Significant Metabolic Alterations Research Articles

Ion suppression correction and normalization for non-targeted metabolomics.

Ion suppression is a major problem in mass spectrometry (MS)-based metabolomics; it can dramatically decrease measurement accuracy, precision, and sensitivity. Here we report a method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) library plus companion algorithms to: 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. We evaluate the method across ion chromatography (IC), hydrophilic interaction liquid chromatography (HILIC), and reversed-phase liquid chromatography (RPLC)-MS systems in both positive and negative ionization modes, with clean and unclean ion sources, and across different biological matrices. Across the broad range of conditions tested, all detected metabolites exhibit ion suppression ranging from 1% to >90% and coefficients of variation ranging from 1% to 20%, but the Workflow and companion algorithms are highly effective at nulling out that suppression and error. To demonstrate a routine application of the Workflow, we employ the Workflow to study ovarian cancer cell response to the enzyme-drug L-asparaginase (ASNase). The IROA-normalized data reveal significant alterations in peptide metabolism, which have not been reported previously. Overall, the Workflow corrects ion suppression across diverse analytical conditions and produces robust normalization of non-targeted metabolomic data.

Cuproptosis-Inducing Functional Nanocomposites for Enhanced and Synergistic Cancer Radiotherapy.

Radiotherapy is crucial in local cancer management and needs advancements. Tumor cells elevate intracellular copper levels to promote growth and resist radiation; thus, targeted copper delivery to mitochondria could enhance radiotherapy by inducing cuproptosis in tumor cells. In this study, we engineered a multifunctional nanoliposome complex, termed Lipo-Ele@CuO2, which encapsulates both copper peroxide (CuO2) and the copper chelator elesclomol, which can delivery Cu ions to the mitochondria. The Lipo-Ele@CuO2 complex induces mitochondria-mediated cuproptosis in tumor cells and synergistically enhances the efficacy of radiotherapy. CuO2 acts as a copper donor and exhibits inherent sensitivity to acidic environments. Additionally, it depletes intracellular glutathione, thereby sensitizing cells to cuproptosis. Leveraging its pH-responsive properties in the acidic tumor microenvironment, the Lipo-Ele@CuO2 facilitate the controlled release of elesclomol, efficiently delivering copper ions to mitochondria at tumor sites. The combined in vitro and in vivo studies demonstrate that Lipo-Ele@CuO2-based therapy significantly improves antitumor efficacy and exhibits excellent safety profiles, effectively inducing cuproptosis in tumor cells and boosting the effectiveness of radiotherapy. Furthermore, metabolomic and transcriptomic analyses reveal that this combination therapy precipitates significant alterations in tumor energy metabolism, notably repressing genes related to iron-sulfur cluster assembly and glycolysis, thereby confirming the induction of cuproptosis. This therapeutic strategy provides a viable approach for addressing clinical radiotherapy resistance and demonstrates significant translational potential.

Metabolomics in Pathogenic Pathways and Targeted Therapies for Diabetic Neuropathy: A Comprehensive Review

Introduction and objective: This literature review aims to provide an overview of the progress in metabolomic assessment in animal and cell models and in humans with diabetic neuropathy (DN). Methods: Metabolomics has emerged as an important approach for investigating, identifying, and describing biomarkers related to DN. None has yet been validated for use in clinical practice. Results: DN induced significant alterations in energy metabolism and carbohydrates, lipids, amino acids, peptides, and proteins. Several treatments for DN, evaluated using metabolomics, were proved to have promising results. Conclusions: The ideal metabolite or set of metabolites that could be used as biomarkers should identify patients with diabetes prone to develop DN or those prone to progress to severe forms of sensory loss, associated with risk of ulcerations and amputation. Another potential use of a metabolite might be as an indicator of treatment response in clinical trials using agents with potential disease-modifying properties.

First-trimester metabolic profiling of gestational diabetes mellitus: insights into early-onset and late-onset cases compared with healthy controls.

Gestational diabetes mellitus (GDM) is a global health concern with significant short and long-term complications for both mother and baby. Early prediction of GDM, particularly late-onset, is crucial for implementing timely interventions to mitigate adverse outcomes. In this study, we conducted a comprehensive metabolomic analysis to explore potential biomarkers for early GDM prediction. Plasma samples were collected during the first trimester from 60 women: 20 with early-onset GDM, 20 with late-onset GDM, and 20 with normal glucose tolerance. Using advanced analytical techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS), we profiled over 150 lipid species and central carbon metabolism intermediates. Significant metabolic alterations were observed in both early- and late-onset GDM groups compared to healthy controls, with a specific focus on glycerolipids, fatty acids, and glucose metabolism. Key findings revealed a 4.0-fold increase in TG(44:0), TG(46:0), TG(46:1) with p-values <0.001 and TG(46:2) with 4.7-fold increase and p-value <0.0001 as well as changes in several phospholipids as PC(38:3), PC(40:4) with 1.4-fold increase, p < 0.001 and PE(34:1), PE(34:2) and PE(36:2) with 1.5-fold change, p < 0.001 in late-onset GDM. Observed lipid changes highlight disruptions in energy metabolism and inflammatory pathways. It is suggested that lipid profiles with distinct fatty acid chain lengths and degrees of unsaturation can serve as early biomarkers of GDM risk. These findings underline the importance of integrating metabolomic insights with clinical data to develop predictive models for GDM. Such models could enable early risk stratification, allowing for timely dietary, lifestyle, or medical interventions aimed at optimizing glucose regulation and preventing complications such as preeclampsia, macrosomia, and neonatal metabolic disorders. By focusing on metabolic disruptions evident in the first trimester, this approach addresses a critical window for improving maternal and fetal outcomes. Our study demonstrates the value of metabolomics in understanding the metabolic perturbations associated with GDM. Future research is needed to validate these biomarkers in larger cohorts and assess their integration into clinical workflows for personalized pregnancy care.

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detection of cyanotic CHD (CCHD) can have disastrous consequences. We therefore sought to use a Precision Fetal Cardiology based approach combining metabolomic profiling of maternal saliva and machine learning, a major branch of artificial intelligence (AI), for the prenatal detection of isolated, non-syndromic cyanotic CHD. Metabolomic analyses using Ultra-High Performance Liquid Chromatography/Mass Spectrometry identified 468 metabolites in the saliva. Six different AI platforms were utilized for the detection of CCHD and CHD overall. AI achieved excellent accuracy for the CCHD detection: Area Under the ROC curve: AUC (95% CI) = 0.819 (0.635-1.00) with a sensitivity and specificity of 92.5% and 87.0%, and for CHD overall: AUC (95% CI) = 0.828 (0.635-1.00) with a sensitivity of 90.5% and specificity of 88.0%. Similarly high accuracies were achieved for the detection of CHD overall: AUC (95% CI) = 0.8488 (0.635-1.00) with a sensitivity of 92.5% and specificity of 91.0%. Pathway analysis showed significant alterations in Arachidonic Acid, Alpha-linoleic acid, and Tryptophan metabolism indicating significant lipid dysfunction in cyanotic CHD. In summary, we report for the first time, the accurate detection of non-syndromic cyanotic CHD using maternal salivary metabolomics. Further, analysis revealed significant alteration of lipid metabolism.

Exploring metabolic reprogramming in esophageal cancer: the role of key enzymes in glucose, amino acid, and nucleotide pathways and targeted therapies.

Esophageal cancer (EC) is one of the most common malignancies worldwide with the character of poor prognosis and high mortality. Despite significant advancements have been achieved in elucidating the molecular mechanisms of EC, for example, in the discovery of new biomarkers and metabolic pathways, effective treatment options for patients with advanced EC are still limited. Metabolic heterogeneity in EC is a critical factor contributing to poor clinical outcomes. This heterogeneity arises from the complex interplay between the tumor microenvironment and genetic factors of tumor cells, which drives significant metabolic alterations in EC, a process known as metabolic reprogramming. Understanding the mechanisms of metabolic reprogramming is essential for developing new antitumor therapies and improving treatment outcomes. Targeting the distinct metabolic alterations in EC could enable more precise and effective therapies. In this review, we explore the complex metabolic changes in glucose, amino acid, and nucleotide metabolism during the progression of EC, and how these changes drive unique nutritional demands in cancer cells. We also evaluate potential therapies targeting key metabolic enzymes and their clinical applicability. Our work will contribute to enhancing knowledge of metabolic reprogramming in EC and provide new insights and approaches for the clinical treatment of EC.

Enalomics: A Mass Spectrometry-Based Approach for Profiling, Identifying, and Semiquantifying Enals in Biological Samples.

Human cells generate a bulk of aldehydes during lipid peroxidation (LPO), influencing critical cellular processes, such as oxidative stress, protein modification, and DNA damage. Enals, highly reactive α,β-unsaturated aldehydic metabolites, are implicated in various human pathologies, especially neurodegenerative disorders, cancer, and cardiovascular diseases. Despite their importance, endogenous enals remain poorly characterized, primarily due to their instability and low abundance. Herein, we introduced "enalomics," a mass spectrometry (MS)-based approach for profiling, identifying, and semiquantifying enals in biological samples. Derivatization with 2,4-dinitrophenylhydrazine and treatment with ascorbic acid stabilized enals in biological matrices and provided a unique MS fragment ([M-H-47]-) for reliable enal identification. Utilizing precursor ion scanning, dynamic multiple reaction monitoring, high-resolution MS, and mathematical correlations between retention times and carbon numbers of enals, we identified 157 enals (127 newly reported) with tissue-specific profiles in rats and 29 enals (24 newly reported) in human plasma. To the best of our knowledge, this represents the comprehensive analysis of enals, i.e., "enalomics," in biological samples. Enalomics demonstrated significant alterations in enal metabolism in rats with myocardial injury, highlighting the potential of medium- and short-chain plasma enals as sensitive diagnostic biomarkers. Further application of enalomics in patients with myocardial infarction (MI) identified 14 plasma diagnostic biomarkers. Receiver operating characteristic curves showed good discrimination (area under curve ≥ 0.8603, p ≤ 0.0043). This research advances the understanding of LPO products and emphasizes the roles of enals in human diseases, offering good prospects for early screening, diagnosis, and clinical interventions targeting LPO products in MI patients.

Developmental and molecular effects of pure-tone sine wave exposure on early zebrafish embryo development: Implications for reproductive health.

Noise pollution has become a significant concern for human health, yet its effects on early embryonic development remain underexplored. Specifically, data on the impact of sine wave noise on newly fertilized embryos is limited. This study aimed to address this gap by using zebrafish embryos at the 1-cell stage as a model to assess the toxicity of sine waves, following OECD Test No. 236. We exposed embryos to sound levels of 90 decibels (dB) and above, observing increased deformity rates, delayed development, and reductions in body length, heart rate and brain size. To elucidate the molecular mechanisms underlying these effects, we employed transcriptomics, metabolomics, and epigenomics (m6A-MeRIP-seq). KEGG enrichment analysis revealed significant alterations in arachidonic acid metabolism, axon guidance, and ubiquitin-mediated proteolysis. In conclusion, our findings demonstrate that high levels of sine wave noise adversely affect early embryo development. These results provide crucial insights for developing strategies to mitigate noise pollution and protect early developmental stages.

Interrelationship between altered metabolites and the gut microbiota in people living with HIV with different immune responses to antiretroviral therapy.

Antiretroviral therapy (ART) effectively reduces opportunistic infections and mortality in people living with HIV (PLWH); however, some patients exhibit poor immune recovery. This study explores the connections among immune responses, metabolites, and the gut microbiota in PLWH with differing reactions to ART. We analyzed the gut microbiota composition, metabolites, and immune markers in 38 PLWH who showed an immunological response (IR) and 32 who did not (INR), as classified according to CD4+ T-cell levels after 24 months of ART. Additionally, in vitro assays using cell counting kit 8, flow cytometry, and quantitative real-time reverse transcription PCR were employed to assess the effects of the metabolites on cell viability, immune marker expression, and cytokine levels. Gut microbiota and metabolic profiles differed significantly between the IR and INR groups. Enterococcus was more abundant in the INR group, whereas [Ruminococcus]_gnavus_group levels were reduced. Significant metabolic pathway alterations included decreased folate biosynthesis and biotin metabolism. We observed negative associations of Parabacteroides with activation markers on CD4+ T-cells, and positive correlations with CD4/CD8 ratios. Enterococcus showed inverse relationships with these markers. Indole-3-acetyl-beta-1-D-glucoside (area under the curve value = 0.8931), had the best discriminatory ability. Further experiments showed that Indole-3-acetyl-beta-1-D-glucoside significantly decreased the proportions of CD4+CD57+, effector CD4+, CD4+PD1+, CD8+CD57+, effector CD8+, and CD8+HLA-DR+ T cells. Moreover, mRNA expression analysis showed that Indole-3-acetyl-beta-1-D-glucoside treatment led to a suppression of pro-inflammatory cytokines. The multi-omics approach highlighted potential biomarkers for immune recovery in HIV, suggesting avenues for further research into treatment strategies.

Saliva Proteome, Metabolome and Microbiome Signatures for Detection of Alzheimer's Disease.

Background: As the burden of Alzheimer's disease (AD) escalates with an ageing population, the demand for early and accessible diagnostic methods becomes increasingly urgent. Saliva, with its non-invasive and cost-effective nature, presents a promising alternative to cerebrospinal fluid and plasma for biomarker discovery. Methods: In this study, we conducted a comprehensive multi-omics analysis of saliva samples (n = 20 mild cognitive impairment (MCI), n = 20 Alzheimer's disease and age- and n = 40 gender-matched cognitively normal individuals), from the South Australian Neurodegenerative Disease (SAND) cohort, integrating proteomics, metabolomics, and microbiome data with plasma measurements, including pTau181. Results: Among the most promising findings, the protein Stratifin emerged as a top candidate, showing a strong negative correlation with plasma pTau181 (r = -0.49, p < 0.001) and achieving an AUC of 0.95 in distinguishing AD and MCI combined from controls. In the metabolomics analysis, 3-chlorotyrosine and L-tyrosine exhibited high correlations with disease severity progression, with AUCs of 0.93 and 0.96, respectively. Pathway analysis revealed significant alterations in vitamin B12 metabolism, with Transcobalamin-1 levels decreasing in saliva as AD progressed despite an increase in serum vitamin B12 levels (p = 0.008). Microbiome analysis identified shifts in bacterial composition, with a microbiome cluster containing species such as Lautropia mirabilis showing a significant decrease in abundance in MCI and AD samples. The overall findings were reinforced by weighted correlation network analysis, which identified key hubs and enriched pathways associated with AD. Conclusions: Collectively, these data highlight the potential of saliva as a powerful medium for early AD diagnosis, offering a practical solution for large-scale screening and monitoring.

Metabolic reprogramming in sepsis-associated acute kidney injury: insights from lipopolysaccharide-induced oxidative stress and amino acid dysregulation.

Sepsis-associated acute kidney injury (SA-AKI) stands out as a critical health issue due to its high mortality and morbidity rates. This study aimed to comprehensively investigate the biochemical and metabolic alterations induced by lipopolysaccharide (LPS) in human embryonic kidney cells (HEK-293) using an in vitro model. The study investigated the impact of LPS on HEK-293 cells by evaluating cytotoxicity using the MTT assay, analyzing apoptosis, cell cycle progression, and oxidative stress via flow cytometry, measuring TNF-α levels through ELISA, and assessing amino acid metabolism with LC-MS/MS. The findings demonstrated that LPS significantly reduced cell viability in a dose-dependent manner, increased apoptotic cell populations, induced DNA damage by arresting the cell cycle in the Sub-G1 phase, and activated oxidative stress pathways. Notably, elevated reactive oxygen species (ROS) production and increased secretion of the pro-inflammatory cytokine TNF-α highlighted LPS's inflammatory and cytotoxic effects. Furthermore, systematic analysis revealed LPS-induced disruptions in amino acid metabolism, including marked reductions in alanine, arginine, and aspartic acid levels. KEGG pathway analysis identified significant metabolic alterations in pathways such as the urea cycle, TCA cycle, and glutathione metabolism. Interestingly, elevated citrulline levels suggested a potential adaptive mechanism to counteract LPS-induced inflammation and oxidative stress. Additionally, ROC analysis identified cystine as a highly reliable biomarker, with an AUC value of 1.00, emphasizing its critical role in metabolic reprogramming associated with SA-AKI. This study provides critical insights into the molecular pathophysiology of SA-AKI and emphasizes the promise of metabolomic approaches in the early diagnosis of sepsis-related complications and the development of targeted therapies.

Palmitoylethanolamide in Postmenopausal Metabolic Syndrome: Current Evidence and Clinical Perspectives.

Menopause leads to a decline in estrogen levels, resulting in significant metabolic alterations that increase the risk of developing metabolic syndrome-a cluster of conditions including central obesity, insulin resistance, dyslipidemia, and hypertension. Traditional interventions such as hormone replacement therapy carry potential adverse effects, and lifestyle modifications alone may not suffice for all women. This review explores the potential role of palmitoylethanolamide (PEA), an endogenous fatty acid amide, in managing metabolic syndrome during the postmenopausal period. PEA primarily acts by activating peroxisome proliferator-activated receptor-alpha (PPAR-α), influencing lipid metabolism, energy homeostasis, and inflammation. Evidence indicates that PEA may promote the browning of white adipocytes, enhancing energy expenditure and reducing adiposity. It also improves lipid profiles by boosting fatty acid oxidation and decreasing lipid synthesis, potentially lowering low-density lipoprotein cholesterol and triglyceride levels while increasing high-density lipoprotein cholesterol. Additionally, the anti-inflammatory properties of PEA enhance insulin sensitivity by reducing pro-inflammatory cytokines that interfere with insulin signaling. PEA may aid in weight management by influencing appetite regulation and improving leptin sensitivity. Furthermore, its neuroprotective effects may address the mood disturbances and cognitive decline associated with menopause. Given these multifaceted biological activities and a favorable safety profile, PEA may represent a promising non-pharmacological supplement for managing metabolic syndrome in postmenopausal women. However, further large-scale clinical studies are necessary to establish its efficacy, optimal dosing, and long-term safety. If validated, PEA could become an integral part of strategies to improve metabolic and neuropsychological health outcomes in this population.

Tear Fluid-Based Metabolomics Profiling in Chronic Dacryocystitis Patients.

Chronic dacryocystitis (CD) can result in severe complications and vision impairment due to ongoing microbial infections and persistent tearing. Tear fluid, which contains essential components vital for maintaining ocular surface health, has been investigated for its potential in the noninvasive identification of ocular biomarkers through metabolomics analysis. In this study, we employed UHPLC-MS/MS to analyze the tear metabolome of CD patients. UHPLC-MS/MS analysis of tear samples from CD patients revealed significant metabolic alterations. Compared with the control group, 298 metabolites were elevated, while 142 were decreased. KEGG pathway analysis suggested that these changes primarily affected arginine and proline metabolism, biosynthesis of amino acids, and phenylalanine biosynthesis in CD. Notably, 3-dehydroquinic acid, anthranilic acid, citric acid, and l-isoleucine emerged as potential biomarker candidates of CD with high diagnostic accuracy (AUC = 0.94). These findings suggest that tear fluid metabolism, particularly amino acid biosynthesis, plays a significant role in the pathogenesis of CD. Uncovering these metabolic products and pathways provides valuable insights into the mechanisms underlying CD and paves the way for the development of diagnostic tools and targeted therapies.

Polyanhydride Copolymer-Based Niclosamide Nanoparticles for Inhibiting Triple-Negative Breast Cancer: Metabolic Responses and Synergism with Paclitaxel.

The heterogeneity of tumors and the lack of effective therapies have resulted in triple-negative breast cancer (TNBC) exhibiting the least favorable outcomes among breast cancer subtypes. TNBC is characterized by its aggressive nature, often leading to high rates of relapse, metastasis, and mortality. Niclosamide (Nic), an Food and Drug Administration-approved anthelmintic drug, has been repurposed for cancer treatment; however, its application for TNBC is hindered by significant challenges, including strong hydrophobicity, poor aqueous solubility, and low bioavailability. This study aimed to develop Nic nanoparticles (Nic NPs) using biodegradable and biocompatible polyanhydride copolymers to enhance Nic's bioavailability and therapeutic efficacy. Nic NPs effectively inhibited migration, proliferation, and clonogenicity in both murine and human TNBC cells, inducing apoptosis and suppressing STAT3 signaling. For the first time, we utilized Raman spectroscopy and Seahorse extracellular flux assays to demonstrate the metabolic responses of TNBC cells to Nic NPs, revealing significant metabolic alterations, including the inhibition of mitochondrial respiration and glycolysis. Additionally, this study is the first to explore the combination therapy of repurposed Nic with the approved chemotherapeutic agent paclitaxel in the 4T1 TNBC immunocompetent mouse model. The combination of Nic NPs and paclitaxel significantly reduced tumor growth without adversely affecting the body weight of tumor-bearing mice. In summary, these findings suggest that Nic NPs could serve as a promising component in combination therapies for the effective treatment of TNBC.

Proteomic analysis of effects of 1% atropine in myopia therapy in Guinea pigs.

Myopia is a significant global public health issue. Key interventions for managing myopia include atropine treatment, optical correction, and surgical methods. This study focused on evaluating alterations in retinal protein expression after atropine therapy for myopia. Guinea pigs were randomly divided into four groups: control (CON), monocular form-deprivation myopia (FDM), FDM with 2-week atropine treatment (FDM+ATR), and atropine-only treatment (ATR). After two weeks of FDM induction, the FDM group showed significant differences in refractive error and increased axial lengths. In comparing the retinas of myopic and normal eyes, 30 proteins were found to have increased expression, while 8 proteins showed decreased expression. Atropine-treated retinas exhibited 73 proteins with increased expression and 29 proteins with decreased expression compared to the normal eyes. A total of 11 regulated proteins overlapped between the FDM+ATR vs FDM and FDM vs CON groups. IPA analysis indicates significant alterations in amino acid metabolism, energy production, post-translational modification, small molecule biochemistry, and free radical scavenging. Our study identifies retinal protein changes in myopic guinea pigs and in guinea pigs treated with atropine after myopia. These proteins could serve as potential targets for atropine treatment of myopia.

MiR-155 mediated regulation of PKG1 and its implications on cell invasion, migration, and apoptosis in preeclampsia through NF-κB pathway

BackgroundPreeclampsia (PE) is a severe pregnancy complication characterized by complex molecular interactions. Understanding these interactions is crucial for developing effective therapeutic strategies.MethodsThis study applies a pharmacometabolomics approach to explore the roles of miR-155 and PKG1 in PE, focusing on the regulatory influence of the NF-κB signaling pathway. Blood metabolomic profiles were analyzed, and bioinformatics tools, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization were employed to determine the expression and function of miR-155 and PKG1. Cell invasion, migration, proliferation, and apoptosis assays were conducted to assess miR-155’s modulation of PKG1. Additionally, RT-qPCR and WB analysis elucidated NF-κB-mediated regulation mechanisms.ResultsOur findings indicate significant metabolic alterations associated with miR-155 modulation of PKG1, with NF-κB acting as a critical upstream regulator. The study demonstrates that miR-155 affects cellular functions such as invasion, migration, proliferation, and apoptosis through PKG1 modulation. Furthermore, the NF-κB signaling pathway regulates miR-155 expression, contributing to the pathological processes of PE.ConclusionThis study provides a proof of concept for using pharmacometabolomics to understand the molecular mechanisms of PE, suggesting new therapeutic targets and advancing personalized medicine approaches. These insights highlight the potential of pharmacometabolomics to complement genomic and transcriptional data in disease characterization and treatment strategies, offering new avenues for therapeutic intervention in PE.

Preliminary exploration of the mechanisms underlying morphology engineering of Monascus purpureus during submerged fermentation via multi-omics approaches

Herein, multi-omics approaches were employed to investigate the relationship between mycelia morphology and biosynthesis of Monascus pigments (MPs) during submerged fermentation of Monascus purpureus. Through heavy ion beam irradiation, eleven mutants with diverse mycelial morphologies and MPs productions were generated. Genome resequencing analysis revealed that the autologous genes of these mutants were primarily enriched in pathways associated with histone ubiquitination and methylation. Among them, M. purpureus ZS exhibited a 2.49-fold increase in MPs production and distinct mycelia morphology compared to the parent strain, thus it was selected for transcriptomic and metabolomic analyses. The results revealed showed significant alterations in lysine metabolism, lipid metabolism, as well as cell wall and membrane components. Additionally, upregulated CoA biosynthesis along with type I polyketide structures and the genetic cluster responsible for MPs biosynthesis facilitated accumulation of MPs. These findings provide a theoretical foundation for morphological engineering of Monascus while offering novel strategies to achieve higher levels of MPs production during submerged fermentation.

Mapping Pesticide-Induced Metabolic Alterations in Human Gut Bacteria.

Pesticides can modulate gut microbiota (GM) composition, but their specific effects on GM remain largely elusive. Our study demonstrated that pesticides inhibit or promote growth in various GM species, even at low concentrations, and can accumulate in GM to prolong their presence in the host. Meanwhile, the pesticide induced changes in GM composition are associated with significant alterations in gut bacterial metabolism that reflected by the changes of hundreds of metabolites. We generated a pesticide-GM-metabolites (PMM) network that not only reveals pesticide-sensitive gut bacteria species but also report specific metabolic changes in 306 pesticide-GM pairs (PGPs). Using an in vivo mice model, we further demonstrated a PGP's interactions and verified the inflammation-inducing effects of pesticides on the host through dysregulated lipid metabolism of microbes. Taken together, our findings generate a PMM interactions atlas, and shed light on the molecular level of how pesticides impact host health by modulating GM metabolism.

Metabolomic Insights into COVID-19 Severity: A Scoping Review.

In 2019, SARS-CoV-2, the novel coronavirus, entered the world scene, presenting a global health crisis with a broad spectrum of clinical manifestations. Recognizing the significance of metabolomics as the omics closest to symptomatology, it has become a useful tool for predicting clinical outcomes. Several metabolomic studies have indicated variations in the metabolome corresponding to different disease severities, highlighting the potential of metabolomics to unravel crucial insights into the pathophysiology of SARS-CoV-2 infection. The PRISMA guidelines were followed for this scoping review. Three major scientific databases were searched: PubMed, the Directory of Open Access Journals (DOAJ), and BioMed Central, from 2020 to 2024. Initially, 2938 articles were identified and vetted with specific inclusion and exclusion criteria. Of these, 42 articles were retrieved for analysis and summary. Metabolites were identified that were repeatedly noted to change with COVID-19 and its severity. Phenylalanine, glucose, and glutamic acid increased with severity, while tryptophan, proline, and glutamine decreased, highlighting their association with COVID-19 severity. Additionally, pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, and arginine biosynthesis were the most significantly impacted pathways in COVID-19 severity. COVID-19 severity is intricately linked to significant metabolic alterations that span amino acid metabolism, energy production, immune response modulation, and redox balance.

TMET-23. MASS SPECTROMETRY-BASED METABOLIC PROFILING AND IMAGING OF ASTROCYTE AND GLIOBLASTOMA INVASIVE MARGIN CELLS

Abstract Despite multimodal treatment, 90% of patients diagnosed with isocitrate dehydrogenase (IDH) wild-type glioblastoma experience tumour recurrence within 5 years. Poor prognosis is in considerable part attributed to the ability of cancer cells to infiltrate a healthy brain. We hypothesise that metabolic changes underpinning cellular crosstalk between astrocytes and glioblastoma cells isolated from the invasive margin within a physiologically representative in-vitro tumour microenvironment may reveal therapeutic targets to prevent or delay glioblastoma recurrence. This study used advanced analytical techniques to establish baseline metabolomic profiles for eGFP-tagged primary glioblastoma cells isolated from the invasive margin and healthy human cortical astrocytes. Liquid chromatography-mass spectrometry (LC-MS) enabled detailed analysis of biochemical pathways, and Atmospheric Pressure-Matrix Assisted Laser Desorption/Ionisation (AP-MALDI) imaging offered spatial localization of metabolites, critical for mapping their distribution within tumour microenvironments. Metabolites were extracted using a biphasic method (methanol:chloroform:water) for LC-MS analysis, and metabolic profiling was conducted using a ZIC-pHILIC column coupled with a Q-Exactive Orbitrap Mass Spectrometer. Additionally, AP-MALDI imaging facilitated the generation of high-resolution spatial distribution maps of selected metabolites, achieving a resolution of 10 µm. Both multivariate and univariate statistical analyses were applied to identify significant metabolic alterations. Metabolic profiling identified distinct pathways altered in glioblastoma cells compared to astrocytes, including alterations in aspartate, glycine and serine, and lipid metabolism. High-resolution imaging outlined the spatial distribution of metabolites involved in these pathways, revealing regions of metabolic heterogeneity. Furthermore, this methodology facilitated an expanded identification range of essential biomolecules, notably lipids and amino acids, thereby augmenting our understanding of their dynamic functions across diverse cellular contexts. By leveraging the complementary strengths of LC-MS and AP-MALDI imaging, this research enhances our understanding of spatial metabolite distribution in glioblastoma cells isolated from the invasive margin and suggests potential applications in patient tissue, offering a deeper exploration of disease mechanisms.