Metabolomics-driven approach to solving a CoA imbalance for improved 1-butanol production in Escherichia coli

High titer 1-butanol production in Escherichia coli has previously been achieved by overexpression of a modified clostridial 1-butanol production pathway and subsequent deletion of native fermentation pathways. This strategy couples growth with production as 1-butanol pathway offers the only available terminal electron acceptors required for growth in anaerobic conditions. With further inclusion of other well-established metabolic engineering principles, a titer of 15 g/L has been obtained. In achieving this titer, many currently existing strategies have been exhausted, and 1-butanol toxicity level has been surpassed. Therefore, continued engineering of the host strain for increased production requires implementation of alternative strategies that seek to identify non-obvious targets for improvement. In this study, a metabolomics-driven approach was used to reveal a CoA imbalance resulting from a pta deletion that caused undesirable accumulation of pyruvate, butanoate, and other CoA-derived compounds. Using metabolomics, the reduction of butanoyl-CoA to butanal catalyzed by alcohol dehydrogenase AdhE2 was determined as a rate-limiting step. Fine-tuning of this activity and subsequent release of free CoA restored the CoA balance that resulted in a titer of 18.3 g/L upon improvement of total free CoA levels using cysteine supplementation. By enhancing AdhE2 activity, carbon flux was directed towards 1-butanol production and undesirable accumulation of pyruvate and butanoate was diminished. This study represents the initial report describing the improvement of 1-butanol production in E. coli by resolving CoA imbalance, which was based on metabolome analysis and rational metabolic engineering strategies.     

Serum metabonomics study of pregnant women with gestational diabetes mellitus based on LC-MS

ObjectiveThrough metabolomics method, the objective of the paper is to differentially screen serum metabolites of GDM patients and healthy pregnant women, to explore potential biomarkers of GDM and analyze related pathways, and to explain the potential mechanism and biological significance of GDM.MethodsThe serum samples from 30 GDM patients and 30 healthy pregnant women were selected to conduct non-targeted metabolomics study by liquid chromatography-mass spectrometry. The differential metabolites between the two groups were searched and the metabolic pathway was analyzed by KEGG database.ResultsMultivariate statistical analysis found that serum metabolism in GDM patients was different significantly from healthy pregnant women, 36 differential metabolites and corresponding metabolic pathways were identified in serum, which involved several metabolic ways like, fatty acid metabolism, butyric acid metabolism, bile secretion, and amino acid metabolism.ConclusionThe discovery of these biomarkers provided a new theoretical basis and experimental basis for further study of the early diagnosis and pathogenesis of GDM. At the same time, LC-MS-based serum metabolomics methods also showed great application values in disease diagnosis and mechanism research.     

Multiple Mass Isotopomer Tracing of Acetyl-CoA Metabolism in Langendorff-perfused Rat Hearts: CHANNELING OF ACETYL-CoA FROM PYRUVATE DEHYDROGENASE TO CARNITINE ACETYLTRANSFERASE*

We developed an isotopic technique to assess mitochondrial acetyl-CoA turnover (≈citric acid flux) in perfused rat hearts. Hearts are perfused with buffer containing tracer [¹³C₂,²H₃]acetate, which forms M5 + M4 + M3 acetyl-CoA. The buffer may also contain one or two labeled substrates, which generate M2 acetyl-CoA (e.g. [¹³C₆]glucose or [1,2-¹³C₂]palmitate) or/and M1 acetyl-CoA (e.g. [1-¹³C]octanoate). The total acetyl-CoA turnover and the contributions of fuels to acetyl-CoA are calculated from the uptake of the acetate tracer and the mass isotopomer distribution of acetyl-CoA. The method was applied to measurements of acetyl-CoA turnover under different conditions (glucose ± palmitate ± insulin ± dichloroacetate). The data revealed (i) substrate cycling between glycogen and glucose-6-P and between glucose-6-P and triose phosphates, (ii) the release of small excess acetyl groups as acetylcarnitine and ketone bodies, and (iii) the channeling of mitochondrial acetyl-CoA from pyruvate dehydrogenase to carnitine acetyltransferase. Because of this channeling, the labeling of acetylcarnitine and ketone bodies released by the heart are not proxies of the labeling of mitochondrial acetyl-CoA.     

Rewired Metabolism in Drug-resistant Leukemia Cells: A METABOLIC SWITCH HALLMARKED BY REDUCED DEPENDENCE ON EXOGENOUS GLUTAMINE*

Cancer cells that escape induction therapy are a major cause of relapse. Understanding metabolic alterations associated with drug resistance opens up unexplored opportunities for the development of new therapeutic strategies. Here, we applied a broad spectrum of technologies including RNA sequencing, global untargeted metabolomics, and stable isotope labeling mass spectrometry to identify metabolic changes in P-glycoprotein overexpressing T-cell acute lymphoblastic leukemia (ALL) cells, which escaped a therapeutically relevant daunorubicin treatment. We show that compared with sensitive ALL cells, resistant leukemia cells possess a fundamentally rewired central metabolism characterized by reduced dependence on glutamine despite a lack of expression of glutamate-ammonia ligase (GLUL), a higher demand for glucose and an altered rate of fatty acid β-oxidation, accompanied by a decreased pantothenic acid uptake capacity. We experimentally validate our findings by selectively targeting components of this metabolic switch, using approved drugs and starvation approaches followed by cell viability analyses in both the ALL cells and in an acute myeloid leukemia (AML) sensitive/resistant cell line pair. We demonstrate how comparative metabolomics and RNA expression profiling of drug-sensitive and -resistant cells expose targetable metabolic changes and potential resistance markers. Our results show that drug resistance is associated with significant metabolic costs in cancer cells, which could be exploited using new therapeutic strategies.     

Influence of ethanol concentration of extraction solvent on metabolite profiling for Salviae Miltiorrhizae Radix et Rhizoma extract by 1H NMR spectroscopy and multivariate data analysis

Salviae Miltiorrhizae Radix et Rhizoma (Danshen in China) and its related preparations are widely used in clinical practice due to its high medicinal value. In recent years, ¹H NMR technology has made great progress and demonstrated its unique advantages in the field of botanical metabolomics. In this study, ¹H NMR-based metabolomics was used to investigate the dissolution of various metabolites in Danshen as a function of ethanol concentration. ¹H NMR spectroscopy of Danshen extract identified 28 metabolites including 6 sugars, 11 amino acids, 3 organic acids, 4 salvianolic acids, and 4 tanshinones. Multivariate statistical analysis was used to classify and compare various Danshen extracts. PCA and HCA were used to obtain a global overview of the similarity in the samples and two-class OPLS-DA models were established for identifying characteristic metabolites. Then, ¹H-qNMR method was used to estimate the concentration of 22 metabolites, which is helpful to further describe the changes in metabolite ratios of various Danshen extracts. The result of this study laid the foundation for further biological activity research, and also provided an important reference for subsequent process research and quality control of Danshen related preparations.     

基于UPLC-QTOF/MS的胆囊癌血清非靶向代谢组学研究

目的:胆囊癌(Gallbladder carcinoma,GBC)是一种常见的胆道系统恶性肿瘤,五年生存率极低,目前临床上缺少有效的诊断标志物。故本研究探索胆囊癌患者与健康人血清的差异性小分子代谢物,用于胆囊癌的定性诊断。方法:本研究以超高效液相色谱联用四极杆飞行时间质谱(UPLC-QTOF/MS)技术为平台,以32例胆囊癌患者和32例健康人血清为研究对象,进行非靶向代谢组学研究分析,用SIMCA-P软件进行PCA和OPLS-DA建模分析,结合T检验结果和代谢物在两组中的差异倍数来筛选潜在小分子代谢标志物,并通过二元逻辑回归分析建立联合诊断模型。结果:溶血磷脂酰胆碱(18:1)(LysoPC(18:1))和十八烷胺(Octadecylamine,ODA)两个代谢物在胆囊癌患者和健康对照组血清中具有显著性差异,差异倍数达到2倍以上。经过二元逻辑回归分析建立诊断模型,两者构建联合诊断的诊断模型为Logit[P=GBC]=26.090*[LysoPC(18:1)]-8.877*[ODA]-113.075,据此建立受试者工作特征曲线(Receiver operating characteristic,ROC)曲线,曲线下面积(Area under the curve,AUC)为0.986,灵敏度为97.1%,特异性为94.6%。结论:LysoPC(18:1)和ODA可作为胆囊癌的潜在诊断标志物,为胆囊癌的诊断提供参考。     

不同病理分期肺腺癌患者血清代谢组学研究

肺癌是当今世界最常见的恶性肿瘤之一,其新发率和死亡率多年来都居于各类癌症之首,其中85%的肺癌都是非小细胞癌,而腺癌又是最常见的非小细胞癌。肺癌的高隐匿性是造成其高死亡率的最主要原因,因此为肺癌的早期诊断和病理分期寻求高效可靠的方法是十分必要的。代谢组学揭示了小分子代谢物的一系列变化,反映了生命活动的最终状态,因此也能直接反映疾病不同发展阶段的病理生理变化。本研究利用核磁共振氢谱(1H-NMR),对在我院就诊的27例不同病理分期的肺腺癌患者和13例健康志愿者进行了血清代谢物分析,运用正交偏最小二乘判别分析(OPLS-DA)对1H-NMR数据进行建模,单变量统计分析对模型进行评价。结果表明肺腺癌患者组的血清中有14种代谢物出现明显差异,其中丙酮酸、丙氨酸、NAC1、乳酸、GPC和甘氨酸比起对照组来有显著上升,而葡萄糖、谷氨酰胺、亮氨酸、异亮氨酸、缬氨酸、丙酮、乙酰乙酸和苏氨酸则显著下降。而在不同分期肺腺癌患者间进行比较后发现,异亮氨酸、乙酰乙酸、NAC1和乳酸的变化与肺腺癌的发展有相关性,可能是肺腺癌早期诊断和分期的潜在生物标志物。