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谷氨酸棒杆菌不同生长时期非编码sRNA的预测与鉴定
引用本文:王弋,范志豪,饶志明,徐美娟. 谷氨酸棒杆菌不同生长时期非编码sRNA的预测与鉴定[J]. 微生物学报, 2023, 63(10): 3876-3890
作者姓名:王弋  范志豪  饶志明  徐美娟
作者单位:江南大学生物工程学院 工业生物技术教育部重点实验室, 江苏 无锡 214122
基金项目:国家自然科学基金(32270036);国家重点研发计划(2021YFC2100900);中央高校基本科研专项资金(JUSRP221012)
摘    要:【目的】探究与挖掘不同生长时期谷氨酸棒杆菌(Corynebacterium glutamicum)中潜在的小的非编码RNA (small non-coding RNA,sRNA)。【方法】检测不同时期和不同工业改造的谷氨酸棒杆菌菌株的RNA-Seq数据构建表达文库,通过sRNA-Detect和APERO两种方法构建潜在的sRNA数据库。以逆转录PCR检测(real-time reverse transcription PCR,RT-PCR)方法检测sRNA的表达,并通过生物信息学方法分析潜在sRNA的调控位点、二级结构及保守结构域。【结果】构建了包含2 653条潜在sRNA的数据库,依据其相较于编码序列(coding sequence,CDS)区域的位置进行分类、预测功能。发现了在高GC革兰氏阳性菌中普遍存在的sRNA00130,随生长时期表达量变化的sRNA00257,常时高表达的sRNA02036、sRNA02037等sRNA。依据自由结合能预测潜在sRNA可能的结合位点、二级结构,预测结果显示潜在的sRNAs同多种细胞复制、代谢通路基因相关。大多数潜在sRNA仅在谷氨酸棒杆菌中具有保守性。【结论】谷氨酸棒杆菌潜在sRNA的发掘对于填补谷氨酸棒杆菌生长调控机制的空缺具有重要作用,提供了新的可能的调控工具与改造位点。

关 键 词:谷氨酸棒杆菌  小的非编码RNA (sRNA)  生物信息学  全基因组分析  sRNA-Detect
收稿时间:2023-02-24
修稿时间:2023-04-27

Prediction and identification of non-coding sRNAs in Corynebacterium glutamicum at different growth stages
WANG Yi,FAN Zhihao,RAO Zhiming,XU Meijuan. Prediction and identification of non-coding sRNAs in Corynebacterium glutamicum at different growth stages[J]. Acta microbiologica Sinica, 2023, 63(10): 3876-3890
Authors:WANG Yi  FAN Zhihao  RAO Zhiming  XU Meijuan
Affiliation:Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi 214122, Jiangsu, China
Abstract:[Objective] To investigate the small non-coding RNAs (sRNAs) in Corynebacterium glutamicum at different growth stages.[Methods] We examined the RNA-Seq data of C. glutamicum strains at different growth stages and transformed for industrial production and then employed sRNA-Detect and APERO approaches to construct the prospective sRNA library. real-time reverse transcription PCR (RT-PCR) was carried out to determine the expression of sRNAs. The functions, secondary structures, and conserved domains of potential sRNAs were predicted by bioinformatics tools. [Results] We constructed a library containing 2 653 potential sRNAs and performed classification and functional prediction based on their positions relative to the coding sequence (CDS) region. We identified sRNA00130 ubiquitous in Gram-positive bacteria with high GC content, sRNA00257 with varied expression during the growth period, and sRNA02036 and sRNA02037 with high expression. We predicted the possible binding sites and secondary structures of potential sRNAs based on free binding energy. The prediction results showed that potential sRNAs were associated with a variety of genes involved in cell replication and metabolic pathways. Most potential sRNAs were conserved only in C. glutamicum. [Conclusion] The discovery of potential sRNAs in C. glutamicum helps to fill the vacancy in the growth regulation mechanism of C. glutamicum and provides a new possible regulation tool and modification site.
Keywords:Corynebacterium glutamicum  small non-coding RNAs (sRNA)  bioinformatics  genome-wide analysis  sRNA-Detect
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