Devi Surekha, Chhibber Sanjay, Harjai Kusum
Department of Microbiology, Panjab University, Chandigarh, India.
3 Biotech. 2022 Jun;12(6):133. doi: 10.1007/s13205-022-03187-2. Epub 2022 May 23.
Disruption of quorum sensing (QS) system, which is a central regulator for pathogenesis of , is referring to as quorum quenching (QQ). This study was undertaken to evaluate and enhance the anti-quorum sensing (AQS) potential of probiotic strain GG. The cell-free supernatant (CFS) of this probiotic strain showed anti-quorum sensing activity against which was determined using well-diffusion agar-plate assay. Anti-quorum sensing potential of GG was enhanced by optimization of various cultural conditions using classical and statistical optimization approaches. Six variables were optimized using one-variable-at-a-time (OVAT) method. Four significant variables, viz., temperature, pH, incubation time, metal ion, and its concentration, were chosen for further optimization by response surface methodology (RSM) using central composite design (CCD). Analysis of variance (ANOVA) demonstrated that the regression model is highly significant, as indicated by F test with a low probability value ( < 0.0002) and high value of coefficient of determination (0.8738) and also had significant influence on the generation of anti-quorum sensing effector molecules. Maximum production of anti-quorum sensing activity, in terms of zones of inhibition, was achieved under the following optimized conditions such as 37 °C temperature, pH 6.5, incubation time 24 h, and 2.5 mM concentration of zinc sulfate (ZnSO). The quadratic model predicted 1.3-fold increase anti-quorum sensing activity production over un-optimized cultural conditions. The present research is the first report representing the enhancement of anti-quorum sensing potential of GG.
The online version contains supplementary material available at 10.1007/s13205-022-03187-2.
群体感应(QS)系统的破坏是指群体猝灭(QQ),而群体感应系统是……发病机制的核心调节因子。本研究旨在评估和增强益生菌菌株GG的抗群体感应(AQS)潜力。该益生菌菌株的无细胞上清液(CFS)对……显示出抗群体感应活性,这是通过琼脂平板扩散法测定的。使用经典和统计优化方法对各种培养条件进行优化,从而增强了GG的抗群体感应潜力。采用一次一个变量(OVAT)方法对六个变量进行了优化。选择了四个显著变量,即温度、pH值、培养时间、金属离子及其浓度,通过响应面法(RSM)和中心复合设计(CCD)进行进一步优化。方差分析(ANOVA)表明回归模型具有高度显著性,F检验的低概率值(<0.0002)和高决定系数值(0.8738)表明了这一点,并且对抗群体感应效应分子的产生也有显著影响。在以下优化条件下,即37°C温度、pH 6.5、培养时间24小时和2.5 mM硫酸锌(ZnSO)浓度下,以抑制圈表示的抗群体感应活性达到最大产量。二次模型预测,与未优化的培养条件相比,抗群体感应活性产量提高了1.3倍。本研究是第一份关于增强GG抗群体感应潜力的报告。
在线版本包含可在10.1007/s13205-022-03187-2获取的补充材料。