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Identification of 7 000–9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC–MS/MS

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NIAID Data Ecosystem2026-03-12 收录
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https://figshare.com/articles/dataset/Identification_of_7_000_9_000_Proteins_from_Cell_Lines_and_Tissues_by_Single-Shot_Microflow_LC_MS_MS/14779595
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A current trend in proteomics is to acquire data in a “single-shot” by LC–MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC–MS/MS system operating a 1 mm i.d. × 150 mm column, at a flow-rate of 50 μL/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of ∼9 000 proteins from 50 μg of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by μLC–MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.̀

当前蛋白质组学领域的主流趋势是采用液相色谱-串联质谱(LC–MS/MS)开展“单针进样”式数据采集,因其可简化实验流程,且相较于需大规模样品分级分离的实验方案,有望实现更高的分析通量与定量准确性。然而,在纳流液相色谱系统上采用数据依赖性采集(data dependent acquisition, DDA)的单针进样方法,往往存在蛋白质组覆盖度不足的缺陷。针对样品量较为充裕的应用场景,本研究表明,使用搭载1 mm内径×150 mm长度色谱柱、流速为50 μL/min的微流液相色谱-串联质谱系统,并耦合轨道阱HF-X(Orbitrap HF-X)质谱仪,可获得高覆盖度的蛋白质组分析结果。实验结果显示,单次分析时长仅3小时的单针进样中,可从50 μg拟南芥根系蛋白酶解产物中鉴定出约9000种蛋白质,从小鼠胸腺样品中鉴定出7500种,从人类乳腺癌细胞样品中鉴定出7300种。采用基于强度的绝对定量法(intensity-based absolute quantification, iBAQ)测得的蛋白质定量动态范围可达5个数量级,重复实验分析显示其中位变异系数低于20%。综上,本研究证实,基于微流液相色谱-串联质谱的单针数据依赖性采集(ssDDA)是一种适用于大规模、全覆盖蛋白质组分析的稳健方法,未来可进一步拓展至更快流速色谱及数据非依赖性采集(data independent acquisition, DIA)等技术方案中。
创建时间:
2021-06-14
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