Suppr超能文献

通过结合肽配体文库处理和无标记蛋白质定量对脑脊液进行深入研究。

In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification.

机构信息

Institut de Pharmacologie et de Biologie Structurale (IPBS), CNRS, 205 route de Narbonne, 31077 Toulouse, France.

出版信息

Mol Cell Proteomics. 2010 May;9(5):1006-21. doi: 10.1074/mcp.M900513-MCP200. Epub 2010 Jan 21.

Abstract

Cerebrospinal fluid (CSF) is the biological fluid in closest contact with the brain and thus contains proteins of neural cell origin. Hence, CSF is a biochemical window into the brain and is particularly attractive for the search for biomarkers of neurological diseases. However, as in the case of other biological fluids, one of the main analytical challenges in proteomic characterization of the CSF is the very wide concentration range of proteins, largely exceeding the dynamic range of current analytical approaches. Here, we used the combinatorial peptide ligand library technology (ProteoMiner) to reduce the dynamic range of protein concentration in CSF and unmask previously undetected proteins by nano-LC-MS/MS analysis on an LTQ-Orbitrap mass spectrometer. This method was first applied on a large pool of CSF from different sources with the aim to better characterize the protein content of this fluid, especially for the low abundance components. We were able to identify 1212 proteins in CSF, and among these, 745 were only detected after peptide library treatment. However, additional difficulties for clinical studies of CSF are the low protein concentration of this fluid and the low volumes typically obtained after lumbar puncture, precluding the conventional use of ProteoMiner with large volume columns for treatment of patient samples. The method has thus been optimized to be compatible with low volume samples. We could show that the treatment is still efficient with this miniaturized protocol and that the dynamic range of protein concentration is actually reduced even with small amounts of beads, leading to an increase of more than 100% of the number of identified proteins in one LC-MS/MS run. Moreover, using a dedicated bioinformatics analytical work flow, we found that the method is reproducible and applicable for label-free quantification of series of samples processed in parallel.

摘要

脑脊液(CSF)是与大脑最接近的生物液体,因此含有神经细胞来源的蛋白质。因此,CSF 是大脑的生化窗口,特别适合寻找神经疾病的生物标志物。然而,与其他生物液体一样,CSF 蛋白质组学特征分析的主要挑战之一是蛋白质的浓度范围非常宽,大大超过了当前分析方法的动态范围。在这里,我们使用组合肽配体文库技术(ProteoMiner)来降低 CSF 中蛋白质浓度的动态范围,并通过在 LTQ-Orbitrap 质谱仪上进行纳升液相色谱-串联质谱(nano-LC-MS/MS)分析来揭示以前未检测到的蛋白质。该方法首先应用于来自不同来源的大量 CSF 池,旨在更好地描述这种液体的蛋白质含量,特别是低丰度成分。我们能够在 CSF 中鉴定出 1212 种蛋白质,其中 745 种蛋白质仅在经过肽文库处理后才能检测到。然而,CSF 进行临床研究的额外困难是这种液体的蛋白质浓度低,以及腰椎穿刺后通常获得的低体积,排除了常规使用 ProteoMiner 对患者样本进行大体积柱处理。因此,该方法已优化为与低体积样品兼容。我们能够证明即使使用这种小型化方案,处理仍然有效,并且蛋白质浓度的动态范围实际上甚至在使用少量珠子时也会降低,导致在一次 LC-MS/MS 运行中鉴定的蛋白质数量增加超过 100%。此外,使用专用的生物信息学分析工作流程,我们发现该方法具有可重复性,并且适用于平行处理的一系列样品的无标记定量。

相似文献

1
In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification.
Mol Cell Proteomics. 2010 May;9(5):1006-21. doi: 10.1074/mcp.M900513-MCP200. Epub 2010 Jan 21.
4
Top-Down Proteomics Applied to Human Cerebrospinal Fluid.
Methods Mol Biol. 2019;2044:193-219. doi: 10.1007/978-1-4939-9706-0_12.
5
Mass Spectrometry-Based Assay for Targeting Fifty-Two Proteins of Brain Origin in Cerebrospinal Fluid.
J Proteome Res. 2020 Aug 7;19(8):3060-3071. doi: 10.1021/acs.jproteome.0c00087. Epub 2020 Jun 3.
7
Proteomic analysis of cerebrospinal fluid extracellular vesicles: a comprehensive dataset.
J Proteomics. 2014 Jun 25;106:191-204. doi: 10.1016/j.jprot.2014.04.028. Epub 2014 Apr 24.

引用本文的文献

1
Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis.
Clin Proteomics. 2024 Jun 16;21(1):42. doi: 10.1186/s12014-024-09494-5.
2
Neuronal autoantibodies in the cerebrospinal fluid of 148 patients with schizophrenia and 151 healthy controls.
Heliyon. 2024 May 5;10(10):e30695. doi: 10.1016/j.heliyon.2024.e30695. eCollection 2024 May 30.
3
Microglia and complement mediate early corticostriatal synapse loss and cognitive dysfunction in Huntington's disease.
Nat Med. 2023 Nov;29(11):2866-2884. doi: 10.1038/s41591-023-02566-3. Epub 2023 Oct 9.
4
Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis.
Clin Proteomics. 2023 Aug 29;20(1):33. doi: 10.1186/s12014-023-09418-9.
5
DIGE Analysis of ProteoMiner™ Fractionated Serum/Plasma Samples.
Methods Mol Biol. 2023;2596:119-125. doi: 10.1007/978-1-0716-2831-7_10.
6
HBFP: a new repository for human body fluid proteome.
Database (Oxford). 2021 Oct 13;2021. doi: 10.1093/database/baab065.
8
Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease.
Clin Proteomics. 2020 May 29;17:19. doi: 10.1186/s12014-020-09285-8. eCollection 2020.

本文引用的文献

3
Quantitative proteomics reveals a dynamic association of proteins to detergent-resistant membranes upon elicitor signaling in tobacco.
Mol Cell Proteomics. 2009 Sep;8(9):2186-98. doi: 10.1074/mcp.M900090-MCP200. Epub 2009 Jun 13.
4
The role of cerebrospinal fluid proteins as early diagnostic markers for sporadic Creutzfeldt-Jakob disease.
Neurosci Lett. 2009 May 8;455(1):56-9. doi: 10.1016/j.neulet.2009.02.067. Epub 2009 Mar 5.
5
Neuropilins: novel targets for anti-angiogenesis therapies.
Cell Adh Migr. 2007 Apr-Jun;1(2):56-61. doi: 10.4161/cam.1.2.4490. Epub 2007 Apr 25.
6
The art of observing rare protein species in proteomes with peptide ligand libraries.
Proteomics. 2009 Mar;9(6):1492-510. doi: 10.1002/pmic.200800389.
8
Mitochondria in neuroplasticity and neurological disorders.
Neuron. 2008 Dec 10;60(5):748-66. doi: 10.1016/j.neuron.2008.10.010.
9
Brain-specific proteins decline in the cerebrospinal fluid of humans with Huntington disease.
Mol Cell Proteomics. 2009 Mar;8(3):451-66. doi: 10.1074/mcp.M800231-MCP200. Epub 2008 Nov 4.
10
Isoform-specific expression of 14-3-3 proteins in human astrocytoma.
J Neurol Sci. 2009 Jan 15;276(1-2):54-9. doi: 10.1016/j.jns.2008.08.040. Epub 2008 Oct 11.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验