Mathematical Modelling of Toxic Metal Uptake and Efflux Pump in Metal-Resistant Bacterium Bacillus cereus Isolated From Heavy Crude Oil

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• 作者：Dario R. Shaw (1)
  Jenny Dussan (1)
  
  1. Centro de Investigaciones Microbiol贸gicas 鈥?CIMIC ; Departamento de Ciencias Biol贸gicas ; Universidad de los Andes ; Cra 1 No 18 A-10 ; Building J- 206 ; Bogot谩 ; Colombia
  
• 关键词：Bacillus cereus ; Toxic metals ; Efflux pump ; Bioaccumulation ; Biosorption ; Mathematical modelling
• 刊名：Water, Air, and Soil Pollution
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：226
• 期：4
• 全文大小：5,974 KB
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• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Environment
  Atmospheric Protection, Air Quality Control and Air Pollution
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  Terrestrial Pollution
  Hydrogeology
  
• 出版者：Springer Netherlands
• ISSN：1573-2932

文摘

The aim of this study was to describe the mechanisms that native Bacillus cereus M6 isolated from heavy crude oil oAPI gravity 11.5 uses to tolerate and/or resist toxic metals. Metal tolerance and removal of Pb(II), Cr(VI), and As(V) was determined. In addition, we evidenced the subcellular distribution of metals, the efflux pump kinetics, and morphological changes in metal-tolerant bacteria. B. cereus M6 exhibited strong tolerance and resistance to the metals evaluated and efficiently removed the metal content by operating efflux pumps and accumulating mainly in membrane fraction. Also, it was found that the model that best fit the efflux corresponds to an equation for resonant oscillations. B. cereus M6 uses mechanisms, including efflux pumps, intracellular and extracellular accumulation in parallel in order to maintain metal levels below a toxic threshold and overcome the effects of high concentrations. These findings are an approach of an energy-dependent efflux system to eliminate excessive amounts of crude oil-associated metals in Bacillus. B. cereus M6 may potentially be useful in designing improved strategies for the bioremediation of soils polluted with metals. Additionally, the prediction model developed would be useful for improving the monitoring of in vitro and in vivo bioremediation processes.