Toxicity assessment of heavy metals and organic compounds using CellSense biosensor with E.coli

Hong Wang Xue Jiang Wang Jian Fu Zhao Ling Chen

引用本文: Hong Wang,  Xue Jiang Wang,  Jian Fu Zhao,  Ling Chen. Toxicity assessment of heavy metals and organic compounds using CellSense biosensor with E.coli[J]. Chinese Chemical Letters, 2008, 19(2): 211-214. doi: 10.1016/j.cclet.2007.10.053 shu
Citation:  Hong Wang,  Xue Jiang Wang,  Jian Fu Zhao,  Ling Chen. Toxicity assessment of heavy metals and organic compounds using CellSense biosensor with E.coli[J]. Chinese Chemical Letters, 2008, 19(2): 211-214. doi: 10.1016/j.cclet.2007.10.053 shu

Toxicity assessment of heavy metals and organic compounds using CellSense biosensor with E.coli

  • 基金项目:

    This work was supported by the National Natural Science Foundation of China (No.20707014) and the Program for Young Excellent Talents of Tongji University.

摘要: A new strategy using an amperometric biosensor with Escherichia coli(E.coli) that provides a rapid toxicity determination of chemical compounds is described.The CellSense biosensor system comprises a biological component immobilized in intimate contact with a transducer which converts the biochemical signal into a quantifiable electrical signal.Toxicity assessment of heavy metals using E.coli biosensors could be finished within 30 min and the 50% effective concentrations (EC50) values of four heavy metals were determined.The results shows that inhibitory effects of four heavy metals to E.coli can be ranked in a decreasing order of Hg2+ > Cu2+ > Zn2+ > Ni2+, which accords to the results of conventional bacterial counting method.The toxicity test of organic compounds by using CellSense biosensor was also demonstrated.The CellSense biosensor with E.coli shows a good, reproducible behavior and can be used for reproducible measurements.

English

  • 加载中
计量
  • PDF下载量:  0
  • 文章访问数:  834
  • HTML全文浏览量:  37
文章相关
  • 收稿日期:  2007-08-28
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

/

返回文章