Aastha Aastha, Filho Leonardo Jose Monteiro Macedo, Woolman Michael, Ignatchenko Vladimir, Keszei Alexander, Remite-Berthet Gabriela, Mansouri Alireza, Kislinger Thomas
University of Toronto.
Penn State Milton S. Hershey Medical Center.
Res Sq. 2025 Jul 15:rs.3.rs-7031998. doi: 10.21203/rs.3.rs-7031998/v1.
Cerebrospinal fluid (CSF) provides a unique window into brain pathology, yet challenges in unbiased mass-spectrometric (MS) discovery persist due to sample complexity and the need for optimized analytical workflows. Multiple laboratory workflows have been developed for CSF proteomics, each with distinct advantages for specific applications. To interrogate which laboratory workflow is most suitable for this biological matrix, we benchmarked five orthogonal sample-preparation strategies-MStern, Proteograph nanoparticle enrichment (Seer), -glycopeptide capture (N-Gp), and two extracellular-vesicle (EV) fractions isolated by differential ultracentrifugation (P20- and P150-EV)-in CSF from 19 patients with central nervous system lymphoma. The protocols span a practical spectrum of input volume (6000-50 μL), hands-on time, and reagent cost, enabling informed method selection for translational applications. In total we performed 82 LC-MS/MS experiments and detected over 38,000 unique peptides and more than 3000 proteins across all modalities. Seer achieved the best proteomic depth (~ 17,000 unique peptides) and the tightest detection across samples, followed by P20-EV (~ 9,000), MStern (~ 5,500), P150-EV (~ 5,000), and N-Gp (~ 1,000). None of the methods introduced systematic bias in peptide or protein isoelectric point or hydrophobicity, yet each selectively highlighted distinct biological niches: P20-EVs favoured mitochondrial signatures, N-Gp capture lysosomal and plasma membrane signatures and Seer enhanced nuclear representation. These findings demonstrate that no single protocol suffices for every research question; instead, workflow selection should align with sample-volume constraints, budget and biological question. Our comparative framework empowers investigators to match CSF proteomics strategies to specific neuro-oncological objectives, thereby accelerating the translation of CSF biomarkers into clinically actionable assays.
脑脊液（CSF）为了解脑部病理状况提供了一个独特的窗口，但由于样本复杂性以及对优化分析工作流程的需求，在无偏质谱（MS）发现方面仍然存在挑战。已经为脑脊液蛋白质组学开发了多种实验室工作流程，每种流程在特定应用中都有不同的优势。为了探究哪种实验室工作流程最适合这种生物基质，我们对19例中枢神经系统淋巴瘤患者脑脊液中的五种正交样本制备策略进行了基准测试，即MStern、Proteograph纳米颗粒富集（Seer）、N-糖肽捕获（N-Gp）以及通过差速超速离心分离的两个细胞外囊泡（EV）组分（P20-EV和P150-EV）。这些方案涵盖了实际的输入体积范围（6000 - 50 μL）、操作时间和试剂成本，有助于为转化应用做出明智的方法选择。我们总共进行了82次液相色谱 - 质谱/质谱实验，在所有模式下检测到超过38000种独特肽段和3000多种蛋白质。Seer实现了最佳的蛋白质组深度（约17000种独特肽段）以及样本间最紧密的检测，其次是P20-EV（约9000种）、MStern（约5500种）、P150-EV（约5000种）和N-Gp（约1000种）。没有一种方法在肽段或蛋白质的等电点或疏水性方面引入系统偏差，但每种方法都选择性地突出了不同的生物生态位：P20-EV有利于线粒体特征，N-Gp捕获溶酶体和质膜特征，Seer增强了核蛋白的代表性。这些发现表明，没有一种单一方案能满足所有研究问题；相反，工作流程的选择应与样本体积限制、预算和生物学问题相匹配。我们的比较框架使研究人员能够将脑脊液蛋白质组学策略与特定的神经肿瘤学目标相匹配，从而加速脑脊液生物标志物向临床可操作检测方法的转化。
