FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts.

FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts.
复制标题

DOI:
10.1038/s41467-022-31922-z
复制
发表时间:
2022-07-29
影响因子:
16.6
通讯作者:
--
中科院分区:
综合性期刊1区
文献类型:
--
作者:

文献摘要

参考文献

被引文献

相似文献

自顶向下蛋白质组学(TDP)对蛋白质形态的详细分析和结构表征在生物医学研究中引起了广泛的兴趣。由于蛋白质形态的多样性和复杂性,完整蛋白质的数据依赖获取(DDA)是非平凡的。因此,专用的获取方法有可能大大提高TDP。在这里,我们提出FLASHIda,一种用于TDP的智能在线数据采集算法,确保实时选择各种蛋白质形态的高质量前体。FLASHIda结合了快速电荷反卷积算法和基于机器学习的质量评估,用于最优前体选择。在大肠杆菌裂解物的分析中,FLASHIda将独特的蛋白质水平鉴定的数量从800个增加到1500个,或者与标准DDA模式相比,在三分之一的仪器时间内产生几乎相同数量的鉴定。此外,FLASHIda能够灵敏地绘制翻译后修饰和检测化学加合物。FLASHIda作为仪器的软件扩展模块,可以很容易地用于复杂样品的TDP研究,以提高蛋白质形态的识别率。适合于自顶向下蛋白质组学(TDP)的数据采集具有显著改善蛋白质形态分析的潜力。在这里,作者提出FLASHIda,这是一种用于TDP的智能在线数据采集算法,它几乎使复杂样品中蛋白质水平的识别数量增加了一倍。
The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates. Data acquisition suitable for top-down proteomics (TDP) has the potential to significantly improve proteoform analysis. Here, the authors present FLASHIda, an intelligent online data acquisition algorithm for TDP that nearly doubles the number of proteoform-level identifications in complex samples.
DOI: 10.1093/nar/gkaa1113
发表时间: 2021-01-08
影响因子: 14.9
作者:
Gene Ontology Consortium
通讯作者: Gene Ontology Consortium
DOI: 10.1080/14789450.2020.1855982
发表时间: 2020-10
影响因子: 3.4
作者:
Brown KA;Melby JA;Roberts DS;Ge Y
通讯作者: Ge Y
DOI: 10.1021/pr401278j
发表时间: 2014-04-04
影响因子: 4.4
作者:
Bailey, Derek J.;McDevitt, Molly T.;Westphall, Michael S.;Pagliarini, David J.;Coon, Joshua J.
通讯作者: Coon, Joshua J.
DOI: 10.1093/bioinformatics/btw398
发表时间: 2016-11-15
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
Kou, Qiang;Xun, Likun;Liu, Xiaowen
通讯作者: Liu, Xiaowen
DOI: 10.1021/acs.jproteome.6b00698
发表时间: 2017-02-01
影响因子: 4.4
作者:
Fornelli, Luca;Durbin, Kenneth R.;Kelleher, Neil L.
通讯作者: Kelleher, Neil L.