Suppr超能文献

从高度污染的橡树岭保留地中筛选出耐多种金属的硝酸盐利用微生物。

Nitrate-Utilizing Microorganisms Resistant to Multiple Metals from the Heavily Contaminated Oak Ridge Reservation.

机构信息

Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia, USA.

Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.

出版信息

Appl Environ Microbiol. 2019 Aug 14;85(17). doi: 10.1128/AEM.00896-19. Print 2019 Sep 1.

Abstract

Contamination of environments with nitrate generated by industrial processes and the use of nitrogen-containing fertilizers is a growing problem worldwide. While nitrate can be removed from contaminated areas by microbial denitrification, nitrate frequently occurs with other contaminants, such as heavy metals, that have the potential to impede the process. Here, nitrate-reducing microorganisms were enriched and isolated from both groundwater and sediments at the Oak Ridge Reservation (ORR) using concentrations of nitrate and metals (Al, Mn, Fe, Co, Ni, Cu, Cd, and U) similar to those observed in a contaminated environment at ORR. Seven new metal-resistant, nitrate-reducing strains were characterized, and their distribution across both noncontaminated and contaminated areas at ORR was examined. While the seven strains have various pH ranges for growth, carbon source preferences, and degrees of resistance to individual and combinations of metals, all were able to reduce nitrate at similar rates both in the presence and absence of the mixture of metals found in the contaminated ORR environment. Four strains were identified in groundwater samples at different ORR locations by exact 16S RNA sequence variant analysis, and all four were found in both noncontaminated and contaminated areas. By using environmentally relevant metal concentrations, we successfully isolated multiple organisms from both ORR noncontaminated and contaminated environments that are capable of reducing nitrate in the presence of extreme mixed-metal contamination. Nitrate contamination is a global issue that affects groundwater quality. In some cases, cocontamination of groundwater with nitrate and mixtures of heavy metals could decrease microbially mediated nitrate removal, thereby increasing the duration of nitrate contamination. Here, we used metal and nitrate concentrations that are present in a contaminated site at the Oak Ridge Reservation to isolate seven metal-resistant strains. All were able to reduce nitrate in the presence of high concentrations of a mixture of heavy metals. Four of seven strains were located in pristine as well as contaminated sites at the Oak Ridge Reservation. Further study of these nitrate-reducing strains will uncover mechanisms of resistance to multiple metals that will increase our understanding of the effect of nitrate and metal contamination on groundwater microbial communities.

摘要

工业过程产生的硝酸盐和含氮肥料的使用导致环境受到污染,这是一个在全球范围内日益严重的问题。虽然可以通过微生物反硝化作用从受污染的区域去除硝酸盐,但硝酸盐经常与其他污染物(如重金属)一起存在,这些污染物有可能阻碍这一过程。在这里,使用与橡树岭保护区(ORR)受污染环境中观察到的浓度相似的硝酸盐和金属(Al、Mn、Fe、Co、Ni、Cu、Cd 和 U),从地下水和沉积物中富集和分离了硝酸盐还原微生物。对 7 种新的耐金属硝酸盐还原菌进行了表征,并研究了它们在 ORR 非污染和污染区域的分布情况。虽然这 7 种菌株的生长 pH 值范围、碳源偏好和对单个及组合金属的抗性程度各不相同,但所有菌株在存在和不存在混合金属的情况下,都能以相似的速率还原硝酸盐。通过精确的 16S RNA 序列变异分析,在 ORR 的不同地点的地下水样本中鉴定出 4 种菌株,而且这 4 种菌株都存在于非污染和污染区域。通过使用与环境相关的金属浓度,我们成功地从 ORR 非污染和污染环境中分离出了多种能够在极端混合金属污染下还原硝酸盐的生物体。硝酸盐污染是一个全球性问题,影响地下水质量。在某些情况下,地下水同时受到硝酸盐和重金属混合物的污染可能会降低微生物介导的硝酸盐去除,从而延长硝酸盐污染的持续时间。在这里,我们使用橡树岭保护区污染场地存在的金属和硝酸盐浓度来分离 7 种耐金属菌株。所有菌株都能够在高浓度混合重金属存在的情况下还原硝酸盐。7 株菌中的 4 株位于橡树岭保护区的原始和污染地点。对这些硝酸盐还原菌的进一步研究将揭示对多种金属的抗性机制,从而增加我们对硝酸盐和金属污染对地下水微生物群落的影响的理解。

相似文献

1
Nitrate-Utilizing Microorganisms Resistant to Multiple Metals from the Heavily Contaminated Oak Ridge Reservation.
Appl Environ Microbiol. 2019 Aug 14;85(17). doi: 10.1128/AEM.00896-19. Print 2019 Sep 1.
2
Molybdenum Availability Is Key to Nitrate Removal in Contaminated Groundwater Environments.
Appl Environ Microbiol. 2015 Aug;81(15):4976-83. doi: 10.1128/AEM.00917-15. Epub 2015 May 15.
3
Genomic Features and Pervasive Negative Selection in Strains Isolated from Nitrate and Heavy Metal Contaminated Aquifer.
Microbiol Spectr. 2022 Feb 23;10(1):e0259121. doi: 10.1128/spectrum.02591-21. Epub 2022 Feb 2.
4
Lateral Gene Transfer in a Heavy Metal-Contaminated-Groundwater Microbial Community.
mBio. 2016 Apr 5;7(2):e02234-15. doi: 10.1128/mBio.02234-15.
5
Iron- and aluminium-induced depletion of molybdenum in acidic environments impedes the nitrogen cycle.
Environ Microbiol. 2019 Jan;21(1):152-163. doi: 10.1111/1462-2920.14435. Epub 2018 Nov 21.
7
Mixed heavy metal stress induces global iron starvation response.
ISME J. 2023 Mar;17(3):382-392. doi: 10.1038/s41396-022-01351-3. Epub 2022 Dec 26.
9
Microbial community dynamics in uranium contaminated subsurface sediments under biostimulated conditions with high nitrate and nickel pressure.
Environ Sci Pollut Res Int. 2008 Sep;15(6):481-91. doi: 10.1007/s11356-008-0034-z. Epub 2008 Aug 19.
10
Linking bacterial diversity and geochemistry of uranium-contaminated groundwater.
Environ Technol. 2012 Jul-Aug;33(13-15):1629-40. doi: 10.1080/09593330.2011.641036.

引用本文的文献

2
Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface.
Environ Microbiome. 2024 Apr 26;19(1):26. doi: 10.1186/s40793-024-00570-9.
3
The Role of Synthetic Biology in Atmospheric Greenhouse Gas Reduction: Prospects and Challenges.
Biodes Res. 2020 Jul 28;2020:1016207. doi: 10.34133/2020/1016207. eCollection 2020.
4
Mixed heavy metal stress induces global iron starvation response.
ISME J. 2023 Mar;17(3):382-392. doi: 10.1038/s41396-022-01351-3. Epub 2022 Dec 26.
6
Development of a Markerless Deletion Mutagenesis System in Nitrate-Reducing Bacterium Rhodanobacter denitrificans.
Appl Environ Microbiol. 2022 Jul 26;88(14):e0040122. doi: 10.1128/aem.00401-22. Epub 2022 Jun 23.
7
Deciphering Microbial Metal Toxicity Responses via Random Bar Code Transposon Site Sequencing and Activity-Based Metabolomics.
Appl Environ Microbiol. 2021 Oct 14;87(21):e0103721. doi: 10.1128/AEM.01037-21. Epub 2021 Aug 25.
8
Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology.
Front Microbiol. 2021 Mar 24;12:642422. doi: 10.3389/fmicb.2021.642422. eCollection 2021.
9
Microbial interaction with and tolerance of radionuclides: underlying mechanisms and biotechnological applications.
Microb Biotechnol. 2021 May;14(3):810-828. doi: 10.1111/1751-7915.13718. Epub 2020 Dec 8.

本文引用的文献

1
Iron- and aluminium-induced depletion of molybdenum in acidic environments impedes the nitrogen cycle.
Environ Microbiol. 2019 Jan;21(1):152-163. doi: 10.1111/1462-2920.14435. Epub 2018 Nov 21.
2
The Madness of Microbiome: Attempting To Find Consensus "Best Practice" for 16S Microbiome Studies.
Appl Environ Microbiol. 2018 Mar 19;84(7). doi: 10.1128/AEM.02627-17. Print 2018 Apr 1.
3
Mechanisms of Chromium and Uranium Toxicity in RCH2 Grown under Anaerobic Nitrate-Reducing Conditions.
Front Microbiol. 2017 Aug 10;8:1529. doi: 10.3389/fmicb.2017.01529. eCollection 2017.
4
Novel Metal Cation Resistance Systems from Mutant Fitness Analysis of Denitrifying Pseudomonas stutzeri.
Appl Environ Microbiol. 2016 Sep 16;82(19):6046-56. doi: 10.1128/AEM.01845-16. Print 2016 Oct 1.
6
Molybdenum Availability Is Key to Nitrate Removal in Contaminated Groundwater Environments.
Appl Environ Microbiol. 2015 Aug;81(15):4976-83. doi: 10.1128/AEM.00917-15. Epub 2015 May 15.
7
Natural bacterial communities serve as quantitative geochemical biosensors.
mBio. 2015 May 12;6(3):e00326-15. doi: 10.1128/mBio.00326-15.
8
Assessing sources of nitrate contamination in the Shiraz urban aquifer (Iran) using the δ(15)N and δ(18)O dual-isotope approach.
Isotopes Environ Health Stud. 2015;51(3):392-410. doi: 10.1080/10256016.2015.1032960. Epub 2015 May 5.
9
Reducing the reliance on nitrogen fertilizer for wheat production.
J Cereal Sci. 2014 May;59(3):276-283. doi: 10.1016/j.jcs.2013.12.001.
10
Fluidized-bed denitrification for mine waters. Part II: effects of Ni and Co.
Biodegradation. 2014 Jun;25(3):417-23. doi: 10.1007/s10532-013-9670-1. Epub 2013 Oct 29.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验