神经肽的靶向分析

Neuropeptides, which are peptide neurotransmitters or hormones found in the brain as well as various peripheral organs, play a critical role in controlling physiological processes. They can be highly specific biomarkers for the early diagnostics of various diseases. However, it remains technically challenging for the discovery of neuropeptide biomarkers for many reasons. To address this issue, our proposed neuropeptidomics study aims to perform an in-depth and comprehensive characterization of neuropeptides, particularly by using targeted liquid chromatography (LC)-mass spectrometry (MS) analysis. We will develop bioinformatics methods to recognize long chain neuropeptides and disulfide bonded neuropeptides, which are extremely rarely sequenced in the current neuropeptidomics. We will then use diabetes mouse as model to find a strategy that is able to discover neuropeptide biomarkers that are of low abundance in the blood. We will sequence neuropeptides in the pancreases, liver, gastroinstenine and brain from the control, early diabetes and diabetes mice. The identified peptides will be submitted to selective reaction monitoring (SRM) LC-MS analysis for quantify the levels of neuropeptides in different organs acquired from the mikes of different groups. Differential analysis will be performed to find the neuropeptides that are significantly altered due to the diabetes disease. The levels of these neuropeptides will be further examined in the blood of mice to very if they can act as blood biomarker for diabetes. The discovery of altered peptides will allow us to optimize and validate our neuropeptidomics approaches. The findings will also pave the way for identifying the possible neuropeptide biomarkers for many other diseases.

神经肽作为肽类递质或荷尔蒙，是疾病早期诊断的高特异性分子标志物。为显著提高发现神经肽标志物的能力,本项目致力于发展高选择性的靶向神经肽组学技术。将发展目标肽的识别工作,以提高神经肽的鉴定率。为此,拟通过编程计算，分析一级质谱信息中数十万肽的质量特性和质量差异，或辅以衍生化的方法，识别出长链肽、二硫键肽等；然后进行靶向的高分辨质谱分析，在优化的条件下，获取目标肽的高质量二级质谱，进行测序。为识别出血液中的微量神经肽标志物，将利用糖尿病小鼠作为模式动物，先比较分析神经肽在器官如胰腺、大脑和肠胃中的特异性变化，通过模式识别和关联性分析发现异变的器官神经肽；然后以这些肽为目标，对血液进行富集处理和靶向的定量分析，验证神经肽变化与疾病进展的联系，进而发现常规血液检测所不能发现的微量神经肽标志物。本项目的实施有望将神经肽组学研究推向新的高度，并大大提升从血液这种常见临床样本中发现神经肽标志物的能力。

神经肽的变化能够敏锐反映生物体的生理或病理状态。监测神经肽有助于深入研究疾病的发生、发展、转移机制等。针对神经肽鉴定率偏低难以满足疾病诊断的难题，我们建立了高效的神经肽识别和靶向分析方法：开发了基于数据挖掘的内源性链内二硫键肽检测新技术，将烷基化前后分子量增加116.0574 amu整数倍的离子对设定为一组潜在二硫键多肽，通过靶向的LC-MS/MS获取离子对的高分辨的二级质谱信息，搜库确认二硫键多肽并确定二硫键的位置，该技术可以将候选多肽的数量减少90%以上；提出了基于nanoLC-MS/MS技术同时分离和表征内源性肽和微蛋白的方法，同时提取微蛋白和多肽，并保存它们的完整状态，在ETD和HCD模式中使用高分辨率碎片方法同时监测内源性肽和微蛋白；利用算法搜索引擎ProteinGoggle对同位素质荷比和指纹进行光谱解释，方法可用于生物标记物发现或治疗诊断的低分子量蛋白质和肽的表征。在应用研究中，我们使用量化差分分析对海马和PFC神经肽进行检测，发现压力条件下，大鼠的神经肽发生明显变化，证明了方法的灵敏度和可靠性。..在项目执行期内，项目负责人及团队发展鉴定神经肽鉴定的核心技术，并在多种模式生物中进行了技术探索和验证，圆满完成了项目计划，总计发表文章7篇，培养神经肽研究人才6名；除完成设定计划外，在项目执行期内，项目负责人及团队开发出生物分子高效识别的算法专利1项，以及高精度测定方法与试剂盒2项，极大提高了成果的应用价值。新方法显著提高了多肽的鉴定率，增强在疾病中发现多肽标志物的能力，具有重要的推广价值。新方法有助于提高疾病潜在生物标志物的发现，促进疾病的分子生物学机理研究以及临床诊断研究，提升我国在神经肽标志物现研究领域的影响力。