De novo profiling of insect-resistant proteins of rice via nanopore peptide differentiation
文献类型: 外文期刊
第一作者: Xiao, Yicen
作者: Xiao, Yicen;Wang, Yunjiao;Chen, Xiaohan;Zhou, Shuo;Li, Minghan;Liang, Liyuan;Wang, Deqiang;Wang, Liang;Xiao, Yicen;Wang, Yunjiao;Chen, Xiaohan;Zhou, Shuo;Li, Minghan;Liang, Liyuan;Wang, Deqiang;Wang, Liang;Ren, Juansheng;Gao, Fangyuan;Ren, Guangjun;Ren, Juansheng;Gao, Fangyuan;Ren, Guangjun
作者机构:
关键词: Nanopore; Peptidome; Insect-resistance gene; Oryza sativa; Bioinformatics
期刊名称:BIOSENSORS & BIOELECTRONICS ( 影响因子:12.545; 五年影响因子:10.722 )
ISSN: 0956-5663
年卷期: 2022 年 212 卷
页码:
收录情况: SCI
摘要: Nanopore is used as a single-molecule detector for proteins, peptides and amino acids identification of biomedical importance. We, on the first try, extended its profiling application for peptidome encoded by the insect-resistance gene in rice. Taking brown planthopper (Bph) for example, we previously cloned and verified Bph32 gene, which encodes SCR ("Bph32") protein as direct executor against this injurious insect. However, the homology protein expressed in susceptible line doesn't have this antibiosis resistance. Hence, profiling the structural modulars (peptide domains) of Bph32 proteins may provide essential basis to understand rice in response to insects. Herein, we combined approaches of bioinformatics, biochemistry and nanopore analysis to profile the rice peptides with diverse properties. Bph32 proteins were theoretically modeled into 24 functional peptide domains using Swiss-Model workspace. Next, 22 water-soluble peptides were identified by biuretchemistry amplified nanopore current modulations. Among those, 16 ones were distinguished at one amino acid resolution via reading the current modulation spectrum, consequently providing the peptidome fingerprints. In addition, the current modulations were evidenced as quadratic function of peptide's molecular masses. These findings suggest that nanopore may work as a new generation of mass detector for more omics analysis, especially in agricultural field where demands strongly.
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