基于多种分析技术的代谢组学方法研究与应用
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摘要
代谢组学是关于定性和定量描述生物体内源性小分子代谢物的整体及其对内因和外因变化应答规律的科学。作为“后基因组学”时代的一门新兴学科和技术,代谢组学已广泛应用于生命科学相关领域。本论文建立了基于1H核磁共振(1HNMR)、高分离度快速分离液相色谱(RRLC)以及高效液相色谱-质谱(HPLC-MS)的代谢组学研究方法,并将这些方法应用于Arthus反应疾病病理机制研究、肿瘤诊断相关标志物的筛选和纳米材料的毒性机制研究中。本论文的主要研究内容包括以下几个方面：
1.建立了2,4-二硝基氟苯(DNFB)柱前衍生化RRLC同时测定大鼠和人血清中23种氨基酸的分析方法。RRLC分离采用Agilent Zorbax Eclipse Plus C18(4.6mm×50mm,1.8μm)反相色谱柱,柱温45℃,流动相采用乙腈-甲醇-10mmol·L-1乙酸铵溶液梯度洗脱,流速1.5mL·min-1.进样量5μL,紫外检测波长360nm。23种氨基酸在10min内可达到良好分离,浓度分别在1～500μmol·L-1范围内线性关系良好(r>0.9962),定量下限为1μmol·L-1,日内、日间RSD值分别在0.32%～3.09%和0.67%～5.82%之间。将建立的方法用于大鼠和人血清中23种氨基酸的同时测定,回收率分别在90.8%～106.0%和88.2%～106.4%之间,RSD值分别在1.8%～4.7%和1.4%～8.5%之间。2.利用基于1HNMR的代谢指纹谱和RRLC的氨基酸靶标分析结合多变量数据处理方法对Arthus反应大鼠的体内代谢特点进行了研究,得到了一些互补信息。将采集的血清和尿液样本进行1HNMR分析,分别发现17个和16个与疾病密切相关的代谢物；血清样本RRLC氨基酸靶标分析发现8个与疾病密切相关的氨基酸。去除共同的代谢物,采用两种代谢组学分析模式,在Arthus反应大鼠血清和尿液中共鉴别到35个与疾病密切相关的特征性代谢物。结果显示,Arthus反应已经引起明显的肝、肾功能损伤,且伴随多条代谢途径的紊乱,如三羧酸循环(TAC)、肠道菌群代谢、脂质和细胞膜代谢、葡萄糖代谢、脂肪酸β-氧化、氨基酸代谢以及酮体的生成和分解等。3.分别建立基于1HNMR和RRLC互补的代谢指纹谱分析方法和氨基酸靶标分析方法,考察25例食管癌患者和25例正常健康人血清的代谢组学差异,进而寻找与食管癌发生、发展密切相关的生物标志物群。结合OPLS-DA对检测数据进行模式识别,结果显示采用两种分析模式均能清晰地区分食管癌患者和正常对照血清,说明相对于正常人而言,食管癌患者的血清代谢谱发生明显改变,并有统计学意义。基于RRLC的氨基酸靶标分析对于食管癌患者和正常健康人之间的区分能力要稍好于基于1HNMR的代谢指纹谱分析,说明代谢物靶标分析定量准确、特异性强,可以作为代谢指纹谱分析的有利补充,在代谢组学研究中具有很广阔的应用前景。本研究共发现19个内源性小分子代谢物在食管癌患者与正常健康人血清中的含量存在显著性差异,提示这些代谢物的异常可能与食管癌患者体内的代谢紊乱存在密切关系,即为潜在的肿瘤生物标志物。通过代谢途径研究发现,与正常人相比,食管癌患者体内多条代谢途径如糖酵解、脂质代谢、能量代谢、酮体的生成和分解、三羧酸循环以及氨基酸代谢等均发生了不同程度的紊乱。
4.采用1HNMR代谢指纹谱分析和RRLC氨基酸靶标分析方法并结合多变量数据处理方法,开展了25例肺癌患者和25例正常健康人血清样品的代谢组学研究。结果显示,两种分析模式均能很好地区分肺癌患者和正常健康人,肺癌患者和正常健康人的血清代谢谱存在明显差异,说明肺癌患者体内的生物代谢通路发生了一定的改变。本研究共发现15个内源性小分子代谢物在肺癌患者与正常健康人血清中的含量存在显著性差异。对差异代谢物的生物代谢路径进行分析发现,肺癌患者的糖酵解代谢显著增加,另外,脂质代谢、氨基酸代谢、酮体的合成和分解等代谢通路均发生不同程度的紊乱。
5.建立了基于HPLC-MS技术的代谢组学研究方法对表面包裹聚乙二醇(PEG)的ZnO量子点染毒大鼠的血清和尿液进行分析,从生物体整体代谢水平探讨了ZnO量子点的生物学效应(毒性)。雄性SD大鼠经尾静脉注射一次染毒1和10mg/kg ZnO QDs-PEG生理盐水溶液后24和72h,采用XCMS online分析其血清和尿液的HPLC-MS代谢谱变化。结果表明,1和10mg/kg ZnO QDs-PEG染毒组大鼠染毒后24、72h的血清和尿液代谢谱与正常对照组相比存在明显差异,没有与组织结构及功能严重受损相关的代谢物发现,说明表面包裹PEG的ZnO量子点毒性较小,不会导致明显的机体组织功能损伤,但引起了轻微的代谢紊乱。
Metabolomics, a relatively novel methodology arising from the post-genomics era, has been increasingly recognized as a valuable complementary approach to other well-established 'omic' sciences to aid in the assessment of disease and toxicity. Metabolic profiling is the comprehensive studying of large numbers of all endogenous low molecular weight metabolites and their roles in various disease states in a global view. In the present study, The proton nuclear magnetic resonance (1H NMR), rapid resolution liquid chromatography (RRLC) and high performance liquid chromatography-mass spectrometry (HPLC-MS) based metabolomic methodology were established and utilized for the research of pathophysiological mechanisms of Arthus reaction, tumor biomarkers discovery and nanotoxicity. The main contents and results are as follows:
1. A RRLC method was developed for the simultaneous determination of23amino acids in rat and human serum after pre-column derivatization with2,4-dinitrofluorobenzene (DNFB). The amino acid derivatives were separated on an Agilent Zorbax Eclipse Plus Cis (4.6mm x50mm,1.8um) column at45℃. Ultraviolet (UV) detection was set at360nm. Good separation of23amino acids was achieved within10min with a ternary gradient elution of mobile phase at a flow rate of1.5mL·min-1. Calibration curves were linear over the range from1to500μmol·L-1with coefficients0.9962or better for each amino acid. The lower limits of quantification (LLOQ) of all23amino acids were1.0μmol·L-1with signal-to-noise (S/N) ratio≥14. Intra-and Inter-day precisions, expressed as relative standard deviation (RSD) percentages, were ranged from0.32%to3.09%and0.67%to5.82%, respectively. Finally, it was successfully applied to the determination of amino acids in rat and human serum with recoveries ranged from90.8%to106.0%and88.2%to106.4%, and RSD percentages ranged from1.78%to4.68%and1.4%to8.5%, respectively.
2. Arthus reaction (AR), a type of unconventional immune complex-mediated inflammation, is likely accompanied by alterations in circulating metabolites. Here, a1H NMR spectroscopy method coupled with a RRLC method was developed to evaluate the systemic metabolic consequences of AR and characterize metabolic aberrations. Serum and urine samples from AR rats and normal controls were compared to determine whether there were significant alterations associated with AR. The partial least squares discriminant analysis (PLS-DA) models of metabolomic results demonstrated good intergroup separations between AR rats and normal controls. Multivariate statistical analysis revealed significant alterations in the levels of35metabolites, which were termed as the disease-associated biomarkers. Differential metabolites identified from the metabolomic analysis suggested that AR caused dysfunctions of kidney and liver accompanied with changes in widespread metabolic pathways including the tricarboxylic acid (TCA) cycle, gut microbiota metabolism, lipids and cell membranes metabolism, glucose metabolism, fatty acid β3-oxidation, amino acids metabolism and ketogenesis.
3. Here, a1H NMR-based metabolomic approach coupled with a relative simple RRLC-based focused metabolomic approach was developed and compared to characterize the systemic metabolic disturbances underlying esophageal cancer (EC) and identify possible early biomarkers for clinical prognosis. Serum metabolic profiling of patients with EC (n=25) and healthy controls (n=25) was performed by using both1H NMR and RRLC, and metabolite identification was achieved by multivariate statistical analysis. Using orthogonal partial least-squares-discriminant analysis (OPLS-DA), we could distinguish EC patients from healthy controls. The predictive power of the model derived from the RRLC-based focused metabolomics performed better in both sensitivity and specificity than the results from the NMR-based metabolomics, suggesting that the focused metabolomic technique may be of advantage in the future for the determination of biomarkers. Moreover, focused metabolic profiling is highly simple, accurate and specific, and should prove equally valuable in metabolomic research applications. A total of nineteen significantly altered metabolites were identified as the potential disease associated biomarkers. Significant changes in lipid metabolism, amino acid metabolism, glycolysis, ketogenesis, tricarboxylic acid (TCA) cycle and energy metabolism were observed in EC patients compared with the healthy controls.
4. In this study, we used a'H NMR-based metabolomic approach and a RRLC-based focused metabolomic approach and profiled small-molecule metabolites in serum of25lung cancer patients and25healthy controls, to determine whether there are significant alterations associated with carcinogenesis. The metabolomic results demonstrate clear intergroup separations between healthy control subjects and lung cancer patients in the OPLS-DA models.15differential metabolites identified from both the two metabolomic analysis suggest a significantly up-regulated glycolysis and the disrupted lipid metabolism, amino acid metabolism and ketogenesis in lung cancer patients.
5. In the present study, the toxicity of ZnO quantum dots (QDs) was investigated using HPLC-MS based metabolic profiling. The serum and urine of rats treated with ZnO QDs-PEG at different doses (1and10mg/kg) were analyzed by integrated metabolomic analysis and in combination with multivariate statistical analysis. All the results indicated that both the doses of1 and10mg/kg ZnO QDs-PEG can induce changes in endogenous metabolic profiles, but no overt sign of toxicity was found in either the two group. In addition, all the data generated from the current study completely supports the fact that the ZnO QDs-PEG are little toxic and metabolic profiling is promising for the development of a rapid in vivo screening tool for nanotoxicity.
1.建立了2,4-二硝基氟苯(DNFB)柱前衍生化RRLC同时测定大鼠和人血清中23种氨基酸的分析方法。RRLC分离采用Agilent Zorbax Eclipse Plus C18(4.6mm×50mm,1.8μm)反相色谱柱,柱温45℃,流动相采用乙腈-甲醇-10mmol·L-1乙酸铵溶液梯度洗脱,流速1.5mL·min-1.进样量5μL,紫外检测波长360nm。23种氨基酸在10min内可达到良好分离,浓度分别在1～500μmol·L-1范围内线性关系良好(r>0.9962),定量下限为1μmol·L-1,日内、日间RSD值分别在0.32%～3.09%和0.67%～5.82%之间。将建立的方法用于大鼠和人血清中23种氨基酸的同时测定,回收率分别在90.8%～106.0%和88.2%～106.4%之间,RSD值分别在1.8%～4.7%和1.4%～8.5%之间。2.利用基于1HNMR的代谢指纹谱和RRLC的氨基酸靶标分析结合多变量数据处理方法对Arthus反应大鼠的体内代谢特点进行了研究,得到了一些互补信息。将采集的血清和尿液样本进行1HNMR分析,分别发现17个和16个与疾病密切相关的代谢物；血清样本RRLC氨基酸靶标分析发现8个与疾病密切相关的氨基酸。去除共同的代谢物,采用两种代谢组学分析模式,在Arthus反应大鼠血清和尿液中共鉴别到35个与疾病密切相关的特征性代谢物。结果显示,Arthus反应已经引起明显的肝、肾功能损伤,且伴随多条代谢途径的紊乱,如三羧酸循环(TAC)、肠道菌群代谢、脂质和细胞膜代谢、葡萄糖代谢、脂肪酸β-氧化、氨基酸代谢以及酮体的生成和分解等。3.分别建立基于1HNMR和RRLC互补的代谢指纹谱分析方法和氨基酸靶标分析方法,考察25例食管癌患者和25例正常健康人血清的代谢组学差异,进而寻找与食管癌发生、发展密切相关的生物标志物群。结合OPLS-DA对检测数据进行模式识别,结果显示采用两种分析模式均能清晰地区分食管癌患者和正常对照血清,说明相对于正常人而言,食管癌患者的血清代谢谱发生明显改变,并有统计学意义。基于RRLC的氨基酸靶标分析对于食管癌患者和正常健康人之间的区分能力要稍好于基于1HNMR的代谢指纹谱分析,说明代谢物靶标分析定量准确、特异性强,可以作为代谢指纹谱分析的有利补充,在代谢组学研究中具有很广阔的应用前景。本研究共发现19个内源性小分子代谢物在食管癌患者与正常健康人血清中的含量存在显著性差异,提示这些代谢物的异常可能与食管癌患者体内的代谢紊乱存在密切关系,即为潜在的肿瘤生物标志物。通过代谢途径研究发现,与正常人相比,食管癌患者体内多条代谢途径如糖酵解、脂质代谢、能量代谢、酮体的生成和分解、三羧酸循环以及氨基酸代谢等均发生了不同程度的紊乱。
4.采用1HNMR代谢指纹谱分析和RRLC氨基酸靶标分析方法并结合多变量数据处理方法,开展了25例肺癌患者和25例正常健康人血清样品的代谢组学研究。结果显示,两种分析模式均能很好地区分肺癌患者和正常健康人,肺癌患者和正常健康人的血清代谢谱存在明显差异,说明肺癌患者体内的生物代谢通路发生了一定的改变。本研究共发现15个内源性小分子代谢物在肺癌患者与正常健康人血清中的含量存在显著性差异。对差异代谢物的生物代谢路径进行分析发现,肺癌患者的糖酵解代谢显著增加,另外,脂质代谢、氨基酸代谢、酮体的合成和分解等代谢通路均发生不同程度的紊乱。
5.建立了基于HPLC-MS技术的代谢组学研究方法对表面包裹聚乙二醇(PEG)的ZnO量子点染毒大鼠的血清和尿液进行分析,从生物体整体代谢水平探讨了ZnO量子点的生物学效应(毒性)。雄性SD大鼠经尾静脉注射一次染毒1和10mg/kg ZnO QDs-PEG生理盐水溶液后24和72h,采用XCMS online分析其血清和尿液的HPLC-MS代谢谱变化。结果表明,1和10mg/kg ZnO QDs-PEG染毒组大鼠染毒后24、72h的血清和尿液代谢谱与正常对照组相比存在明显差异,没有与组织结构及功能严重受损相关的代谢物发现,说明表面包裹PEG的ZnO量子点毒性较小,不会导致明显的机体组织功能损伤,但引起了轻微的代谢紊乱。
Metabolomics, a relatively novel methodology arising from the post-genomics era, has been increasingly recognized as a valuable complementary approach to other well-established 'omic' sciences to aid in the assessment of disease and toxicity. Metabolic profiling is the comprehensive studying of large numbers of all endogenous low molecular weight metabolites and their roles in various disease states in a global view. In the present study, The proton nuclear magnetic resonance (1H NMR), rapid resolution liquid chromatography (RRLC) and high performance liquid chromatography-mass spectrometry (HPLC-MS) based metabolomic methodology were established and utilized for the research of pathophysiological mechanisms of Arthus reaction, tumor biomarkers discovery and nanotoxicity. The main contents and results are as follows:
1. A RRLC method was developed for the simultaneous determination of23amino acids in rat and human serum after pre-column derivatization with2,4-dinitrofluorobenzene (DNFB). The amino acid derivatives were separated on an Agilent Zorbax Eclipse Plus Cis (4.6mm x50mm,1.8um) column at45℃. Ultraviolet (UV) detection was set at360nm. Good separation of23amino acids was achieved within10min with a ternary gradient elution of mobile phase at a flow rate of1.5mL·min-1. Calibration curves were linear over the range from1to500μmol·L-1with coefficients0.9962or better for each amino acid. The lower limits of quantification (LLOQ) of all23amino acids were1.0μmol·L-1with signal-to-noise (S/N) ratio≥14. Intra-and Inter-day precisions, expressed as relative standard deviation (RSD) percentages, were ranged from0.32%to3.09%and0.67%to5.82%, respectively. Finally, it was successfully applied to the determination of amino acids in rat and human serum with recoveries ranged from90.8%to106.0%and88.2%to106.4%, and RSD percentages ranged from1.78%to4.68%and1.4%to8.5%, respectively.
2. Arthus reaction (AR), a type of unconventional immune complex-mediated inflammation, is likely accompanied by alterations in circulating metabolites. Here, a1H NMR spectroscopy method coupled with a RRLC method was developed to evaluate the systemic metabolic consequences of AR and characterize metabolic aberrations. Serum and urine samples from AR rats and normal controls were compared to determine whether there were significant alterations associated with AR. The partial least squares discriminant analysis (PLS-DA) models of metabolomic results demonstrated good intergroup separations between AR rats and normal controls. Multivariate statistical analysis revealed significant alterations in the levels of35metabolites, which were termed as the disease-associated biomarkers. Differential metabolites identified from the metabolomic analysis suggested that AR caused dysfunctions of kidney and liver accompanied with changes in widespread metabolic pathways including the tricarboxylic acid (TCA) cycle, gut microbiota metabolism, lipids and cell membranes metabolism, glucose metabolism, fatty acid β3-oxidation, amino acids metabolism and ketogenesis.
3. Here, a1H NMR-based metabolomic approach coupled with a relative simple RRLC-based focused metabolomic approach was developed and compared to characterize the systemic metabolic disturbances underlying esophageal cancer (EC) and identify possible early biomarkers for clinical prognosis. Serum metabolic profiling of patients with EC (n=25) and healthy controls (n=25) was performed by using both1H NMR and RRLC, and metabolite identification was achieved by multivariate statistical analysis. Using orthogonal partial least-squares-discriminant analysis (OPLS-DA), we could distinguish EC patients from healthy controls. The predictive power of the model derived from the RRLC-based focused metabolomics performed better in both sensitivity and specificity than the results from the NMR-based metabolomics, suggesting that the focused metabolomic technique may be of advantage in the future for the determination of biomarkers. Moreover, focused metabolic profiling is highly simple, accurate and specific, and should prove equally valuable in metabolomic research applications. A total of nineteen significantly altered metabolites were identified as the potential disease associated biomarkers. Significant changes in lipid metabolism, amino acid metabolism, glycolysis, ketogenesis, tricarboxylic acid (TCA) cycle and energy metabolism were observed in EC patients compared with the healthy controls.
4. In this study, we used a'H NMR-based metabolomic approach and a RRLC-based focused metabolomic approach and profiled small-molecule metabolites in serum of25lung cancer patients and25healthy controls, to determine whether there are significant alterations associated with carcinogenesis. The metabolomic results demonstrate clear intergroup separations between healthy control subjects and lung cancer patients in the OPLS-DA models.15differential metabolites identified from both the two metabolomic analysis suggest a significantly up-regulated glycolysis and the disrupted lipid metabolism, amino acid metabolism and ketogenesis in lung cancer patients.
5. In the present study, the toxicity of ZnO quantum dots (QDs) was investigated using HPLC-MS based metabolic profiling. The serum and urine of rats treated with ZnO QDs-PEG at different doses (1and10mg/kg) were analyzed by integrated metabolomic analysis and in combination with multivariate statistical analysis. All the results indicated that both the doses of1 and10mg/kg ZnO QDs-PEG can induce changes in endogenous metabolic profiles, but no overt sign of toxicity was found in either the two group. In addition, all the data generated from the current study completely supports the fact that the ZnO QDs-PEG are little toxic and metabolic profiling is promising for the development of a rapid in vivo screening tool for nanotoxicity.
引文
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