Cell Metabolomics Research Articles

Studies on the Changes of Fermentation Metabolites and the Protective Effect of Fermented Edible Grass on Stress Injury Induced by Acetaminophen in HepG2 Cells

In this study, gas chromatography-mass spectrometry (GC-MS) based untargeted metabolomics was used to describe the changes of metabolites in edible grass with Lactobacillus plantarum (Lp) fermentation durations of 0 and 7 days, and subsequently to investigate the protective effect of fermented edible grass on acetaminophen-induced stress injury in HepG2 cells. Results showed that 53 differential metabolites were identified, including 31 significantly increased and 22 significantly decreased metabolites in fermented edible grass. Fermented edible grass protected HepG2 cells against acetaminophen-induced stress injury, which profited from the reduction in lactate dehydrogenase (LDH) and malondialdehyde (MDA) levels and the enhancement in superoxide dismutase (SOD) activity. Cell metabolomics analysis revealed that a total of 13 intracellular and 20 extracellular differential metabolites were detected. Fermented edible grass could regulate multiple cell metabolic pathways to exhibit protective effects on HepG2 cells. These findings provided theoretical guidance for the formation and regulation of bioactive metabolites in fermented edible grass and preliminarily confirmed the protective effects of fermented edible grass on drug-induced liver damage.

Abstract C054: Topographical investigation of metabolites in excised squares (TIMES2): Mapping in vivo of metabolic heterogeneity in pancreatic tumors

Abstract Background: Pancreatic cancer is a lethal malignancy characterized by complex intratumoral metabolic reprogramming and intercellular nutrient sharing between cells in the tumor microenvironment (TME) that promote pancreatic cancer progression. However, this crosstalk, as well as regional variation in perfusion and oxygenation, can lead to metabolic heterogeneity that has not been appreciated by metabolomics of whole tumors. Here we quantify amino acids and tricarboxylic acid cycle (TCA) intermediates using a novel methodology that allows us to portray global tumor metabolite heterogeneity in a tumor. Methods: Human PaTu-8902 or murine HY19636 (from female KPC mice p48-Cre+, KRASLSL-G12D/+, Trp53lox/+) pancreatic cancer cell lines were orthotopically injected into pancreata of NCr nude mice (n=3) or C57BL/6 mice (n=2). Mice were euthanized after 3-5 weeks and tumors were harvested. Tumor slices were further sectioned into 1mm x 1mm x 1mm cubes using a custom-made multisectional slicing device and each cube location was recorded. Each cube was extracted using methanol, water, and chloroform with labelled amino acid standards, derivitized, and resolved using gas chromatography-mass spectrometry (DB-35MS column with Agilent 7890B gas chromatograph coupled to a single quadrupole 5977B mass spectrometer). 22 metabolites (15 amino acids, 5 TCA intermediates, lactate, and pyruvate) were identified by unique fragments and retention time compared to known standards. Peaks were picked using OpenChrom and analyzed using MATLAB. Data was analyzed using Graphpad Prism. Principal Component Analysis (PCA) was visualized using Python on a Jupyter notebook. Results: Both orthotopic human and murine pancreatic tumors demonstrated striking levels of intratumoral metabolite heterogeneity. Glycine, glutamine, and proline were the amino acids with the highest coefficient of variance, while leucine, isoleucine, and serine had the lowest coefficient of variance. α-ketoglutarate and succinate were the TCA intermediates with highest coefficient of variance. Lactate had the lowest coefficient of variance among all examined metabolites. Spatial mapping of each metabolite demonstrated distinct regions with varying abundance levels of metabolites. PCA demonstrated 75% of variance was carried by PC1 and 10% carried by PC2. Conclusions: This study reveals insights into the degree of intratumoral heterogeneity present in pancreatic tumors that illustrate the difficulty of in vivo metabolomics analysis and suggest that high-resolution (single cell) metabolomics techniques will be critical to study metabolism in the complex TME. Citation Format: Peter Yu, Robert Banh, Stephen Martis, Douglas Biancur, Albert Sohn, Elaine Lin, Keisuke Yamamoto, Benjamin Greenbaum, Alec Kimmelman. Topographical investigation of metabolites in excised squares (TIMES2): Mapping in vivo of metabolic heterogeneity in pancreatic tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C054.

Sucrose and Mannans Affect Arabidopsis Shoot Gravitropism at the Cell Wall Level.

Gravitropism is the plant organ bending in response to gravity. Gravitropism, phototropism and sufficient mechanical strength define the optimal position of young shoots for photosynthesis. Etiolated wild-type Arabidopsis seedlings grown horizontally in the presence of sucrose had a lot more upright hypocotyls than seedlings grown without sucrose. We studied the mechanism of this effect at the level of cell wall biomechanics and biochemistry. Sucrose strengthened the bases of hypocotyls and decreased the content of mannans in their cell walls. As sucrose is known to increase the gravitropic bending of hypocotyls, and mannans have recently been shown to interfere with this process, we examined if the effect of sucrose on shoot gravitropism could be partially mediated by mannans. We compared cell wall biomechanics and metabolomics of hypocotyls at the early steps of gravitropic bending in Col-0 plants grown with sucrose and mannan-deficient mutant seedlings. Sucrose and mannans affected gravitropic bending via different mechanisms. Sucrose exerted its effect through cell wall-loosening proteins, while mannans changed the walls' viscoelasticity. Our data highlight the complexity of shoot gravitropism control at the cell wall level.

Deciphering the metabolic heterogeneity of hematopoietic stem cells with single-cell resolution

Metabolic status is crucial for stem cell functions; however, the metabolic heterogeneity of endogenous stem cells has never been directly assessed. Here, we develop a platform for high-throughput single-cell metabolomics (hi-scMet) of hematopoietic stem cells (HSCs). By combining flow cytometric isolation and nanoparticle-enhanced laser desorption/ionization mass spectrometry, we routinely detected >100 features from single cells. We mapped the single-cell metabolomes of all hematopoietic cell populations and HSC subpopulations with different division times, detecting 33 features whose levels exhibited trending changes during HSC proliferation. We found progressive activation of the oxidative pentose phosphate pathway (OxiPPP) from dormant to active HSCs. Genetic or pharmacological interference with OxiPPP increased reactive oxygen species level in HSCs, reducing HSC self-renewal upon oxidative stress. Together, our work uncovers the metabolic dynamics during HSC proliferation, reveals a role of OxiPPP for HSC activation, and illustrates the utility of hi-scMet in dissecting metabolic heterogeneity of immunophenotypically defined cell populations.

Comprehensive assessment of per and polyfluoroalkyl substances (PFAS) contamination in groundwater of Kamrup, Assam, India: occurrence, health risks, and metabolomic insights.

Per-and polyfluoroalkyl substances (PFAS) are synthetic chemicals that are known for their environmental persistence and adverse health effects. This study comprehensively assessed PFAS contamination in the Kamrup region of Assam, India, focusing on its presence in groundwater and associated health risks. The analysis detected 12 PFAS in groundwater samples from both the Kamrup Metro and Rural regions. In Kamrup Rural, Perfluorohexanoic acid (PFHxA), perfluorononanoic acid (PFNA), and perfluorooctanesulfonic acid (PFOS) were prevalent, whereas in Kamrup Metro, PFNA and PFOS were dominant, based on detection frequencies. These findings are noteworthy, as they demonstrate the widespread presence of PFAS in groundwater, a vital source of drinking water in the region. The assessment of PFAS health risks in India involved hazard quotient calculations for different age groups. Perfluorobutanesulfonic acid (PFBS) posed the highest risk, ranking children > boys > men > girls > women. Overall, ∑PFAS had low hazard (HQ: 0.27-0.41). Further, this study assessed PFBS and PFOS toxicity in human kidney epithelial cell lines (HEK293T) cells, revealing that PFBS was more cytotoxic than PFOS. The study examined the metabolomics of HEK293T cells after PFBS exposure, revealing significant alterations in lipid metabolism, particularly glycerophospholipids, potentially affecting cellular function and health. These findings underscore the importance of monitoring PFAS contamination in drinking water sources, especially in regions such as Kamrup, where groundwater is a primary source. Our metabolomics results show significant health effects at the cellular level, raising concerns about the impact of PFAS exposure on human health. This study highlights PFAS contamination in Kamrup, Assam's groundwater and its health risks, providing valuable insights for policymakers and public health management.

Analysis of cellular response to drugs with a microfluidic single-cell platform based on hyperspectral imaging

BackgroundCellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics examination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co-culture with drugs, which are relatively complex and time-consuming. Moreover, these methods can only indicate the drug effectiveness on cell colony rather than single cells. Thus, to meet the requirements of personal precision medicine, the development of drug response analysis on the high resolution of single cell is demanded. ResultsTo provide precise result for drug response on single-cell level, a microfluidic platform coupled with the label-free hyperspectral imaging was developed. With the help of horizontal single-cell trapping sieves, hundreds of single cells were trapped independently in microfluidic channels for the purposes of real-time drug delivery and single-cell hyperspectral image recording. To significantly identify the cellular hyperspectral change after drug stimulation, the differenced single-cell spectrum was proposed. Compared with the deep learning classification method based on hyperspectral images, an optimal performance can be achieved by the classification strategy based on differenced spectra. And the cellular response to different reagents, for example, K+, Epidermal Growth Factor (EGF), and Gefitinib at different concentrations can be accurately characterized by the differenced single-cell spectra analysis. Significance and noveltyThe high-throughput, rapid analysis of cellular response to drugs at the single-cell level can be accurately performed by our platform. After systematically analyzing the materials and the structures of the single-cell microfluidic chip, the optimal single-cell trapping method was proposed to contribute to the further application of hyperspectral imaging on microfluidic single-cell analysis. And the hyperspectral characterization of single-cell with cancer drug stimulation proved the application potential of our method in personal cancer medication.

Integrated cell metabolomics and network pharmacology approach deciphers the anti-testosterone deficiency mechanisms of Bushen Zhuanggu Tang

Testicular dysfunction is distinguished by a deficiency in testosterone levels, which can be attributed to the occurrence of oxidative stress injury in Leydig cells. The empirical prescription known as Bushen Zhuanggu Tang, developed by a highly experienced traditional Chinese medicine practitioner with six decades of clinical expertize, aligns with the traditional Chinese medicine principle of "kidney governing bone". Researchers have demonstrated that the administration of BSZGT can effectively enhance testosterone production. The objective of this study is to investigate the potential anti-testicular dysfunction effects of BSZGT and elucidate its underlying mechanism in an in vitro setting. Specifically, the impact of oxidative stress induced by H2O2 on the activity and testosterone levels of Leydig cells (TM3) was examined. Furthermore, the utilization of UPLC-QE-Qrbitrap-MS enabled the identification of the involvement of BSZGT in various metabolic pathways, including arginine biosynthesis, amino acyl-tRNA biosynthesis, Alanine, aspartate and glutamine metabolism, and Citrate Cycle, through the modulation of 25 distinct metabolites. Additionally, a network pharmacological analysis was conducted to investigate the pivotal protein targets associated with the therapeutic effects of BSZGT. The findings demonstrate the identification of six key proteins (CYP19A1, CYP1B1, ALOX5, ARG1, XDH, and MPO) that play a significant role in augmenting testicular function through their involvement in the ovarian steroid production pathway. In summary, our study presents a comprehensive research methodology that combines cell metabonomics and network pharmacology to enhance the discovery of new therapeutic agents for TD.

Untargeted metabolomics reveals the regulatory effect of geniposidic acid on lipid accumulation in HepG2 cells and Caenorhabditis elegans and validation in hyperlipidemic hamsters

BackgroundGeniposidic acid (GPA) alleviates oxidative stress and inflammation in mice However, whether it can effectively regulate lipid accumulation and prevent hyperlipidemia requires further investigation. PurposeThis study combined the untargeted metabolomics of cells and a Caenorhabditis elegans model to evaluate the anti-hyperlipidemic potential of GPA by modulating oxidative stress and regulating lipid metabolism. A golden hamster model of hyperlipidemia was used to further validate the lipid-lowering effect and mechanism of action of GPA. MethodsChemical staining, immunofluorescence, and flow cytometry were performed to examine the effects of GPA on lipid accumulation and oxidative stress. Untargeted metabolomic analysis of cells and C. elegans was performed using ultra-performance liquid chromatography coupled with quadrupole electrostatic field Orbitrap high-resolution mass spectrometry (UPLC-Q-Orbitrap MS) to identify biomarkers altered by GPA action, analyze the affected metabolic pathways, and validate the mechanisms by which GPA regulates lipid metabolism and oxidative stress. A golden hamster model of hyperlipidemia was established to test the lipid-lowering effects of GPA. Body weight, biochemical markers, rate-limiting enzymes, and key proteins were assessed. Hematoxylin and eosin (H&E) and Oil Red O staining were performed. ResultsPhenotypic data showed that GPA decreased free fatty acid (FFA)-induced lipid buildup and high reactive oxygen species (ROS) levels, reversed the decrease in mitochondrial membrane potential (MMP), and increased the cellular reduced glutathione/oxidized glutathione disulfide (GSH/GSSG) ratio. GPA also reduces high glucose-induced lipid build-up and ROS production in C. elegans. Metabolomic analysis showed that GPA affected purine, lipid, and amino acid metabolism. Moreover, GPA inhibited xanthine oxidase (XOD), glutamate dehydrogenase (GLDH), fatty acid synthase (FAS), phosphorylation of P38 MAPK, and upregulated the expression of SIRT3 and CPT1A protein production to control lipid metabolism and produce antioxidant benefits in cells and golden hamsters. ConclusionCurrent evidence suggests that GPA can effectively regulate lipid metabolism and the oxidative stress response, and has the potential to prevent hyperlipidemia. This study also provided an effective method for evaluating the mechanism of action of GPA.

Comprehensive dissection of variation and accumulation of free amino acids in tea accessions.

Free amino acids (FAAs) positively determine the tea quality, notably theanine (Thea), endowing umami taste of tea infusion, which is the profoundly prevalent research in albino tea genetic resources. Therefore, 339 tea accessions were collected to study FAAs level for deciphering its variation and accumulation mechanism. Interestingly, alanine (Ala) and Thea which had the highest diversity index (H') value among three varieties of Camellia sinensis (L.) O. Kuntze were significantly higher than wild relatives (P < 0.05). The intraspecific arginine (Arg) and glutamine (Gln) contents in C. sinensis var. assamica were significantly lower than sinensis and pubilimba varieties. Moreover, the importance of interdependencies operating across FAAs and chlorophyll levels were highlighted via the cell ultrastructure, metabolomics, and transcriptome analysis. We then determined that the association between phytochrome interacting factor 1 (CsPIF1) identified by weighted gene co-expression network analysis (WGCNA) and Thea content. Intriguingly, transient knock-down CsPIF1 expression increased Thea content in tea plant, and the function verification of CsPIF1 in Arabidopsis also indicated that CsPIF1 acts as a negative regulator of Thea content by mainly effecting the genes expression related to Thea biosynthesis, transport, and hydrolysis, especially glutamate synthase (CsGOGAT), which was validated to be associated with Thea content with a nonsynonymous SNP by Kompetitive Allele-Specific PCR (KASP). We also investigated the interspecific and geographical distribution of this SNP. Taken together, these results help us to understand and clarify the variation and profile of major FAAs in tea germplasms and promote efficient utilization in tea genetic improvement and breeding.

Cell-type proteomic and metabolomic resolution of early and late grain filling stages of wheat endosperm.

The nutritional value of wheat grains, particularly their protein and metabolite composition, is a result of the grain-filling process, especially in the endosperm. Here, we employ laser microdissection (LMD) combined with shotgun proteomics and metabolomics to generate a cell type-specific proteome and metabolome inventory of developing wheat endosperm at the early (15 DAA) and late (26 DAA) grain-filling stages. We identified 1803 proteins and 41 metabolites from four different cell types (aleurone (AL), sub-aleurone (SA), starchy endosperm (SE) and endosperm transfer cells (ETCs). Differentially expressed proteins were detected, 67 in the AL, 31 in the SA, 27 in the SE and 50 in the ETCs between these two-time points. Cell-type accumulation of specific SUT and GLUT transporters, sucrose converting and starch biosynthesis enzymes correlate well with the respective sugar metabolites, suggesting sugar upload and starch accumulation via nucellar projection and ETC at 15 DAA in contrast to the later stage at 26 DAA. Changes in various protein levels between AL, SA and ETC support this metabolic switch from 15 to 26 DAA. The distinct spatial and temporal abundances of proteins and metabolites revealed a contrasting activity of nitrogen assimilation pathways, e.g. for GOGAT, GDH and glutamic acid, in the different cell types from 15 to 26 DAA, which can be correlated with specific protein accumulation in the endosperm. The integration of cell-type specific proteome and metabolome data revealed a complex metabolic interplay of the different cell types and a functional switch during grain development and grain-filling processes.

Information-Theoretic Analysis of a Model of CAR-4-1BB-Mediated NFκB Activation

Systems biology utilizes computational approaches to examine an array of biological processes, such as cell signaling, metabolomics and pharmacology. This includes mathematical modeling of CAR T cells, a modality of cancer therapy by which genetically engineered immune cells recognize and combat a cancerous target. While successful against hematologic malignancies, CAR T cells have shown limited success against other cancer types. Thus, more research is needed to understand their mechanisms of action and leverage their full potential. In our work, we set out to apply information theory on a mathematical model of NFκB signaling initiated by the CAR following antigen encounter. First, we estimated channel capacity for CAR-4-1BB-mediated NFκB signal transduction. Next, we evaluated the pathway’s ability to distinguish contrasting “low” and “high” antigen concentration levels, depending on the amount of variability in protein concentrations. Finally, we assessed the fidelity by which NFκB activation reflects the encountered antigen concentration, depending on the prevalence of antigen-positive targets in tumor population. We found that in most scenarios, fold change in the nuclear concentration of NFκB carries a higher channel capacity for the pathway than NFκB’s absolute response. Additionally, we found that most errors in transducing the antigen signal through the pathway skew towards underestimating the concentration of encountered antigen. Finally, we found that disabling IKKβ deactivation could increase signaling fidelity against targets with antigen-negative cells. Our information-theoretic analysis of signal transduction can provide novel perspectives on biological signaling, as well as enable a more informed path to cell engineering.

Integrated network pharmacology and metabolomics reveal the action mechanisms of vincristine combined with celastrol against colon cancer

Colon cancer is associated with a high mortality rate. Vincristine (VCR) is a commonly used chemotherapeutic drug. Celastrol (CEL) is an effective component which exerts inhibitory effects on colon cancer. Combination treatment improves resistance to chemotherapeutic drugs and enhances their efficacy. Therefore, we aimed to explore the molecular mechanisms of VCR combined with CEL in colon cancer treatment. We verified the effects of VCR combined with CEL on the proliferation, cell cycle, and apoptosis of HCT-8 cells. Non-targeted metabolomic techniques were used to analyse the changes in cellular metabolites after administration. Finally, network pharmacology technology was used to screen the potential targets and pathways. VCR combined with CEL had synergistic inhibitory effects on HCT-8 colon cancer cells. Cell metabolomics identified 12 metabolites enriched in metabolic pathways, such as the phenylalanine, tyrosine and tryptophan biosynthesis pathways. Network pharmacology revealed that MAPK1, AKT1, PIK3CB, EGFR, and VEGFA were the key targets. Western blotting revealed that VCR combined with CEL activated the P53 pathway by suppressing the PI3K/AKT signalling pathway activation and Bcl-2 expression, promoting the Bax expression. Therefore, VCR combined with CEL potentially treats colon cancer by increasing the apoptosis, improving energy metabolism, and inhibiting PI3K/AKT pathway in colon cancer cells.

AML Drug Tolerant Persister (DTP) Cells Survive Chemotherapy By Transiently Altering Cellular Lipidomics to Increase Plasma Membrane Rigidity, but Also Increases Sensitivity to Immune Cell Killing

Emerging evidence indicates that cancer persister cells, including AML, stochastically and transiently upregulate stress pathways to survive acute exposure to chemotherapy. Here, we explore the biology of these persister cells and identify a T cell-based immunotherapy that targets this surviving fraction. To investigate the drug-tolerant persister (DTP) state, we established a model of DTP AML cells. AML cell lines (MOLM13, OCI-AML2, OCI-AML3, MV4-11, THP1 and NB4) were treated with a combination of Daunorubicin and Ara-C, at their IC90 - a concentration at which 90% of the cells were dead by day 7. Surviving cells displayed a lag phase in their proliferation for 7 to 15 days post-chemotherapy. As determined by EdU (5-ethynyl-2'-deoxyuridine) labeling, persisting cells actively proliferated during this time, albeit slower than parental cells. Upon cell regrowth, rates of proliferation returned to normal and cells regained chemosensitivity similar to parental cells, demonstrating the DTP phenotype. To understand mechanisms of the DTP state, we used liquid chromatography-mass spectrometry (LC-MS) to analyze the metabolome and lipidome of MOLM13 and OCI-AML2 cells before Daunorubicin and Ara-C treatment, 7 days posttreatment as well as 12 days after treatment removal (i.e., recovery period). Among the most prominent changes in the DTP cells was an alteration in the global lipidome, with an increase in the levels of unsaturated and elongated fatty acids across the main lipid classes (e.g., triglycerides, phosphatidylcholines, phosphatidylethanolamines, etc.). Increased unsaturated and elongated fatty acids have been associated with increased plasma membrane rigidity and we previously demonstrated that increased plasma membrane rigidity impairs the uptake of chemotherapeutic agents such as Daunorubicin. Therefore, we measured membrane rigidity in AML persisters by staining cells with a lipophilic pyrene dye. DTP AML cells (MOLM13, OCI-AML2, OCI-AML3, MV4-11, THP1 and NB4) acutely increased membrane rigidity upon exposure to chemotherapy and membrane rigidity returned to baseline after recovery from chemotherapy when proliferation and chemosensitivity returned to baseline. We also demonstrated that primary AML cells isolated from a patient on d5 of “7+3” induction chemotherapy had increased membrane rigidity compared to their cells prior to chemotherapy. As a non-pharmacologic approach to mimic the DTP state and increase membrane rigidity, we cultured AML cells at lower temperature (31 oC). Culturing cells at 31 oC mimicked the DTP phenotype as the cells that survived culture at reduced temperature displayed slower proliferation and were resistant to Daunorubicin and Ara-C. Upon returning cells to 37 oC, proliferation and chemosensitivity returned to baseline, similar to DTP cells. Interestingly, the lipidome alterations of AML cells at lower temperatures matched the DTP state with increased unsaturation and elongated fatty acids across the main lipid classes. Increasing membrane rigidity can increase sensitivity to immune-mediated killing. Therefore, we explored the sensitivity of persisting AML cells to immune-mediated killing using Double Negative T (DNT) cells, a subset of CD3+ CD4- CD8- T cells that possess anti-cancer properties. We established a mouse model of AML persisters by engrafting primary AML cells into immune-deficient mice and treating mice with Ara-C or vehicle control. Eight days after treatment, primary AML cells were isolated from Ara-C treated or control mice. Isolated primary AML cells were treated with DNTs for 2 hours. AML DTPs from mice treated with Ara-C were more susceptible to DNT cell-mediated killing compared to AML cells from vehicle-treated mice. Likewise, AML cells that persisted at 31 oC displayed increased sensitivity to DNT-mediated killing compared to cells cultured at 37 oC. In conclusion, AML persister cells adapt and survive chemotherapy by transiently increasing fatty acid unsaturation and elongation resulting in increasing plasma membrane rigidity. Although these cells survive chemotherapy, they have increased susceptibility to T cell-mediated killing, thus highlighting a potential therapeutic strategy for this disease.

Deciphering Metabolomic Signatures Associated with Sickle Cell Disease Using Mouse Models

Introduction: Sickle cell disease (SCD) is debilitating and affects millions of people worldwide. Although SCD is caused by a single-point mutation of the β-globin chain of hemoglobin, the clinical manifestations are heterogeneous, and there is a lack of well-characterized predictive biomarkers of disease progression. Metabolomics is a promising tool to interrogate disease pathophysiology and underlying molecular mechanisms. Although prior metabolomic studies have been performed on human and murine red blood cells (RBCs) in the context of SCD, no systematic investigation across commonly used mouse models of SCD has been published. In the present study, we examined the blood cell metabolome of 2 widely used SCD mouse models to study and compare the metabolomic changes in disease models. Methods: Blood samples were collected from 5 groups of mice (10-14 weeks old, n=6-7 per group): wild-type (WT) C57BL/6J mice; Townes AA, AS, and SS mice; and Berkeley SCD mice. Direct injection high-resolution mass spectrometry was used to generate untargeted metabolomics data. Three matrices (RBC, plasma, and whole blood) were isolated from each mouse group. The RBC fraction, containing peripheral blood mononuclear cells, was separated from plasma via centrifugation of whole blood. The current study focuses on the RBC dataset.Raw profile data were centroided, merged, and recalibrated using methods previously described (Fuhrer et al. Anal Chem 2011). Putative annotations were generated based on compounds contained in the Human Metabolome Database, KEGG, and ChEBI databases using accurate mass per charge (tolerance 0.001 m/z) and isotopic correlation patterns. Z-score normalization was applied across all samples for unsupervised clustering using principal component analysis (PCA) and to identify metabolites with significant changes between groups. Metabolites were mapped to central RBC metabolic pathways using MetaboAnalyst (Xia et al. Nat Protoc 2011) and manual curation. Results: Unsupervised PCA that used all detectable RBC metabolites resulted in clear separation of mouse groups by disease status (Figure 1), suggesting robust metabolomic changes in mouse models of SCD. Focusing on the top divergent metabolites across the mouse groups, several enriched pathways were identified, such as amino acid metabolism, pyrimidine and purine metabolism, and aminoacyl-tRNA biosynthesis, all potentially attributable to the buildup of RBC precursors. Metabolites characteristic of immature RBCs were further examined, with elevated hexokinase activity (hexose:hexose-6-phosphate ratio), ATP levels, and mitochondrial metabolites found in RBCs from SCD, in line with the significantly elevated reticulocyte content in SCD mice. Metabolites were curated from additional relevant RBC metabolic pathways; some showed significant differences among mouse groups, and others were significantly elevated in sickle mice (Townes SS and Berkeley SCD) compared with non-SCD controls (WT and Townes AA), including some glycolytic and pentose phosphate pathway (PPP) intermediates (Figure 2). The product-to-substrate ratios of metabolite levels from glycolytic and oxidative PPP (oxPPP) steps suggested glycolysis was favored and the later stage of the oxPPP was reduced in mouse models of SCD. There was also a higher metabolic turnover of glutathione, which is characteristic of SCD in humans, but we observed divergent metabolomic signatures between the disease models in our study (Figure 2). Conclusions: To our knowledge, this is the most comprehensive metabolomics study in mouse models of SCD. It provides a foundation to assess disease biology and response to treatment in future studies. Untargeted RBC metabolomics revealed metabolomic signatures that are consistent with human disease pathology in both murine SCD models, including reticulocytosis, hemolysis, and mitochondria retention in RBCs, and signatures that are unique to the murine models. Of the 2 main RBC metabolic pathways, glycolysis was favored over the oxPPP in SCD mice. This is the first step towards understanding the impact of SCD on RBC carbohydrate metabolism.

Influence of Polycyclic Aromatic Compounds and Oxidation States of Soot Organics on the Metabolome of Human-Lung Cells (A549): Implications for Vehicle Fuel Selection.

Decades of research have established the toxicity of soot particles resulting from incomplete combustion. However, the unique chemical compounds responsible for adverse health effects have remained uncertain. This study utilized mass spectrometry to analyze the chemical composition of extracted soot organics at three oxidation states, aiming to establish quantitative relationships between potentially toxic chemicals and their impact on human alveolar basal epithelial cells (A549) through metabolomics-based evaluations. Targeted analysis using MS/MS indicated that particles with a medium oxidation state contained the highest total abundance of compounds, particularly oxygen-containing polycyclic aromatic hydrocarbons (OPAHs) composed of fused benzene rings and unsaturated carbonyls, which may cause oxidative stress, characterized by the upregulation of three specific metabolites. Further investigation focused on three specific OPAH standards: 1,4-naphthoquinone, 9-fluorenone, and anthranone. Pathway analysis indicated that exposure to these compounds affected transcriptional functions, the tricarboxylic acid cycle, cell proliferation, and the oxidative stress response. Biodiesel combustion emissions had higher concentrations of PAHs, OPAHs, and nitrogen-containing PAHs (NPAHs) compared with other fuels. Quinones and 9,10-anthraquinone were identified as the dominant compounds within the OPAH category. This knowledge enhances our understanding of the compounds contributing to adverse health effects observed in epidemiological studies and highlights the role of aerosol composition in toxicity.

Analysis of the mechanism of curcumin against osteoarthritis using metabolomics and transcriptomics

Curcumin, a polyphenolic compound derived from the turmeric plant (Curcuma longa), has been extensively studied for its anti-inflammatory and anti-proliferative properties. The safety and efficacy of curcumin have been thoroughly validated. Nevertheless, the underlying mechanism for treating osteoarthritis remains ambiguous. This study aims to reveal the potential mechanism of curcumin in treating osteoarthritis by using metabolomics and transcriptomics. Firstly, we validated the effect of curcumin on inflammatory factors in human articular chondrocytes. Secondly, we explored the cellular metabolism mechanism of curcumin against osteoarthritis using cell metabolomics. Thirdly, we assessed the differences in gene expression of human articular chondrocytes through transcriptomics. Lastly, to evaluate the essential targets and elucidate the potential mechanism underlying the therapeutic effects of curcumin in osteoarthritis, we conducted a screening of the proteins within the shared pathway of metabolomics and transcriptomics. Our results demonstrated that curcumin significantly decreased the levels of inflammatory markers, such as IL-β, IL-6, and TNF-α, in human articular chondrocytes. Cell metabolomics identified 106 differential metabolites, including beta-aminopropionitrile, 3-amino-2-piperidone, pyrrole-2-carboxaldehyde, and various other components. The transcriptomic analysis yielded 1050 differential mRNAs. Enrichment analysis showed that the differential metabolites and mRNAs were significantly enriched in seven pathways, including glycine, serine, and threonine metabolism; pentose and glucuronate interconversions; glycerolipid metabolism; histidine metabolism; mucin-type o-glycan biosynthesis; inositol phosphate metabolism; and cysteine and methionine metabolism. A total of 23 key targets were identified to be involved in these pathways. We speculate that curcumin may alleviate osteoarthritis by targeting key proteins involved in glycine, serine, and threonine metabolism; inhibiting pyruvate production; and modulating glycolysis.

Exploring the in vitro anti-inflammatory activity of gross saponins of Tribulus terrestris L. fruit by using liquid chromatography-mass spectrometry-based cell metabolomics approach.

Our previous studies confirmed the efficacy of gross saponins of Tribulus terrestris L. fruit in treating cerebral ischemia. This study aimed to investigate the related mechanisms in vitro. The lipopolysaccharide-induced BV2 cells model was constructed and treated with gross saponins at different concentrations to explore its anti-inflammatory activity. The cell metabolite changes were tracked by liquid chromatography-mass spectrometry (LC-MS)-based metabolomics, and the metabolic biomarkers and related metabolic pathways were analyzed. Molecular biochemistry analysis was further used to verify the relevant inflammatory pathways. The results showed that the saponins reduced nitric oxide release and the secretion of tumor necrosis factor-alpha, interleukin-1β, and interleukin-6 from lipopolysaccharide-induced BV2 cells. Metabolic perturbations occurred in lipopolysaccharide-treated BV2 cells, which could be reversed by drug treatment via mainly regulating glycerophospholipid metabolism, tryptophan metabolism, purine metabolism pathways, etc. The western blot analysis demonstrated that saponin could suppress the activation of the inflammatory-related signaling pathway. The present study explored the in vitro anti-inflammatory mechanism of gross saponins of Tribulus terrestris L. fruit using an LC-MS-based cell metabolomics approach, which confirms the great potential of LC-MS for drug efficacy evaluation and can be applied in other herbal medicine-related analyses.

56 Biomarker-Based High Throughput Sperm Phenotyping: the Good, the Bad and the Ugly

Abstract Research in our laboratory addresses the unmet need for developing high throughput phenotyping for collecting comprehensive phenotypes of production, reproduction and fitness traits, a major emphasis area of the USDA Blueprint for Animal Genome Research 2022-2027. Our short- and long-term goal within this emphasis area is to identify specific genomic determinants of aberrant sperm quality and integrity that impart unique morphometric and optical properties on functionally defective spermatozoa that can be captured in next generation flow cytometry at a high speed/throughput, and without the need for costly, time-consuming sample processing. We identified a large set of deleterious gene variants associated with specific sperm defects in the genomes of 85 genetically valuable bulls with suboptimal artificial insemination (AI) fertility. Ongoing efforts focus on developing a second generation, label-free sperm phenotyping pipeline, eliminating variance and costs associated with the conventional, probe-based approaches, based on the specific genomic determinants of aberrant sperm quality resulting in unique morphometric and optical properties of spermatozoa, captured by the next-generation, brightfield image-based flow cytometry (IBFC) and translatable to high-precision phenotyping of heritable production traits. First step is to phenotype and validate rare deleterious polymorphisms associated with aberrant sperm head and tail morphologies in aforementioned cohort of 85 genome-sequenced bulls grouped based on prevailing sperm defect phenotype. Focus is on sperm defects predicted to be heritable and non-compensable by increasing sperm number per AI dose, such as knobbed acrosomes (sperm head caps), nuclear vacuoles and aplastic defects of sperm mitochondrial sheath (the major source of energy to fuel sperm movement). Other potentially heritable defects of interest may not be manifested by aberrant sperm morphologies, and only detectable at subcellular/molecular level by applying biomarkers validated by past and ongoing genome-to-phenotype studies. In the second phase, a label free sperm phenotyping pipeline for bull fertility testing will be developed, translatable to somatic cell phenotyping for other heritable traits by using the dedicated FeatureFinder IFBC software integrated with our machine learning pipeline, followed by validation assessing sperm structural integrity, “gentle” live cell sorting and metabolomics. This approach literary puts artificial intelligence in artificial insemination (AI in AI approach). Altogether, such genome-to-phenome efforts align the livestock genomic selection with state-of-the-art animal andrology, veterinary diagnostics and precision breeding, supporting the improvement of livestock industry efficiency through global approaches integrating production, reproduction, nutrition, health, and welfare.

Neuronal progenitor cells-based metabolomics study reveals dysregulated lipid metabolism and identifies putative biomarkers for CLN6 disease

Neuronal ceroid lipofuscinosis 6 (CLN6) is a rare and fatal autosomal recessive disease primarily affecting the nervous system in children. It is caused by a pathogenic mutation in the CLN6 gene for which no therapy is available. Employing an untargeted metabolomics approach, we analyzed the metabolic changes in CLN6 subjects to see if this system could potentially yield biomarkers for diagnosis and monitoring disease progression. Neuronal-like cells were derived from human fibroblast lines from CLN6-affected subjects (n = 3) and controls (wild type, n = 3). These were used to assess the potential of a neuronal-like cell-based metabolomics approach to identify CLN6 distinctive and specific biomarkers. The most impacted metabolic profile is associated with sphingolipids, glycerophospholipids metabolism, and calcium signaling. Over 2700 spectral features were screened, and fifteen metabolites were identified that differed significantly between both groups, including the sphingolipids C16 GlcCer, C24 GlcCer, C24:1 GlcCer and glycerophospholipids PG 40:6 and PG 40:7. Of note, these fifteen metabolites were downregulated in the CLN6 disease group. This study is the first to analyze the metabolome of neuronal-like cells with a pathogenic mutation in the CLN6 gene and to provide insights into their metabolomic alterations. This could allow for the development of novel biomarkers for monitoring CLN6 disease.

Global and Spatial Metabolomics of Individual Cells Using a Tapered Pneumatically Assisted nano-DESI Probe.

Single-cell metabolomics has the potential to reveal unique insights into intracellular mechanisms and biological processes. However, the detection of metabolites from individual cells is challenging due to their versatile chemical properties and concentrations. Here, we demonstrate a tapered probe for pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) mass spectrometry that enables both chemical imaging of larger cells and global metabolomics of smaller 15 μm cells. Additionally, by depositing cells in predefined arrays, we show successful metabolomics from three individual INS-1 cells per minute, which enabled the acquisition of data from 479 individual cells. Several cells were used to optimize analytical conditions, and 93 or 97 cells were used to monitor metabolome alterations in INS-1 cells after exposure to a low or high glucose concentration, respectively. Our analytical approach offers insights into cellular heterogeneity and provides valuable information about cellular processes and responses in individual cells.