Immune cell activation and proliferation are closely linked to their metabolic programming. These activated immune cells share many features with tumor cells and are capable to respond to stimulations quickly and reprogram their metabolism to fight with invading pathogens. The corresponding changes in metabolism provide immune cells with energy and bio-precursors to match with necessity of immune functions. The major metabolic pathways utilized by immune cells for the purpose of protecting body from invading pathogens are glycolysis, glutaminolysis, fatty acid synthesis and oxidation, and mitochondria oxidative phosphorylation. These pathways play crucial roles in immune cell activation and differentiation. In this review, we describe how immune cells engage in certain metabolic processes according to their functional needs with a focus on T cells and macrophages.
Due to the potential risk of accidental exposure to gamma radiation, it's critical to identify the biomarkers of radiation exposed creatures. In the present study, NMR based metabolomics combined with multivariate data analysis to evaluate the metabolites changed in the C57BL/6 mouse spleen after 4 days whole body exposure to 3.0 Gy and 7.8 Gy gamma radiations. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification potential biomarkers associated with gamma irradiation. Two different strategies for NMR spectral data reduction (i.e., spectral binning and spectral deconvolution) are combined with normalize to constant sum and unit weight before multivariate data analysis, respectively. The combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Normalized to the constant sum may achieve some pseudo biomarkers. PCA and OPLS results shown that the exposed groups can be well separated from the control group. Leucine, 2-aminobutyrate, valine, lactate, arginine, glutathione, 2-oxoglutarate, creatine, tyrosine, phenylalanine, π-methylhistidine, taurine, myoinositol, glycerol and uracil are significantly elevated while ADP is decreased significantly. These significantly changed metabolites are associated with multiple metabolic pathways and may be potential biomarkers in the spleen exposed to gamma irradiation.
Gas Chromatography coupled with Mass Spectrometry (GC-MS) has been broadly used for the detection of changes in metabolite levels in complex samples. Internal Standards (IS) spiked into a complex background at different concentrations help assess the capability of GC-MS in detecting changes in metabolite levels. This study uses a Latin square design to evaluate the ability of GC-MS in full scan and Single Ion Monitoring (SIM) modes to detect changes among IS spiked into human plasma samples at varying concentrations. Statistical analysis of the data demonstrates the potential of GC-MS to detect true differences over a wide range of concentration levels.
Pancreatic Cancer (PC) is a devastating lethal disease. Therefore, there is an urgent need to develop new intervention strategies. The mammalian Target of Rapamycin (mTOR) is a conserved kinase and master regulator of metabolism and cell growth. mTOR is dysregulated in chronic diseases including diabetes and pancreatic cancer. Recent reports indicate that 50% of Pancreatic Ductal Adenocarcinoma (PDAC) patients are diabetic at the time of diagnosis. Furthermore, the anti-diabetic drug, metformin, which indirectly inhibits mTOR, has emerged as a potential therapeutic target for PC. The objective of this study is to determine the targeted-metabolomics profile in PDAC cell line (HPAF-II) with mTOR inhibition and the interaction between mTOR ATP-competitive inhibitor (Torin 2) and metformin as potential combined therapy in PC. HPAF-II cell lines were cultured in the presence of either Torin 2, metformin, both, or control vehicle. We utilized targeted LC/MS/MS to characterize the alterations in glycolytic and tricarboxylic acid cycle metabolomics, and employed Western Blot analysis for cell signaling activation by phosphorylation. Comparisons between groups were analyzed using one-way Analysis of Variance followed by secondary post-hoc analysis. After 1 h incubation with metformin, AMP concentration was significantly increased compared to other groups (p<0.03). After 24 h, Torin-2 significantly decreased glycolysis intermediates (fructose 1,6-bisphosphate (FBP), and 2-phosphoglycerate/3-phosphoglycerate), TCA intermediate metabolites (citrate/isocitrate, and malate), as well as Nicotinamide Adenine Dinucleotide (NAD+) and Flavin Adenine Dinucleotide (FAD), and ATP levels. When HPAF-II cells were incubated with both Torin-2 and metformin, there was a significant reduction in NAD+ and FAD, suggesting decreased levels of the energy equivalents that are available to the electron transport chain. Targeted metabolomics data indicate that mTOR complexes inhibition by Torin 2 reduced glycolytic intermediates and TCA metabolites in HPAF- II and may synergize with metformin to decrease the electron acceptors NAD+ and FAD which may lead to reduced energy production.
Nuclear Magnetic Resonance (NMR) spectroscopy is a nondestructive, quantitative, reproducible, untargeted and unbiased method that requires no or minimal sample preparation, and is one of the leading analytical tools for metabolomics research [1-3]. The easy quantification and the no need of prior knowledge about compounds present in a sample associated with NMR are advantageous over other techniques [1,4]. 1H NMR is especially attractive because protons are present in virtually all metabolites and its NMR sensitivity is high, enabling the simultaneous identification and monitoring of a wide range of low molecular weight metabolites.
BACKGROUND:This study's aim was to compare the dental biofilm metabolite-profile of caries-active (N=11) or caries-free (N=4) children by gas chromatography-mass spectrometry (GC/MS) analyses.METHODS:Samples collected after overnight fasting, with or without a previous glucose rinse, were combined for each child based on the caries status of the site, re-suspended in ethanol and analyzed by GC/MS.RESULTS:Biofilm from caries-active sites exhibited a different chromatographic profile compared to caries-free sites. Qualitative and quantitative analysis suggested a special cluster of branched alcohols and esters present at substantially higher intensity in biofilms of caries-active sites.CONCLUSIONS:This pilot study indicates that there are metabolites present in the biofilm which have the potential to provide a characteristic metabolomics signature for caries activity.
1H-NMR metabolomics was used to investigate the changes of metabolites in the lungs of mice with and without being exposed to a controlled amount of cigarette smoke. It was found that the concentrations of adenosine derivatives (i.e. ATP, ADP and AMP), inosine and uridine were significantly changed in the lungs of mice exposed to cigarette smoke when compared with controls regardless the mice were obese or of regular weight. The decreased ATP, ADP, AMP and elevated inosine suggested that the deaminases in charge of adenosine derivatives to inosine derivatives conversion would be significantly changed in the lungs of mice exposed to cigarette smoke. Indeed, transcriptional study confirmed that the concentrations of adenosine monophosphate deaminase 2 and adenosine deaminase 2 were significantly changed in the lungs of mice exposed to cigarette smoke. We also found that the ratio of glycerophosphocholine (GPC) to phosphocholine (PC) was significantly increased in the lungs of obese mice compared with those of the regular weight mice. The GPC/PC ratio was further elevated in the lungs of obese group exposed to cigarette smoke.
Melanoma is a malignant tumor of melanocytes with high capability of invasion and rapid metastasis to other organs. Malignant melanoma is the most common metastatic malignancy found in Gastrointestinal Tract (GI). In this work, the 1H NMR-based metabolomics approach is used to investigate the metabolite profile differences of stomach tissue extracts of metastatic B16-F10 melanoma and control groups in C57BL/6J mouse and to search for specific metabolite biomarker candidates. Principal Component Analysis (PCA), an unsupervised multivariate data analysis method, is used to detect possible outliers, while Orthogonal Projection to Latent Structure (OPLS), a supervised multivariate data analysis method, is employed to evaluate important metabolites responsible for discriminating the control and the melanoma groups. Both PCA and OPLS results reveal that the melanoma group can be well separated from its control group. Among the 50 identified metabolites, it is found that the concentrations of 19 metabolites are significantly changed with the levels of O-phosphocholine and hypoxanthine down-regulated while the levels of isoleucine, leucine, valine, isobutyrate, threonine, cadaverine, alanine, glutamate, glutamine, methionine, citrate, asparagine, tryptophan, glycine, serine, uracil, and formate up-regulated in the melanoma group. These significantly changed metabolites are associated with multiple biological pathways and may be potential biomarkers for metastatic melanoma in stomach.
Each year about 1.4 million people die from lung cancer worldwide. Despite efforts in prevention, diagnosis and treatment, survival rate remains poor for this disease. This unfortunate situation is largely due to the fact that a high proportion of cases are diagnosed at advanced stages, highlighting the great need for identifying new biomarkers in order to improve early diagnosis and treatment. Recent studies on microRNAs have not only shed light on their involvement in tumor development and progression, but also suggested their potential utility as biomarkers for subtype diagnostics, staging and prediction of treatment response. This review article summarizes the impact of microRNAs on lung cancer biology, and highlights their role in the detection and classification of lung cancer as well as direct targets for drug development.
BACKGROUND:Alzheimer's disease (AD) is the most common neurodegenerative disorder, manifesting clinical symptoms of cognitive impairment and dementia. The vast majority of cases are late onset AD (LOAD), which are genetically heterogeneous and occur sporadically. The neuropathological changes of LOAD can be reproduced by supplementing a rabbit's diet with 2% cholesterol for 12 weeks.METHODS:In the present study, a non-targeted Fourier transform ion cyclotron resonance mass spectrometry based metabolomics approach and multivariate statistics were used to survey the effect of cholesterol on cerebrospinal fluid metabolites over a 12 week time-course.RESULTS:Of the 6515 accurate masses detected in the rabbit CSF, 375 showed significant differences in intensity (p < 0.05) between samples collected at different time points. Further analysis of top 95 (p < 0.01) revealed four clusters of metabolites with different expression patterns throughout the course of the cholesterol treatment. The majority of effects were observed in 12 weeks of cholesterol treated samples, while certain masses showed transient changes at 8 weeks but returned back to near the levels of the controls at 12 weeks. The masses that started to change 8 weeks into the treatment may represent early metabolic changes linked to certain defects in the brain related to AD development. Putative metabolite identifications revealed certain phosphorylated glycerolipids and peptide fragments decreased after 8 weeks of cholesterol treatment.CONCLUSION:This study showed that there are specific metabolic perturbations which occur in the CSF as a result of high cholesterol loading. Given the changes of short peptide fragments in particular, the effects are likely the consequence of brain degeneration caused by high cholesterol levels. Further investigations of these masses will lead to a greater understanding of the metabolic mechanisms associated with cholesterol-related AD development. Some of these masses may be used as candidates for the development of diagnostic, prognostic or theranostic markers.
BACKGROUND CANCER SIGNIFICANCE AND QUESTION BioProspecting is a novel approach that enabled our team to mine genetic marker related data from the New England Journal of Medicine (NEJM) utilizing Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) and the Human Gene Ontology (HUGO). Genes associated with disorders using the Multi-threaded Clinical Vocabulary Server (MCVS) Natural Language Processing (NLP) engine, whose output was represented as an ontology-network incorporating the semantic encodings of the literature. Metabolic functions were used to identify potentially novel relationships between (genes or proteins) and (diseases or drugs). In an effort to identify genes important to transformation of normal tissue into a malignancy, we went on to identify the genes linked to multiple cancers and then mapped those genes to metabolic and signaling pathways. FINDINGS Ten Genes were related to 30 or more cancers, 72 genes were related to 20 or more cancers and 191 genes were related to 10 or more cancers. The three pathways most often associated with the top 200 novel cancer markers were the Acute Phase Response Signaling, the Glucocorticoid Receptor Signaling and the Hepatic Fibrosis/Hepatic Stellate Cell Activation pathway. MEANING AND IMPLICATIONS OF THE ADVANCE This association highlights the role of inflammation in the induction and perhaps transformation of mortal cells into cancers. MAJOR FINDINGS BioProspecting can speed our identification and understanding of synergies between articles in the biomedical literature. In this case we found considerable synergy between the Oncology literature and the Sepsis literature. By mapping these associations to known metabolic, regulatory and signaling pathways we were able to identify further evidence for the inflammatory basis of cancer.
these evidences doesn’t exclude the differential efficacy of probiotics in human subjects, hence very well controlled/ designed studies are urgently needed to check the efficacy of probiotics in human health against obesity and diabetes. A deeper knowledge of our gut ecology will be mandatory in the hope to target much more specific probiotic intervention. In this regards it is of interest the recent intriguing review from Rastmanesh [13] suggesting that a high-polyphenol and selectively-restricted probiotic diet could represent a novel strategy for planning a successful dietary regimen and/or neutraceutical/ pharmaceutical preparations to achieve and maintain a normal body weight in obese individuals. Overall, such studies will also give opportunities to industries to think about the risk vs safety of probiotic formulations for obesity and diabetes in consumers, worldwide.
