Liu Xinyue, Dawson Shane L, Gygi Steven P, Paulo Joao A
Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States.
J Proteome Res. 2025 Mar 7;24(3):1414-1424. doi: 10.1021/acs.jproteome.4c01107. Epub 2025 Feb 12.
Comprehensive global proteome profiling that is amenable to high throughput processing will broaden our understanding of complex biological systems. Here, we evaluate two leading mass spectrometry techniques, Data Independent Acquisition (DIA) and Tandem Mass Tagging (TMT), for extensive protein abundance profiling. DIA provides label-free quantification with a broad dynamic range, while TMT enables multiplexed analysis using isobaric tags for efficient cross-sample comparisons. We analyzed 18 samples, including four cell lines (IHCF, HCT116, HeLa, MCF7) under standard growth conditions, in addition to IHCF treated with two HO concentrations, all in triplicate. Experiments were conducted on an Orbitrap Astral mass spectrometer, employing Field Asymmetric Ion Mobility Spectrometry (FAIMS). Despite utilizing different acquisition strategies, both the DIA and TMT approaches achieved comparable proteome depth and quantitative consistency, with each method quantifying over 10,000 proteins across all samples, with marginally higher protein-level precision for the TMT strategy. Relative abundance correlation analysis showed strong agreement at both peptide and protein levels. Our findings highlight the complementary strengths of DIA and TMT for high-coverage proteomic studies, providing flexibility in method selection based on specific experimental needs.
适用于高通量处理的全面全球蛋白质组分析将拓宽我们对复杂生物系统的理解。在此,我们评估了两种领先的质谱技术,即数据非依赖采集(DIA)和串联质量标签(TMT),用于广泛的蛋白质丰度分析。DIA提供具有宽动态范围的无标记定量,而TMT使用等压标签实现多重分析,以便进行高效的跨样本比较。我们分析了18个样本,包括处于标准生长条件下的四种细胞系(IHCF、HCT116、HeLa、MCF7),以及用两种HO浓度处理的IHCF,所有样本均为一式三份。实验在配备场不对称离子迁移谱(FAIMS)的Orbitrap Astral质谱仪上进行。尽管采用了不同的采集策略,但DIA和TMT方法都实现了相当的蛋白质组深度和定量一致性,每种方法在所有样本中都能定量超过10,000种蛋白质,TMT策略在蛋白质水平上的精度略高。相对丰度相关性分析表明,在肽和蛋白质水平上都有很强的一致性。我们的研究结果突出了DIA和TMT在高覆盖蛋白质组学研究中的互补优势,为根据特定实验需求选择方法提供了灵活性。