Mass spectrometry is the driving force behind current brain proteome analysis. In a typical proteomics approach, a protein isolate is digested into tryptic peptides and then analyzed by liquid chromatography–mass spectrometry. The recent advancements in data independent acquisition (DIA) mass spectrometry provide higher sensitivity and protein coverage than the classic data dependent acquisition. DIA cycles through a pre-defined set of peptide precursor isolation windows stepping through 400–1,200 m/z across the whole liquid chromatography gradient. All peptides within an isolation window are fragmented simultaneously and detected by tandem mass spectrometry. Peptides are identified by matching the ion peaks in a mass spectrum to a spectral library that contains information of the peptide fragment ions' pattern and its chromatography elution time. Currently, there are several reports on DIA in brain research, in particular the quantitative analysis of cellular and synaptic proteomes to reveal the spatial and/or temporal changes of proteins that underlie neuronal plasticity and disease mechanisms. Protocols in DIA are continuously improving in both acquisition and data analysis. The depth of analysis is currently approaching proteome-wide coverage, while maintaining high reproducibility in a stable and standardisable MS environment. DIA can be positioned as the method of choice for routine proteome analysis in basic brain research and clinical applications.

质谱分析是当前脑蛋白质组分析背后的驱动力。在典型的蛋白质组学方法中，蛋白质分离物被消化成胰蛋白酶肽，然后通过液相色谱-质谱法进行分析。数据独立获取（DIA）质谱的最新进展提供了比传统的数据依赖获取更高的灵敏度和蛋白质覆盖率。DIA在整个液相色谱梯度中循环通过一组预先定义的肽前体分离窗口，逐步通过400–1,200 m / z。同时分离窗口中的所有肽片段，并通过串联质谱检测。通过将质谱中的离子峰与包含肽片段离子的信息的光谱库进行匹配来鉴定肽 图案及其色谱洗脱时间。当前，在脑研究中有一些关于DIA的报道，特别是对细胞和突触蛋白质组的定量分析，以揭示构成神经元可塑性和疾病机制基础的蛋白质的时空变化。DIA中的协议在获取和数据分析方面都在不断改进。目前，分析的深度已接近蛋白质组的覆盖范围，同时在稳定且可标准化的MS环境中保持了高重现性。DIA可以定位为基础脑研究和临床应用中常规蛋白质组分析的首选方法。特别是对细胞和突触蛋白质组的定量分析，以揭示构成神经元可塑性和疾病机制基础的蛋白质的时空变化。DIA中的协议在获取和数据分析方面都在不断改进。目前，分析的深度已接近蛋白质组的覆盖范围，同时在稳定且可标准化的MS环境中保持了高重现性。DIA可以定位为基础脑研究和临床应用中常规蛋白质组分析的首选方法。特别是对细胞和突触蛋白质组的定量分析，以揭示构成神经元可塑性和疾病机制基础的蛋白质的时空变化。DIA中的协议在获取和数据分析方面都在不断改进。目前，分析的深度已接近蛋白质组的覆盖范围，同时在稳定且可标准化的MS环境中保持了高重现性。DIA可以定位为基础脑研究和临床应用中常规蛋白质组分析的首选方法。同时在稳定和标准化的MS环境中保持高重现性。DIA可以定位为基础脑研究和临床应用中常规蛋白质组分析的首选方法。同时在稳定和标准化的MS环境中保持高重现性。DIA可以定位为基础脑研究和临床应用中常规蛋白质组分析的首选方法。