代谢组学详细

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            代谢组学
    (Metabolomics)的概念最早由英国   Nicholson于1999年提出,是系统生物学的有机组成部分。代谢组学旨在对生物体内所有代谢物进行定量分析,并寻找代谢物与生理病理变化的相对关系。代谢组学的研究对象大都是相对分子质量小于1000小分子物质,它们参与到生物体的新陈代谢和生长发育的方方面面,是生物现象的最终产物。


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            相比基因组和蛋白组的研究,代谢组学研究具有独特的应用优势:1. 基因和蛋白表达的微小变化可通过代谢酶的催化反应在代谢物上得以放大,从而使检测和分析更加容易;2. 代谢物的变化除了反应基因组变化外,还受到环境因素、肠道菌群的影响,其动态性更强,对生物体变化的反映更加灵敏(如上图);3. 代谢反应及终产物在各个物种的生物体系中都是类似的,因此,代谢组学方法学通用性更强;4. 代谢组学的技术不需建立全基因组测序及大量表达序列数据库,直接对几乎所有样本类型进行检测,包括全血、血浆/血清、组织、细胞、细胞培养上清、尿液、粪便、食物、唾液、脑脊液、脂肪等。

         
            经过近20年的发展,代谢组学的研究技术手段逐步成熟。目前质谱技术:气质联用技术(GC-MS)和液质联用技术(LC-MS),已逐步取代核磁技术(NMR),成为代谢组学研究的主流技术。GC-MS和LC-MS在其所检测的代谢物谱上各有偏向性(如下图),一般情况两种技术联合使用是常规全谱代谢组分析的主要实验策略。

     


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    技术路线:



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    样品要求:



            代谢组的差异变化是基因组变化放大效应的呈现,不同个体中代谢物的波动性也就较大。另一方面,代谢组学的差异分析一般是基于PCA和PLS-DA等多元统计分析方法进行的,只有较大的样本量抽提出的主成分才具有群体代表性。因此,相对于基因组学等技术方法,代谢组学要求样品的生物学重复要更多。

                           1.细胞样品大于6例
                           2.临床标本大于30例
                           3.模式动物样品大于10例
                           4.植物微生物样品每组大于8例



    应用方向:



                             1.疾病标志物开发        
                             2.肿瘤/癌症        
                             3.代谢疾病/心血管疾病       
                             4.营养学        
                             5.炎症/免疫         
                             6.感染性疾病        
                             7.神经科学        
                             8.植物学        
                             9.药物开发        
                             10.毒理研究         
                             11.微生物研究 


    代谢组学知识问答(Q&A)


    1.代谢组学与基因组学、转录组学、蛋白质组学之间有着明显的差别。
    首先它们的研究对象不同:基因组学、转录组学、蛋白质组和代谢组学的研究对象分别是DNA、mRNA、蛋白质和代谢产物;其次是它们的研究对象之间的对应关系有差别;另外,它们的研究手段也有较大的差异。基因组和转录组学主要依靠日益成熟的DNA测序仪和基因芯片等技术手段;蛋白质组学和代谢组学主要依赖高通量高灵敏度的化学分析仪器。虽然在研究对象和方法上有着明显的区别,基因组学、转录组学、蛋白质组学与代谢组学之间还是存在十分密切的联系:生物信息从DNA、mRNA、蛋白质、代谢产物、细胞、组织、器官、个体的方向进行流动,形成了DNA、mRNA、蛋白质、代谢产物、细胞、组织、器官到个体这几个自下而上、逐级上升的研究层次。

     

    2.与基因组,转录组学和蛋白质组学相比,代谢组学有什么优势?

    1)基因和蛋白表达的微小变化会在代谢物上得到放大,从而使检测更容易;

    2)小分子的产生和代谢是生物机体作用的最终结果,生物体液的代谢产物分析能够更直接,更准确的反映生物体的病理生理状态

    3)代谢组学的研究不需建立全基因组测序及大量表达序列标签(EST)的数据库;

    4)代谢物的种类要远小于基因和蛋白的数目,物质的分子结构简单很多(每个组织中大约为103数量级,而最小的细菌基因组中也有几千个基因;

    5)代谢产物在各个生物体系中都是类似的,所以代谢组学研究中采用的技术更容易在各个领域中应用。

     

    3.代谢组学检测的手段有哪些?

    目前主要技术手段是核磁共振(NMR ),液-质联用(GC-TOF-MS),气-质联用(GC-MS),等。通过检测一系列样品的谱图,再结合化学模式识别方法,可以判断出生物体的病理生理状态,基因的功能,药物的毒性和药效等,并有可能找出与之相关的生物标志物(biomarker)。

     

    4. 代谢组学可以检测哪些样品,应该怎么选择研究的样本类型?

    代谢组学主要研究的是作为各种代谢路径的底物和产物的小分子代谢物(MW<1000)。其样品主要是血清、血浆、尿液、粪便、细胞、细菌、组织、培养液等。实验研究样本类型,取决于课题的研究目的和检测目标。血、唾液、尿、粪便等生物样品无创或微创方式的采集方式便于临床转化和推广,常用于临床诊断的生物标志物发现和验证,探索和解释疾病的病理机制研究常选用组织和细胞样品。

     

    5. 做代谢组学的样本应如何处理?

    代谢研究的样本处理和采集要遵循“保持最鲜活状态”的原则,样本采集后立置于液氮、干冰或者-80°C冰箱中保存,深低温使酶失活,细胞内生化反应停止,阻止样本离体后的进一步代谢活动,效果稳定。具体样品的收集方法可咨询华盈生物技术支持。

    6. 检测菌群相关代谢物,应该选择什么类型的样品,怎么收集?

    粪便是肠道菌群和宿主互作的终端,具有无创、易于获得特点,常被选择用于菌群相关代谢物的检测。大鼠直接取2-3粒;小鼠粪便小,需要收集≥5粒,将待取样的小鼠放进干净的铺有消毒滤纸的笼子里,小鼠排便后立即收集粪便样本。不同的小鼠取样要更换新的滤纸;小鼠粪便采用灭菌离心管,分装好后立即放入-80℃保存;人的粪便样品收集需注意:粪便样本存在异质性,新鲜粪便冻存之前,用无菌棒将样品混匀。粪便可以

     

    7. 代谢组学研究大概需要多少样本数量?

    动物样本:小鼠每组8只,大鼠每组10只;

    临床样本:每组50例,样本重复数越多数据结果越可靠,样本能排除其他疾病干扰或者是性别、年龄、BMI指数均一的样本最好;

    细胞的非靶向代谢组学的量建议在5*106-107,细胞的功能代谢组学最好在107

     

    8. 代谢组学研究怎么设置生物学重复?

    代谢物处于生命活动的下游,其动态波动性相较于基因和蛋白较大,需要生物学重复来增加数据的可靠性和说服力。对于临床样品:30-50例/组,模式动物:10-20例/组,细胞样本:4-6例/组,微生物:8-15例/组。样本重复数量最好大于6个,样本数量过少,后续多元统计分析模型容易过拟合,统计结果不可靠,会受到质疑。每组样本的生物学重复的个数最好相差不要太多,差别不要超过2/3。

     

    9. 同一个实验的样品可不可以分成两批检测?

    建议最好不要分成两批检测,因为这不同时间点仪器的响应可能会发生变化,一些含量低的物质可能只在一个批次里被检出,导致最终的结果不可靠,因此我们应当尽可能的减少人为因素以及仪器对实验结果的影响。

     


    相关文献:


    转录组与代谢组联合分析

    1. He J, et al. Metformin suppressed the proliferation of LoVo cells and induced a time-dependent metabolic and transcriptional alteration. Sci Rep-UK, 2015, 5:17423.

    2. Langley R J, et al. Integrative “omic” analysis of experimental bacteremia identifies a metabolic signature that distinguishes human sepsis from systemic inflammatory response syndromes. Am J Resp Crit Care, 2014, 190(4): 445-455.

    3. Zhou M, et al. Transcriptomic and metabonomic profiling reveal synergistic effects of quercetin and resveratrol supplementation in high fat diet fed mice. J Proteome Res, 2012, 11(10): 4961-4971.

    4. Li H, et al. Transcriptomic and metabonomic profiling of obesity-prone and obesity-resistant rats under high fat diet. J Proteome Res, 2008, 7(11): 4775-4783.

       

    疾病标志物研究

    1. Butte N F, et al. Global metabolomic profiling targeting childhood obesity in the Hispanic population. Am J Clin Nutr, 2015, 102(2): 256-67.

    2. Barrios C, et al. Gut-Microbiota-Metabolite Axis in Early Renal Function Decline. PloS one, 2015, 10(8): e0134311.

    3. Mondul A M, et al. Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha‐tocolpherol, beta‐carotene cancer prevention (ATBC) study. Int J Cancer, 2015, 137(9): 2124-2132.

    4. Yousri N A, et al. A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control. Diabetologia, 2015, 58(8): 1855-1867.

    5. Kurland I J, et al. Integrative metabolic signatures for hepatic radiation injury. PloS one, 2015, 10(6): e0124795.

       

    肿瘤/癌症研究

    1. Modesitt S C, et al. Women at extreme risk for obesity-related carcinogenesis: Baseline endometrial pathology and impact of bariatric surgery on weight, metabolic profiles and quality of life. Gynecol Oncol, 2015, 138(2): 238-245. 

    2. Ventura R, et al. Inhibition of de novo palmitate synthesis by fatty acid synthase induces apoptosis in tumor cells by remodeling cell membranes, inhibiting signaling pathways, and reprogramming gene expression. EBioMedicine, 2015, 2(8): 808-824.

    3. Pan P, et al. Black raspberries suppress colonic adenoma development in ApcMin/+ mice: relation to metabolite profiles. Carcinogenesis, 2015, 36(10): 1245-1253.

    4. Wettersten H I, et al. Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis. Cancer Res, 2015, 75(12): 2541-2552.

    5. Granata A, et al. Global metabolic profile identifies choline kinase alpha as a key regulator of glutathione-dependent antioxidant cell defense in ovarian carcinoma. Oncotarget, 2015, 6(13): 11216.


    代谢疾病/心血管疾病

    1. Modesitt S C, et al. Women at extreme risk for obesity-related carcinogenesis: Baseline endometrial pathology and impact of bariatric surgery on weight, metabolic profiles and quality of life. Gynecol Oncol, 2015; 138(2): 238-245. 

    2. Li Q, et al. Veterinary medicine and multi-omics research for future nutrition targets: Metabolomics and transcriptomics of the common degenerative mitral valve disease in dogs. Omics, 2015; 19(8): 461-470.

    3. Shirai M, et al. Hepatic glutathione contributes to attenuation of thioacetamide-induced hepatic necrosis due to suppression of oxidative stress in diet-induced obese mice. J Toxicol Sci, 2015; 40(4): 509-521.

    4. Menghini R, et al. FoxO1 regulates asymmetric dimethylarginine via downregulation of dimethylaminohydrolase 1 in human endothelial cells and subjects with atherosclerosis. Atherosclerosis, 2015; 242(1): 230-235.

    5. Guo L, et al. Plasma metabolomic profiles enhance precision medicine for volunteers of normal health. PNAS, 2015; 112(35): E4901-E4910.

     

    营养学研究

    1. Li Q, et al. Veterinary medicine and multi-omics research for future nutrition targets: Metabolomics and transcriptomics of the common degenerative mitral valve disease in dogs. Omics, 2015; 19(8): 461-470.

    2. Prasad G L, et al. Global metabolomic profiles reveal differences in oxidative stress and inflammation pathways in smokers and moist snuff consumers. J Metabolomics, 2015; 1(1): 2.

    3. Richter C L, et al. Metabolomic Measurement of Three Timepoints in a Saccharomyces cerevisiae Chardonnay Wine Fermentation. Am J Poentgenol, 2015; ajev. 2015.14062.

    4. Marchesan J T, et al. Association of Synergistetes and Cyclodipeptides with Periodontitis. J Dent Res, 2015; 94(10): 1425-31.

    5. Beltrán-Debón R, et al. The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses. Food & Function, 2015; 6(9): 2957-2966.


    药理/毒理

    1. Okamoto H, et al. Glucagon Receptor Blockade With a Human Antibody Normalizes Blood Glucose in Diabetic Mice and Monkeys. Endocrinology, 2015; 156(8): 2781-2794.

    2. Zhao Y, et al. SoNar, a Highly Responsive NAD+/NADH Sensor, Allows High-Throughput Metabolic Screening of Anti-tumor Agents. Cell Metab, 2015; 21(5): 777-789.

    3. Shirai M, et al. Hepatic glutathione contributes to attenuation of thioacetamide-induced hepatic necrosis due to suppression of oxidative stress in diet-induced obese mice. J Toxicol Sci, 2015; 40(4): 509-521.

    4. Miller D B, et al. Inhaled ozone (O 3)-induces changes in serum metabolomic and liver transcriptomic profiles in rats.Toxicol Appl Pharm, 2015; 286(2): 65-79.

    5. Zhao Z, et al. Metabolite profiling of 5′-AMP induced hypometabolism. Metabolomics, 2014; 10(1): 63-76.


    炎症/免疫/感染

    1. Greineisen W E, et al. Chronic Insulin Exposure Induces ER Stress and Lipid Body Accumulation in Mast Cells at the Expense of Their Secretory Degranulation Response. PloS one, 2015; 10(8): e0130198.

    2. Tarasenko T N, et al. Kupffer cells modulate hepatic fatty acid oxidation during infection with PR8 influenza. BBA-Mol Basis Dis, 2015; 1852(11): 2391-2401.

    3. Patsoukis N, et al. PD-1 alters T-cell metabolic reprogramming by inhibiting glycolysis and promoting lipolysis and fatty acid oxidation. Nat Commun, 2015; 6:6692.

    4. Gerriets V A, et al. Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation. J Clin Invest, 2015; 125(1): 194.

    5. Chuang Y M, et al. Deficiency of the novel exopolyphosphatase Rv1026/PPX2 leads to metabolic downshift and altered cell wall permeability in Mycobacterium tuberculosis. MBio, 2015; 6(2): e02428-14.


    植物学/微生物学

    1. Rabara R C, et al. Tobacco drought stress responses reveal new targets for Solanaceae crop improvement. BMC Genomics, 2015; 16: 484. 

    2. Tuttle J R, et al. Metabolomic and transcriptomic insights into how cotton fiber transitions to secondary wall synthesis, represses lignification, and prolongs elongatio. BMC Genomics, 2015; 16(1): 1.

    3. Rudd J J, et al. Transcriptome and metabolite profiling of the infection cycle of Zymoseptoria tritici on wheat reveals a biphasic interaction with plant immunity involving differential pathogen chromosomal contributions and a variation on the hemibiotrophic lifestyle definition. Plant Physiol, 2015; 167(3): 1158-1185.

    4. Marchesan J T, et al. Association of Synergistetes and Cyclodipeptides with Periodontitis. J Dent Res, 2015; 94(10): 1425-31.

    5. He B, et al. Transmissible microbial and metabolomic remodeling by soluble dietary fiber improves metabolic homeostasis. Sci Rep-UK, 2015; 5.