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Current Metabolomics最新文献

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Model-guided Metabolic Gene Knockout of pflA in Escherichia coli Increases Succinic Acid Production from Glycerol Carbon Source 模型引导的大肠杆菌pflA代谢基因敲除增加甘油碳源琥珀酸产量
Pub Date : 2019-01-22 DOI: 10.2174/2213235X06666181012143004
Bashir Sajo Mienda, A. Adamu, M. S. Shamsir
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引用次数: 1
Volatile Metabolomics with Focus on Fungal and Plant Applications - A Review 挥发性代谢组学在真菌和植物中的应用综述
Pub Date : 2019-01-22 DOI: 10.2174/2213235X06666180924103416
Jinyan She, D. Mlsna, R. Baird, Chathuri U. G. Mohottige, T. Mlsna
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引用次数: 4
Understanding Prostate Cancer Cells Metabolome: A Spectroscopic Approach 了解前列腺癌细胞代谢组:一种光谱方法
Pub Date : 2019-01-22 DOI: 10.2174/2213235X07666181122124106
Francisco Santos, S. Magalhães, M. Henriques, B. Silva, I. Valença, D. Ribeiro, M. Fardilha, A. Nunes
Prostate cancer (PCa) is the second most common neoplasia in men. Because it is often diagnosed at a late stage, mortality rates remain high. Studying cancer metabolome, which reflects early changes that occur in cells, has gained relevance and may contribute to the identification of early diagnostic biomarkers and understanding tumor biology. Fourier-transform infrared (FTIR) spectroscopy is a metabolomics technique that probes the biochemical composition of the analyzed samples and allows to discriminate samples with distinct metabolic profiles, allowing the discrimination between cancerous and non-cancerous samples. In this study, FTIR spectra were acquired from PCa and normal prostate cell lines and analyzed by principal component analysis (PCA). Our results indicate a clear discrimination between the different cell lines, meaning that they exhibit distinct metabolic profiles. This discrimination can be attributed to an altered lipid metabolism (3000-2800 cm-1, 1800-1700 cm-1 and 15001400 cm-1) and changes in protein conformation (1700-1600 cm-1). These results suggest that studying cancer metabolome with FTIR spectroscopy not only allows the understanding of tumor metabolic behavior and may be useful to the development of new therapeutic targets.
前列腺癌(PCa)是男性第二常见的肿瘤。由于该病往往在晚期才被诊断出来,死亡率仍然很高。研究反映细胞早期变化的癌症代谢组已经获得了相关性,并可能有助于识别早期诊断生物标志物和了解肿瘤生物学。傅里叶变换红外(FTIR)光谱是一种代谢组学技术,它探测被分析样品的生化组成,并允许区分具有不同代谢谱的样品,从而区分癌变和非癌变样品。本研究采集了前列腺癌和正常前列腺细胞株的FTIR光谱,并用主成分分析(PCa)进行了分析。我们的结果表明不同细胞系之间存在明显的区别,这意味着它们表现出不同的代谢谱。这种区别可归因于脂质代谢的改变(3000-2800 cm-1、1800-1700 cm-1和15001400 cm-1)和蛋白质构象的改变(1700-1600 cm-1)。这些结果表明,利用FTIR光谱研究肿瘤代谢组不仅可以了解肿瘤的代谢行为,而且可能有助于开发新的治疗靶点。
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引用次数: 6
Genome-scale Metabolic Modelling for Succinic Acid Production in Escherichia coli 大肠杆菌琥珀酸生产的基因组代谢模型
Pub Date : 2019-01-22 DOI: 10.2174/2213235x07666181219110630
Bashir Sajo Mienda
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引用次数: 1
Meet Our Associate Editor 认识我们的副主编
Pub Date : 2019-01-22 DOI: 10.2174/2213235X0603190122154018
F. Assadi-Porter
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引用次数: 0
Metabolite Profiling of Fruit and Seed Extracts of Garcinia Xanthochymus Using RP-HPLC-ESI-Q-TOF-MS and Progenesis QI 利用反相高效液相色谱- esi - q - tof - ms和Progenesis QI分析黄藤黄果实和种子提取物的代谢物谱
Pub Date : 2019-01-22 DOI: 10.2174/2213235X06666181005143806
Shankara H. Nanjegowda, Manasa G. Papanna, T. Bharathi, Raghu Ram Achar Rr, H. Prakash, S. N. Swamy, P. Mallu
Natural products research is the most enormous field of research in terms of the amount of data and importance of information. Natural products discovery and metabolomics deals with a crucial mode of representation of the profile of biologically active metabolites. In this regard, the profiling of the chemical makeup of complex natural plant extracts necessarily requires employing sophisticated and advanced analytical methods like RP-HPLC–ESI-Q-TOF-MS as well as data mining and processing methods. The genus Garcinia (Clusiaceae) contains phenolic, flavonoids, xanthones, triterpenes, and benzophenones which have been reported for their significant biological properties. Due to its high content of secondary metabolites and its large domestic usage, we have developed a simple, rapid and precise method to characterize all the secondary metabolites using Reverse-Phase Ultra Performance Liquid Chromatography coupled to Electrospray Ionization Quadruple Time-of-Flight Mass Spectrometry (RP-HPLC–ESI-Q- TOF-MS) for the hydro-methanolic extract. A total of about 3443 secondary metabolites from the fruit and 3757 secondary metabolites from the seed were identified by the Progenesis-QI data analysis. Among these a total of 74 compounds from fruits and 86 polar compounds from seeds were manually identified using the mass error limit of < ± 5 ppm including the score less than 40. The unexplored bioactives belonging to the class of glycosides, flavones, xanthones, organic acids and other phenolic derivatives. Garcinia xanthochymus was found to contain significant number of diverse phytochemical components. These results indicate the profile of molecules present in G. xanthochymus and will be helpful for industries and researchers involved in isolation of their molecules of interest.
就数据量和信息重要性而言,天然产物研究是最庞大的研究领域。天然产物发现和代谢组学处理生物活性代谢物剖面的一个关键模式。在这方面,分析复杂的天然植物提取物的化学组成必须采用复杂和先进的分析方法,如RP-HPLC-ESI-Q-TOF-MS,以及数据挖掘和处理方法。藤黄属(藤黄科)含有酚类、黄酮类、山酮类、三萜和二苯甲酮类物质,具有重要的生物学特性。由于其次生代谢物含量高且国内使用量大,我们开发了一种简单、快速、精确的方法,使用反相超高效液相色谱-电喷雾电离四倍飞行时间质谱(RP-HPLC-ESI-Q - TOF-MS)对水甲醇提取物进行表征。通过Progenesis-QI数据分析,共鉴定出3443种次生代谢物和3757种次生代谢物。在质量误差限<±5 ppm的情况下,人工鉴定了74种来自果实的化合物和86种来自种子的极性化合物,其中分数小于40。未开发的生物活性物质属于苷类、黄酮类、山酮类、有机酸类和其他酚类衍生物。黄花藤黄含有大量不同的植物化学成分。这些结果揭示了黄茎草中存在的分子特征,将有助于工业和研究人员分离其感兴趣的分子。
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引用次数: 1
Urinary Exosomal Lipidomics Reveals Markers for Diabetic Nephropathy 尿外泌体脂组学揭示糖尿病肾病的标志物
Pub Date : 2018-07-16 DOI: 10.2174/2213235X05666170607135244
Sangeeta Kumari and Ajeet Singh
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引用次数: 9
Editor's Perspective: Metabolomics Currently 编者观点:代谢组学
Pub Date : 2018-07-16 DOI: 10.2174/2213235x0602180716092501
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引用次数: 0
Liquid Chromatography Mass Spectrometry (LCMS) and Phenotype Microarray Profiling of Ovarian Cancer Cells After Exposure to Cisplatin 顺铂暴露后卵巢癌细胞的液相色谱质谱(LCMS)和表型微阵列分析
Pub Date : 2018-07-16 DOI: 10.2174/2213235X05666170203120840
Sanad Alonezi, Mohammed Al Washih, C. Clements, L. Young, V. Ferro, D. Watson
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引用次数: 3
Spectroscopic Features of Cancer Cells: FTIR Spectroscopy as a Tool for Early Diagnosis 癌细胞的光谱特征:FTIR光谱作为早期诊断的工具
Pub Date : 2018-07-16 DOI: 10.2174/2213235X06666180521084551
Francisco Santos, S. Magalhães, M. Henriques, M. Fardilha, A. Nunes
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引用次数: 13
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Current Metabolomics
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