儿童中枢神经系统癌症脑脊液的深度蛋白质组分析

Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer

JOURNAL OF PROTEOME RESEARCH

影响因子:3.6

分区:生物学2区 / 生化研究方法2区

发表日期:2024 Nov 01

作者: Christian Mirian, Ole Østergaard, Maria Thastrup, Signe Modvig, Jon Foss-Skiftesvik, Jane Skjøth-Rasmussen, Marianne Berntsen, Josefine Britze, Alex Christian Yde Nielsen, René Mathiasen, Kjeld Schmiegelow, Jesper Velgaard Olsen

DOI: 10.1021/acs.jproteome.4c00471

摘要

脑脊液（CSF）是发现与预后相关的生物标志物及开发治疗靶点的重要基质，尤其在儿童中枢神经系统恶性肿瘤中具有重要意义。然而，儿童CSF蛋白浓度范围广泛且存在年龄相关差异，增加了研究难度。此外，儿童CSF样本常常稀少，首要用于临床诊断。本研究旨在优化蛋白质组分析流程，最大限度提取有限CSF资源中的详细蛋白质信息。策略包括应用连续超离心法富集细胞外囊泡（EV），以及分析少量原始CSF，从而在400 μL CSF中定量识别1351种蛋白（相对于原始CSF提升55%），加上光谱库，总共可定量2103种蛋白（提升240%）。通过优化输入体积、胰蛋白酶消化方法、梯度长度、质谱数据采集方式和数据库搜索策略，最大化蛋白质的检测。最终方案包括蛋白凝聚捕获（PAC）消化，结合数据无关采集（DIA，21分钟梯度），仅用400 μL CSF就能定量2989种独特蛋白，比分析原始CSF胰蛋白酶消化样品提升340%。

Abstract

The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.