脂质组学分析技术及其在发现免疫性疾病和病毒性肝炎相关生物标志物方面的研究
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摘要
近年来,随着科学技术的发展与人们认识水平的提高,大量研究表明,以鞘脂为代表的功能性脂质类化合物不仅参与生物体内的能量代谢、构建细胞质膜结构,还具有广泛的生物学活性,譬如调控细胞增殖、分化、胞内交流和迁徙、胞间(或胞外)的信号传导、膜结构的转运、自噬和细胞凋亡等。因此,脂质类化合物的生物活性成为了近年来的研究热点。随着质谱技术的发展,特别是液相色谱联用质谱技术,脂质类化合物的结构信息被更多的揭示出来,其结构与功能的关系得到了更好的诠释,脂质组学也应运而生。脂质组学分析技术研究成为了分析化学领域的热点。
内源性的脂质类化合物在机体内的天然丰度差别非常大,生源丰度通常从纳克级到微克级不等。其中,鞘脂类化合物通常在纳克级水平,且离子化效率较低,属于比较难检测的一类化合物。鉴于脂质类化合物自然丰度差异巨大,结合其结构特点,我们采用了不同类型的质谱来研究脂质分析技术,构建了一套组合式的脂质分析平台。本论文首先基于鞘脂代谢网络,采用高效液相色谱串联三重四级杆质谱(HPLC-MS/MS),建立了一套靶向鞘脂质组学的定量分析方法,能够同时分析43个鞘脂代谢网络核心化合物。本论文首先优化了生物样本(血浆、血清或组织匀浆液,0.1mL)前处理方法,采用甲基叔丁基醚-甲醇-水(20：6：5,v/v/v)三元混合溶剂系统对生物样本(血浆、血清或组织匀浆液,0.1mL)进行脂质提取,提取回收率达到60%-80%。液相色谱分析采用反相C8色谱柱,流动相分别为,A相：0.2%甲酸2.0mM甲酸铵水溶液,B相：0.2%甲酸1.0mM甲酸铵甲醇溶液,梯度洗脱模式,质谱检测采用ESI正离子分段多反应离子监测模式,分段检测的引入显著提高了平台的灵敏度。每一个检测分段内均至少有一个非内源性同系物作为内标来保证定量准确性。方法验证表明,最低定量限：1.0pmol/mg protein(所有鞘脂)；线性范围：12.5-2000.0pmol/mg protein(鞘磷脂类)、2.5-400.0pmol/mg protein(其他鞘脂类)；线性相关系数：r>0.99；日内日间精密度均小于15%；准确度：80%-120%;工作溶液室温放置6小时和-20℃放置60天稳定。上述结果证明方法准确可靠,适合常规生物样品分析。为了更全面的使方法覆盖鞘脂代谢网络的核心化合物,我们依据鞘脂类化合物的结构和质谱裂解规律,推演并增加了多反应监测的离子对的数目,扩充了鞘脂组学分析方法所监测的目标化合物的数量从43个到74个。同时,我们引入了高效液相色谱联用高分辨质谱仪——傅里叶变换离子回旋共振质谱仪(HPLC-LTQ-FTICRMS)建立一套适用于分析高丰度脂质的脂质组学定量分析平台,液相色谱分析采用反相C8色谱柱,流动相分别为,A相：2mM乙酸铵缓冲盐水溶液含有0.1%甲酸,B相：含有2mM乙酸铵和0.1%甲酸的异丙醇／乙腈(2：5,v/v)溶液,梯度洗脱模式。ESI正离子高分辨全扫描模式监测,利用一级高分辨质谱数据,我们采用Lipid Data Analyzer(?)软件对数据进行高内涵高通量的处理。该平台可以同时监测4大类,包括甘油三酯、甘油二酯、甘油磷脂酰胆碱、甘油磷脂酰乙醇胺合计216种脂质类化合物。部分方法验证表明：最低定量限：0.02nmol/mg protein(所有脂质)；线性范围：0.02-200nmol/mL;线性相关系数：r>0.95；精密度小于15%,准确度：80%-120%。上述结果证明该平台适合用于生物样品靶向定量脂质组学研究。具有使用样品量少、高内涵、高通量,并具有同时定性和定量分析的特点。
在进行脂质分析技术平台建立过程中,我们将所建立的分析方法及时应用于实际生物样本的分析以及筛选与疾病相关生物标志物的研究中。首先,我们将鞘脂分析技术用于了寻找2,4-二硝基氟苯诱发的迟发型超敏反应模型小鼠的血浆、肾脏、肝脏和脾脏中与模型相关的生物标志物,及模型小鼠给予治疗剂量雷公藤甲素后的与药效相关的生物标志物。经过所建立鞘脂组学方法分析后,我们对得到的鞘脂组学数据进行了统计分析,发现了23个鞘脂类化合物(12个神经酰胺类化合物,3个鞘胺醇类化合物,3个糖基化神经酰胺类化合物和5个神经鞘磷脂类化合物)为迟发超敏反应和雷公藤甲素治疗的潜在生物标志物。同时,我们发现雷公藤甲素使得迟发超敏反应模型小鼠的肾脏中10个鞘脂类化合物的代谢发生显著变化,可能与雷公藤甲素潜在的肾毒性相关。该研究表明,靶向定量鞘脂组学结合多变量统计方法能够在生物样品中有效的筛选潜在的鞘脂生物标志物。
已有文献研究结果表明肝炎病毒和丙型肝炎病毒侵入、复制、转录和出芽过程均与鞘脂密切相关,因此本论文首次开展了乙肝及其相关慢性肝病的鞘脂组学研究,利用鞘脂组学分析技术,分析慢性乙肝患者血清中的鞘脂类化合物。该研究总共使用了两个临床队列,合计156例血清样本,由北京佑安医院提供。每个临床队列分为健康对照组、慢乙肝组和慢乙肝导致的慢加急性肝衰竭组(HBV-ACLF)。结果表明,鞘脂代谢网络的紊乱与疾病的发展密切相关,发现并确认了9个鞘脂生物标志物,为慢性乙肝疾病发病机理研究提供线索。此外,发现了血清中dhCer(d18:0/24:0)水平的降低预示着HBV-ACLF患者预后不良,提供了一种新的方法评估HBV-ACLF的预后,进而有助于优化治疗方案,选择保守治疗或者尽早肝移植。
随着脂质组学分析技术平台的建立完善,我们将脂质组学分析技术应用于研究慢性丙肝患者的血浆脂质组。患者血浆样品由北京佑安医院提供。包括113例慢性丙肝患者和11例健康受试者,其中患者组根据其肝穿活检结果显示的肝内炎症级别分为IG01,IG2,IG34三组。结果表明,各疾病组与健康受试者之间的血浆脂质水平差异显著(检出的117个脂质中,47个脂质水平显著改变),而患者中不同炎症组之间差异较小(只有8个脂质水平显著改变)。说明血浆脂质组的改变与疾病的发生更相关,而不是炎症发展程度。丙肝慢性感染导致的营养不良很可能是一个重要原因。HexCer(d18:1/22:0)、HexCer (d18:1/24:1)、HexCer (d18:1/24:0)、PC(34:4)和PC(40：5)在轻度和重度肝内炎症组之间存在显著差异,显示它们可作为评价肝内炎症的潜在非侵入性指标。
本论文研究后期探索性的建立脂质组学整体定性筛查和靶向定量分析新技术,首次建立了一套在线串联二维(HILIC×RP)超高效液相色谱串联三重四级杆质谱仪脂质组学平台。三步筛选脂质化合物的策略充分展示了平台的对于各种生物样品都具有普适性,后续的使用MRM模式对筛选出来的化合物进行定量展示了平台准确定量的能力。尤其是该平台可以在线同时区分并准确定量PC和SM类化合物,使得需要前处理去除两类化合物测定干扰的问题得以解决,提高了测定的效率和准确性。我们进一步将所建立的平台用于大鼠血浆脂质组的分析,其中包括雄性和雌性大鼠的血浆和采集于不同位置的血浆(眼缘静脉、腹主动脉、尾静脉)。结果表明,所建立的方法可以同时定量154个脂质类化合物,包括1个ceramide,1个ceramide-1P,1个sphingosine,60个PC,19个SM和72个TG。统计分析表明,雄性和雌性大鼠血浆脂质组差异显著。来自不同取血位置的血浆中的个别脂质也存在显著差异。上述结果可以给我们一个启示,即当我们去重复或者验证一个脂质组学的研究时,重复同样的样品采集方法非常重要,不仅包括实验动物的性别还有样品的采集部位。
本论文建立了覆盖脂质代谢网络核心脂质的整体定性和靶向定量分析平台,通过分析实际生物样品,充分展示了方法的深度和广度,并将分析结果与生物学意义相关联,表明生命体的脂质组与疾病发生发展息息相关,为疾病的诊断、预后以及疾病机理的研究奠定了基础。由于本论文的研究均属于单一时间点的截面研究类型,无法动态关注脂质的代谢转化,今后可采用药代动力学的原理和手段关注这一方面。
In recent years, many studies demonstrated that lipids, especially sphingolipids are highly bioactive compounds that serve not only as core components of biological structures, such as membranes and lipoproteins, but also as regulators of cell proliferation, differentiation, cellular interactions and migration, intracellular (and extracellular) signaling, membrane trafficking, autophagy, and cell death. Therefore, lipids have become the new focus of biochemistry. Meanwhile, development of new analytical platform for lipids has become the hotspot in the field of analytical chemistry. With the development of modern mass spectrometry, especially mass spectrometry coupled to liquid chromatography, more structural details of lipids have been revealed, which make the connection between structure and function clearer. Based on the strategy of targeted metabolomics, lipidomics was introduced as the large-scale study of pathways and networks of cellular lipids in biological systems.
Natural abundance of lipids varies a lot in biological system, ranging from nanogram scale to microgram scale. Among those lipids, sphingolipids belong to one subclass of lipids whose abundance is among nanogram scale. With relatively low ionization efficiency, sphingolipids should be detected in a more sentive mass spectrometer, eg. triple quadruple mass spectrometer. According to the variance of natural abundance and structural characteristics of those lipids, we have built an integrated lipidomics platform to fulfil the detection and quantification. In this thesis, we first developed a targeted sphingolipidomic platform, consisting of a high performance liquid chromatography coupled with tandem triple quadruple mass spectrometry. This platform was capable of quantification of43sphingolipids, covering the core metabolic network of sphingolipids. In the beginning, we optimized the extraction method by introducing methyl-tert-butyl-ether:methanol:water (20:6:5, v/v/v) solvent system. The sample volume was0.1mL for liquid samples (eg. plasma, serum, tissue homogenates) and1mg protein for solid samples (eg. cell). The absolute recovery was among60-80%. A reversed phase C8column in gradient mode was employed in the chromatography part. Mobile Phase A consisted of2mM ammonium formate in water containing0.2%formic acid. Mobile Phase B consisted of1mM ammonium formate in methanol containing0.2%formic acid. In the mass spectrometry, all target compounds were detected in ESI-positive mode. The approach of segmental multiple reaction monitoring improved the sensitivity and accuracy. At least one internal standard was introduced in each segment. The result of method validation demonstrated that the limit of quantification was1.0pmol/mg protein; linear range:12.5-2000.0pmol/mg protein (for sphingomyelins) and2.5-400.0pmol/mg protein (for other sphingolipids) with linear correlation coefficient greater than0.99; The intra-day and inter-day precision was less than15%; the accuracy was among80～120%; The working solution was stable in room temperature for6hours and in-20°for60days. Above results proved this method was accurate and reliable for investigating the sphingolipid levels in biological samples. In order to fully cover whole metabolomic network of sphingolipids, we further expanded the number of target sphingolipids from43to74and integrated the linear ion trap-Fourier transform ion cyclotron resonance (LTQ-FT) mass spectrometer as a complementation to profile the four categories of highly abundant lipids, including glycerophosphocholines, glycerophosphoethanolamines, diacylglycerol and triglycerides, totally216lipids. The LTQ-FT was working in ESI positive full scan mode. A reversed phase C8column in gradient mode was employed in the chromatography part before the mass spectrometry. Mobile phase A was comprised of0.1%formic acid in water containing2mM ammonium acetate. Mobile phase B was comprised of2-propanol/acetonitrile (2:5, v/v) containing2mM ammonium acetate and0.1%formic acid. The Lipid Data Analyzer(?) was used to analyze the raw data file in a high throughout manner. Partial validation demonstrated that the limit of quantification was0.02nmol/mg protein; the linear range was among0.02-200nmol/mL with linear correlation coefficient greater than0.95; the precision was less than15%; the accuracy was among80%-120%. Above results confirmed that this lipidomics platform was accurate and reliable for investigating the lipidome qualitatively and quantitatively in biological sample.
During the method development, we timely applied the method in real sample analysis. First of all, we used the sphingolipidomic method to profile sphingolipids in the plasma, kidneys, livers and spleens of BALB/c mice from four experimental groups:control, delayed-type hypersensitivity (DTH) model, DTH+triptolide, and control+triptolide. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify potential biomarkers associated with variance between groups. Relationships between the identified biomarkers and disease markers were evaluated by Spearman correlation. The sphingolipidomic result revealed marked alterations in sphingolipid levels between groups that were associated with the effects of the disease and triptolide treatment. Based on this data,23potential biomarkers were identified by OPLS-DA, and seven of them correlated markedly with the disease markers (p<0.05). Restoration of proper sphingolipid levels may attribute to the therapeutic effect of triptolide treatment. Furthermore, these findings demonstrate that targeted sphingolipidomic analysis followed by multivariate analysis presents a novel strategy for the identification of biomarkers in biological samples.
It is reported that hepatitis viruses rely on constituents of the host cell to provide the energy, macromolecules, and structural organization necessary for survival, and they must cross membranes either by transient local disruption of membrane integrity or by cell lysis. Above processes are related with sphingolipid metabolism. Therefore, we conducted a research on the relationship between serum lipids and chronic HBV infection. The sphingolipidomic platform was used to examine the sphingolipids in156serum samples prospectively collected from two independent cohorts. The training and validation cohorts comprised20and28healthy controls (CTRL),29and23patients with chronic hepatitis B (CHB), and30and26patients with hepatitis B virus related acute on chronic liver failure (HBV-ACLF), respectively. Nine potential biomarkers were found and confirmed between CHB and HBV-ACLF, whereas none was confirmed between CTRL and CHB by multivariate analysis. Such result provided new clues for pathogenesis research for chronic HBV infection. Further, a3-month mortality evaluation of HBV-ACLF patients showed that dhCer(d18:0/24:0) was significantly higher in survivors than in non-survivors (including deceased patients and those undergoing liver transplantation, p<0.05), and showed a prognostic performance similar to that of the MELD score. This preliminary study firstly revealed that the serum sphingolipid composition varies between CTRL and patients with chronic HBV infection and provided new potential method in the prognosis of HBV-ACLF patients.
Based on our previous study, we further applied the integrated lipidomics platform on plasma samples collected from patients with chronic hepatitis C virus (HCV) infection. The plasma samples were collected by Beijing YouAn Hospital, including11healthy controls and113patients with chronic HCV infection. All the patients were grouped by their intrahepatic inflammation grade (IG) of liver tissue into IG01, IG2and IG34. As a result, the plasma lipid profile varies a lot between healthy controls and patients with chronic HCV infection (47of117quantified lipids significantly changed). Only eight lipids (HexCer (dl8:1/22:0), HexCer (d18:1/24:1), HexCer (d18:1/24:0), PC(34:4) and PC(40:5)) showed significant differences between mild and severe intrahepatic inflammation grades, indicating that they could be useful as novel non-invasive indicators of intrahepatic IG. Based on these results, we speculate that variations in lipid composition arise as a result of HCV infection, and are caused by HCV-related digestive system disorders rather than progression of the disease.
Later on, we further developed an online HILIC×RP2D-lipidomic platform consisted of a3-step strategic approach for screening candidate compounds in an untargeted way and quantitation of those compounds in MRM mode, a targeted way. A triple quadruple mass spectrometry was used in this study. This platform was demonstrate to be especially useful in discrimination of PCs and SMs by resolving those two types of compounds mutually and internally. Mild alkaline hydrolysis, an unstable factor in previous sample preparation was no more needed. The accuracy, precision and limit of detection were evaluated. We further applied this platform in analyzing lipidome of male and female mice plasma obtained from three different positions. Totally,154lipids were correctly quantified in all samples, including1ceramide,1ceramide-1P,1sphingosine,60PCs,19SMs and72TGs. The results demonstrated that male and female mice plasma shows significant distinct lipid profile. The plasma lipidome from retro-orbital sinus/plexus, abdominal aorta and tail vein are also different. Above result provided us a hint that when to repeat a lipidomics experiment, repeating the method of sample collection is very important, which includes not only animal gender but also its originate.
This thesis work has built a series of qualitative and quantitative lipidomics platforms. By analyzing actual biological samples, the coverage and depth of them was amply demonstrated. Our results showed that lipids are tightly connected with disease progression, providing novel clues for diagnosis, prognosis and mechanism research.
内源性的脂质类化合物在机体内的天然丰度差别非常大,生源丰度通常从纳克级到微克级不等。其中,鞘脂类化合物通常在纳克级水平,且离子化效率较低,属于比较难检测的一类化合物。鉴于脂质类化合物自然丰度差异巨大,结合其结构特点,我们采用了不同类型的质谱来研究脂质分析技术,构建了一套组合式的脂质分析平台。本论文首先基于鞘脂代谢网络,采用高效液相色谱串联三重四级杆质谱(HPLC-MS/MS),建立了一套靶向鞘脂质组学的定量分析方法,能够同时分析43个鞘脂代谢网络核心化合物。本论文首先优化了生物样本(血浆、血清或组织匀浆液,0.1mL)前处理方法,采用甲基叔丁基醚-甲醇-水(20：6：5,v/v/v)三元混合溶剂系统对生物样本(血浆、血清或组织匀浆液,0.1mL)进行脂质提取,提取回收率达到60%-80%。液相色谱分析采用反相C8色谱柱,流动相分别为,A相：0.2%甲酸2.0mM甲酸铵水溶液,B相：0.2%甲酸1.0mM甲酸铵甲醇溶液,梯度洗脱模式,质谱检测采用ESI正离子分段多反应离子监测模式,分段检测的引入显著提高了平台的灵敏度。每一个检测分段内均至少有一个非内源性同系物作为内标来保证定量准确性。方法验证表明,最低定量限：1.0pmol/mg protein(所有鞘脂)；线性范围：12.5-2000.0pmol/mg protein(鞘磷脂类)、2.5-400.0pmol/mg protein(其他鞘脂类)；线性相关系数：r>0.99；日内日间精密度均小于15%；准确度：80%-120%;工作溶液室温放置6小时和-20℃放置60天稳定。上述结果证明方法准确可靠,适合常规生物样品分析。为了更全面的使方法覆盖鞘脂代谢网络的核心化合物,我们依据鞘脂类化合物的结构和质谱裂解规律,推演并增加了多反应监测的离子对的数目,扩充了鞘脂组学分析方法所监测的目标化合物的数量从43个到74个。同时,我们引入了高效液相色谱联用高分辨质谱仪——傅里叶变换离子回旋共振质谱仪(HPLC-LTQ-FTICRMS)建立一套适用于分析高丰度脂质的脂质组学定量分析平台,液相色谱分析采用反相C8色谱柱,流动相分别为,A相：2mM乙酸铵缓冲盐水溶液含有0.1%甲酸,B相：含有2mM乙酸铵和0.1%甲酸的异丙醇／乙腈(2：5,v/v)溶液,梯度洗脱模式。ESI正离子高分辨全扫描模式监测,利用一级高分辨质谱数据,我们采用Lipid Data Analyzer(?)软件对数据进行高内涵高通量的处理。该平台可以同时监测4大类,包括甘油三酯、甘油二酯、甘油磷脂酰胆碱、甘油磷脂酰乙醇胺合计216种脂质类化合物。部分方法验证表明：最低定量限：0.02nmol/mg protein(所有脂质)；线性范围：0.02-200nmol/mL;线性相关系数：r>0.95；精密度小于15%,准确度：80%-120%。上述结果证明该平台适合用于生物样品靶向定量脂质组学研究。具有使用样品量少、高内涵、高通量,并具有同时定性和定量分析的特点。
在进行脂质分析技术平台建立过程中,我们将所建立的分析方法及时应用于实际生物样本的分析以及筛选与疾病相关生物标志物的研究中。首先,我们将鞘脂分析技术用于了寻找2,4-二硝基氟苯诱发的迟发型超敏反应模型小鼠的血浆、肾脏、肝脏和脾脏中与模型相关的生物标志物,及模型小鼠给予治疗剂量雷公藤甲素后的与药效相关的生物标志物。经过所建立鞘脂组学方法分析后,我们对得到的鞘脂组学数据进行了统计分析,发现了23个鞘脂类化合物(12个神经酰胺类化合物,3个鞘胺醇类化合物,3个糖基化神经酰胺类化合物和5个神经鞘磷脂类化合物)为迟发超敏反应和雷公藤甲素治疗的潜在生物标志物。同时,我们发现雷公藤甲素使得迟发超敏反应模型小鼠的肾脏中10个鞘脂类化合物的代谢发生显著变化,可能与雷公藤甲素潜在的肾毒性相关。该研究表明,靶向定量鞘脂组学结合多变量统计方法能够在生物样品中有效的筛选潜在的鞘脂生物标志物。
已有文献研究结果表明肝炎病毒和丙型肝炎病毒侵入、复制、转录和出芽过程均与鞘脂密切相关,因此本论文首次开展了乙肝及其相关慢性肝病的鞘脂组学研究,利用鞘脂组学分析技术,分析慢性乙肝患者血清中的鞘脂类化合物。该研究总共使用了两个临床队列,合计156例血清样本,由北京佑安医院提供。每个临床队列分为健康对照组、慢乙肝组和慢乙肝导致的慢加急性肝衰竭组(HBV-ACLF)。结果表明,鞘脂代谢网络的紊乱与疾病的发展密切相关,发现并确认了9个鞘脂生物标志物,为慢性乙肝疾病发病机理研究提供线索。此外,发现了血清中dhCer(d18:0/24:0)水平的降低预示着HBV-ACLF患者预后不良,提供了一种新的方法评估HBV-ACLF的预后,进而有助于优化治疗方案,选择保守治疗或者尽早肝移植。
随着脂质组学分析技术平台的建立完善,我们将脂质组学分析技术应用于研究慢性丙肝患者的血浆脂质组。患者血浆样品由北京佑安医院提供。包括113例慢性丙肝患者和11例健康受试者,其中患者组根据其肝穿活检结果显示的肝内炎症级别分为IG01,IG2,IG34三组。结果表明,各疾病组与健康受试者之间的血浆脂质水平差异显著(检出的117个脂质中,47个脂质水平显著改变),而患者中不同炎症组之间差异较小(只有8个脂质水平显著改变)。说明血浆脂质组的改变与疾病的发生更相关,而不是炎症发展程度。丙肝慢性感染导致的营养不良很可能是一个重要原因。HexCer(d18:1/22:0)、HexCer (d18:1/24:1)、HexCer (d18:1/24:0)、PC(34:4)和PC(40：5)在轻度和重度肝内炎症组之间存在显著差异,显示它们可作为评价肝内炎症的潜在非侵入性指标。
本论文研究后期探索性的建立脂质组学整体定性筛查和靶向定量分析新技术,首次建立了一套在线串联二维(HILIC×RP)超高效液相色谱串联三重四级杆质谱仪脂质组学平台。三步筛选脂质化合物的策略充分展示了平台的对于各种生物样品都具有普适性,后续的使用MRM模式对筛选出来的化合物进行定量展示了平台准确定量的能力。尤其是该平台可以在线同时区分并准确定量PC和SM类化合物,使得需要前处理去除两类化合物测定干扰的问题得以解决,提高了测定的效率和准确性。我们进一步将所建立的平台用于大鼠血浆脂质组的分析,其中包括雄性和雌性大鼠的血浆和采集于不同位置的血浆(眼缘静脉、腹主动脉、尾静脉)。结果表明,所建立的方法可以同时定量154个脂质类化合物,包括1个ceramide,1个ceramide-1P,1个sphingosine,60个PC,19个SM和72个TG。统计分析表明,雄性和雌性大鼠血浆脂质组差异显著。来自不同取血位置的血浆中的个别脂质也存在显著差异。上述结果可以给我们一个启示,即当我们去重复或者验证一个脂质组学的研究时,重复同样的样品采集方法非常重要,不仅包括实验动物的性别还有样品的采集部位。
本论文建立了覆盖脂质代谢网络核心脂质的整体定性和靶向定量分析平台,通过分析实际生物样品,充分展示了方法的深度和广度,并将分析结果与生物学意义相关联,表明生命体的脂质组与疾病发生发展息息相关,为疾病的诊断、预后以及疾病机理的研究奠定了基础。由于本论文的研究均属于单一时间点的截面研究类型,无法动态关注脂质的代谢转化,今后可采用药代动力学的原理和手段关注这一方面。
In recent years, many studies demonstrated that lipids, especially sphingolipids are highly bioactive compounds that serve not only as core components of biological structures, such as membranes and lipoproteins, but also as regulators of cell proliferation, differentiation, cellular interactions and migration, intracellular (and extracellular) signaling, membrane trafficking, autophagy, and cell death. Therefore, lipids have become the new focus of biochemistry. Meanwhile, development of new analytical platform for lipids has become the hotspot in the field of analytical chemistry. With the development of modern mass spectrometry, especially mass spectrometry coupled to liquid chromatography, more structural details of lipids have been revealed, which make the connection between structure and function clearer. Based on the strategy of targeted metabolomics, lipidomics was introduced as the large-scale study of pathways and networks of cellular lipids in biological systems.
Natural abundance of lipids varies a lot in biological system, ranging from nanogram scale to microgram scale. Among those lipids, sphingolipids belong to one subclass of lipids whose abundance is among nanogram scale. With relatively low ionization efficiency, sphingolipids should be detected in a more sentive mass spectrometer, eg. triple quadruple mass spectrometer. According to the variance of natural abundance and structural characteristics of those lipids, we have built an integrated lipidomics platform to fulfil the detection and quantification. In this thesis, we first developed a targeted sphingolipidomic platform, consisting of a high performance liquid chromatography coupled with tandem triple quadruple mass spectrometry. This platform was capable of quantification of43sphingolipids, covering the core metabolic network of sphingolipids. In the beginning, we optimized the extraction method by introducing methyl-tert-butyl-ether:methanol:water (20:6:5, v/v/v) solvent system. The sample volume was0.1mL for liquid samples (eg. plasma, serum, tissue homogenates) and1mg protein for solid samples (eg. cell). The absolute recovery was among60-80%. A reversed phase C8column in gradient mode was employed in the chromatography part. Mobile Phase A consisted of2mM ammonium formate in water containing0.2%formic acid. Mobile Phase B consisted of1mM ammonium formate in methanol containing0.2%formic acid. In the mass spectrometry, all target compounds were detected in ESI-positive mode. The approach of segmental multiple reaction monitoring improved the sensitivity and accuracy. At least one internal standard was introduced in each segment. The result of method validation demonstrated that the limit of quantification was1.0pmol/mg protein; linear range:12.5-2000.0pmol/mg protein (for sphingomyelins) and2.5-400.0pmol/mg protein (for other sphingolipids) with linear correlation coefficient greater than0.99; The intra-day and inter-day precision was less than15%; the accuracy was among80～120%; The working solution was stable in room temperature for6hours and in-20°for60days. Above results proved this method was accurate and reliable for investigating the sphingolipid levels in biological samples. In order to fully cover whole metabolomic network of sphingolipids, we further expanded the number of target sphingolipids from43to74and integrated the linear ion trap-Fourier transform ion cyclotron resonance (LTQ-FT) mass spectrometer as a complementation to profile the four categories of highly abundant lipids, including glycerophosphocholines, glycerophosphoethanolamines, diacylglycerol and triglycerides, totally216lipids. The LTQ-FT was working in ESI positive full scan mode. A reversed phase C8column in gradient mode was employed in the chromatography part before the mass spectrometry. Mobile phase A was comprised of0.1%formic acid in water containing2mM ammonium acetate. Mobile phase B was comprised of2-propanol/acetonitrile (2:5, v/v) containing2mM ammonium acetate and0.1%formic acid. The Lipid Data Analyzer(?) was used to analyze the raw data file in a high throughout manner. Partial validation demonstrated that the limit of quantification was0.02nmol/mg protein; the linear range was among0.02-200nmol/mL with linear correlation coefficient greater than0.95; the precision was less than15%; the accuracy was among80%-120%. Above results confirmed that this lipidomics platform was accurate and reliable for investigating the lipidome qualitatively and quantitatively in biological sample.
During the method development, we timely applied the method in real sample analysis. First of all, we used the sphingolipidomic method to profile sphingolipids in the plasma, kidneys, livers and spleens of BALB/c mice from four experimental groups:control, delayed-type hypersensitivity (DTH) model, DTH+triptolide, and control+triptolide. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify potential biomarkers associated with variance between groups. Relationships between the identified biomarkers and disease markers were evaluated by Spearman correlation. The sphingolipidomic result revealed marked alterations in sphingolipid levels between groups that were associated with the effects of the disease and triptolide treatment. Based on this data,23potential biomarkers were identified by OPLS-DA, and seven of them correlated markedly with the disease markers (p<0.05). Restoration of proper sphingolipid levels may attribute to the therapeutic effect of triptolide treatment. Furthermore, these findings demonstrate that targeted sphingolipidomic analysis followed by multivariate analysis presents a novel strategy for the identification of biomarkers in biological samples.
It is reported that hepatitis viruses rely on constituents of the host cell to provide the energy, macromolecules, and structural organization necessary for survival, and they must cross membranes either by transient local disruption of membrane integrity or by cell lysis. Above processes are related with sphingolipid metabolism. Therefore, we conducted a research on the relationship between serum lipids and chronic HBV infection. The sphingolipidomic platform was used to examine the sphingolipids in156serum samples prospectively collected from two independent cohorts. The training and validation cohorts comprised20and28healthy controls (CTRL),29and23patients with chronic hepatitis B (CHB), and30and26patients with hepatitis B virus related acute on chronic liver failure (HBV-ACLF), respectively. Nine potential biomarkers were found and confirmed between CHB and HBV-ACLF, whereas none was confirmed between CTRL and CHB by multivariate analysis. Such result provided new clues for pathogenesis research for chronic HBV infection. Further, a3-month mortality evaluation of HBV-ACLF patients showed that dhCer(d18:0/24:0) was significantly higher in survivors than in non-survivors (including deceased patients and those undergoing liver transplantation, p<0.05), and showed a prognostic performance similar to that of the MELD score. This preliminary study firstly revealed that the serum sphingolipid composition varies between CTRL and patients with chronic HBV infection and provided new potential method in the prognosis of HBV-ACLF patients.
Based on our previous study, we further applied the integrated lipidomics platform on plasma samples collected from patients with chronic hepatitis C virus (HCV) infection. The plasma samples were collected by Beijing YouAn Hospital, including11healthy controls and113patients with chronic HCV infection. All the patients were grouped by their intrahepatic inflammation grade (IG) of liver tissue into IG01, IG2and IG34. As a result, the plasma lipid profile varies a lot between healthy controls and patients with chronic HCV infection (47of117quantified lipids significantly changed). Only eight lipids (HexCer (dl8:1/22:0), HexCer (d18:1/24:1), HexCer (d18:1/24:0), PC(34:4) and PC(40:5)) showed significant differences between mild and severe intrahepatic inflammation grades, indicating that they could be useful as novel non-invasive indicators of intrahepatic IG. Based on these results, we speculate that variations in lipid composition arise as a result of HCV infection, and are caused by HCV-related digestive system disorders rather than progression of the disease.
Later on, we further developed an online HILIC×RP2D-lipidomic platform consisted of a3-step strategic approach for screening candidate compounds in an untargeted way and quantitation of those compounds in MRM mode, a targeted way. A triple quadruple mass spectrometry was used in this study. This platform was demonstrate to be especially useful in discrimination of PCs and SMs by resolving those two types of compounds mutually and internally. Mild alkaline hydrolysis, an unstable factor in previous sample preparation was no more needed. The accuracy, precision and limit of detection were evaluated. We further applied this platform in analyzing lipidome of male and female mice plasma obtained from three different positions. Totally,154lipids were correctly quantified in all samples, including1ceramide,1ceramide-1P,1sphingosine,60PCs,19SMs and72TGs. The results demonstrated that male and female mice plasma shows significant distinct lipid profile. The plasma lipidome from retro-orbital sinus/plexus, abdominal aorta and tail vein are also different. Above result provided us a hint that when to repeat a lipidomics experiment, repeating the method of sample collection is very important, which includes not only animal gender but also its originate.
This thesis work has built a series of qualitative and quantitative lipidomics platforms. By analyzing actual biological samples, the coverage and depth of them was amply demonstrated. Our results showed that lipids are tightly connected with disease progression, providing novel clues for diagnosis, prognosis and mechanism research.
引文
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