Liang Yajing, Li Beibei, Zhang Qi, Zhang Shilong, He Xiaoqing, Jiang Libo, Jin Yi
College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China.
Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China.
AMB Express. 2021 Mar 1;11(1):34. doi: 10.1186/s13568-021-01192-x.
To accurately explore the interaction mechanism between Escherichia coli and Staphylococcus aureus, we designed an ecological experiment to monoculture and co-culture E. coli and S. aureus. We co-cultured 45 strains of E. coli and S. aureus, as well as each species individually to measure growth over 36 h. We implemented a genome wide association study (GWAS) based on growth parameters (λ, R, A and s) to identify significant single nucleotide polymorphisms (SNPs) of the bacteria. Three commonly used growth regression equations, Logistic, Gompertz, and Richards, were used to fit the bacteria growth data of each strain. Then each equation's Akaike's information criterion (AIC) value was calculated as a commonly used information criterion. We used the optimal growth equation to estimate the four parameters above for strains in co-culture. By plotting the estimates for each parameter across two strains, we can visualize how growth parameters respond ecologically to environment stimuli. We verified that different genotypes of bacteria had different growth trajectories, although they were the same species. We reported 85 and 52 significant SNPs that were associated with interaction in E. coli and S. aureus, respectively. Many significant genes might play key roles in interaction, such as yjjW, dnaK, aceE, tatD, ftsA, rclR, ftsK, fepA in E. coli, and scdA, trpD, sdrD, SAOUHSC_01219 in S. aureus. Our study illustrated that there were multiple genes working together to affect bacterial interaction, and laid a solid foundation for the later study of more complex inter-bacterial interaction mechanisms.
为准确探究大肠杆菌与金黄色葡萄球菌之间的相互作用机制，我们设计了一项生态实验，对大肠杆菌和金黄色葡萄球菌进行单培养和共培养。我们将45株大肠杆菌和金黄色葡萄球菌进行共培养，并分别对每种细菌进行单独培养，以测量其36小时内的生长情况。我们基于生长参数（λ、R、A和s）开展了全基因组关联研究（GWAS），以鉴定这些细菌的显著单核苷酸多态性（SNP）。使用三个常用的生长回归方程，即逻辑斯蒂方程、冈珀茨方程和理查兹方程，对各菌株的细菌生长数据进行拟合。然后计算每个方程的赤池信息准则（AIC）值，作为常用的信息准则。我们使用最优生长方程来估计共培养菌株的上述四个参数。通过绘制两种菌株各参数的估计值，我们可以直观地了解生长参数如何对环境刺激做出生态响应。我们证实，尽管是同一物种，但不同基因型的细菌具有不同的生长轨迹。我们分别报告了85个和52个与大肠杆菌和金黄色葡萄球菌相互作用相关的显著SNP。许多重要基因可能在相互作用中起关键作用，如大肠杆菌中的yjjW、dnaK、aceE、tatD、ftsA、rclR、ftsK、fepA，以及金黄色葡萄球菌中的scdA、trpD、sdrD、SAOUHSC_01219。我们的研究表明，有多个基因共同作用影响细菌间的相互作用，为后续研究更复杂的细菌间相互作用机制奠定了坚实基础。
