基于反义RNA技术的FabI抑制剂筛选模型的构建

目的基于反义RNA沉默技术构建针对细菌FabI的超敏全细胞筛选模型,用于筛选FabI抑制剂。方法以Escherichia coli基因组DNA为模板,PCR扩增fabI基因的–74~86bp核苷酸序列,反向插入携带paired termini结构的反义质粒pHN678中,得到重组质粒pHNF,再转化至E.coli中,得到反义工程菌E.coli/pHNF;通过平板表型观察对反义工程菌进行筛选;考察了IPTG浓度对筛选模型的影响,确定96孔板抗菌筛选模型的条件,并用三氯生作为阳性对照、氨苄西林和浅蓝菌素作为阴性对照对该模型进行评价。结果获得了针对fabI的反义工程菌,确定了最适IPTG浓度为40μmol/L,成功构建了FabI特异性酶抑制剂的超敏全细胞筛选模型,并验证了其可行性。应用该筛选模型对5847个内生真菌次级代谢产物进行活性筛选,初筛阳性率约为9.7%,经复筛后获得8份阳性样品。结论成功建立了基于反义RNA沉默技术的FabI超敏全细胞筛选模型,并利用该模型筛选到8份阳性样品。

Establishment of screening model for FabI inhibitors based on antisense RNA technology

Objective To establish a highly sensitive whole-cell screening model targeting FabI based on antisense RNA silencing technology for FabI inhibitors screening. Methods In order to improve silencing effect, vector with paired termini was utilized. Transformants were identified by phenotype screening on solid plates. Effect of IPTG concentration was studied and the optimal screening parameters were determined. Triclosan and ampicillin were used as positive and negative control to evaluate the feasibility of this screening model, respectively. Results FabI antisense strain was obtained. The optimal concentration of IPTG was 40 μmol/L. The highly sensitive whole-cell FabI specific inhibitor screening model was established and evaluated. 5847 fermentation samples from endophytic fungi were screened and the positive rate was about 9.7%. Eight active samples were gained in secondary screening. Conclusion One highly sensitive whole-cell FabI specific inhibitor screening model was established based on antisense RNA technology and eight active samples were gained.