five

Identification and Characterization of the Sulfolobus solfataricus P2 Proteome

收藏
acs.figshare.com2023-05-31 更新2025-03-25 收录
下载链接:
https://acs.figshare.com/articles/dataset/Identification_and_Characterization_of_the_i_Sulfolobus_i_i_s_i_i_olfataricus_i_P2_Proteome/3264205/1
下载链接
链接失效反馈
官方服务:
资源简介:
Via combined separation approaches, a total of 1399 proteins were identified, representing 47% of the Sulfolobus solfataricus P2 theoretical proteome. This includes 1323 proteins from the soluble fraction, 44 from the insoluble fraction and 32 from the extra-cellular or secreted fraction. We used conventional 2-dimensional gel electrophoresis (2-DE) for the soluble fraction, and shotgun proteomics for all three cell fractions (soluble, insoluble, and secreted). Two gel-based fractionation methods were explored for shotgun proteomics, namely:  (i) protein separation utilizing 1-dimensional gel electrophoresis (1-DE) followed by peptide fractionation by iso-electric focusing (IEF), and (ii) protein and peptide fractionation both employing IEF. Results indicate that a 1D-IEF fractionation workflow with three replicate mass spectrometric analyses gave the best overall result for soluble protein identification. A greater than 50% increment in protein identification was achieved with three injections using LC−ESI−MS/MS. Protein and peptide fractionation efficiency; together with the filtration criteria are also discussed. Keywords: 2-DE • shotgun • LC−MS/MS • multiple injections • pre-fractionation • S. solfataricus

通过综合的分离方法,共鉴定出1399种蛋白质,占到了苏铁硫磺菌P2理论蛋白组总量的47%。其中,1323种蛋白质来自可溶性部分,44种来自不溶性部分,32种来自细胞外或分泌部分。对于可溶性部分,我们采用了传统的二维凝胶电泳(2-DE)技术;而对于所有三个细胞部分(可溶性、不溶性及分泌部分),我们使用了射弹蛋白质组学技术。在射弹蛋白质组学中,我们探讨了两种基于凝胶的分级方法:(一)通过一维凝胶电泳(1-DE)进行蛋白质分离,随后采用等电聚焦(IEF)进行肽段分级;(二)同时利用IEF对蛋白质和肽段进行分级。结果表明,采用一维IEF分级流程并结合三次重复质谱分析,在可溶性蛋白质鉴定方面取得了最佳的整体效果。通过三次进样,LC-ESI-MS/MS技术实现了蛋白质鉴定率超过50%的提升。蛋白质和肽段的分级效率,以及过滤标准也在此进行了讨论。 关键词:2-DE • 射弹法 • LC-ESI-MS/MS • 多次进样 • 预分级 • 苏铁硫磺菌
提供机构:
acs.figshare.com
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作