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Deng, Lingli, Lei Ma, Kian-Kai Cheng, Xiangnan Xu, Daniel Raftery, and Jiyang Dong. "Sparse PLS-Based Method for Overlapping Metabolite Set Enrichment Analysis." Journal of Proteome Research 20, no. 6 (May 18, 2021): 3204–13. http://dx.doi.org/10.1021/acs.jproteome.1c00064.
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Martins, Raquel G., Luís G. Gonçalves, Nuno Cunha, and Maria João Bugalho. "Metabolomic Urine Profile: Searching for New Biomarkers of SDHx-Associated Pheochromocytomas and Paragangliomas." Journal of Clinical Endocrinology & Metabolism 104, no. 11 (July 23, 2019): 5467–77. http://dx.doi.org/10.1210/jc.2019-01101.
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Abstract Context Metabolomic studies of pheochromocytoma and paraganglioma tissue showed a correlation between metabolomic profile and presence of SDHx mutations, especially a pronounced increase of succinate. Objective To compare the metabolomic profile of 24-hour urine samples of SDHx mutation carriers with tumors (affected mutation carriers), without tumors (asymptomatic mutation carriers), and patients with sporadic pheochromocytomas and paragangliomas. Methods Proton nuclear magnetic resonance spectroscopic profiling of urine samples and metabolomic analysis using pairwise comparisons were complemented by metabolite set enrichment analysis to identify meaningful patterns. Results The urine of the affected SDHx carriers showed substantially lower levels of seven metabolites than the urine of asymptomatic mutation carriers (including, succinate and N-acetylaspartate). The urine of patients with SDHx-associated tumors presented substantially higher levels of three metabolites compared with the urine of patients without mutation; the metabolite set enrichment analysis identified gluconeogenesis, pyruvate, and aspartate metabolism as the pathways that most probably explained the differences found. N-acetylaspartate was the only metabolite the urinary levels of which were significantly different between the three groups. Conclusions The metabolomic urine profile of the SDHx mutation carriers with tumors is different from that of asymptomatic carriers and from that of patients with sporadic neoplasms. Differences are likely to reflect the altered mitochondria energy production and pseudohypoxia signature of these tumors. The urinary levels of N-acetylaspartate and succinate contrast with those reported in tumor tissue, suggesting a defective washout process of oncometabolites in association with tumorigenesis. The role of N-acetylaspartate as a tumor marker for these tumors merits further investigation.
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Chandler, Paulette D., Raji Balasubramanian, Nina Paynter, Franco Giulianini, Teresa Fung, Lesley F. Tinker, Linda Snetselaar, et al. "Metabolic signatures associated with Western and Prudent dietary patterns in women." American Journal of Clinical Nutrition 112, no. 2 (June 10, 2020): 268–83. http://dx.doi.org/10.1093/ajcn/nqaa131.
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ABSTRACT Background The Western dietary pattern (WD) is positively associated with risk of coronary artery disease (CAD) and cancer, whereas the Prudent dietary pattern (PD) may be protective. Foods may influence metabolite concentrations as well as oxidative stress and lipid dysregulation, biological mechanisms associated with CAD and cancer. Objective The aim was to assess the association of 2 derived dietary pattern scores with serum metabolites and identify metabolic pathways associated with the metabolites. Methods We evaluated the cross-sectional association between each dietary pattern (WD, PD) and metabolites in 2199 Women's Health Initiative (WHI) participants. With FFQ and factor analysis, we determined 2 dietary patterns consistent with WD and PD. Metabolites were measured with LC–tandem MS. Metabolite discovery among 904 WHI Observational Study (WHI-OS) participants was replicated among 1295 WHI Hormone Therapy Trial (WHI-HT) participants. We analyzed each of 495 metabolites with each dietary score (WD, PD) in linear regression models. Results The PD included higher vegetables and fruit intake compared with the WD with higher saturated fat and meat intake. Independent of energy intake, BMI, physical activity, and other confounding variables, 45 overlapping metabolites were identified (WHI-OS) and replicated (WHI-HT) with an opposite direction of associations for the WD compared with the PD [false discovery rate (FDR) P < 0.05]. In metabolite set enrichment analyses, phosphatidylethanolamine (PE) plasmalogens were positively enriched for association with WD [normalized enrichment score (NES) = 2.01, P = 0.001, FDR P = 0.005], and cholesteryl esters (NES = −1.77, P = 0.005, FDR P = 0.02), and phosphatidylcholines (NES = −1.72, P = 0.01, P = 0.03) were negatively enriched for WD. PE plasmalogens were positively correlated with saturated fat and red meat. Phosphatidylcholines and cholesteryl esters were positively correlated with fatty fish. Conclusions Distinct metabolite signatures associated with Western and Prudent dietary patterns highlight the positive association of mitochondrial oxidative stress and lipid dysregulation with a WD and the inverse association with a PD.
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Fan, Sili, Muhammad Shahid, Peng Jin, Arash Asher, and Jayoung Kim. "Identification of Metabolic Alterations in Breast Cancer Using Mass Spectrometry-Based Metabolomic Analysis." Metabolites 10, no. 4 (April 24, 2020): 170. http://dx.doi.org/10.3390/metabo10040170.
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Breast cancer (BC) is a major global health issue and remains the second leading cause of cancer-related death in women, contributing to approximately 41,760 deaths annually. BC is caused by a combination of genetic and environmental factors. Although various molecular diagnostic tools have been developed to improve diagnosis of BC in the clinical setting, better detection tools for earlier diagnosis can improve survival rates. Given that altered metabolism is a characteristic feature of BC, we aimed to understand the comparative metabolic differences between BC and healthy controls. Metabolomics, the study of metabolism, can provide incredible insight and create useful tools for identifying potential BC biomarkers. In this study, we applied two analytical mass spectrometry (MS) platforms, including hydrophilic interaction chromatography (HILIC) and gas chromatography (GC), to generate BC-associated metabolic profiles using breast tissue from BC patients. These metabolites were further analyzed to identify differentially expressed metabolites in BC and their associated metabolic networks. Additionally, Chemical Similarity Enrichment Analysis (ChemRICH), MetaMapp, and Metabolite Set Enrichment Analysis (MSEA) identified significantly enriched clusters and networks in BC tissues. Since metabolomic signatures hold significant promise in the clinical setting, more effort should be placed on validating potential BC biomarkers based on identifying altered metabolomes.
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Isserlin, Ruth, Daniele Merico, Veronique Voisin, and Gary D. Bader. "Enrichment Map – a Cytoscape app to visualize and explore OMICs pathway enrichment results." F1000Research 3 (July 1, 2014): 141. http://dx.doi.org/10.12688/f1000research.4536.1.
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High-throughput OMICs experiments generate signals for millions of entities (i.e. genes, proteins, metabolites or any measurable biological entity) in the cell. In an effort to summarize and explore these signals, expression results are examined in the context of known pathways and processes, through enrichment analysis to generate a set of pathways and processes that is significantly enriched. Due to the high redundancy in annotation resources this often results in hundreds of sets. To facilitate the analysis of these results, we have developed the Enrichment Map app to visualize enrichments as a network. We have updated Enrichment Map to support Cytoscape 3, and have added additional features including new data formats and command line access.
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McLuskey, Karen, Joe Wandy, Isabel Vincent, Justin J. J. van der Hooft, Simon Rogers, Karl Burgess, and Rónán Daly. "Ranking Metabolite Sets by Their Activity Levels." Metabolites 11, no. 2 (February 11, 2021): 103. http://dx.doi.org/10.3390/metabo11020103.
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Related metabolites can be grouped into sets in many ways, e.g., by their participation in series of chemical reactions (forming metabolic pathways), or based on fragmentation spectral similarities or shared chemical substructures. Understanding how such metabolite sets change in relation to experimental factors can be incredibly useful in the interpretation and understanding of complex metabolomics data sets. However, many of the available tools that are used to perform this analysis are not entirely suitable for the analysis of untargeted metabolomics measurements. Here, we present PALS (Pathway Activity Level Scoring), a Python library, command line tool, and Web application that performs the ranking of significantly changing metabolite sets over different experimental conditions. The main algorithm in PALS is based on the pathway level analysis of gene expression (PLAGE) factorisation method and is denoted as mPLAGE (PLAGE for metabolomics). As an example of an application, PALS is used to analyse metabolites grouped as metabolic pathways and by shared tandem mass spectrometry fragmentation patterns. A comparison of mPLAGE with two other commonly used methods (overrepresentation analysis (ORA) and gene set enrichment analysis (GSEA)) is also given and reveals that mPLAGE is more robust to missing features and noisy data than the alternatives. As further examples, PALS is also applied to human African trypanosomiasis, Rhamnaceae, and American Gut Project data. In addition, normalisation can have a significant impact on pathway analysis results, and PALS offers a framework to further investigate this. PALS is freely available from our project Web site.
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Lokhov, Petr G., Elena E. Balashova, Oxana P. Trifonova, Dmitry L. Maslov, Elena A. Ponomarenko, and Alexander I. Archakov. "Mass Spectrometry-Based Metabolomics Analysis of Obese Patients’ Blood Plasma." International Journal of Molecular Sciences 21, no. 2 (January 15, 2020): 568. http://dx.doi.org/10.3390/ijms21020568.
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Scientists currently use only a small portion of the information contained in the blood metabolome. The identification of metabolites is a huge challenge because only highly abundant and well-separated compounds can be easily identified in complex samples. However, new approaches that enhance the identification of compounds have emerged; among them, the identification of compounds based on their involvement in a particular biological context is a recent development. In this work, this approach was first applied to identify metabolites in complex samples and, together with metabolite set enrichment analysis, was used for the evaluation of blood plasma from obese patients. The proposed approach was found to provide a statistically sound overview of the biochemical pathways, thus presenting additional information on obesity. Obesity progression was demonstrated to be accompanied by marked alterations in steroidogenesis, androstenedione metabolism, and androgen and estrogen metabolism. The findings of this study suggest that the workflow used for blood analysis is sufficient to demonstrate obesity at the biochemical pathway level as well as to monitor the response to treatment. This workflow is also expected to be suitable for studying other metabolic diseases.
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Tietz-Bogert, Pamela, Minsuk Kim, Angela Cheung, James Tabibian, Julie Heimbach, Charles Rosen, Madhumitha Nandakumar, et al. "Metabolomic Profiling of Portal Blood and Bile Reveals Metabolic Signatures of Primary Sclerosing Cholangitis." International Journal of Molecular Sciences 19, no. 10 (October 16, 2018): 3188. http://dx.doi.org/10.3390/ijms19103188.
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Primary sclerosing cholangitis (PSC) is a pathogenically complex, chronic, fibroinflammatory disorder of the bile ducts without known etiology or effective pharmacotherapy. Emerging in vitro and in vivo evidence support fundamental pathophysiologic mechanisms in PSC centered on enterohepatic circulation. To date, no studies have specifically interrogated the chemical footprint of enterohepatic circulation in PSC. Herein, we evaluated the metabolome and lipidome of portal venous blood and bile obtained at the time of liver transplantation in patients with PSC (n = 7) as compared to individuals with noncholestatic, end-stage liver disease (viral, metabolic, etc. (disease control, DC, n = 19)) and to nondisease controls (NC, living donors, n = 12). Global metabolomic and lipidomic profiling was performed on serum derived from portal venous blood (portal serum) and bile using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and differential mobility spectroscopy-mass spectroscopy (DMS-MS; complex lipid platform). The Mann–Whitney U test was used to identify metabolites that significantly differed between groups. Principal-component analysis (PCA) showed significant separation of both PSC and DC from NC for both portal serum and bile. Metabolite set enrichment analysis of portal serum and bile demonstrated that the liver-disease cohorts (PSC and DC) exhibited similar enrichment in several metabolite categories compared to NC. Interestingly, the bile in PSC was uniquely enriched for dipeptide and polyamine metabolites. Finally, analysis of patient-matched portal serum and biliary metabolome revealed that these biological fluids were more homogeneous in PSC than in DC or NC, suggesting aberrant bile formation and enterohepatic circulation. In summary, PSC and DC patients exhibited alterations in several metabolites in portal serum and bile, while PSC patients exhibited a unique bile metabolome. These specific alterations in PSC are amenable to hypothesis testing and, potentially, therapeutic pharmacologic manipulation.
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Persicke, Marcus, Christian Rückert, Jens Plassmeier, Leonhardt Jonathan Stutz, Nikolas Kessler, Jörn Kalinowski, Alexander Goesmann, and Heiko Neuweger. "MSEA: metabolite set enrichment analysis in the MeltDB metabolomics software platform: metabolic profiling of Corynebacterium glutamicum as an example." Metabolomics 8, no. 2 (May 1, 2011): 310–22. http://dx.doi.org/10.1007/s11306-011-0311-6.
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Dwivedi, Prarambh SR, V. P. Rasal, Ekta Kotharkar, Shailaja Nare, and Pukar Khanal. "Gene set enrichment analysis of PPAR-γ regulators from Murraya odorata Blanco." Journal of Diabetes & Metabolic Disorders 20, no. 1 (February 17, 2021): 369–75. http://dx.doi.org/10.1007/s40200-021-00754-x.
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Paes de Araújo, Rachel, Natália Bertoni, Ana Seneda, Tainara Felix, Márcio Carvalho, Keir Lewis, Érica Hasimoto, et al. "Defining Metabolic Rewiring in Lung Squamous Cell Carcinoma." Metabolites 9, no. 3 (March 7, 2019): 47. http://dx.doi.org/10.3390/metabo9030047.
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Metabolomics based on untargeted flow infusion electrospray ionization high-resolution mass spectrometry (FIE-HRMS) can provide a snap-shot of metabolism in living cells. Lung Squamous Cell Carcinoma (SCC) is one of the predominant subtypes of Non-Small Cell Lung Cancers (NSCLCs), which usually shows a poor prognosis. We analysed lung SCC samples and matched histologically normal lung tissues from eight patients. Metabolites were profiled by FIE-HRMS and assessed using t-test and principal component analysis (PCA). Differentially accumulating metabolites were mapped to pathways using the mummichog algorithm in R, and biologically meaningful patterns were indicated by Metabolite Set Enrichment Analysis (MSEA). We identified metabolic rewiring networks, including the suppression of the oxidative pentose pathway and found that the normal tricarboxylic acid (TCA) cycle were decoupled from increases in glycolysis and glutamine reductive carboxylation. Well-established associated effects on nucleotide, amino acid and thiol metabolism were also seen. Novel aspects in SCC tissue were increased in Vitamin B complex cofactors, serotonin and a reduction of γ-aminobutyric acid (GABA). Our results show the value of FIE-HRMS as a high throughput screening method that could be exploited in clinical contexts.
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Zhang, Yiru, Trang Nguyen, Junfei Zhao, Enyuan Shang, Consuelo Torrini, Peter D. Canoll, Georg Karpel-Massler, and Markus Siegelin. "CBMT-15. MET INHIBITION DRIVES PGC1A DEPENDENT METABOLIC REPROGRAMMING AND ELICITS UNIQUE METABOLIC VULNERABILITIES IN GLIOBLASTOMA." Neuro-Oncology 21, Supplement_6 (November 2019): vi36. http://dx.doi.org/10.1093/neuonc/noz175.137.
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Abstract The receptor kinase, c-MET, has emerged as a target for glioblastoma therapy. However, treatment resistance evolves inevitably. By performing a global metabolite screen with metabolite set enrichment coupled with transcriptome and gene set enrichment analysis and proteomic screening, we have identified substantial reprogramming of tumor metabolism, involving oxidative phosphorylation and fatty acid oxidation (FAO) with a substantial accumulation of acyl-carnitines accompanied by an increase of PGC1a in response to genetic (shRNA and CRISPR/Cas9) and pharmacological (crizotinib) inhibition of c-MET. Extracellular flux and carbon tracing analyses (U-13C-Glucose and U-13C-Glutamine) demonstrated enhanced oxidative metabolism, which was driven by FAO and supported by increased anaplerosis of glucose carbons. These findings were observed in concert with increased number and fusion of mitochondria and production of reactive oxygen species (ROS). Genetic interference with PGC1a rescued this oxidative phenotype driven by c-MET inhibition. Silencing and chromatin immunoprecipitation experiments demonstrated that CREB regulates the expression of PGC1a in the context of c-MET inhibition. Interference with both oxidative phosphorylation (metformin, oligomycin) and beta-oxidation of fatty acids (etomoxir) enhanced the anti-tumor efficacy of c-MET inhibition. Moreover, based on a high-throughput drug screen, we show that gamitrinib along with c-MET inhibition results in synergistic cell death. Finally, utilizing patient-derived xenograft models, we provide evidence that the combination treatments (crizotinib+etomoxir and crizotinib+gamitrinib) were significantly more efficacious than single treatment without induction of toxicity. Collectively, we have unraveled the mechanistic underpinnings of c-MET inhibitor treatment and identified novel combination therapies that may enhance the therapeutic efficacy of c-MET inhibition.
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Li, Haojie, Wenli Cao, Mengxi Lu, Chunxiao Wu, Xinguo Wang, and Liying Niu. "Urinary and Serum Metabolomics Analyses Uncover That Total Glucosides of Paeony Protect Liver against Acute Injury Potentially via Reprogramming of Multiple Metabolic Pathways." Evidence-Based Complementary and Alternative Medicine 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/9038260.
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Total glucosides of paeony (TGP) have been confirmed to be hepatoprotective. However, the underlying mechanism is largely unclear. In this study, we investigated the metabolic profiles of urine and serum in rats with carbon tetrachloride- (CCl4-) induced experimental liver injury and TGP administration by using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The vehicle or a single dose of TGP was intragastrically administered to Wistar rats once a day for 14 consecutive days. To induce ALI, 50% CCl4 was injected intraperitoneally into these rats 2 hours after the last time administration of saline of TGP at the 14th day. The results indicated that TGP administration could protect rats from CCl4-induced ALI and alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation, as well as hepatocyte apoptosis and inflammation. Furthermore, metabolomics analysis showed that TGP treatment significantly attenuated CCl4-triggered deregulation of multiple metabolites in both urine and serum, including glycine, alanine, proline, and glutamine. Metabolite set enrichment and pathway analyses demonstrated that amino acid cycling and glutathione metabolism were two main pathways involved in CCl4-induced experimental liver injury and TGP administration. Taken together, these findings revealed that regulation of metabolites potentially plays a pivotal role in the protective effect of TGP on ALI.
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Ogunade, Ibukun, Adeoye Oyebade, Bremansu Osa-Andrews, and Sunday Peters. "Plasma Carboxyl-Metabolome Is Associated with Average Daily Gain Divergence in Beef Steers." Animals 11, no. 1 (January 1, 2021): 67. http://dx.doi.org/10.3390/ani11010067.
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We applied an untargeted metabolomics technique to analyze the plasma carboxyl-metabolome of beef steers with divergent average daily gain (ADG). Forty-eight newly weaned Angus crossbred beef steers were fed the same total mixed ration ad libitum for 42 days. On day 42, the steers were divided into two groups of lowest (LF: n = 8) and highest ADG (HF: n = 8), and blood samples were obtained from the two groups for plasma preparation. Relative quantification of carboxylic-acid-containing metabolites in the plasma samples was determined using a metabolomics technique based on chemical isotope labeling liquid chromatography mass spectrometry. Metabolites that differed (fold change (FC) ≥ 1.2 or ≤ 0.83 and FDR ≤ 0.05) between LF and HF were identified using a volcano plot. Metabolite set enrichment analysis (MSEA) of the differential metabolites was done to determine the metabolic pathways or enzymes that were potentially altered. In total, 328 metabolites were identified. Volcano plot analysis revealed 43 differentially abundant metabolites; several short chain fatty acids and ketone bodies had greater abundance in HF steers. Conversely, several long chain fatty acids were greater in LF steers. Five enzymatic pathways, such as fatty acyl CoA elongation and fatty-acid CoA ligase were altered based on MSEA. This study demonstrated that beef steers with divergent ADG had altered plasma carboxyl-metabolome, which is possibly caused by altered abundances and/or activities of enzymes involved in fatty acid oxidation and biosynthesis in the liver.
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Bagheri, Minoo, Jonathan D. Mosley, and Jane F. Ferguson. "Diet Quality, Gut Microbiome and Metabolism." Current Developments in Nutrition 5, Supplement_2 (June 2021): 1148. http://dx.doi.org/10.1093/cdn/nzab054_003.
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Abstract Objectives Dietary pattern is associated with circulatory and gut metabolome variation. However, it is unclear if this association is mediated by gut microbiome composition. We investigated whether the interaction between diet quality and gut microbiome influenced circulatory and gut metabolites. Methods We conducted a cross-sectional study among 75 healthy adults in the ABO Study. Diet quality was assessed using the Healthy Eating Index (HEI). Metabolome profiling (800 circulatory and 767 gut metabolites) was performed at Metabolon Inc. Two gut microbiome Enterotypes (1 and 2) were identified using the Partitioning Around Medoids method. Metabolite set enrichment analysis was performed using Metaboanalyst 4.0. Multivariable linear regression was conducted to test for an interaction between the gut microbiome-HEI and metabolite levels. Results Diet quality was significantly higher in participants with Enterotype 2, compared to those with Enterotype 1 (P = 0.01). The gut microbiome-HEI interaction (Enterotype 2 and higher HEI) was directly related to omega-3/omega-6 poly-unsaturated fatty acids (PUFAs) and acetyl/acyl derivatives of amino acids. It was inversely linked to polar lipids including 1-palmitoyl-2-linoleoyl-GPC (16:0/18:2), which demonstrated the most significant association (β = 0.008, P = 0.0009) among circulatory metabolites. Considering gut metabolome, however, the interaction directly associated with metabolites involved in DNA synthesis including thymidine 5′-monophosphate, which showed the strongest association (β = 0.041, P = 0.0007), and bile acids derivatives. It inversely associated with fatty acids and branch chain amino acids. ‘Glycine and serine metabolism’ was the only pathway that was significantly enriched by the interaction (P = 0.044). Conclusions Future research is warranted; however, these findings suggest that the efficacy of dietary interventions targeted at altering metabolism (the metabolism of lipids (PUFAs and polar lipids), amino acids and nucleotides) may be dependent on gut microbiome composition. Funding Sources The National Institutes of Health.
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Muroya, Susumu, Yi Zhang, Aoi Kinoshita, Kounosuke Otomaru, Kazunaga Oshima, Yuji Gotoh, Ichiro Oshima, et al. "Maternal Undernutrition during Pregnancy Alters Amino Acid Metabolism and Gene Expression Associated with Energy Metabolism and Angiogenesis in Fetal Calf Muscle." Metabolites 11, no. 9 (August 28, 2021): 582. http://dx.doi.org/10.3390/metabo11090582.
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To elucidate the mechanisms underlying maternal undernutrition (MUN)-induced fetal skeletal muscle growth impairment in cattle, the longissimus thoracis muscle of Japanese Black fetal calves at 8.5 months in utero was analyzed by an integrative approach with metabolomics and transcriptomics. The pregnant cows were fed on 60% (low-nutrition, LN) or 120% (high-nutrition, HN) of their overall nutritional requirement during gestation. MUN markedly decreased the bodyweight and muscle weight of the fetus. The levels of amino acids (AAs) and arginine-related metabolites including glutamine, GABA, and putrescine were higher in the LN group than those in the HN group. Metabolite set enrichment analysis revealed that the highly different metabolites were associated with the metabolic pathways of pyrimidine, glutathione, and AAs such as arginine and glutamate, suggesting that MUN resulted in AA accumulation rather than protein accumulation. The mRNA expression levels of energy metabolism-associated genes, such as PRKAA1, ANGPTL4, APLNR, CPT1B, NOS2, NOS3, UCP2, and glycolytic genes were lower in the LN group than in the HN group. The gene ontology/pathway analysis revealed that the downregulated genes in the LN group were associated with glucose metabolism, angiogenesis, HIF-1 signaling, PI3K-Akt signaling, pentose phosphate, and insulin signaling pathways. Thus, MUN altered the levels of AAs and expression of genes associated with energy expenditure, glucose homeostasis, and angiogenesis in the fetal muscle.
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Troisi, Jacopo, Angelo Colucci, Pierpaolo Cavallo, Sean Richards, Steven Symes, Annamaria Landolfi, Giovanni Scala, et al. "A Serum Metabolomic Signature for the Detection and Grading of Bladder Cancer." Applied Sciences 11, no. 6 (March 22, 2021): 2835. http://dx.doi.org/10.3390/app11062835.
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Bladder cancer has a high incidence and is marked by high morbidity and mortality. Early diagnosis is still challenging. The objective of this study was to create a metabolomics-based profile of bladder cancer in order to provide a novel approach for disease screening and stratification. Moreover, the study characterized the metabolic changes associated with the disease. Serum metabolomic profiles were obtained from 149 bladder cancer patients and 81 healthy controls. Different ensemble machine learning models were built in order to: (1) differentiate cancer patients from controls; (2) stratify cancer patients according to grading; (3) stratify patients according to cancer muscle invasiveness. Ensemble machine learning models were able to discriminate well between cancer patients and controls, between high grade (G3) and low grade (G1-2) cancers and between different degrees of muscle invasivity; ensemble model accuracies were ≥80%. Relevant metabolites, selected using the partial least square discriminant analysis (PLS-DA) algorithm, were included in a metabolite-set enrichment analysis, showing perturbations primarily associated with cell glucose metabolism. The metabolomic approach may be useful as a non-invasive screening tool for bladder cancer. Furthermore, metabolic pathway analysis can increase understanding of cancer pathophysiology. Studies conducted on larger cohorts, and including blind trials, are needed to validate results.
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Schneider, Kevin, Benedikt Venn, and Timo Mühlhaus. "TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation." Entropy 22, no. 9 (September 15, 2020): 1030. http://dx.doi.org/10.3390/e22091030.
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The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA.
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Weiner, January, Teresa Domaszewska, Simon Donkor, Stefan H. E. Kaufmann, Philip C. Hill, and Jayne S. Sutherland. "Changes in Transcript, Metabolite, and Antibody Reactivity During the Early Protective Immune Response in Humans to Mycobacterium tuberculosis Infection." Clinical Infectious Diseases 71, no. 1 (August 15, 2019): 30–40. http://dx.doi.org/10.1093/cid/ciz785.
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Abstract Background Strategies to prevent Mycobacterium tuberculosis (Mtb) infection are urgently required. In this study, we aimed to identify correlates of protection against Mtb infection. Methods Two groups of Mtb-exposed contacts of tuberculosis (TB) patients were recruited and classified according to their Mtb infection status using the tuberculin skin test (TST; cohort 1) or QuantiFERON (QFT; cohort 2). A negative reading at baseline with a positive reading at follow-up classified TST or QFT converters and a negative reading at both time points classified TST or QFT nonconverters. Ribonucleic acid sequencing, Mtb proteome arrays, and metabolic profiling were performed. Results Several genes were found to be differentially expressed at baseline between converters and nonconverters. Gene set enrichment analysis revealed a distinct B-cell gene signature in TST nonconverters compared to converters. When infection status was defined by QFT, enrichment of type I interferon was observed. A remarkable area under the curve (AUC) of 1.0 was observed for IgA reactivity to Rv0134 and an AUC of 0.98 for IgA reactivity to both Rv0629c and Rv2188c. IgG reactivity to Rv3223c resulted in an AUC of 0.96 and was markedly higher compared to TST nonconverters. We also identified several differences in metabolite profiles, including changes in biomarkers of inflammation, fatty acid metabolism, and bile acids. Pantothenate (vitamin B5) was significantly increased in TST nonconverters compared to converters at baseline (q = 0.0060). Conclusions These data provide new insights into the early protective response to Mtb infection and possible avenues to interfere with Mtb infection, including vitamin B5 supplementation. Analysis of blood from highly exposed household contacts from The Gambia who never develop latent Mycobacterium tuberculosis infection shows distinct transcriptomic, antibody, and metabolomic profiles compared to those who develop latent tuberculosis infection but prior to any signs of infection.
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Rocchetti, Gabriele, Francesca Ghilardelli, Paolo Bonini, Luigi Lucini, Francesco Masoero, and Antonio Gallo. "Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows." Metabolites 11, no. 8 (July 23, 2021): 475. http://dx.doi.org/10.3390/metabo11080475.
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In this study, an untargeted metabolomics approach based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) was used for investigating changes in chemical profiles of cow milk considering diets based on mycotoxins-contaminated corn silages. For this purpose, 45 milk samples were classified into five clusters according to the corn silage contamination profile, namely (1) low levels of Aspergillus- and Penicillium-mycotoxins; (2) low levels of fumonisins and other Fusarium-mycotoxins; (3) high levels of Aspergillus-mycotoxins; (4) high levels of non-regulated Fusarium-mycotoxins; (5) high levels of fumonisins and their metabolites, and subsequently analyzed by UHPLC-HRMS followed by a multivariate statistical analysis (both unsupervised and supervised statistical approaches). Overall, the milk metabolomic profile highlighted potential correlations between the quality of contaminated corn silages (as part of the total mixed ration) and milk composition. Metabolomics allowed to identify 628 significant milk metabolites as affected by the five levels of corn silage contamination considered, with amino acids and peptides showing the highest metabolite set enrichment (134 compounds). Additionally, 78 metabolites were selected as the best discriminant of the prediction model built, possessing a variable importance in projection score >1.2. The average Log Fold-Change variations of the discriminant metabolites provided evidence that sphingolipids, together with purine and pyrimidine-derived metabolites were the most affected chemical classes. Also, metabolomics revealed a significant accumulation of oxidized glutathione in milk samples belonging to the silage cluster contaminated by emerging Aspergillus toxins, likely involved in the oxidative imbalance. These preliminary findings provide new insights into the potential role of milk metabolomics to provide chemical indicators of mycotoxins-contaminated corn silage feeding systems.
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Percival, Benita C., Yvonne L. Latour, Cynthia J. Tifft, and Martin Grootveld. "Rapid Identification of New Biomarkers for the Classification of GM1 Type 2 Gangliosidosis Using an Unbiased 1H NMR-Linked Metabolomics Strategy." Cells 10, no. 3 (March 5, 2021): 572. http://dx.doi.org/10.3390/cells10030572.
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Biomarkers currently available for the diagnosis, prognosis, and therapeutic monitoring of GM1 gangliosidosis type 2 (GM1T2) disease are mainly limited to those discovered in targeted proteomic-based studies. In order to identify and establish new, predominantly low-molecular-mass biomarkers for this disorder, we employed an untargeted, multi-analyte approach involving high-resolution 1H NMR analysis coupled to a range of multivariate analysis and computational intelligence technique (CIT) strategies to explore biomolecular distinctions between blood plasma samples collected from GM1T2 and healthy control (HC) participants (n = 10 and 28, respectively). The relationship of these differences to metabolic mechanisms underlying the pathogenesis of GM1T2 disorder was also investigated. 1H NMR-linked metabolomics analyses revealed significant GM1T2-mediated dysregulations in ≥13 blood plasma metabolites (corrected p < 0.04), and these included significant upregulations in 7 amino acids, and downregulations in lipoprotein-associated triacylglycerols and alanine. Indeed, results acquired demonstrated a profound distinctiveness between the GM1T2 and HC profiles. Additionally, employment of a genome-scale network model of human metabolism provided evidence that perturbations to propanoate, ethanol, amino-sugar, aspartate, seleno-amino acid, glutathione and alanine metabolism, fatty acid biosynthesis, and most especially branched-chain amino acid degradation (p = 10−12−10−5) were the most important topologically-highlighted dysregulated pathways contributing towards GM1T2 disease pathology. Quantitative metabolite set enrichment analysis revealed that pathological locations associated with these dysfunctions were in the order fibroblasts > Golgi apparatus > mitochondria > spleen ≈ skeletal muscle ≈ muscle in general. In conclusion, results acquired demonstrated marked metabolic imbalances and alterations to energy demand, which are consistent with GM1T2 disease pathogenesis mechanisms.
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Gao, Bei, Hui-Wen Lue, Jennifer Podolak, Sili Fan, Ying Zhang, Archana Serawat, Joshi J. Alumkal, Oliver Fiehn, and George V. Thomas. "Multi-Omics Analyses Detail Metabolic Reprogramming in Lipids, Carnitines, and Use of Glycolytic Intermediates between Prostate Small Cell Neuroendocrine Carcinoma and Prostate Adenocarcinoma." Metabolites 9, no. 5 (April 26, 2019): 82. http://dx.doi.org/10.3390/metabo9050082.
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As the most common cancer in men, prostate cancer is molecularly heterogeneous. Contributing to this heterogeneity are the poorly understood metabolic adaptations of the two main types of prostate cancer, i.e., adenocarcinoma and small cell neuroendocrine carcinoma (SCNC), the latter being more aggressive and lethal. Using transcriptomics, untargeted metabolomics and lipidomics profiling on LASCPC-01 (prostate SCNC) and LNCAP (prostate adenocarcinoma) cell lines, we found significant differences in the cellular phenotypes of the two cell lines. Gene set enrichment analysis on the transcriptomics data showed 62 gene sets were upregulated in LASCPC-01, while 112 gene sets were upregulated in LNCAP. ChemRICH analysis on metabolomics and lipidomics data revealed a total of 25 metabolite clusters were significantly different. LASCPC-01 exhibited a higher glycolytic activity and lower levels of triglycerides, while the LNCAP cell line showed increases in one-carbon metabolism as an exit route of glycolytic intermediates and a decrease in carnitine, a mitochondrial lipid transporter. Our findings pinpoint differences in prostate neuroendocrine carcinoma versus prostate adenocarcinoma that could lead to new therapeutic targets in each type.
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Saw, Nay Min Min Thaw, Pipob Suwanchaikasem, Rogelio Zuniga-Montanez, Guanglei Qiu, Ezequiel M. Marzinelli, Stefan Wuertz, and Rohan B. H. Williams. "Influence of Extraction Solvent on Nontargeted Metabolomics Analysis of Enrichment Reactor Cultures Performing Enhanced Biological Phosphorus Removal (EBPR)." Metabolites 11, no. 5 (April 26, 2021): 269. http://dx.doi.org/10.3390/metabo11050269.
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Metabolome profiling is becoming more commonly used in the study of complex microbial communities and microbiomes; however, to date, little information is available concerning appropriate extraction procedures. We studied the influence of different extraction solvent mixtures on untargeted metabolomics analysis of two continuous culture enrichment communities performing enhanced biological phosphate removal (EBPR), with each enrichment targeting distinct populations of polyphosphate-accumulating organisms (PAOs). We employed one non-polar solvent and up to four polar solvents for extracting metabolites from biomass. In one of the reactor microbial communities, we surveyed both intracellular and extracellular metabolites using the same set of solvents. All samples were analysed using ultra-performance liquid chromatography mass spectrometry (UPLC-MS). UPLC-MS data obtained from polar and non-polar solvents were analysed separately and evaluated using extent of repeatability, overall extraction capacity and the extent of differential abundance between physiological states. Despite both reactors demonstrating the same bioprocess phenotype, the most appropriate extraction method was biomass specific, with methanol: water (50:50 v/v) and methanol: chloroform: water (40:40:20 v/v/v) being chosen as the most appropriate for each of the two different bioreactors, respectively. Our approach provides new data on the influence of solvent choice on the untargeted surveys of the metabolome of PAO enriched EBPR communities and suggests that metabolome extraction methods need to be carefully tailored to the specific complex microbial community under study.
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Mazzolari, Angelica, Giulio Vistoli, Bernard Testa, and Alessandro Pedretti. "Prediction of the Formation of Reactive Metabolites by A Novel Classifier Approach Based on Enrichment Factor Optimization (EFO) as Implemented in the VEGA Program." Molecules 23, no. 11 (November 13, 2018): 2955. http://dx.doi.org/10.3390/molecules23112955.
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The study is aimed at developing linear classifiers to predict the capacity of a given substrate to yield reactive metabolites. While most of the hitherto reported predictive models are based on the occurrence of known structural alerts (e.g., the presence of toxophoric groups), the present study is focused on the generation of predictive models involving linear combinations of physicochemical and stereo-electronic descriptors. The development of these models is carried out by using a novel classification approach based on enrichment factor optimization (EFO) as implemented in the VEGA suite of programs. The study took advantage of metabolic data as collected by manually curated analysis of the primary literature and published in the years 2004–2009. The learning set included 977 substrates among which 138 compounds yielded reactive first-generation metabolites, plus 212 substrates generating reactive metabolites in all generations (i.e., metabolic steps). The results emphasized the possibility of developing satisfactory predictive models especially when focusing on the first-generation reactive metabolites. The extensive comparison of the classifier approach presented here using a set of well-known algorithms implemented in Weka 3.8 revealed that the proposed EFO method compares with the best available approaches and offers two relevant benefits since it involves a limited number of descriptors and provides a score-based probability thus allowing a critical evaluation of the obtained results. The last analyses on non-cheminformatics UCI datasets emphasize the general applicability of the EFO approach, which conveniently performs using both balanced and unbalanced datasets.
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Walejko, Jacquelyn M., Jeremy P. Koelmel, Timothy J. Garrett, Arthur S. Edison, and Maureen Keller-Wood. "Multiomics approach reveals metabolic changes in the heart at birth." American Journal of Physiology-Endocrinology and Metabolism 315, no. 6 (December 1, 2018): E1212—E1223. http://dx.doi.org/10.1152/ajpendo.00297.2018.
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During late gestation, the fetal heart primarily relies on glucose and lactate to support rapid growth and development. Although numerous studies describe changes in heart metabolism to utilize fatty acids preferentially a few weeks after birth, little is known about metabolic changes of the heart within the first day following birth. Therefore, we used the ovine model of pregnancy to investigate metabolic differences between the near-term fetal and the newborn heart. Heart tissue was collected for metabolomic, lipidomic, and transcriptomic approaches from the left and right ventricles and intraventricular septum in 7 fetuses at gestational day 142 and 7 newborn lambs on the day of birth. Significant metabolites and lipids were identified using a Student’s t-test, whereas differentially expressed genes were identified using a moderated t-test with empirical Bayes method [false discovery rate (FDR)-corrected P < 0.10]. Single-sample gene set enrichment analysis (ssGSEA) was used to identify pathways enriched on a transcriptomic level (FDR-corrected P < 0.05), whereas overrepresentation enrichment analysis was used to identify pathways enriched on a metabolomic level ( P < 0.05). We observed greater abundance of metabolites involved in butanoate and propanoate metabolism, and glycolysis in the term fetal heart and differential expression in these pathways were confirmed with ssGSEA. Immediately following birth, newborn hearts displayed enrichment in purine, fatty acid, and glycerophospholipid metabolic pathways as well as oxidative phosphorylation with significant alterations in both lipids and metabolites to support transcriptomic findings. A better understanding of metabolic alterations that occur in the heart following birth may improve treatment of neonates at risk for heart failure.
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Johnson, Matthew E., Jonathan Schug, Andrew D. Wells, Klaus H. Kaestner, and Struan F. A. Grant. "Genome-Wide Analyses of ChIP-Seq Derived FOXA2 DNA Occupancy in Liver Points to Genetic Networks Underpinning Multiple Complex Traits." Journal of Clinical Endocrinology & Metabolism 99, no. 8 (August 1, 2014): E1580—E1585. http://dx.doi.org/10.1210/jc.2013-4503.
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Background: Forkhead Box A2 (FOXA2) exerts an influence on glucose homeostasis via activity in the liver. In addition, a key genome-wide association study (GWAS) recently demonstrated that genetic variation, namely rs6048205, at the FOXA2 locus is robustly associated with fasting glucose levels. Our hypothesis was that this DNA-binding protein regulates the expression of a set of molecular pathways critical to endocrine traits. Methods: Drawing on our laboratory and bioinformatic experience with chromatin immunoprecipitation followed by massively parallel sequencing, we analyzed our existing FOXA2 chromatin immunoprecipitation followed by massively parallel sequencing data generated in human liver, using the algorithm hypergeometric optimization of motif enrichment, to gain insight into its global genomic binding pattern from a disease perspective. Results: We performed a pathway analysis of the gene list using the gene set enrichment analysis algorithm, which yielded a number of significant annotations. Motivated by the fact that the FOXA2 locus has been implicated by GWAS, we cross-referenced the occupancy sites with the National Institutes of Health GWAS catalog and found strong evidence for the enrichment of loci implicated in endocrine, neuropsychiatric, cardiovascular, and cancer trait categories, but interestingly there was no evidence for enrichment for inflammation related traits. Intriguingly, a FOXA2 occupancy site coincided with rs6048205, suggesting that this variant confers its effect, at least partially, via a perturbation of a FOXA2 feedback mechanism. Conclusion: Our data strongly suggest that FOXA2 is acting as a master regulator of key pathways that are enriched for loci implicated by GWAS for most trait categories, with the clear exception of inflammation, suggesting that this factor exerts its effect in this context via noninflammatory processes.
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Ibrahim, Mahmoud A. A., Alaa H. M. Abdelrahman, Tarik A. Mohamed, Mohamed A. M. Atia, Montaser A. M. Al-Hammady, Khlood A. A. Abdeljawaad, Eman M. Elkady, et al. "In Silico Mining of Terpenes from Red-Sea Invertebrates for SARS-CoV-2 Main Protease (Mpro) Inhibitors." Molecules 26, no. 7 (April 5, 2021): 2082. http://dx.doi.org/10.3390/molecules26072082.
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19 pandemic, which generated more than 1.82 million deaths in 2020 alone, in addition to 83.8 million infections. Currently, there is no antiviral medication to treat COVID-19. In the search for drug leads, marine-derived metabolites are reported here as prospective SARS-CoV-2 inhibitors. Two hundred and twenty-seven terpene natural products isolated from the biodiverse Red-Sea ecosystem were screened for inhibitor activity against the SARS-CoV-2 main protease (Mpro) using molecular docking and molecular dynamics (MD) simulations combined with molecular mechanics/generalized Born surface area binding energy calculations. On the basis of in silico analyses, six terpenes demonstrated high potency as Mpro inhibitors with ΔGbinding ≤ −40.0 kcal/mol. The stability and binding affinity of the most potent metabolite, erylosides B, were compared to the human immunodeficiency virus protease inhibitor, lopinavir. Erylosides B showed greater binding affinity towards SARS-CoV-2 Mpro than lopinavir over 100 ns with ΔGbinding values of −51.9 vs. −33.6 kcal/mol, respectively. Protein–protein interactions indicate that erylosides B biochemical signaling shares gene components that mediate severe acute respiratory syndrome diseases, including the cytokine- and immune-signaling components BCL2L1, IL2, and PRKC. Pathway enrichment analysis and Boolean network modeling were performed towards a deep dissection and mining of the erylosides B target–function interactions. The current study identifies erylosides B as a promising anti-COVID-19 drug lead that warrants further in vitro and in vivo testing.
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Vaswani, Kanchan, Murray D. Mitchell, Olivia J. Holland, Yong Qin Koh, Rebecca J. Hill, Tracy Harb, Peter S. W. Davies, and Hassendrini Peiris. "A Method for the Isolation of Exosomes from Human and Bovine Milk." Journal of Nutrition and Metabolism 2019 (December 3, 2019): 1–6. http://dx.doi.org/10.1155/2019/5764740.
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Scope. Milk provides a natural means of nutrient supply to infants. Exosomes are an important component of milk that are not only being studied for their promise in translational medicine but also in infant nutrition. They also play important roles in intercellular communication and immune function in mammary glands and are able to transfer their materials to the recipient. Therefore, the isolation of high-quality exosomes is an important aspect of exosome research. Methods and Results. This study is a technical study, which provides a detailed methodology for the isolation and enrichment of exosomes from milk. In this study, we evaluate the suitability of using the exosome enrichment method that we have recently published for bovine milk, on human milk. We initially isolated extracellular vesicles from human and bovine milk on a fresh set of samples, using ultracentrifugation, and then exosomes were subsequently enriched via size exclusion chromatography (SEC). Following isolation and enrichment, exosomes from both species were characterized by particle concentration (nanoparticle tracking analysis, NTA), morphology (transmission electron microscopy, TEM), and the presence of exosomal markers (immunoblotting and mass spectrometry using information dependant acquisition (IDA)). The key exosomal characteristics of spherical/donut-shaped morphology, the presence of exosomal markers, e.g., FLOT-1 and the tetraspanins, CD9 and CD81), and particle concentration were confirmed in both human and bovine milk exosomes. Conclusion. We conclude that our robust exosome enrichment method, previously published for bovine milk, is suitable for use on human milk.
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Stefan, Joanna, Tae-Kang Kim, Fiona Schedel, Zorica Janjetovic, David K. Crossman, Kerstin Steinbrink, Radomir M. Slominski, et al. "Differential and Overlapping Effects of Melatonin and Its Metabolites on Keratinocyte Function: Bioinformatics and Metabolic Analyses." Antioxidants 10, no. 4 (April 17, 2021): 618. http://dx.doi.org/10.3390/antiox10040618.
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We investigated the effects of melatonin and its selected metabolites, i.e., N1-Acetyl-N2-formyl-5-methoxykynurenamine (AFMK) and 6-hydroxymelatonin (6(OH)Mel), on cultured human epidermal keratinocytes (HEKs) to assess their homeostatic activities with potential therapeutic implications. RNAseq analysis revealed a significant number of genes with distinct and overlapping patterns, resulting in common regulation of top diseases and disorders. Gene Set Enrichment Analysis (GSEA), Reactome FIViZ, and Ingenuity Pathway Analysis (IPA) showed overrepresentation of the p53-dependent G1 DNA damage response gene set, activation of p53 signaling, and NRF2-mediated antioxidative pathways. Additionally, GSEA exhibited an overrepresentation of circadian clock and antiaging signaling gene sets by melatonin derivatives and upregulation of extension of telomere signaling in HEKs, which was subsequently confirmed by increased telomerase activity in keratinocytes, indicating possible antiaging properties of metabolites of melatonin. Furthermore, Gene Ontology (GO) showed the activation of a keratinocyte differentiation program by melatonin, and GSEA indicated antitumor and antilipidemic potential of melatonin and its metabolites. IPA also indicated the role of Protein Kinase R (PKR) in interferon induction and antiviral response. In addition, the test compounds decreased lactate dehydrogenase A (LDHA) and lactate dehydrogenase C (LDHC) gene expression. These results were validated by qPCR and by Seahorse metabolic assay with significantly decreased glycolysis and lactate production under influence of AFMK or 6(OH)Mel in cells with a low oxygen consumption rate. In summary, melatonin and its metabolites affect keratinocytes’ functions via signaling pathways that overlap for each tested molecule with some distinctions.
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Bortolasci, Chiara C., Briana Spolding, Srisaiyini Kidnapillai, Timothy Connor, Trang T. T. Truong, Zoe S. J. Liu, Bruna Panizzutti, et al. "Transcriptional Effects of Psychoactive Drugs on Genes Involved in Neurogenesis." International Journal of Molecular Sciences 21, no. 21 (November 6, 2020): 8333. http://dx.doi.org/10.3390/ijms21218333.
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Although neurogenesis is affected in several psychiatric diseases, the effects and mechanisms of action of psychoactive drugs on neurogenesis remain unknown and/or controversial. This study aims to evaluate the effects of psychoactive drugs on the expression of genes involved in neurogenesis. Neuronal-like cells (NT2-N) were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM) for 24 h. Genome wide mRNA expression was quantified and analysed using gene set enrichment analysis, with the neurogenesis gene set retrieved from the Gene Ontology database and the Mammalian Adult Neurogenesis Gene Ontology (MANGO) database. Transcription factors that are more likely to regulate these genes were investigated to better understand the biological processes driving neurogenesis. Targeted metabolomics were performed using gas chromatography-mass spectrometry. Six of the eight drugs decreased the expression of genes involved in neurogenesis in both databases. This suggests that acute treatment with these psychoactive drugs negatively regulates the expression of genes involved in neurogenesis in vitro. SOX2 and three of its target genes (CCND1, BMP4, and DKK1) were also decreased after treatment with quetiapine. This can, at least in part, explain the mechanisms by which these drugs decrease neurogenesis at a transcriptional level in vitro. These results were supported by the finding of increased metabolite markers of mature neurons following treatment with most of the drugs tested, suggesting increased proportions of mature relative to immature neurons consistent with reduced neurogenesis.
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Deshpande, Ruta Suresh, Devi Sundaravadivelu, Pablo Campo, Jorge W. SantoDomingo, and Robyn N. Conmy. "Comparative Study on Rate of Biodegradation of Diluted Bitumen and Conventional Oil in Fresh Water." International Oil Spill Conference Proceedings 2017, no. 1 (May 1, 2017): 2256–67. http://dx.doi.org/10.7901/2169-3358-2017.1.2256.
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Abstract 2017-271 In recent years, diluted bitumen (or dilbit) has become an important source of hydrocarbon-based fuel. While information on the degradation of crude oils has been well researched, dilbit degradation has been studied at a much lesser extent. The objective of this study was to compare biodegradation of dilbit with a conventional crude oil (CCO) under various conditions. Two different microcosm experiments were set up, one containing a mixed culture acclimated to dilbit (Kalamazoo River Enrichment, KRC) and the other having a mixed culture enriched on soil contaminated with hydrocarbons (Anderson Ferry Enrichment, AFC). The microcosms were run for 60 d at 25 °C and for 72 days at 5 °C in flasks containing sterile Bushnell Hass broth and naturally dispersed oil. Each flask was inoculated with the KRC and AFC mixed cultures, and rotated on an orbital shaker (200 rpm) at the above stated temperatures. On each sampling day, triplicates were sacrificed to determine the residual hydrocarbon concentration. Additionally, some samples were used to determine the bacterial composition using 16S rRNA gene sequencing analysis. Hydrocarbon analysis (alkanes and PAHs) was performed by gas chromatography/mass spectrometry (GC/MS/MS). Higher degradation rates were achieved at 25 °C as compared to 5 °C. All the enrichments metabolized CCO as well dilbit, but the nature and extent of the degradation was distinct. KRC meso culture was the most effective among all, as it completely removed alkanes and most of the PAHs. AFC enrichment performed differently at the two temperatures; an acclimation period (8 d) was observed at 5 °C while there was no lag at 25 °C. KRC cryo culture as well as AFC culture at both temperatures degraded alkanes completely while they were not able to metabolize heavier fractions of the oil (C2–4 homologues of 3- and 4-ring compounds). All cultures showed the presence of diverse oil degrading bacteria and the differences in their compositions affected the biodegradation. Although dilbit was biodegraded, for all the treatments except AFC at 5 °C, the rate of degradation and the extent of degradation was greater for CCO owing to the higher concentrations of lighter hydrocarbons.
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Mevy, Jean-Philippe, Beatrice Loriod, Xi Liu, Erwan Corre, Magali Torres, Michael Büttner, Anne Haguenauer, Ilja Marco Reiter, Catherine Fernandez, and Thierry Gauquelin. "Response of Downy Oak (Quercus pubescens Willd.) to Climate Change: Transcriptome Assembly, Differential Gene Analysis and Targeted Metabolomics." Plants 9, no. 9 (September 4, 2020): 1149. http://dx.doi.org/10.3390/plants9091149.
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Global change scenarios in the Mediterranean basin predict a precipitation reduction within the coming hundred years. Therefore, increased drought will affect forests both in terms of adaptive ecology and ecosystemic services. However, how vegetation might adapt to drought is poorly understood. In this report, four years of climate change was simulated by excluding 35% of precipitation above a downy oak forest. RNASeq data allowed us to assemble a genome-guided transcriptome. This led to the identification of differentially expressed features, which was supported by the characterization of target metabolites using a metabolomics approach. We provided 2.5 Tb of RNASeq data and the assembly of the first genome guided transcriptome of Quercus pubescens. Up to 5724 differentially expressed transcripts were obtained; 42 involved in plant response to drought. Transcript set enrichment analysis showed that drought induces an increase in oxidative pressure that is mitigated by the upregulation of ubiquitin-like protein protease, ferrochelatase, oxaloacetate decarboxylase and oxo-acid-lyase activities. Furthermore, the downregulation of auxin biosynthesis and transport, carbohydrate storage metabolism were observed as well as the concomitant accumulation of metabolites, such as oxalic acid, malate and isocitrate. Our data suggest that early metabolic changes in the resistance of Q. pubescens to drought involve a tricarboxylic acid (TCA) cycle shunt through the glyoxylate pathway, galactose metabolism by reducing carbohydrate storage and increased proteolytic activity.
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Stauffer, Elena, Peter Weber, Theresa Heider, Claudia Dalke, Andreas Blutke, Axel Walch, Gerald Burgstaller, et al. "Transcriptomic landscape of radiation-induced murine thyroid proliferative lesions." Endocrine-Related Cancer 28, no. 3 (March 2021): 213–24. http://dx.doi.org/10.1530/erc-21-0019.
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Thyroid carcinoma incidence rates in western societies are among the fastest rising, compared to all malignant tumors over the past two decades. While risk factors such as age and exposure to ionizing radiation are known, early-state carcinogenic processes or pre-lesions are poorly understood or unknown. This study aims at the identification and characterization of early-state radiation-associated neoplastic processes by histologic and transcriptomic analyses of thyroid tissues derived from a mouse model. Comprehensive histological examination of 246 thyroids (164 exposed, 82 non-exposed) was carried out. Proliferative and normal tissues from exposed cases and normal tissue from non-exposed cases were collected by laser-capture microdissection, followed by RNAseq transcriptomic profiling using a low input 3′-library preparation protocol, differential gene expression analysis and functional association by gene set enrichment analysis. Nine exposed samples exhibited proliferative lesions, while none of the non-exposed samples showed histological abnormalities, indicating an association of ionizing radiation exposure with histological abnormalities. Activated immune response signaling and deregulated metabolic processes were observed in irradiated tissue with normal histology compared to normal tissue from non-exposed samples. Proliferative lesions compared to corresponding normal tissues showed enrichment for mainly proliferation-associated gene sets. Consistently, proliferative lesion samples from exposed mice showed elevated proliferation-associated signaling and deregulated metabolic processes compared to normal samples from non-exposed mice. Our findings suggest that a molecular deregulation may be detectable in histologically normal thyroid tissues and in early proliferative lesions in the frame of multi-step progression from irradiated normal tissue to tumorous lesions.
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Kankainen, Matti, Peddinti Gopalacharyulu, Liisa Holm, and Matej Orešič. "MPEA—metabolite pathway enrichment analysis." Bioinformatics 27, no. 13 (May 5, 2011): 1878–79. http://dx.doi.org/10.1093/bioinformatics/btr278.
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Almeida, Madson Q., Michelle Harran, Eirini I. Bimpaki, Hui-Pin Hsiao, Anelia Horvath, Chris Cheadle, Tonya Watkins, Maria Nesterova, and Constantine A. Stratakis. "Integrated Genomic Analysis of Nodular Tissue in Macronodular Adrenocortical Hyperplasia: Progression of Tumorigenesis in a Disorder Associated with Multiple Benign Lesions." Journal of Clinical Endocrinology & Metabolism 96, no. 4 (April 1, 2011): E728—E738. http://dx.doi.org/10.1210/jc.2010-2420.
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Abstract Context: Massive macronodular adrenocortical disease or ACTH-independent macronodular adrenal hyperplasia (AIMAH) is a clinically and genetically heterogeneous disorder. Objective and Design: Whole-genome expression profiling and oligonucleotide array comparative genomic hybridization changes were analyzed in samples of different nodules from the same patients with AIMAH. Quantitative RT-PCR and staining were employed to validate the mRNA array data. Results: Chromosomal gains were more frequent in larger nodules when compared with smaller nodules from the same patients. Among the 50 most overexpressed genes, 50% had a chromosomal locus that was amplified in the comparative genomic hybridization data. Although the list of most over- and underexpressed genes was similar between the nodules of different size, the gene set enrichment analysis identified different pathways associated with AIMAH that corresponded to the size; the smaller nodules were mainly enriched for metabolic pathways, whereas p53 signaling and cancer genes were enriched in larger nodules. Confirmatory studies demonstrated that BCL2, E2F1, EGF, c-KIT, MYB, PRKCA, and CTNNB1 were overexpressed in the larger nodules at messenger and/or protein levels. Chromosomal enrichment analysis showed that chromosomes 20q13 and 14q23 might be involved in progression of AIMAH from smaller to larger tumors. Conclusion: Integrated transcriptomic and genomic data for AIMAH provides supporting evidence to the hypothesis that larger adrenal lesions, in the context of this chronic, polyclonal hyperplasia, accumulate an increased number of genomic and, subsequently, transcript abnormalities. The latter shows that the disease appears to start with mainly tissue metabolic derangements, as suggested by the study of the smaller nodules, but larger lesions showed aberrant expression of oncogenic pathways.
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Lalwani, Ashna M., Ali Yilmaz, Halil Bisgin, Zafer Ugur, Sumeyya Akyol, and Stewart Francis Graham. "The Biochemical Profile of Post-Mortem Brain from People Who Suffered from Epilepsy Reveals Novel Insights into the Etiopathogenesis of the Disease." Metabolites 10, no. 6 (June 23, 2020): 261. http://dx.doi.org/10.3390/metabo10060261.
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Epilepsy not-otherwise-specified (ENOS) is one of the most common causes of chronic disorders impacting human health, with complex multifactorial etiology and clinical presentation. Understanding the metabolic processes associated with the disorder may aid in the discovery of preventive and therapeutic measures. Post-mortem brain samples were harvested from the frontal cortex (BA8/46) of people diagnosed with ENOS cases (n = 15) and age- and sex-matched control subjects (n = 15). We employed a targeted metabolomics approach using a combination of proton nuclear magnetic resonance (1H-NMR) and direct injection/liquid chromatography tandem mass spectrometry (DI/LC-MS/MS). We accurately identified and quantified 72 metabolites using 1H-NMR and 159 using DI/LC-MS/MS. Among the 212 detected metabolites, 14 showed significant concentration changes between ENOS cases and controls (p < 0.05; q < 0.05). Of these, adenosine monophosphate and O-acetylcholine were the most commonly selected metabolites used to develop predictive models capable of discriminating between ENOS and unaffected controls. Metabolomic set enrichment analysis identified ethanol degradation, butyrate metabolism and the mitochondrial beta-oxidation of fatty acids as the top three significantly perturbed metabolic pathways. We report, for the first time, the metabolomic profiling of postmortem brain tissue form patients who died from epilepsy. These findings can potentially expand upon the complex etiopathogenesis and help identify key predictive biomarkers of ENOS.
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Stanley, Takara Leah, Lindsay T. Fourman, Lai Ping Wong, Ruslan Sadreyev, James T. Billingsley, Meghan N. Feldpausch, Autumn Boutin, et al. "Growth Hormone Releasing Hormone Reduces Plasma Markers of Immune Activation and Hepatic Immune Pathways in Nonalcoholic Fatty Liver Disease." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A628—A629. http://dx.doi.org/10.1210/jendso/bvab048.1282.
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Abstract Introduction: The GH/IGF-1 axis affects multiple metabolic pathways, and animal models demonstrate that it also modulates immune function. Little is known, however, regarding effects of augmenting GH secretion on immune function in humans. This study used proteomics and gene set enrichment analysis to assess effects of a GH releasing hormone (GHRH) analog, tesamorelin, on circulating immune markers and immune-related gene pathways in the liver in people with HIV (PWH) and NAFLD. We hypothesized that tesamorelin would decrease circulating markers of immune activation in conjunction with previously reported reductions in visceral fat and hepatic triglyceride. Methods: 92 biomarkers associated with immune function (Olink Immuno-Oncology panel) were measured in plasma samples from 61 PWH with NAFLD who participated in a double-blind, randomized, 12-month trial of tesamorelin versus identical placebo. Proteins differentially altered by tesamorelin at a false discovery rate < 0.1 were considered significantly changed. Gene set enrichment analysis targeted to immune pathways was subsequently performed on liver tissue from serial biopsies. Results: Compared to placebo, tesamorelin decreased circulating concentrations of 13 proteins, including four chemokines (C-C Motif Chemokine Ligands 3 [CCL3, effect size -0.38 Log2 fold change], 4 [CCL4, -0.36 Log2 fold change], and 13 [CCL13 or MCP4, -0.42 Log2 fold change] and interleukin-8 [-0.50 Log2 fold change]), two cytokines (interleukin-10 [-0.32 Log2 fold change] and cytokine stimulating factor 1 [-0.22 Log2 fold change]), and four T-cell associated molecules (CD8A [-0.37 Log2 fold change], Cytotoxic And Regulatory T Cell Molecule [CRTAM, -0.47 Log2 fold change], granzyme A [-0.53 Log2 fold change], and adhesion G protein-coupled receptor G1 [ADGRG1, -0.54 Log2 fold change]), as well as arginase-1 [-0.95 Log2 fold change], galectin-9 [-0.26 Log2 fold change], and hepatocyte growth factor [-0.30 Log2 fold change]. No proteins in the panel were significantly increased by tesamorelin. Network analysis indicated close interaction among the gene pathways responsible for the reduced proteins, with imputational analyses suggesting down regulation of a closely related cluster of immune pathways. Targeted transcriptomics using tissue from liver biopsy confirmed an end-organ signal of down-regulated immune pathways, including pathways involved in antigen presentation, complement activation, toll like receptor and inflammatory signaling, and T-cell activation. Conclusions: Long-term treatment with tesamorelin decreased circulating markers of T-cell and monocyte/macrophage activity, with corresponding downregulation of immune pathways in the liver. These findings suggest that augmenting pulsatile GH may ameliorate immune activation in a population with metabolic dysregulation and systemic inflammation.
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Chervo, Maria F., Micaela Parra, Nicolas Bellora, Ezequiel Petrillo, Santiago Madera, Agustina Roldan Deamicis, Kohzoh Mitsuya, et al. "Nuclear ErbB-2-Induced Transcriptome Drives Triple Negative Breast Cancer Growth." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A1028—A1029. http://dx.doi.org/10.1210/jendso/bvab048.2104.
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Abstract Triple negative breast cancer (TNBC) refers to tumors that do not express clinically significant levels of estrogen and progesterone receptors, and lack membrane overexpression or gene amplification of ErbB-2 tyrosine kinase receptor. Transcriptome and proteome heterogeneity of TNBC poses a major challenge to precision medicine. Gene expression analyses have categorized TNBC into distinct molecular subtypes. Up to 78% of clinical TNBCs belong to the basal-like (BL) subtype. Here we found ErbB-2 in an unanticipated scenario: the nucleus of TNBC (NErbB-2). Our study on ErbB-2 alternative splicing, using a PCR-sequencing approach combined with RNA interference, revealed that BL TNBC cells express the canonical ErbB-2 (WTErbB-2), encoded by transcript 1, and the non-canonical isoform c, encoded by alternative transcript 3 (T3). The latter was not previously reported in normal or malignant cells. To characterize the isoform c we designed siRNAs targeting T3 (T3 siRNAs), which silenced up to 93% of said isoform. Transfection of T3 siRNAs into BL cells expressing only isoform c or both isoform c and WTErbB-2 was sufficient to decrease cell proliferation. Intratumoral injections of T3 siRNAs into mice bearing BL TN tumors also blocked in vivo growth. To explore whether isoform c growth-promoting effect is due to its functions as a transcriptional regulator, we performed RNA-seq in BL cells expressing only this isoform. We identified a set of genes differentially regulated in BL cells where we evicted isoform c from the nucleus, as compared to control cells. In the up-regulated group, we found enrichment of pro-apoptotic and tumor suppressor genes and in the down-regulated one, genes involved in proliferation and stemness. We used gene set enrichment analysis (GSEA) to identify the biological processes associated with these isoform c-regulated genes. We found a pronounced enrichment of gene sets related to apoptosis, activation of DNA damage pathways and cell cycle arrest in response to eviction of nuclear isoform c. GSEA also revealed negative regulation of gene sets involved in cell motility, cellular differentiation and growth pathways in BL cells lacking nuclear isoform c expression. These results suggest that NErbB-2 function modulates tumor growth and promotes a metastatic phenotype in TNBC. Furthermore, our clinical findings identified NErbB-2 as an independent predictor of shorter OS (HR 2.54; 95% CI 1.22-5.28; P = 0.013), DFS (HR 2.91; 95% CI 1.44-5.87; P = 0.003), and DMFS (HR 2.59; 95% CI 1.20-5.60; P = 0.015) in 99 TN primary tumors. Our discoveries challenge the present scenario of drug development for personalized BC medicine that focuses on wild-type proteins, which conserve the canonical domains and are located in their classical cellular compartments, highlighting the potential of NErbB-2 isoforms as novel therapeutic targets and clinical biomarkers in TNBC.
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Pikman, Yana, Alexandre Puissant, Gabriela Alexe, Stacey M. Frumm, Linda Ross, Liying Chen, Nina Fenouille, et al. "Targeting Folate Metabolism In Acute Myelogenous Leukemia." Blood 122, no. 21 (November 15, 2013): 3798. http://dx.doi.org/10.1182/blood.v122.21.3798.3798.
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Abstract There is increasing evidence that deranged metabolism is an important mechanism of cancer pathogenesis. We conducted multiple genomic analyses of publicly available acute myelogenous leukemia (AML) data sets that revealed a critical role for one carbon and nucleotide metabolism, particularly mitochondrial, in a subset of AML samples. One carbon metabolism is a complex series of pathways involving several amino acids, the synthesis of purines, thymidylate, S-adenosylmethionine, and the support of cellular methylation reactions. SHMT2, MTHFD2, and MTHFD1L are the major enzymes functional in the one carbon folate pathway in the mitochondria. MTHFD2 is a NAD-dependent, mitochondrial methylenetetrahydrofolate dehydrogenase and cyclohydrolase, derived from a similar trifunctional cytoplasmic protein. In the mitochondria, the formyltetrahydrofolate synthetase activity is performed by MTHFD1L. We noted that these enzymes are downregulated with suppression of MYC. Gene set enrichment analysis (GSEA) of cell lines treated with JQ1, a small molecule BET bromodomain inhibitor which suppresses MYC, showed a significant enrichment in genes of the one carbon pool by folate KEGG pathway. We show that treatment of AML cells with JQ1 causes a decrease in MTHFD2 and MTHFD1L levels. This is recapitulated with knockdown of MYC with four shRNAs in multiple AML cell lines. Analysis of ENCODE ChIP-Seq data revealed MYC binding at SHMT2, MTHFD2 and MTHFD1L promoters, which we confirmed with ChIP-qPCR in human AML cell lines. Moreover, Independent component analysis (ICA) of primary AML samples in The Cancer Genome Atlas (TCGA) showed a significant correlation between high MTHFD2 and high MYC expression and a metabolic gene expression signature. MTHFD2 is differentially expressed in transformed and non-differentiated cells, and is thus an attractive drug target given its limited expression in normal tissues. Knockdown of MTHFD2 with four shRNAs in five AML cell lines caused a decrease in cell proliferation as measured by BrdU incorporation and a decrease in colony formation in methylcellulose. MTHFD2 knockdown also induced myeloid differentiation, as measured by Cd11b expression, morphologic changes and induction of a previously validated AML differentiation gene expression signature. AML cells transduced with MTHFD2-directed shRNAs demonstrated attenuated growth in an orthotopic mouse model of AML at day 15 post-injection. We next deployed a doxycycline inducible shRNA system to demonstrate that shRNAs directed against MTHFD2 cause a decrease in AML burden in mice with established disease as measured by bioluminescence with an increase in survival. Metabolite profiling is currently underway to further elucidate the metabolic consequences of MTHFD2 loss in AML. In summary, in silico analyses of primary patient AML data sets revealed a subset of AML samples enriched for a metabolic gene expression signature. We demonstrate that MYC is a regulator of the one carbon folate pathway, modulating expression of SHMT2, MTHFD2 and MTHFD1L. In vitro and in vivo data strongly supports a critical role for MTHFD2 in AML pathogenesis and its potential as a new target for AML therapy. Disclosures: No relevant conflicts of interest to declare.
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Wang, Jiju, Yunhui Tang, Songcun Wang, Liyuan Cui, Dajin Li, and Meirong Du. "Norepinephrine exposure restrains endometrial decidualization during early pregnancy." Journal of Endocrinology 248, no. 3 (March 2021): 277–88. http://dx.doi.org/10.1530/joe-20-0479.
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Previous studies have focused on the role of norepinephrine on arrhythmias, generalized anxiety disorder, and cancer. This study aimed to investigate the effect of norepinephrine on endometrial decidualization. Artificial decidualization and norepinephrine-treated mice were established in vivo. In vitro, human endometrial stromal cells were treated with MPA and cAMP to induce decidualization. Decidual markers and important signaling molecules during decidualization were detected using quantitative real-time PCR and Western blot. RNA sequencing was performed to determine related signaling pathways. Exposure to excess norepinephrine significantly restricted the induced expression of decidualized markers Dtprp, BMP2, WNT4, and Hand2 in mice. In vitro, 10 µM norepinephrine markedly downregulated the expressions of prolactin, IGFBP1, and PLZF, which are the specifical markers of decidual stromal cells during decidualization. The gene set enrichment analysis showed a significant enrichment in neuroactive ligand–receptor interactions of norepinephrine treatment group. The α1b-adrenergic receptor expression was upregulated by norepinephrine. Interestingly, norepinephrine did not inhibit the expression of IGFBP1 in endometrial stromal cells after silencing α1b-adrenergic receptor, while significantly suppressed the induced decidualization with overexpression of α1b-adrenergic receptor. When α1b-adrenergic receptor was activated, endometrial p-PKC was significantly increased under post-treatment with norepinephrine in vivo and in vitro. In addition, norepinephrine treatment inhibited embryo and fetal development using a normal pregnancy model. Therefore, norepinephrine exposure inhibited endometrial decidualization through the activation of the PKC signaling pathway by upregulating α1b-adrenergic receptor. Our study could explain some female reproductive problems due to stress and provide some novel strategies for this disorder.
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Wu, Jiayan, Junchao Xie, Yanxin Zhao, Li Gong, Xueyuan Liu, and Wangmi Liu. "Serum Calcium is Related to the Degree of Artery Stenosis in Acute Ischemic Stroke." Cellular Physiology and Biochemistry 46, no. 3 (2018): 1189–97. http://dx.doi.org/10.1159/000489069.
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Background/Aims: Acute ischemic stroke is caused by stenosis of artery supplying to brain. We aimed to detect some metabolites in the serum that would be related to the degree of artery stenosis and to analyze potential mechanisms. Methods: Patients diagnosed with acute ischemic stroke were divided into two groups according to their degree of artery stenosis (which was determined by computed tomographic angiography): a mild group (stenosis ≤ 30%) and a severe group (stenosis > 30%). Serum from these patients was collected, and we focused on the differences in the concentrations of calcium, uric acid, low density lipoprotein and homocysteine. The dataset GSE11583 from the Gene Expression Omnibus database was analyzed to find the potential mechanism using bioinformatics methods. Results: Among the four metabolites, the only difference that reached significance between the two groups was in the concentration of calcium in serum (2.27±0.08 mmol/L vs 2.21±0.08 mmol/L). By comparing the gene expression levels between normal endothelial cells and adaptive remodeling endothelial cells in GSE11583, we identified 51 upregulated and 40 downregulated genes in adaptive remodeling endothelial cells. The gene set enrichment analysis revealed that upregulated genes were enriched in a phosphatidylinositol signaling system, which is closely involved in the calcium signaling pathway. Conclusion: Our results suggest that the concentration of serum calcium is higher in patients with more severe artery stenosis lesions and that the phosphatidylinositol signaling system is a key biological pathway involved in this process.
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Ried, Janina S., So-Youn Shin, Jan Krumsiek, Thomas Illig, Fabian J. Theis, Tim D. Spector, Jerzy Adamski, et al. "Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses." Human Molecular Genetics 23, no. 21 (June 13, 2014): 5847–57. http://dx.doi.org/10.1093/hmg/ddu301.
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Su, Lei, Soravis Osataphan, Jessica Desmond, Rui Fang, Jeremy Chimene-Weiss, Liyuan Zhou, Vissarion Efthymiou, Jonathan Dreyfuss, Hui Pan, and Mary-Elizabeth Patti. "Paternal Obesity and SGLT2 Inhibition Alter Expression of Placental Regulatory Genes." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A752—A753. http://dx.doi.org/10.1210/jendso/bvab048.1530.
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Abstract We previously demonstrated that paternal obesity is associated with offspring metabolic risk during later life, and that paternal SGLT2i treatment improves offspring metabolic phenotypes. Since the placenta is a key determinant of prenatal growth and development, we hypothesized the placenta could mediate the impact of paternal obesity and paternal SGLT2i treatment. Male C57BL/6J mice were fed standard chow (Purina 9F) or 60% high-fat diet (HFD, D12492, Research Diet), or 60% HFD plus the SGLT2 inhibitor canagliflozin (CANA, 25 mg/kg/d) for 4 weeks before mating with chow-fed females. Placenta were collected on E16.5, and RNA-seq was performed on placenta from male offspring (paternal chow, pChow, n=4, pHFD, n=5, and pHFD+CANA, n=4), and differentially expressed genes were identified using Limma. Placenta weight was significantly lower in pHFD (0.089±0.004 g, 7 litters from 6 fathers) vs. both pChow (0.108±0.011 g, 4 litters, 4 fathers) and pHFD+CANA (0.107±0.013 g, 5 litters, 5 fathers)(p<0.05). Litter size, fetal or liver weight, or fetal/placental weight ratio did not differ between groups. No genes were differentially expressed in pHFD vs. pChow (FDR<0.1). Gene set enrichment analysis (GSEA) identified significance (FDR<0.05, NES>1.8) for gene sets in steroid metabolic, drug catabolic, and protein-containing complex remodeling processes. Genes responsible for enrichment included cholesterol biosynthesis (Hmgcs1), transport (Apob, Apoa1/2/4, Apom, Apoc1, Vldlr, Pcsk9) and steroid hormone biosynthesis genes (Hsd3b1, Cyp11b1), all upregulated in pHFD by 1.5-3-fold. These results suggest pHFD could potentially affect maternal and fetal cholesterol homeostasis. pHFD+CANA altered expression of 154 genes vs. pHFD (7 up-, 147 down, FDR <0.1, FC >|1.5|); 18 gene sets were downregulated by pHFD+CANA (GSEA NES<-1.8 and FDR<0.05), including the 3 sets upregulated by pHFD. ChEA3 enrichment analysis (ENCODE library) predicted regulation by transcription factors important for cholesterol and sterol biosynthesis (Srebf1/2), embryonic development (Foxa2), & glucose homeostasis (Hnf4g), suggesting these pathways could mediate the “rescue” effect of pHFD+CANA (FDR<0.05). Expression of Foxa2 was significantly downregulated (4-fold) in pHFD+CANA vs. pHFD. We independently analyzed expression of the 78 detected imprinted genes. None were significantly different in pHFD, but both paternally expressed (Nnat) and maternally expressed genes (H19, Phlda2, Meg3, Meg8) were downregulated in pHFD+CANA vs. pHFD by 1.4 to 3.8 fold in pHFD+CANA (p<0.001,FDR<0.1). In summary, paternal SGLT2i reversed the impact of pHFD on placental weight. Robust impact of both pHFD and pSGLT2i on the transcriptome suggests that the placenta is a key mediator of paternal metabolic effects on offspring development and metabolic disease risk, potentially via modification of lipid transport.
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Li, Lian, Hong Zheng, Yubei Huang, Caiyun Huang, Shuang Zhang, Jing Tian, Pei Li, Anil K. Sood, Wei Zhang, and Kexin Chen. "DNA methylation signatures and coagulation factors in the peripheral blood leucocytes of epithelial ovarian cancer." Carcinogenesis 38, no. 8 (June 16, 2017): 797–805. http://dx.doi.org/10.1093/carcin/bgx057.
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Abstract Solid tumors are increasingly recognized as a systemic disease that is manifested by changes in DNA, RNA, proteins and metabolites in the blood. Whereas many studies have reported gene mutation events in the circulation, few studies have focused on epigenetic DNA methylation markers. To identify DNA methylation biomarkers in peripheral blood for ovarian cancer, we performed a two-stage epigenome-wide association study. In the discovery stage, we measured genome wide DNA methylation for 485 000 CpG sites in peripheral blood in 24 epithelial ovarian cancer (EOC) cases and 24 age-matched healthy controls. We selected 96 significantly differentially methylated CpG sites for validation using Illumina’s Custom VeraCode methylation assay in 206 EOC cases and 205 controls and 46 CpG sites validated in the independent replication samples. A set of 6 of these 46 CpG sites was found by the receiver operating characteristic analysis to have a prediction accuracy of 77.3% for all EOC (95% confidence interval: 72.9–81.8%). Pathway analysis of the genes associated with the 46 CpG sites revealed an enrichment of immune system process genes, including LYST (cg16962115, FDR = 1.24E−04), CADM1 (cg21933078, FDR = 1.22E−02) and NFATC1 (cg06784563, FDR = 1.46E−02). Furthermore, DNA methylation status in peripheral blood was correlated with platelet parameters/coagulation factor levels. This study discovered a panel of epigenetic liquid biopsy markers closely associated with overall immunologic conditions and platelet parameters/coagulation systems of the patients for detection of all stages and subtypes of EOC.
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Çorapçıoğlu, M. Erdem, and Hasan Oğul. "miSEA: microRNA set enrichment analysis." Biosystems 134 (August 2015): 37–42. http://dx.doi.org/10.1016/j.biosystems.2015.05.004.
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Cottle, Louise, Ian Gilroy, Kylie Deng, Thomas Loudovaris, Helen E. Thomas, Anthony J. Gill, Jaswinder S. Samra, Melkam A. Kebede, Jinman Kim, and Peter Thorn. "Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells." Metabolites 11, no. 6 (June 7, 2021): 363. http://dx.doi.org/10.3390/metabo11060363.
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Pancreatic β cells secrete the hormone insulin into the bloodstream and are critical in the control of blood glucose concentrations. β cells are clustered in the micro-organs of the islets of Langerhans, which have a rich capillary network. Recent work has highlighted the intimate spatial connections between β cells and these capillaries, which lead to the targeting of insulin secretion to the region where the β cells contact the capillary basement membrane. In addition, β cells orientate with respect to the capillary contact point and many proteins are differentially distributed at the capillary interface compared with the rest of the cell. Here, we set out to develop an automated image analysis approach to identify individual β cells within intact islets and to determine if the distribution of insulin across the cells was polarised. Our results show that a U-Net machine learning algorithm correctly identified β cells and their orientation with respect to the capillaries. Using this information, we then quantified insulin distribution across the β cells to show enrichment at the capillary interface. We conclude that machine learning is a useful analytical tool to interrogate large image datasets and analyse sub-cellular organisation.
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Saben, Jessica, Ying Zhong, Horacio Gomez-Acevedo, Keshari M. Thakali, Sarah J. Borengasser, Aline Andres, and Kartik Shankar. "Early growth response protein-1 mediates lipotoxicity-associated placental inflammation: role in maternal obesity." American Journal of Physiology-Endocrinology and Metabolism 305, no. 1 (July 1, 2013): E1—E14. http://dx.doi.org/10.1152/ajpendo.00076.2013.
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Obesity is associated with low-grade chronic inflammation, which contributes to cellular dysfunction promoting metabolic disease. Obesity during pregnancy leads to a proinflammatory milieu in the placenta; however, the underlying causes for obesity-induced placental inflammation remain unclear. Here, we examine the mechanisms by which saturated fatty acids and inflammatory cytokines induce inflammation in placental trophoblasts. We conducted global transcriptomic profiling in BeWo cells following palmitate and/or TNFα treatment and gene/protein expression analyses of MAPK pathways and characterized downstream transcription factors directly regulating inflammatory cytokines. Microarray analysis revealed increased expression of genes regulating inflammation, stress response, and immediate early response in cytotrophoblasts in response to palmitic acid (PA), TNFα, or a combination of both (PA + TNFα). Both gene ontology and gene set enrichment analysis revealed MAPK and EGR-1 signaling to be upregulated in BeWo cells, which was confirmed via immunoblotting. Importantly, activation of JNK signaling was necessary for increased proinflammatory cytokine ( IL-6, TNFα, and IL-8) and EGR1 mRNA. Consistent with the requirement of JNK signaling, ChIP analysis confirmed the recruitment of c-Jun and other MAPK-responsive immediate early factors on the EGR1 promoter. Moreover, recruitment of EGR-1 on cytokine promoters ( IL-6, TNFα, and IL-8) and an impaired proinflammatory response following knockdown of EGR-1 suggested it as a central component of the mechanism facilitating inflammatory gene expression. Finally, akin to in vitro findings, term placenta from obese women also had both increased JNK and p38 signaling and greater EGR-1 protein relative to lean women. Our results demonstrate that lipotoxic insults induce inflammation in placental cells via activation of JNK/EGR-1 signaling.
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Saxena, Vishal, Dennis Orgill, and Isaac Kohane. "Absolute enrichment: gene set enrichment analysis for homeostatic systems." Nucleic Acids Research 34, no. 22 (November 27, 2006): e151-e151. http://dx.doi.org/10.1093/nar/gkl766.
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Halldorsson, Skarphedinn, Siri Fløgstad Svensson, Henriette Engen Berg, Denise Wolrab, Frode Rise, Alistair Wilkins, Steven Ray Wilson, Michal Holcapek, Kyrre Eeg Emblem, and Einar O. Vik-Mo. "OTEH-7. Molecular characterization of tumor stiffness in glioblastoma." Neuro-Oncology Advances 3, Supplement_2 (July 1, 2021): ii11—ii12. http://dx.doi.org/10.1093/noajnl/vdab070.046.
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Abstract Tumor heterogeneity is one of the hallmarks of glioblastoma multiforme (GBM). Morphology within a given GBM tumor can be extremely variable where some regions of the tumor have a soft, gel-like structure while other areas are dense and fibrous. Abnormal mechanical stress and tissue stiffening caused by cancer proliferation are believed to affect vascularity by compressing structurally weak blood vessels and restricting the supply of nutrients and oxygen to the tissue. These effects contribute to a hypoxic microenvironment that promotes disease progression and chemoresistance. The genetic and molecular mechanisms that govern tissue stiffness within GBM tumors, however, are largely unknown. Magnetic Resonance Elastography (MRE) is an emerging technique for quantifying tissue stiffness non-invasively. We have evaluated 10 GBM patients by MRE imaging obtained prior to surgical resection. During surgery, 2–7 stereotactically navigated biopsies were collected from locations within the tumor with varying degrees of measured stiffness. Biopsies were processed to extract RNA, proteins, polar metabolites and lipids. Biomolecules were analyzed on relevant -omics platforms (RNA sequencing, MS-proteomics and lipidomics, NMR of polar metabolites). Differential expression and gene set enrichment analysis of patient paired biopsies indicate an overall increase in macrophage infiltration and extracellular matrix re-organization associated with increased tumor stiffness. Among the most highly upregulated genes in stiff tumor tissue were lymphatic endothelial hyaluronic acid receptor 1 (LYVE-1) and macrophage receptor with collagenous structure (MARCO), both of which have been associated with immune cell infiltration and tissue stiffness. Our preliminary findings offer novel insights into tumor morphology in GBM that can be inferred from imaging prior to surgery. This can be used to identify tumor regions with high risk of progression and infiltration, thereby informing and guiding surgical strategy and may ultimately lead to novel treatment strategies.
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Dasari, Surendra, Sean A. Newsom, Sarah E. Ehrlicher, Harrison D. Stierwalt, and Matthew M. Robinson. "Remodeling of skeletal muscle mitochondrial proteome with high-fat diet involves greater changes to β-oxidation than electron transfer proteins in mice." American Journal of Physiology-Endocrinology and Metabolism 315, no. 4 (October 1, 2018): E425—E434. http://dx.doi.org/10.1152/ajpendo.00051.2018.
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Excess fat intake can increase lipid oxidation and expression of mitochondrial proteins, indicating remodeling of the mitochondrial proteome. Yet intermediates of lipid oxidation also accumulate, indicating a relative insufficiency to completely oxidize lipids. We investigated remodeling of the mitochondrial proteome to determine mechanisms of changes in lipid oxidation following high-fat feeding. C57BL/6J mice consumed a high-fat diet (HFD, 60% fat from lard) or a low-fat diet (LFD, 10% fat) for 12 wk. Mice were fasted for 4 h and then anesthetized by pentobarbital sodium overdose for tissue collection. A mitochondrial-enriched fraction was prepared from gastrocnemius muscles and underwent proteomic analysis by high-resolution mass spectrometry. Mitochondrial respiratory efficiency was measured as the ratio of ATP production to O2 consumption. Intramuscular acylcarnitines were measured by liquid chromatography-mass spectrometry. A total of 658 mitochondrial proteins were identified: 40 had higher abundance and 14 had lower abundance in mice consuming the HFD than in mice consuming the LFD. Individual proteins that changed with the HFD were primarily related to β-oxidation; there were fewer changes to the electron transfer system. Gene set enrichment analysis indicated that the HFD increased pathways of lipid metabolism and β-oxidation. Intramuscular concentrations of select acylcarnitines (C18:0) were greater in the HFD mice and reflected dietary lipid composition. Mitochondrial respiratory ATP production-to-O2 consumption ratio for lipids was not different between LFD and HFD mice. After the 60% fat diet, remodeling of the mitochondrial proteome revealed upregulation of proteins regulating lipid oxidation that was not evident for all mitochondrial pathways. The accumulation of lipid metabolites with obesity may occur without intrinsic dysfunction to mitochondrial lipid oxidation.