Objective To establish a highly sensitive whole-cell screening model targeting FabI based on antisense RNA silencing technology for FabI inhibitors screening.rnMethods 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.rnResults FabI antisense strain was obtained. The optimal concentration of IPTG was 40 umol/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.rnConclusion One highly sensitive whole-cell FabI specific inhibitor screening model was established based on antisense RNA technology and eight active samples were gained.%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 ～ 86 bp 核苷酸序列,反向插入携带 pairedtermini 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 40 μmol/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.
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