Abstract:Bisphenol A (BPA) is a widely used material known to cause adverse effects in humans and other mammals. To date, little is known about the global metabolomic alterations caused by BPA using urinalysis. Sprague-Dawley rats were orally administrated BPA at the levels of 0, 0.5 μg/kg/day and 50 mg/kg/day covering a low dose and a reference dose for 8 weeks. We conducted a capillary electrophoresis in tandem with electrospray ionization time-of-flight mass spectrometry based nontargeted metabolomic analysis using … Show more
“…Currently, integration of multiple layers of information is promising for acquiring a precise understanding of disease. The combination of metabolomic results and metabolic enzyme gene expression data can support the metabolomic results, and also provide deeper insight into the metabolomic findings (8).…”
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Elucidating the molecular network that is altered in PTC may lead to the identification of the critical insight into the pathogenesis of PTC. Thus far, little is known regarding the global metabolomic alterations of PTC. Gas chromatography coupled with mass spectrometry-based metabolomics was used to analyze metabolomic alterations in matched PTC and normal thyroid tissues obtained from the patients. Multivariate statistical analyses were employed to determine the significant metabolomic differences. The mRNA levels of the associated metabolic enzyme genes were further assayed with reverse transcription-quantitative polymerase chain reaction analysis. Principal component analysis, partial least-squares discriminant analysis (PLS-DA) and orthogonal PLS-DA models were established, which could clearly separate human normal thyroid and PTC samples, and identified that metabolites in carbohydrate metabolism, including glucose, fructose, galactose, mannose, 2-keto-D-gluconic acid and rhamnose, consistently decreased, while metabolites in nucleotide metabolism, including malonic acid and inosine, and lipid metabolism, including cholesterol and arachidonic acid, significantly altered in PTC. Furthermore, the mRNA levels of metabolic enzyme genes, including glucose-6-phosphate dehydrogenase, phosphoglycerate kinase 1, lactate dehydrogenase A, phosphoglycerate dehydrogenase and prostaglandin-endoperoxide synthase 2, significantly increased in PTC. Based on the metabolomic and mRNA data, various metabolites may be used for increased synthesis of nucleotides and oncogenic lipids in PTC, which may contribute to the pathogenesis of PTC. The present study provides a new understanding of the dysregulated metabolism in PTC and identifies potential avenues for the therapeutic intervention for this disease.
“…Currently, integration of multiple layers of information is promising for acquiring a precise understanding of disease. The combination of metabolomic results and metabolic enzyme gene expression data can support the metabolomic results, and also provide deeper insight into the metabolomic findings (8).…”
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Elucidating the molecular network that is altered in PTC may lead to the identification of the critical insight into the pathogenesis of PTC. Thus far, little is known regarding the global metabolomic alterations of PTC. Gas chromatography coupled with mass spectrometry-based metabolomics was used to analyze metabolomic alterations in matched PTC and normal thyroid tissues obtained from the patients. Multivariate statistical analyses were employed to determine the significant metabolomic differences. The mRNA levels of the associated metabolic enzyme genes were further assayed with reverse transcription-quantitative polymerase chain reaction analysis. Principal component analysis, partial least-squares discriminant analysis (PLS-DA) and orthogonal PLS-DA models were established, which could clearly separate human normal thyroid and PTC samples, and identified that metabolites in carbohydrate metabolism, including glucose, fructose, galactose, mannose, 2-keto-D-gluconic acid and rhamnose, consistently decreased, while metabolites in nucleotide metabolism, including malonic acid and inosine, and lipid metabolism, including cholesterol and arachidonic acid, significantly altered in PTC. Furthermore, the mRNA levels of metabolic enzyme genes, including glucose-6-phosphate dehydrogenase, phosphoglycerate kinase 1, lactate dehydrogenase A, phosphoglycerate dehydrogenase and prostaglandin-endoperoxide synthase 2, significantly increased in PTC. Based on the metabolomic and mRNA data, various metabolites may be used for increased synthesis of nucleotides and oncogenic lipids in PTC, which may contribute to the pathogenesis of PTC. The present study provides a new understanding of the dysregulated metabolism in PTC and identifies potential avenues for the therapeutic intervention for this disease.
“…Moreover, metabolic patterns between WT and KO cells differed markedly between days 1 and 3 (Supplementary Figure and Supplementary table). Among 196 metabolites detected on day 1, 35 were significantly ( P < 0.05 by Welch's t ‐test and q < 0.2 by false discovery rate method) increased and eight were significantly decreased in KO cells compared with WT cells (Supplementary table). After classifying these compounds and mapping the metabolites into general biochemical pathways, as illustrated in KEGG (http://www.genome.jp/kegg/kegg2.html), the metabolic differences between WT and KO cells were attributable to the pentose phosphate pathway (PPP) and glycolysis (seven out of 43), but did not involve the TCA cycle (changes in glucose metabolite concentrations, glycolysis, PPP, and the TCA cycle are shown in Figure C.)…”
Previously, we showed that drs contributes to suppression of malignant tumor formation in drs-knockout (KO) mice. In this study, we demonstrate the regulation of glucose metabolism by drs using comparisons of drs-KO and wild-type (WT) mouse embryonic fibroblasts (MEFs). Extracellular acidification, lactate concentration, and glucose consumption in drs-KO cells were significantly greater than those in WT cells. Metabolomic analyses also confirmed enhanced glycolysis in drs-KO cells. Among glycolysis-regulating proteins, expression of lactate dehydrogenase (LDH)-B was upregulated at the post-transcriptional level in drs-KO cells and increased LDH-B expression, LDH activity, and acidification of culture medium in drs-KO cells were suppressed by retroviral rescue of drs, indicating that LDH-B plays a critical role for glycolysis regulation mediated by drs. In WT cells transformed by activated K-ras, expression of endogenous drs mRNA was markedly suppressed and LDH-B expression was increased. In human cancer cell lines with low drs expression, LDH-B expression was increased. Database analyses also showed the correlation between downregulation of drs and upregulation of LDH-B in human colorectal cancer and lung adenocarcinoma tissues. Furthermore, an LDH inhibitor suppressed anchorage-independent growth of human cancer cells and MEF cells transformed by activated K-ras. These results indicate that drs regulates glucose metabolism via LDH-B. Downregulating drs may contribute to the Warburg effect, which is closely associated with malignant progression of cancer cells.
“…2 A), but none provided explanation regarding the selection of the summary statistics. Median survival time from survival analysis was presented in one study which measured mice’s survival (26) and levels in metabolites, mRNA and protein by bisphenol A exposure were presented as median with interquartile range in one paper (35) . For the dispersion of the data, SEM/SE was most frequently used (66/113, 58%), followed by SD (39/113, 34%) ( Fig.…”
Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.
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