生物学杂志 ›› 2022, Vol. 39 ›› Issue (2): 69-.doi: 10.3969/j.issn.2095-1736.2022.02.069

• 研究报告 • 上一篇    下一篇

一株自生固氮菌的筛选、鉴定及生长条件优化

  

  1. 湖南农业大学 生物科学技术学院, 长沙 410128
  • 出版日期:2022-04-18 发布日期:2022-04-18
  • 通讯作者: 田云,博士,教授,研究方向为生物化学与分子生物学,E-mail: tianyun@hunau.edu.cn
  • 作者简介:汪蕊露,硕士研究生,研究方向为生物化学与分子生物学,E-mail: 673079992@qq.com
  • 基金资助:
    湖南省科技重大专项(2018NK1030); 湖南省科技特派员创新创业项目(2020NK4194); 湖南战略性新兴产业科技攻关与重大科技成果转化项目(2019GK4018); 湖南农业大学“双一流”建设项目(SYL201802002)

A strain of abiogenousazotobacter: screening, identification and optimization of growth conditions

  1. College of Biological Science and Technology, Hunan Agricultural University, Changsha 410128, China
  • Online:2022-04-18 Published:2022-04-18

摘要: 为筛选获得稳定高效的自生固氮菌,从多个地区植物根际土壤以及淤泥中选取样品,以无氮培养基进行分离筛选,采用乙炔还原法测定固氮酶活性,经形态学观察、生理生化试验以及16S rDNA序列分子鉴定,并通过单因素与响应面试验相结合的方式对生长条件进行优化。结果表明,从山西省朔州市玉米根际的土壤中筛选到一株固氮酶活性达140.14 nmol C2H4/mg·protein·hr的自生固氮菌,该菌鉴定为Azotobacter属,命名Azotobacter sp. strain C-5-2;菌株最适生长的条件为蔗糖浓度 10 g/L、转速 148 r/min、温度32 ℃以及初始pH 9.0。

关键词: 自生固氮菌, 筛选, 生长条件, 响应面优化

Abstract: In order to screen and obtain stable and efficient abiogenousazotobacter, samples were selected from the soil of plant rhizosphere and silt in multiple regions, separated and screened with nitrogen-free medium, and nitrogenase activity was determined by acetylene reduction method. Morphological observation, physiological and biochemical test and 16S rDNA sequence molecular identification were made. Furthermore, the growth conditions were optimized through a combination of single factor and response surface test. The results showed that a strain of abiogenousazotobacter with nitrogenase activity of 140.14 nmol C2H4/mg·protein·hr was screened from the soil of the corn rhizosphere in Shuozhou, Shanxi Province. It was identified as Azotobacter and named Azotobacter sp. strain C-5-2; the optimal conditions for the growth of the strain were sucrose concentration 10 g/L, rotation speed 148 r/min, temperature 32 ℃ and initial pH 9.0.

Key words: abiogenousazotobacter, screening, growth conditions, response surface optimization

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