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鉴定大肠杆菌中的新小蛋白。

Identifying New Small Proteins in Escherichia coli.

机构信息

Department of Biological Sciences, Smith Hall, Towson University, Towson, MD, USA.

出版信息

Proteomics. 2018 May;18(10):e1700064. doi: 10.1002/pmic.201700064. Epub 2018 May 2.

Abstract

The number of small proteins (SPs) encoded in the Escherichia coli genome is unknown, as current bioinformatics and biochemical techniques make short gene and small protein identification challenging. One method of small protein identification involves adding an epitope tag to the 3' end of a short open reading frame (sORF) on the chromosome, with synthesis confirmed by immunoblot assays. In this study, this strategy was used to identify new E. coli small proteins, tagging 80 sORFs in the E. coli genome, and assayed for protein synthesis. The selected sORFs represent diverse sequence characteristics, including degrees of sORF conservation, predicted transmembrane domains, sORF direction with respect to flanking genes, ribosome binding site (RBS) prediction, and ribosome profiling results. Of 80 sORFs, 36 resulted in encoded synthesized proteins-a 45% success rate. Modeling of detected versus non-detected small proteins analysis showed predictions based on RBS prediction, transcription data, and ribosome profiling had statistically-significant correlation with protein synthesis; however, there was no correlation between current sORF annotation and protein synthesis. These results suggest substantial numbers of small proteins remain undiscovered in E. coli, and existing bioinformatics techniques must continue to improve to facilitate identification.

摘要

大肠杆菌基因组中编码的小蛋白(SPs)数量未知,因为当前的生物信息学和生化技术使得短基因和小蛋白的鉴定具有挑战性。一种小蛋白鉴定方法涉及在染色体上的短开放阅读框(sORF)的 3' 端添加一个表位标签,通过免疫印迹分析来确认合成。在这项研究中,该策略用于鉴定新的大肠杆菌小蛋白,标记大肠杆菌基因组中的 80 个 sORF,并对蛋白质合成进行了检测。所选的 sORF 代表了不同的序列特征,包括 sORF 保守程度、预测的跨膜结构域、相对于侧翼基因的 sORF 方向、核糖体结合位点(RBS)预测和核糖体谱分析结果。在 80 个 sORF 中,有 36 个产生了编码合成的蛋白质——成功率为 45%。对检测到的和未检测到的小蛋白分析表明,基于 RBS 预测、转录数据和核糖体谱分析的预测与蛋白质合成具有统计学显著相关性;然而,当前 sORF 注释与蛋白质合成之间没有相关性。这些结果表明,大肠杆菌中仍有大量的小蛋白未被发现,现有的生物信息学技术必须不断改进,以促进鉴定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d60/6001520/5887e07b305d/PMIC-18-na-g001.jpg

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