken, were applied to increase extraction efficiency for metabolites and lipids and optimize instrumental parameters, including sample preparation and chromatographic parameters. The superior simultaneous extraction of metabolites and lipids from brain samples was achieved by the methanol-water-dichloromethane (2:1:3, v/v/v) mixture. For GC-MS based metabolomics analysis, incubation time, temperature, and methoxyamine concentration (10 mg/mL) affected metabolite coverage significantly. For LC-qTOF-MS based metabolomics analysis, the extraction solvent (methanol-water; 2:1, v/v) and the reconstitution solvent (%0.1 FA in acetonitrile) were superior on the metabolite coverage. On the other hand, the ionic strength and column temperature were critical and significant parameters for high throughput metabolomics and lipidomics studies using LC-qTOF-MS. In conclusion, DoE-based optimization strategies for a three-in-one single-step extraction enabled rapid, comprehensive, high-throughput, and simultaneous analysis of metabolites, lipids, and even proteins from a 10 mg brain sample. Under optimized conditions, 475 lipids and 158 metabolites were identified in brain samples.

Metabolomics of Chinese Hamster Ovary Cells

Increasing demand of protein biotherapeutics produced using Chinese hamster ovary (CHO) cell lines necessitates improvement in the production yield of the bioprocess. Various cell engineering, improved media formulation and process-design based approaches utilizing the power of OMICS technologies, specifically, genomics and proteomics, have been employed; however, the potential of metabolomics largely remains unexplored. Metabolomics enables the detection, identification, and/or quantitation of small molecules, commonly known as metabolites, in and around the cells and may help to unlock the cellular molecular mechanism(s) that regulates cell growth and productivity in the bioprocess and improves cellular performance during the bioprocess. Currently, liquid chromatography (LC)/gas chromatography (CG)- coupled with mass-spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the most commonly used approaches for metabolomics. Therefore, in this chapter, we have discussed the standard procedures of investigating CHO metabolites using LC/GC-MS and/or NMR-based approaches.

Identification and Profiling of Primary Metabolites Through GC-MS and Associated Data Processing

This chapter presents a comprehensive approach to profiling plant-derived primary metabolites using metabolomics, highlighting its critical role in decoding the biosynthesis of bioactive plant compounds. It details the utilization of gas chromatography-mass spectrometry (GC-MS) for the effective analysis and profiling of these metabolites. The process, encompassing extraction methods, chemical derivatization, and data processing, is thoroughly outlined. This methodology outlines comprehensive procedures for each stage of the workflow, encompassing metabolite extraction, GC-MS analysis, and data alignment, to produce a metabolomics dataset.

Metabolic Reprogramming in Cancer: Implications for Immunosuppressive Microenvironment

Cancer is a complex and heterogeneous disease characterised by uncontrolled cell growth and proliferation. One hallmark of cancer cells is their ability to undergo metabolic reprogramming, which allows them to sustain their rapid growth and survival. This metabolic reprogramming creates an immunosuppressive microenvironment that facilitates tumour progression and evasion of the immune system. In this article, we review the mechanisms underlying metabolic reprogramming in cancer cells and discuss how these metabolic alterations contribute to the establishment of an immunosuppressive microenvironment. We also explore potential therapeutic strategies targeting metabolic vulnerabilities in cancer cells to enhance immune-mediated anti-tumour responses. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02044861, NCT03163667, NCT04265534, NCT02071927, NCT02903914, NCT03314935, NCT03361228, NCT03048500, NCT03311308, NCT03800602, NCT04414540, NCT02771626, NCT03994744, NCT03229278, NCT04899921.

(Pre)Clinical Metabolomics Analysis

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Sample Preparation of Caenorhabditis elegans for GC-MS-Based Metabolomics in Toxicity Assessment

The nematode Caenorhabditis elegans, widely recognized as a model organism due to its ease of breeding and well-characterized genomes, boasts complete digestive, reproductive, and endocrine systems, as well as conserved signaling pathways shared with mammals. It has become an invaluable resource for metabolomics research, particularly in examining responses to chemical or environmental factors and toxicity assessments. In this article, we provide detailed, step-by-step protocols for cultivating C. elegans and conducting metabolomics analyses, specifically focusing on sample preparation for GC-MS analysis in response to toxic compound treatments. We highlight the critical choice of extraction solvent, introducing two representative systems for extracting metabolites from C. elegans.

Detecting N-Phenyl-2-Naphthylamine, L-Arabinose, D-Mannose, L-Phenylalanine, L-Methionine, and D-Trehalose via Photocurrent Measurement

The concentration of small molecules reflects the normality of physiological processes in the human body, making the development of simple and efficient detection equipment essential. In this work, inspired by a facile strategy in point-of-care detection, two devices were fabricated to detect small molecules via photocurrent measurement. A linear response of the photocurrent against the concentration of the small molecules was found. In the first device, metal ions were introduced into gel substrates made by xanthan gum to enhance photocurrent response. N-phenyl-2-naphthylamine was measured when iron or manganese ions were used. L-Phenylalanine was measured when the gel was modified by samarium, iron, cerium, or ytterbium ions. L-(+)-Arabinose was detected via the gels modified by iron or holmium ions. D-(+)-Mannose was detected when the gel was modified by ytterbium, manganese, chromium, or sodium ions. L-Methionine was detected in the gels modified by samarium, zinc, or chromium ions. The second device was based on a paper sheet. A sugar-like molecule was first synthesized, which was then used to modify the paper. The detection was possible since the photocurrent showed a linear trend against the concentration of D-Trehalose. A linear fit was conducted to derive the sensitivity, whose value was found to be 5542.4. This work offers a novel, simple, and environmentally sustainable platform that is potentially useful in remote areas lacking medical devices.

Current Role and Potential of Triple Quadrupole Mass Spectrometry in Biomedical Research and Clinical Applications

Mass-spectrometry-based assays nowadays play an essential role in biomedical research and clinical applications. There are different types of commercial mass spectrometers on the market today, and triple quadrupole (QqQ) is one of the time-honored systems. Here, we overview the main areas of QqQ applications in biomedicine and assess the current level, evolution, and trends in the use of QqQ in these areas. Relevant data were extracted from the Scopus database using the specified terms and Boolean operators defined for each field of the QqQ application. We also discuss the recent advances in QqQ and QqQ-based analytical platforms, which promote the clinical application of these systems, and explain the indicated substantial increase in triple quadrupole use in biomedicine. The number of biomedical studies utilizing QqQ increased 2-3 times this decade. Triple quadrupole is most intensively used in the field of endocrine research and testing. On the contrary, the relative rate of immunoassay utilization-a major competitor of chromatography-mass spectrometry-decreased in this area as well as its use within Therapeutic drug monitoring (TDM) and forensic toxicology. Nowadays, the applications of high-resolution accurate mass (HRAM) mass spectrometers in the investigated areas represent only a small fraction of the total amount of research using mass spectrometry; however, their application substantially increased during the last decade in the untargeted search for new biomarkers.

From Division to Death: Metabolomic Analysis of Nicotiana tabacum BY-2 Cells Reveals the Complexity of Life in Batch Culture

Tobacco BY-2 cell culture is one of the most widely used models in plant biology. The main advantage of BY-2 suspension cultures is the synchronization of cell development and the appearance of polar elongation. In batch culture, BY-2 cells passed through the lag, proliferation, elongation, and stationary phases. During this process, the composition of the growth medium changed dramatically. Sucrose was rapidly eliminated; hexose first accumulated and then depleted. The medium's pH initially decreased and then rose with aging. As a result of the crosstalk between the internal and external stimuli, cells pass through complicated systemic rearrangements, which cause metabolomic alterations. The early stages were characterized by high levels of amino acids and sterols, which could be interpreted as the result of synthetic activity. The most intense rearrangements occurred between the proliferation and active elongation stages, including repression of amino acid accumulation and up-regulation of sugar metabolism. Later stages were distinguished by higher levels of secondary metabolites, which may be a non-specific response to deteriorating conditions. Senescence was followed by some increase in fatty acids and sterols as well as amino acids, and probably led to self-destructive processes. A correlation analysis revealed relationships between metabolites' covariation, their biochemical ratio, and the growth phase.

Metabolomics-based study on the significance of differential metabolite binding IgG isoforms in Hemolytic disease of newborn

BACKGROUND

Hemolytic disease of the newborn (HDN) is a common condition that can have a severe impact on the health of newborns due to the hemolytic reactions it triggers. Although numerous studies have focused on understanding the pathogenesis of HDN, there are still many unanswered questions.

METHODS

In this retrospective study, serum samples were collected from 15 healthy newborns and 8 infants diagnosed with hemolytic disease. The relationship between different metabolites and various IgG subtypes in Healthy, HDN and BLI groups was studied by biochemical technique and enzyme-linked immunosorbent assay (ELISA). Metabolomics analysis was conducted to identify the differential metabolites associated with HDN. Subsequently, Pearson's correlation analysis was used to determine the relation of these differential metabolites with IgG isoforms. The relationship between the metabolites and IgG subtypes was observed after treatment.

RESULTS

The study results revealed that infants with hemolytic disease exhibited abnormal elevations in TBA, IgG1, IgG2a, IgG2b, IgG3, and IgG4 levels when compared to healthy newborns. Additionally, differences in metabolite contents were also observed. N, N-DIMETHYLARGININE showed negative correlations with TBA, IgG1, IgG2a, IgG2b, IgG3, and IgG4, while 2-HYDROXYBUTYRATE, AMINOISOBUTANOATE, Inosine, and ALLYL ISOTHIOCYANATE exhibited positive correlations with TBA, IgG1, IgG2a, IgG2b, IgG3, and IgG4. Through metabolomics-based research, we have discovered associations between differential metabolites and different IgG isoforms during the onset of HDN.

CONCLUSION

These findings suggest that changes in metabolite and IgG isoform levels are linked to HDN. Understanding the involvement of IgG isoforms and metabolites can provide valuable guidance for the diagnosis and treatment of HDN.

Differential regulation of brain microvessel transcriptome and brain metabolome by western and heart-healthy dietary patterns in Ossabaw pigs

Diet is a potentially modifiable neurodegenerative disease risk factor. We studied the effects of a typical Western diet (WD; high in refined carbohydrates, cholesterol and saturated fat), relative to a heart-healthy diet (HHD; high in unrefined carbohydrates, polyunsaturated fat and fiber, and low in cholesterol) on brain microvessel transcriptomics and brain metabolomics of the temporal region in Ossabaw minipigs. Thirty-two pigs (16 male and 16 females) were fed a WD or HHD starting at the age of 4 months for a period of 6 months. The WD and HHD were isocaloric and had a similar macronutrient content but differed in macronutrient quality. Within each dietary group, half of the pigs also received atorvastatin. Relative to HHD-fed pigs, WD-fed pigs had 175 genes differentially expressed (fold change > 1.3, FDR < 0.05) by diet, 46 upregulated and 129 downregulated. Gene Set Enrichment Analysis identified 22 gene sets enriched in WD-fed pigs, comprising pathways related to inflammation, angiogenesis, and apoptosis, and 53 gene sets enriched in the HHD-fed pigs, including cell energetics, neurotransmission, and inflammation resolution pathways. Metabolite analysis showed enrichment in arginine, tyrosine, and lysine in WD-fed pigs, and ergothioneine and S-adenosyl methionine in HHD-fed pigs. Atorvastatin treatment did not affect gene expression. These results suggest a likely contribution of diet to brain pathologies characterized by neuroinflammation and neurodegeneration.

Advances and challenges in non-targeted analysis: An insight into sample preparation and detection by liquid chromatography-mass spectrometry

Unknown impurities, metabolites and harmful pollutants present in pharmaceutical products, biological and environmental samples, respectively are of high concern in terms of their detection and quantification. The targeted analysis aims to quantify known chemical entities, but it lacks the ability to identify unknown components present in a sample. Non-targeted analysis is an analytical approach that can be made applicable to various disciplines of science to effectively search for unknown chemical, biological, or environmental entities that can answer various baffling mysteries of research. It employs various high-end analytical techniques that can specifically screen out multiple unknown compounds from complex mixtures. Non-targeted analysis is also applicable for complex studies such as metabolomics to search unidentified metabolites of new chemical entities. This review critically discusses the current advancements in non-targeted analysis related to the analysis of pharmaceutical, biological, and environmental samples. Various steps like sample collection, handling, preparation, extraction, its analysis using advanced techniques like high-resolution mass spectrometry, liquid chromatography mass spectrometry, and lastly interpretation of the huge amounts of complex data obtained upon analysis of complex matrices have been discussed broadly in this article. Besides the advantages of non-targeted analysis over targeted analysis, limitations, bioinformatics tools, sources of error, and research gaps have been critically analyzed.

Metabolomic Profiling and Machine Learning Models for Tumor Classification in Patients with Recurrent IDH-Wild-Type Glioblastoma: A Prospective Study

BACKGROUND/OBJECTIVES

The recurrence of glioblastoma is an inevitable event in this disease's course. In this study, we sought to identify the metabolomic signature in patients with recurrent glioblastomas undergoing surgery and radiation therapy.

METHODS

Blood samples collected prospectively from six patients with recurrent IDH-wildtype glioblastoma who underwent one surgery at diagnosis and a second surgery at relapse were analyzed using untargeted gas chromatography-time-of-flight mass spectrometry to measure metabolite abundance. The data analysis techniques included univariate analysis, correlation analysis, and a sample t-test. For predictive modeling, machine learning (ML) algorithms such as multinomial logistic regression, gradient boosting, and random forest were applied to predict the classification of samples in the correct treatment phase.

RESULTS

Comparing samples after the first surgery and after the relapse surgeries to the pre-operative samples showed a significant decrease in sorbitol and mannitol; there was a significant increase in urea, oxoproline, glucose, and alanine. After chemoradiation, two metabolites, erythritol and 6-deoxyglucitol, showed a decrease, with a cut-off of three and a significant reduction for 6-deoxyglucitol, while 2,4-difluorotoluene and 9-myristoleate showed an increase post radiation, with a fold-change cut-off of three. The gradient-boosting ML model achieved a high performance for the prediction of tumor conditions in patients with glioblastoma who had undergone relapse surgery.

CONCLUSIONS

We developed an ML predictor for tumor phase based on the plasma metabolomic profile. Our study suggests the potential of combining metabolomics with ML as a new tool to stratify the risk of tumor progression in patients with glioblastoma.

Glycogen Supplementation in Vitro Promotes pH Decline in Dark-Cutting Beef by Reverting Muscle's Metabolome toward a Normal Postmortem Muscle State

Dysregulated muscle glycogen metabolism preslaughter contributes to aberrant postmortem muscle pH (>5.8) in dark-cutting beef phenotypes. However, the underlying mechanisms have remained elusive. Herein, we examine the glycogen dependent regulation of postmortem muscle pH decline and darkening in beef. We show that supplementation of glycogen in vitro restores postmortem pH decline in dark-cutting beef by reverting the metabolome toward a typical postmortem muscle state characterized by increased activities of enzymes glycogen phosphorylase and lactate dehydrogenase (p < 0.05) coupled with a pronounced abundance of glycolytic metabolites and reduced abundance of tricarboxylic acid cycle and amino acid metabolites. Furthermore, concurrent inhibition of mitochondrial respiration at complexes I, IV, and V with glycogen supplementation stimulates greater pH decline. Together, our findings show that supplementing glycogen at low concentrations (10 mM) can reprogram the dark-cutting beef muscle's metabolome toward typical postmortem state and promote muscle acidification. Thus, enhancing glycogen levels could represent a promising strategy for mitigating dark-cutting beef phenotypes and improving meat quality.

Enhanced lipid accumulation in microalgae Scenedesmus sp. under nitrogen limitation

Microalgae-based biofuel production is cost-effective only in a biorefinery, where valuable co-products offset high costs. Fatty acids produced by photosynthetic microalgae can serve as raw materials for bioenergy and pharmaceuticals. This study aims to understand the metabolic imprints of Scenedesmus sp. CABeR52, to decipher the physiological mechanisms behind lipid accumulation under nitrogen deprivation. Metabolomics profiles were generated using gas chromatography-mass spectrometry (GC-MS) of Scenedesmus sp. CABeR52 subjected to nutrient deprivation. Our initial data sets indicate that deprived cells have an increased accumulation of lipids (278.31 mg.g-1 dcw), 2.0 times higher than the control. The metabolomic profiling unveils a metabolic reprogramming, highlighting the upregulation of key metabolites involved in fatty acid biosynthesis, such as citric acid, succinic acid, and 2-ketoglutaric acid. The accumulation of trehalose, a stress-responsive metabolite, further underscores the microalga's adaptability. Interestingly, we found that a new fatty acid, nervonic acid, was identified in the complex, which has a significant role in brain development. These findings provide valuable insights into the metabolic pathways governing lipid accumulation in Scenedesmus sp., paving the way for its exploitation as a sustainable biofuel feedstock.

Multiplatform metabolomic interlaboratory study of a whole human stool candidate reference material from omnivore and vegan donors

INTRODUCTION

Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.

OBJECTIVES

This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.

METHODS

An interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR).

RESULTS

Different laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC-MS), 58% (GC-MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques.

CONCLUSION

This collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies.

Changes in SWEET-mediated sugar partitioning affect photosynthesis performance and plant response to drought

Sugars, produced through photosynthesis, are at the core of all organic compounds synthesized and used for plant growth and their response to environmental changes. Their production, transport, and utilization are highly regulated and integrated throughout the plant life cycle. The maintenance of sugar partitioning between the different subcellular compartments and between cells is important in adjusting the photosynthesis performance and response to abiotic constraints. We investigated the consequences of the disruption of four genes coding for SWEET sugar transporters in Arabidopsis (SWEET11, SWEET12, SWEET16, and SWEET17) on plant photosynthesis and the response to drought. Our results show that mutations in both SWEET11 and SWEET12 genes lead to an increase of cytosolic sugars in mesophyll cells and phloem parenchyma cells, which impacts several photosynthesis-related parameters. Further, our results suggest that in the swt11swt12 double mutant, the sucrose-induced feedback mechanism on stomatal closure is poorly efficient. On the other hand, changes in fructose partitioning in mesophyll and vascular cells, measured in the swt16swt17 double mutant, positively impact gas exchanges, probably through an increased starch synthesis together with higher vacuolar sugar storage. Finally, we propose that the impaired sugar partitioning, rather than the total amount of sugars observed in the quadruple mutant, is responsible for the enhanced sensitivity upon drought. This work highlights the importance of considering SWEET-mediated sugar partitioning rather than global sugar content in photosynthesis performance and plant response to drought. Such knowledge will pave the way to design new strategies to maintain plant productivity in a challenging environment.

Altered Metabolism in Knockdown Lines of Two HXXXD/BAHD Acyltransferases During Wound Healing in Potato Tubers

Suberin biosynthesis involves the coordinated regulation of both phenolic and aliphatic metabolisms. HXXXD/BAHD acyltransferases occupy a unique place in suberization, as they function to crosslink phenolic and aliphatic monomers during suberin assembly. To date, only one suberin-associated HXXXD/BAHD acyltransferase, StFHT, has been described in potatoes, whereas, in Arabidopsis, at least two are implicated in suberin biosynthesis. RNAseq data from wound-induced potato tubers undergoing suberization indicate that transcripts for 28 HXXXD/BAHD acyltransferase genes accumulate in response to wounding. In the present study, we generated RNAi knockdown lines for StFHT and another highly wound-induced HXXXD/BAHD acyltransferase, designated StHCT, and characterized their wound-induced suberin phenotype. StFHT-RNAi and StHCT-RNAi knockdown lines share the same aliphatic suberin phenotype of reduced esterified ferulic acid and ferulates, which is similar to the previously described StFHT-RNAi knockdown suberin phenotype. However, the phenolic suberin phenotype differed between the two knockdown genotypes, with StHCT-RNAi knockdown lines having proportionately more p-hydroxyphenyl-derived moieties than either StFHT-RNAi knockdown or empty vector control lines. Analysis of soluble polar metabolites revealed that StHCT catalyzes a step upstream from StFHT. Overall, our data support the involvement of more than one HXXXD/BAHD acyltransferase in potato suberin biosynthesis.

Pharmacometabolomics in Drug Disposition, Toxicity, and Precision Medicine

The precision medicine initiative has driven a substantial change in the way scientists and health care practitioners think about diagnosing and treating disease. While it has long been recognized that drug response is determined by the intersection of genetic, environmental, and disease factors, improvements in technology have afforded precision medicine guided dosing of drugs to improve efficacy and reduce toxicity. Pharmacometabolomics aims to evaluate small molecule metabolites in plasma and/or urine to help evaluate mechanisms that predict and/or reflect drug efficacy and toxicity. In this mini review, we provide an overview of pharmacometabolomic approaches and methodologies. Relevant examples where metabolomic techniques have been used to better understand drug efficacy and toxicity in major depressive disorder and cancer chemotherapy are discussed. In addition, the utility of metabolomics in drug development and understanding drug metabolism, transport, and pharmacokinetics is reviewed. Pharmacometabolomic approaches can help describe factors mediating drug disposition, efficacy, and toxicity. While important advancements in this area have been made, there remain several challenges that must be overcome before this approach can be fully implemented into clinical drug therapy. SIGNIFICANCE STATEMENT: Pharmacometabolomics has emerged as an approach to identify metabolites that allow for implementation of precision medicine approaches to pharmacotherapy. This review article provides an overview of pharmacometabolomics including highlights of important examples.

Enhancing gas chromatography-mass spectrometry resolution and pure analyte discovery using intra-chromatogram elution profile matching

Chemometric decomposition methods like multivariate curve resolution-alternating least squares (MCR-ALS) are often employed in gas chromatography-mass spectrometry (GC-MS) to improve analyte identification and quantitation. However, these methods can perform poorly for analytes with a low chromatographic resolution (Rs) and a high degree of spectral contamination from noise and background interferences. Thus, we propose a novel computational algorithm, termed mzCompare, to improve analyte identification and quantitation when coupled to MCR-ALS. The mzCompare method utilizes an underlying requirement that the retention time and peak shape between mass channels (m/z) of the same analyte should be similar. By discovering the selective m/z for a given analyte in a chromatogram, a pure elution profile can be generated and used as an equality constraint in MCR-ALS. The performance of the mzCompare methodology is demonstrated with both experimental and simulated chromatograms. Experimentally, unresolved analytes with a Rs as low as 0.05 could be confidently identified with mzCompare assisted MCR-ALS. Furthermore, application of the mzCompare algorithm to a complex aerospace fuel resulted in the discovery of 335 analytes, a 44 % increase compared to conventional peak detection methods. GC-MS simulations of target-interferent analyte pairs demonstrated that the performance of MCR-ALS deteriorated below a Rs of ∼0.25. However, mzCompare assisted MCR-ALS showed excellent identification and acceptable quantitative accuracy at a Rs of ∼0.02. These results show that the mzCompare algorithm can help analysts overcome modeling ambiguities resulting from the chemometric multiplex disadvantage.

Simultaneous multi-targeted forensic toxicological screening in biological matrices by MRM-IDA-EPI mode

The toxicologist ascertains drug assumptions in case of paediatric intoxications and death for overdose. The analytical approach consists of initially screening and consequently confirming drug positivity. We developed a toxicological screening method and validated its use comparing the results with a LC-MS/MS analysis. The method identifies 751 drugs and metabolites (704 in positive and 47 in negative mode). Chromatographic separation was achieved eluting mobile phase A (10 mM ammonium formate) and B (0.05% formic acid in methanol) in gradient on Kinetex Phenyl-Hexyl (50 × 4.6 mm, 2.6 μm) with 0.7 mL/min flow rate for 11 min. Multiple Reaction Monitoring (MRM) was adopted as survey scan and, after an Information-Dependent Analysis (IDA) (threshold of 30,000 for positive and 1000 cps for negative mode), the Enhanced Product Ion (scan range: 50-700 amu) was triggered. The MS/MS spectrum generated was compared with one of the libraries for identification. Data processing was optimised through creation of rules. Sample preparation, mainly consisting of deproteinization and enzymatic hydrolysis, was set up for different matrices (blood, urine, vitreous humor, synovial fluid, cadaveric tissues and larvae). Cut-off for most analytes resulted in the lowest concentration tested. When the results from the screening and LC-MS/MS analysis were compared, an optimal percentage of agreement (100%) was assessed for all matrices. Method applicability was evaluated on real paediatric intoxications and forensic cases. In conclusion, we proposed a multi-targeted, fast, sensitive and specific MRM-IDA-EPI screening having an extensive use in different toxicological fields.

A Proteogenomic Approach to Unveiling the Complex Biology of the Microbiome

The complex biology of the microbiome was elucidated once the genomics era began. The proteogenomic approach analyzes and integrates genetic makeup (genomics) and microbial communities' expressed proteins (proteomics). Therefore, researchers gained insights into gene expression, protein functions, and metabolic pathways, understanding microbial dynamics and behavior, interactions with host cells, and responses to environmental stimuli. In this context, our work aims to bring together data regarding the application of genomics, proteomics, and bioinformatics in microbiome research and to provide new perspectives for applying microbiota modulation in clinical practice with maximum efficiency. This review also synthesizes data from the literature, shedding light on the potential biomarkers and therapeutic targets for various diseases influenced by the microbiome.

Linoleic Acid Induces Metabolic Reprogramming and Inhibits Oxidative and Inflammatory Effects in Keratinocytes Exposed to UVB Radiation

Linoleic acid (LA), the primary ω-6 polyunsaturated fatty acid (PUFA) found in the epidermis, plays a crucial role in preserving the integrity of the skin's water permeability barrier. Additionally, vegetable oils rich in LA have been shown to notably mitigate ultraviolet (UV) radiation-induced effects, including the production of reactive oxygen species (ROS), cellular damage, and skin photoaging. These beneficial effects are primarily ascribed to the LA in these oils. Nonetheless, the precise mechanisms through which LA confers protection against damage induced by exposure to UVB radiation remain unclear. This study aimed to examine whether LA can restore redox and metabolic equilibria and to assess its influence on the inflammatory response triggered by UVB radiation in keratinocytes. Flow cytometry analysis unveiled the capacity of LA to diminish UVB-induced ROS levels in HaCaT cells. GC/MS-based metabolomics highlighted significant metabolic changes, especially in carbohydrate, amino acid, and glutathione (GSH) metabolism, with LA restoring depleted GSH levels post-UVB exposure. LA also upregulated PI3K/Akt-dependent GCLC and GSS expression while downregulating COX-2 expression. These results suggest that LA induces metabolic reprogramming, protecting against UVB-induced oxidative damage by enhancing GSH biosynthesis via PI3K/Akt signaling. Moreover, it suppresses UVB-induced COX-2 expression in HaCaT cells, making LA treatment a promising strategy against UVB-induced oxidative and inflammatory damage.

Automated Mixture Analysis via Structural Evaluation

The determination of chemical mixture components is vital to a multitude of scientific fields. Oftentimes spectroscopic methods are employed to decipher the composition of these mixtures. However, the sheer density of spectral features present in spectroscopic databases can make unambiguous assignment to individual species challenging. Yet, components of a mixture are commonly chemically related due to environmental processes or shared precursor molecules. Therefore, analysis of the chemical relevance of a molecule is important when determining which species are present in a mixture. In this paper, we combine machine-learning molecular embedding methods with a graph-based ranking system to determine the likelihood of a molecule being present in a mixture based on the other known species and/or chemical priors. By incorporating this metric in a rotational spectroscopy mixture analysis algorithm, we demonstrate that the mixture components can be identified with extremely high accuracy (≥97%) in an efficient manner.

Insecticide-Induced Metabolic Dysregulation in Model Microbe E. coli Discovered by Comprehensive Metabolic Profiling

Fipronil, malathion, and permethrin are widely used insecticides in agriculture, public areas, and residential spaces. The globally abused application of these chemicals results in residues surpassing established maximum residue levels, giving rise to potential toxicity in unintended organisms. Long-term exposure and the persistent accumulation of these insecticides in animals and humans pose threats such as neurotoxicity, liver and kidney damage, and microbiota dysbiosis. Despite the known risks, the specific impact of these insecticides on gut microbiota and their metabolic processes, as well as the subsequent effects on host health, remain largely unknown. This study aimed to address this gap by utilizing nonpathogenic Escherichia coli as a representative of human gut bacteria and examining its growth and metabolic perturbations induced by exposure to fipronil, malathion, and permethrin. Our research showed that exposure of E. coli to fipronil, malathion, and permethrin at physiologically relevant concentrations resulted in significant growth inhibition. Furthermore, we have observed the biodegradation of fipronil and permethrin by E. coli, while no biodegradation was found for malathion. Thus, E. coli is capable of degrading fipronil and permethrin, thereby enabling the removal of those substances. Next, we studied how insecticides affect bacterial metabolism to understand their influence on the functions of the microbes. Our metabolomics analysis revealed chemical-dependent alterations in metabolic profiles and metabolite compositions following insecticide exposure. These changes encompassed shifts in carboxylic acids and derivatives, organooxygen compounds, as well as indoles and their derivatives. To gain a deeper insight into the systematic changes induced by these insecticides, we conducted a metabolic pathway analysis. Our data indicated that fipronil, compared with malathion and permethrin, exhibited opposite regulation in glycine, serine, and threonine metabolism and valine, leucine, and isoleucine biosynthesis. In summary, our study demonstrates the capability of E. coli to degrade fipronil and permethrin, leading to their removal, while malathion remains unaffected. Additionally, we reveal chemical-dependent alterations in bacterial metabolism induced by insecticide exposure, with specific impacts on metabolic pathways, particularly in pathways related to amino acid metabolism.