浸矿微生物群落基因组芯片的构建与评估及其在酸性环境中的应用
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摘要
采矿活动使金属硫化矿大量暴露于地表,经过自然与生物的氧化作用导致酸性矿坑水(AMD)的产生,并造成严重的环境污染。酸性矿坑水通常含有高浓度的金属离子与硫酸盐,在AMD这样的极端环境中仍然生存着多种微生物。这些微生物主要是细菌与古菌,它们的活动促进AMD的形成,同时这些微生物对金属的生物浸出以及环境的生物治理也具有重要的意义。
理解微生物群落的结构,组成和环境适应性有助于阐述微生物与矿石以及AMD环境的生物与非生物因素之间的内在联系。AMD环境相比许多生态环境更加简单,这使得我们可以更加深入地研究微生物群落结构和功能与地理化学变量之间的关系。生物浸出过程中,微生物群落组成以及种群比例受矿石种类与浸出条件影响较大。
因此,研究酸性矿坑水中的微生物群落结构及其功能活动具有重要的意义。本文利用基因芯片技术对微生物群落的多样性进行了研究。构建并评估了适用于微生物群落结构解析的群落基因组芯片,优化了芯片杂交检测的技术方法,探索了它们在AMD环境微生物群落分析上的应用。
传统的微生物群落结构研究方法是以培养性状为依据,此类方法可以提供微生物群落多样性以及物种发育史等信息,但是其工作量巨大,对于群落多样性的描述与量化仍有其局限性。迅速发展的以核酸(基因)为基础的分子生物学技术使微生物群落研究有了显著的进展。分子生物学技术的应用过程对目标基因的选择是非常重要的,16SrRNA或rDNA是微生物多样性分析常用的基因,但它有识别能力的限制以及不能直接反应微生物的代谢与生理特征的缺陷。
目前常用的各种分子生物学分析方法都有这样那样的缺点,没有一种合适的方法可以用来同时快速、适时、准确、灵敏地检测环境微生物群落的多样性。基因芯片是最近发展起来的基因组研究技术之一,现已表明它是在基因组规模上研究基因表达和调控的一种强有力的研究工具,同时它也是研究原核和真核生物基因多态性的极好方法。基因芯片技术可以同时但它在环境微生物研究中的应用尚处于起步阶段,目前已有功能基因组芯片(FGA)、系统发育寡核苷酸芯片(POA)和群落基因组芯片(CGA)等三种基因芯片被用于环境微生物基因表达分析、比较基因组分析和混合微生物群落的分析。
本文构建并评估适用于菌种鉴定与群落分析的群落基因组芯片。CGA是用51株纯培养微生物的整个DNA基因组构建的,根据可培养的微生物来研究环境微生物群落。此方法类似于反向样品基本组探针法(RSGP),RSGP法是一种利用基因组DNA杂交来鉴定微生物的方法。为了确定此种类型芯片在研究环境微生物多样性的潜在作用,我们就其杂交特异性、检测灵敏度和定量性能进行了研究。在特定实验条件下,CGA的特异性实验表明目的DNA与同种细菌存在特异性杂交,同属之间不存在非特异性杂交,即CGA可区分属内菌种的染色体基因组。对于标记的纯培养基因组DNA,CGA的检测灵敏度大约为0.2 ng,对于混合培养物,检测灵敏度大约为5 ng。对于纯培养微生物,CGA具有定量特性,实验表明在0.2 ng至2000 ng的一定浓度范围内,DNA量与杂交信号强度之间存在明显的线性关系(r~2=0.985)。当将来自与五种微生物的基因组DNA以不同浓度混合并选取五个浓度梯度进行杂交实验,DNA量与杂交信号强度之间显著相关(r~2=0.95)。使用CGA分别杂交AMD环境样品与生物浸出系统样品,杂交结果显示CGA可以有效分辨两者之间微生物群落结构的差异性。CGA表明基因组芯片技术可以根据微生物基因型的变异应用于确定微生物群落的特性。评估微生物的群落组成和结构要求对单个目的种群进行定量分析,通过检测标记的目的DNA浓度和杂交信号强度的关系来探索CGA作为定量工具的杂交能力。所以,群落基因组芯片是一种特异、灵敏和具有定量能力的微生物生态研究的方法。
Mining activities result in the formation of a widespread environmental problem known as acid mine drainage (AMD), which results from chemical and biological oxidation of exposed sulfide minerals. AMD have high concentration of sulfate and toxic metals. A surprisingly wide diversity of microorganisms populate AMD environments. These organisms, mostly bacteria and archaea, can form a chemautotrophically-based biosphere in the subsurface and their activity increases the rate of AMD formation and may be responsible for the bulk of AMD generated.
The intention of understanding the structure, composition, and adaptive responses of microbial community is to elucidate the factors by examining the interactions of microorganisms and mineral and the biotic and abiotic characteristics of AMD environment. The notable simplicity of AMD environments may permit a more fundamental understanding of biogeochemical interactions and feedbacks and microbial communities structure and function than is possible through study of more complex ecosystems. The composition and proportion of microbes could be influenced by the mineral and the condition of bioleaching systems.
Culture-independent methods have provided a detailed understanding of the full diversity and phylogeny of organisms populating AMD and bioleaching systems. However, the detection, characterization, and quantification of microbial population diversity in various environments are formidable tasks. Microarray-based genomic technology provides the opportunity to identify thousands of microbial genes or populations simultaneously and the high-throughput advantages necessary for comprehensive characterization of complex microbial community overcomes the limitations of traditional microbial characterization. However, applications of this technology to the characterization of microbial communities are still limited, mainly because of the inherent unknown and miscellaneous composition of these samples. There are several types of microarrays has been successfully applied to microbial ecology research, such as functional gene array (FGA), community genome array (CGA) and phylogenetic oligonucleotide array (POA).
This research have been developed and evaluated a community genome array (CGA) for bacterial detection and microbial community analysis of acid mine drainage and bioleaching systems. Community genome array (CGA) consisting of whole genomic DNA is used as a probe for identifying microorganisms within the context of microbial communities isolated from 51 closely or distantly related representative bacterial strains. This approach is similar to the Reverse Sample Genome Probing (RSGP) methodology but modification. Based on the results of microarray hybridization, specificity tests with representation pure cultures indicated that the probes on the arrays appeared the be specific to their corresponding target genomic DNA. Cross-hybridization occurred between strains of the same species, but little cross-hybridization was observed among different species. The detection limit was estimated to be approximately 0.2 ng with genomic DNA from a single pure culture bacterial and 5 ng with mixed genomic DNA from mixtures of known amounts of different species' genomic DNA. In addition, strong linear relationships were observed between hybridization signal intensity and the target DNA concentrations from 0.2 ng to 2000 ng for pure cultures and a mixture of DNA template (r~2=0.95 to 0.985). Application of this type of the microarray revealed differences in microbial community composition. The results indicate that this technology has potential as a specific, sensitive and quantitative tool for detection and identification of acidophilic microorganism and the microbial community in acid mine drainage and bioleaching systems, although more work is needed to improve.
理解微生物群落的结构,组成和环境适应性有助于阐述微生物与矿石以及AMD环境的生物与非生物因素之间的内在联系。AMD环境相比许多生态环境更加简单,这使得我们可以更加深入地研究微生物群落结构和功能与地理化学变量之间的关系。生物浸出过程中,微生物群落组成以及种群比例受矿石种类与浸出条件影响较大。
因此,研究酸性矿坑水中的微生物群落结构及其功能活动具有重要的意义。本文利用基因芯片技术对微生物群落的多样性进行了研究。构建并评估了适用于微生物群落结构解析的群落基因组芯片,优化了芯片杂交检测的技术方法,探索了它们在AMD环境微生物群落分析上的应用。
传统的微生物群落结构研究方法是以培养性状为依据,此类方法可以提供微生物群落多样性以及物种发育史等信息,但是其工作量巨大,对于群落多样性的描述与量化仍有其局限性。迅速发展的以核酸(基因)为基础的分子生物学技术使微生物群落研究有了显著的进展。分子生物学技术的应用过程对目标基因的选择是非常重要的,16SrRNA或rDNA是微生物多样性分析常用的基因,但它有识别能力的限制以及不能直接反应微生物的代谢与生理特征的缺陷。
目前常用的各种分子生物学分析方法都有这样那样的缺点,没有一种合适的方法可以用来同时快速、适时、准确、灵敏地检测环境微生物群落的多样性。基因芯片是最近发展起来的基因组研究技术之一,现已表明它是在基因组规模上研究基因表达和调控的一种强有力的研究工具,同时它也是研究原核和真核生物基因多态性的极好方法。基因芯片技术可以同时但它在环境微生物研究中的应用尚处于起步阶段,目前已有功能基因组芯片(FGA)、系统发育寡核苷酸芯片(POA)和群落基因组芯片(CGA)等三种基因芯片被用于环境微生物基因表达分析、比较基因组分析和混合微生物群落的分析。
本文构建并评估适用于菌种鉴定与群落分析的群落基因组芯片。CGA是用51株纯培养微生物的整个DNA基因组构建的,根据可培养的微生物来研究环境微生物群落。此方法类似于反向样品基本组探针法(RSGP),RSGP法是一种利用基因组DNA杂交来鉴定微生物的方法。为了确定此种类型芯片在研究环境微生物多样性的潜在作用,我们就其杂交特异性、检测灵敏度和定量性能进行了研究。在特定实验条件下,CGA的特异性实验表明目的DNA与同种细菌存在特异性杂交,同属之间不存在非特异性杂交,即CGA可区分属内菌种的染色体基因组。对于标记的纯培养基因组DNA,CGA的检测灵敏度大约为0.2 ng,对于混合培养物,检测灵敏度大约为5 ng。对于纯培养微生物,CGA具有定量特性,实验表明在0.2 ng至2000 ng的一定浓度范围内,DNA量与杂交信号强度之间存在明显的线性关系(r~2=0.985)。当将来自与五种微生物的基因组DNA以不同浓度混合并选取五个浓度梯度进行杂交实验,DNA量与杂交信号强度之间显著相关(r~2=0.95)。使用CGA分别杂交AMD环境样品与生物浸出系统样品,杂交结果显示CGA可以有效分辨两者之间微生物群落结构的差异性。CGA表明基因组芯片技术可以根据微生物基因型的变异应用于确定微生物群落的特性。评估微生物的群落组成和结构要求对单个目的种群进行定量分析,通过检测标记的目的DNA浓度和杂交信号强度的关系来探索CGA作为定量工具的杂交能力。所以,群落基因组芯片是一种特异、灵敏和具有定量能力的微生物生态研究的方法。
Mining activities result in the formation of a widespread environmental problem known as acid mine drainage (AMD), which results from chemical and biological oxidation of exposed sulfide minerals. AMD have high concentration of sulfate and toxic metals. A surprisingly wide diversity of microorganisms populate AMD environments. These organisms, mostly bacteria and archaea, can form a chemautotrophically-based biosphere in the subsurface and their activity increases the rate of AMD formation and may be responsible for the bulk of AMD generated.
The intention of understanding the structure, composition, and adaptive responses of microbial community is to elucidate the factors by examining the interactions of microorganisms and mineral and the biotic and abiotic characteristics of AMD environment. The notable simplicity of AMD environments may permit a more fundamental understanding of biogeochemical interactions and feedbacks and microbial communities structure and function than is possible through study of more complex ecosystems. The composition and proportion of microbes could be influenced by the mineral and the condition of bioleaching systems.
Culture-independent methods have provided a detailed understanding of the full diversity and phylogeny of organisms populating AMD and bioleaching systems. However, the detection, characterization, and quantification of microbial population diversity in various environments are formidable tasks. Microarray-based genomic technology provides the opportunity to identify thousands of microbial genes or populations simultaneously and the high-throughput advantages necessary for comprehensive characterization of complex microbial community overcomes the limitations of traditional microbial characterization. However, applications of this technology to the characterization of microbial communities are still limited, mainly because of the inherent unknown and miscellaneous composition of these samples. There are several types of microarrays has been successfully applied to microbial ecology research, such as functional gene array (FGA), community genome array (CGA) and phylogenetic oligonucleotide array (POA).
This research have been developed and evaluated a community genome array (CGA) for bacterial detection and microbial community analysis of acid mine drainage and bioleaching systems. Community genome array (CGA) consisting of whole genomic DNA is used as a probe for identifying microorganisms within the context of microbial communities isolated from 51 closely or distantly related representative bacterial strains. This approach is similar to the Reverse Sample Genome Probing (RSGP) methodology but modification. Based on the results of microarray hybridization, specificity tests with representation pure cultures indicated that the probes on the arrays appeared the be specific to their corresponding target genomic DNA. Cross-hybridization occurred between strains of the same species, but little cross-hybridization was observed among different species. The detection limit was estimated to be approximately 0.2 ng with genomic DNA from a single pure culture bacterial and 5 ng with mixed genomic DNA from mixtures of known amounts of different species' genomic DNA. In addition, strong linear relationships were observed between hybridization signal intensity and the target DNA concentrations from 0.2 ng to 2000 ng for pure cultures and a mixture of DNA template (r~2=0.95 to 0.985). Application of this type of the microarray revealed differences in microbial community composition. The results indicate that this technology has potential as a specific, sensitive and quantitative tool for detection and identification of acidophilic microorganism and the microbial community in acid mine drainage and bioleaching systems, although more work is needed to improve.
引文
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