石油降解菌功能特性高通量评价方法研究
Study on High-Throughput Evaluation Method of Functional Characteristics of Petroleum Degrading Bacteria
贺嘉妮 1孙先锋 1张丹 2梁蝶 3谢翼飞2
作者信息
- 1. 西安工程大学环境与化学工程学院,陕西 西安 710048
- 2. 中国科学院成都生物研究所,四川 成都 610041
- 3. 成都理工大学生态环境学院,四川 成都 610059
- 折叠
摘要
针对传统石油降解菌降解性能测定方法存在操作繁琐、周期长、工作量大等问题,探究菌株石油烃降解率与 4 个参数(脂肪酶、脱氢酶、邻苯二酚 2,3-双加氧酶、表面活性剂)之间的相关性,从而建立石油烃降解菌功能特性的高通量评价方法.通过 SPSS 统计软件进行回归分析,得到单一参数响应关系方程与多参数拟合方程并对方程进行优化.结果表明:菌株的石油烃降解率与各参数均成正相关,其中菌株的表面活性剂乳化性能、邻苯二酚2,3-双加氧酶活性与石油烃降解率呈显著相关(R2 分别为0.612 和0.673,P＜0.05).基于优化后的方程,用高通量的菌株酶活测定方法代替传统降解率测定方法对石油降解菌进行功能评价的方法操作简单、快速、通量高,在石油降解菌株筛选、菌群合成方面具有广阔的应用前景.
Abstract
Aiming at the problems of cumbersome operation,long cycle and large workload in the traditional petroleum-degrading bacteria degradation performance determination method,the correlation between the degradation rate of petroleum hydrocarbons and four parameters(lipase,dehydrogenase,catechol 2,3-dioxygenase,surfactant)was explored,so as to establish a high-throughput evaluation method for the functional characteristics of petroleum-degrading bacteria.The regression analysis was carried out by SPSS statistical software,and the single-parameter response relationship equation and the multi-parameter fitting equation were obtained and optimized.The results showed that the degradation rate of petroleum hydrocarbons was positively correlated with all parameters,and the emulsification performance of surfactant and the activity of catechol 2,3-dioxygenase were significantly correlated with the degradation rate of petroleum hydrocarbons(R2=0.612 and R2=0.673,P<0.05,respectively).Based on the optimized equation,the method of functional evaluation of petroleum-degrading bacteria by replacing the traditional degradation rate determination method with high-throughput strain enzyme activity determination method is simple,fast and high-throughput,which has broad application prospects in petroleum-degrading strain screening and biota synthesis.
关键词
石油烃降解/微生物修复/酶活/高通量评价/多元线性回归Key words
Petroleum hydrocarbon degradation/Microbial remediation/Enzyme activity/High-throughput evaluation/Multiple linear regression引用本文复制引用
基金项目
中国科学院战略生物资源服务网络计划"生物资源衍生库"项目(KFJ-BRP-009)
四川省重点研发项目(2020YFS0021)
出版年
2024
NETL
NSTL
万方数据