从采样到数据非依赖型采集质谱的神经肽表征工作流程

Neuropeptide Characterization Workflow from Sampling to Data-Independent Acquisition Mass Spectrometry.

作者信息

Okyem Samuel, Tan Yanqi, Romanova Elena, Sweedler Jonathan V

机构信息

Department of Chemistry, University of Illinois Urbana-Champaign; Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign.

Department of Chemistry, University of Illinois Urbana-Champaign; Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign;

出版信息

J Vis Exp. 2025 Aug 8(222). doi: 10.3791/68741.

Abstract

Endogenous neuropeptides are key modulators of brain function, playing critical roles in behavior, stress, pain, and homeostatic regulation, yet their analysis remains difficult. Biologically, they are low in abundance, rapidly degraded, and processed variably from precursor proteins, with expression limited to small, localized cell populations. Technically, their detection is complicated by a wide dynamic range, diverse post-translational modifications, and sparse signals in mass spectrometry datasets. This protocol outlines a comprehensive workflow for neuropeptide analysis in Rattus norvegicus brain tissue using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry (MS) on a timsTOF platform. Following optimized brain sample preparation, including dissection, peptide extraction and clean-up, nano liquid chromatography (LC)-MS is performed with ion mobility gas-phase fractionation to improve detection sensitivity and accuracy. The DDA-generated spectral library supports DIA-based quantification in Skyline, enabling high-confidence MS2-level measurements. This integrated workflow increases neuropeptide coverage and enhances quantitative reproducibility, providing a robust platform for studying neuropeptides in complex brain tissue.

摘要

内源性神经肽是脑功能的关键调节因子,在行为、应激、疼痛和稳态调节中发挥着关键作用,但其分析仍然困难。从生物学角度来看,它们丰度低、降解快,并且从前体蛋白加工而来的方式多变,其表达仅限于小的局部细胞群体。从技术角度而言,它们的检测因动态范围宽、翻译后修饰多样以及质谱数据集中信号稀疏而变得复杂。本方案概述了一种在timsTOF平台上使用数据依赖型采集(DDA)和数据非依赖型采集(DIA)质谱(MS)对褐家鼠脑组织中的神经肽进行分析的综合工作流程。在优化脑样本制备(包括解剖、肽提取和净化)之后,采用离子淌度气相分级的纳米液相色谱(LC)-MS来提高检测灵敏度和准确性。DDA生成的谱库支持在Skyline中基于DIA的定量分析,从而实现高可信度的二级质谱(MS2)水平测量。这种集成工作流程增加了神经肽的覆盖范围并提高了定量重现性,为研究复杂脑组织中的神经肽提供了一个强大的平台。

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