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从垃圾渗滤液中分离出可在生物修复中应用的砷积累细菌。

Isolation of arsenic accumulating bacteria from garbage leachates for possible application in bioremediation.

作者信息

Taran Mojtaba, Fateh Roohollah, Rezaei Shima, Gholi Mohammad Khalifeh

机构信息

Department of Biology, Faculty of Sciences, Razi University, Kermanshah, Iran.

Cellular and Molecular Research Center, Qom University of Medical Sciences, Qom, Iran.

出版信息

Iran J Microbiol. 2019 Feb;11(1):60-66.

Abstract

BACKGROUND AND OBJECTIVES

Bioremediation is a process to reduce toxic heavy-metals, such as arsenic, in the environment using microorganisms. This study aimed to isolate arsenic remediating microbial strains from garbage leachates and to evaluate the effects of several factors on bioremediation by isolated strains.

MATERIALS AND METHODS

After isolating arsenic-resistant bacteria from garbage leachates and determining their MIC values, Taguchi design of experiments was used to evaluate the effect of arsenic concentration, pH solution, temperature, and contact time on arsenic bioremediation by isolated bacteria.

RESULTS

The results revealed that 3 arsenic-resistant strains of genus characterized as KL1, KL4, and KL6 had arsenic bioremediation activity. Based on the results, the highest bioremediation of arsenic by sp. KL1 was obtained as 77% after 24 hours at 40°C, pH 5, and 150 ppm concentration. However, the maximum bioremediation of arsenic by KL4 (91.66%) and KL6 (88%) was achieved after 24 hours at 40°C, pH 5, and 60 ppm concentration and at 35°C, 90 ppm concentration, pH 5 after 36 hours, respectively.

CONCLUSION

The results presented here may facilitate improvements in the eliminating arsenic from contaminated sites and reducing environmental pollutions.

摘要

背景与目的

生物修复是利用微生物减少环境中有毒重金属(如砷)的过程。本研究旨在从垃圾渗滤液中分离砷修复微生物菌株,并评估多种因素对分离菌株生物修复的影响。

材料与方法

从垃圾渗滤液中分离抗砷细菌并测定其最低抑菌浓度(MIC)值后,采用田口实验设计评估砷浓度、溶液pH值、温度和接触时间对分离细菌砷生物修复的影响。

结果

结果显示,鉴定为KL1、KL4和KL6的3株抗砷菌株具有砷生物修复活性。根据结果,在40°C、pH值为5、浓度为150 ppm的条件下培养24小时后,KL1菌株对砷的最高生物修复率为77%。然而,KL4(91.66%)和KL6(88%)对砷的最大生物修复率分别在40°C、pH值为5、浓度为60 ppm的条件下培养24小时后以及在35°C、浓度为90 ppm、pH值为5的条件下培养36小时后实现。

结论

此处呈现的结果可能有助于改进从污染场地去除砷并减少环境污染。

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本文引用的文献

1
Biosorption of arsenic (III) from aqueous solution by living cells of Bacillus cereus.
Environ Sci Pollut Res Int. 2013 Mar;20(3):1281-91. doi: 10.1007/s11356-012-1249-6. Epub 2012 Oct 24.
2
Arsenic bioremediation potential of a new arsenite-oxidizing bacterium Stenotrophomonas sp. MM-7 isolated from soil.
Biodegradation. 2012 Nov;23(6):803-12. doi: 10.1007/s10532-012-9567-4. Epub 2012 Jul 4.
3
Arsenic-resistant bacteria isolated from agricultural soils of Bangladesh and characterization of arsenate-reducing strains.
J Appl Microbiol. 2009 Jul;107(1):145-56. doi: 10.1111/j.1365-2672.2009.04188.x. Epub 2009 Mar 9.
4
On the potential of biological treatment for arsenic contaminated soils and groundwater.
J Environ Manage. 2009 Jun;90(8):2367-76. doi: 10.1016/j.jenvman.2009.02.001. Epub 2009 Mar 9.
5
Kinetic and equilibrium studies of biosorption of Pb(II) and Cd(II) from aqueous solution by macrofungus (Amanita rubescens) biomass.
J Hazard Mater. 2009 May 30;164(2-3):1004-11. doi: 10.1016/j.jhazmat.2008.09.002. Epub 2008 Sep 5.
6
Arsenic-resistant bacteria isolated from contaminated sediments of the Orbetello Lagoon, Italy, and their characterization.
J Appl Microbiol. 2007 Dec;103(6):2299-308. doi: 10.1111/j.1365-2672.2007.03471.x.
7
Arsenic geochemistry and health.
Environ Int. 2005 Jul;31(5):631-41. doi: 10.1016/j.envint.2004.10.020. Epub 2004 Dec 8.
8
Adsorption of Pb(II) from aqueous solution by Azadirachta indica (Neem) leaf powder.
J Hazard Mater. 2004 Sep 10;113(1-3):97-109. doi: 10.1016/j.jhazmat.2004.05.034.

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