Li Kai, Teo Guo Ci, Yang Kevin L, Yu Fengchao, Nesvizhskii Alexey I
Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
Nat Commun. 2025 Jan 2;16(1):95. doi: 10.1038/s41467-024-55448-8.
Data-independent acquisition has become a widely used strategy for peptide and protein quantification in liquid chromatography-tandem mass spectrometry-based proteomics studies. The integration of ion mobility separation into data-independent acquisition analysis, such as the diaPASEF technology available on Bruker's timsTOF platform, further improves the quantification accuracy and protein depth achievable using data-independent acquisition. We introduce diaTracer, a spectrum-centric computational tool optimized for diaPASEF data. diaTracer performs three-dimensional (mass to charge ratio, retention time, ion mobility) peak tracing and feature detection to generate precursor-resolved "pseudo-tandem mass spectra", facilitating direct ("spectral-library free") peptide identification and quantification from diaPASEF data. diaTracer is available as a stand-alone tool and is fully integrated into the widely used FragPipe computational platform. We demonstrate the performance of diaTracer and FragPipe using diaPASEF data from triple-negative breast cancer, cerebrospinal fluid, and plasma samples, data from phosphoproteomics and human leukocyte antigens immunopeptidomics experiments, and low-input data from a spatial proteomics study. We also show that diaTracer enables unrestricted identification of post-translational modifications from diaPASEF data using open/mass-offset searches.
在基于液相色谱-串联质谱的蛋白质组学研究中,数据非依赖采集已成为一种广泛应用于肽段和蛋白质定量分析的策略。将离子淌度分离技术整合到数据非依赖采集分析中,如布鲁克timsTOF平台上的diaPASEF技术,进一步提高了使用数据非依赖采集所能达到的定量准确性和蛋白质鉴定深度。我们介绍了diaTracer,这是一种针对diaPASEF数据优化的以谱图为中心的计算工具。diaTracer执行三维(质荷比、保留时间、离子淌度)峰追踪和特征检测,以生成前体解析的“伪串联质谱”,便于从diaPASEF数据中直接(“无需谱图库”)进行肽段鉴定和定量分析。diaTracer可作为独立工具使用,并已完全集成到广泛使用的FragPipe计算平台中。我们使用来自三阴性乳腺癌、脑脊液和血浆样本的diaPASEF数据、磷酸化蛋白质组学和人类白细胞抗原免疫肽组学实验的数据以及空间蛋白质组学研究的低输入数据,展示了diaTracer和FragPipe的性能。我们还表明,diaTracer能够通过开放/质量偏移搜索从diaPASEF数据中无限制地鉴定翻译后修饰。