一种简单有效且适于土壤微生物多样性分析的DNA提取方法

参照Zhou[11]的方法进行了改进,获得了一种简单、有效的DNA提取方法.此方法操作简单、从大量样品改为小量样品的提取,利用高浓度的PEG沉淀,不作回收纯化,所提DNA片段较大,在23 kb以上,每克土的DNA提取量从3.74～15.28 μg,OD260/OD230比值在0.89～1.21范围内,用真菌和细菌核糖体特异性引物进行PCR扩增,均获得较好的结果,DGGE图谱显示丰富性较高,可用于细菌多样性和真菌多样性的分析.此方法能够从4种不同性质土壤中提取出DNA,但提取盐渍土壤和碱性土壤的效果更好一些,为土壤微生物群落结构的多样性分析奠定良好的基础.     

高通量测序技术在线虫多样性研究中的应用

土壤线虫多样性是土壤生态学研究的热点之一, 然而对土壤线虫群落组成及多样性的研究通常受到分类学和方法学的限制。当前, 分子生物学技术的快速发展丰富了我们对土壤线虫多样性的认识, 但也存在一定的局限性。本文综述了常用分子生物学技术如变性梯度凝胶电泳(denaturing gradient gel electrophoresis, DGGE)、末端限制性片段长度多态性分析(terminal restriction fragment length polymorphism, T-RFLP)、实时荧光定量PCR (quantitative real-time PCR, qPCR)和高通量测序(high-throughput sequencing, HTS)技术近年来在线虫多样性研究中的应用, 重点从土壤线虫DNA提取方法、引物和数据库的选择、高通量测序技术和形态学鉴定结果的比较等方面阐述了高通量测序技术在线虫多样性研究中的优势与不足, 并提出选择合适的线虫DNA提取方法结合特定引物和数据库进行注释分析, 仍是今后使用高通量测序技术开展线虫多样性研究的重点。当研究目标是土壤线虫多样性时, 优先推荐富集线虫悬液提取DNA的方法, 因此, 研究人员应根据具体目标选择最优组合开展实验研究。     

提取北方土壤真菌DNA的一种方法

由于土壤理化性质的复杂性和真菌细胞壁结构的特殊性,从土壤样品中提取真菌基因组DNA比较困难.中国北方土壤与其它地区土壤相比有其自身的特点,因此,有必要优化一种适合于北方土壤真菌DNA提取的方法.本实验向灭菌黑土中分别投加12种在系统分类上差别较大的真菌,以传统土壤总DNA提取方法及纯菌DNA提取方法为基础,分别与蜗牛酶,纤维素酶进行组合、优化,得到7种不同的土壤真菌基因组DNA提取方法.利用真菌28S rDNA通用引物U1/U2-GC PCR-DGGE分析方法分别考察了7种不同方法所提取土壤真菌基因组DNA的多样性和代表性.结果表明:1)液氮研磨,纤维素酶、蜗牛酶和溶菌酶(浓度分别为6 、3和1 mg·ml-1)37 ℃作用60 min,2% SDS于65 ℃裂解30 min;2)-65 ℃～65 ℃冻融3次,纤维素酶、蜗牛酶和溶菌酶(浓度分别为6、3和1 mg·ml-1)37 ℃作用180 min,2%SDS于65 ℃裂解30 min的组合具有较好的提取效果.利用后一种方法分别对3种理化性质差异较大的中国北方自然土壤样品真菌DNA进行提取并分析,表明所提取土壤基因组DNA真菌特异性PCR-DGGE图谱条带丰富,该方法可用于多种北方土壤真菌多样性研究.     

三种土壤微生物总DNA提取方法的比较

本文对3种常用的土壤微生物总DNA提取方法Martin法、高盐改进法及试剂盒法进行了比较,并通过DNA得率、纯度及16S rDNA V3可变区的PCR扩增结合DGGE法(denaturing gradient gel electrophoresis),分别对3种方法进行评价.结果表明,3种方法提取的DNA均能满足土壤微生物多样性分析的要求.其中试剂盒方法操作简单,提取的DNA质量较高,但DNA得率较低且成本昂贵.Martin法和高盐改进法用时较长,DNA得率较高,纯度较低,但对后续PCR扩增和DGGE分析没有明显影响,且成本低廉.     

新疆一号冰川土壤细菌多样性的研究*

应用变性梯度凝胶电泳(DGGE)技术分离PCR扩增的16S rDNA来研究土壤微生物的多样性。直接从新疆一号冰川不同海拔高度的土壤样品中提取总DNA。用两套细菌通用引物分别扩增16S rDNA的V3和V6/V9高变区的特异性片段,PCR产物进行DGGE分析。PCR-DGGE图谱表明,PCR产物经DGGE检测到的条带清晰且分离效果好。结果表明,PCR-DGGE是一种快速研究微生物群落结构的有效方法。     

海南东寨港红树林不同植被土壤微生物群落结构比较

【目的】比较不同植被下红树林土壤细菌和古菌的多样性及群落结构,认识红树林土壤微生物资源多样性。【方法】直接提取红树林土壤总DNA,采用细菌通用引物27F/1492R和古菌通用引物Arch21F/Arch958R进行PCR扩增,构建细菌和古菌16S rRNA基因文库,对海南东寨港自然保护区秋茄林、无瓣海桑林和无红树林裸滩土壤的细菌和古菌多样性和群落结构进行分析和比较。【结果】3种土壤样品的细菌类群包括变形细菌门(Proteobacteria)等16个类群,其中变形细菌门(Proteobacteria)与绿屈挠菌门(Chloroflexi)是优势类群;古菌包括6个嗜泉古菌界(Crenarchaeota)类群和7个广域古菌界(Euryarchaeota)类群,分别以Marine Benthic Group C、Marine Benthic Group D为优势类群。多样性指数(H’)和物种丰富度指数(Schao1)表明,本地种秋茄林下土壤细菌和古菌的多样性指数最高,外来种无瓣海桑显著低于秋茄林,甚至明显低于相邻无红树林裸滩沉积物;不同植被下土壤细菌和古菌群落结构存在显著差异,秋茄林土壤微生物群落结构和无红树林裸滩沉积物更相似。【结论】红树林土壤微生物类群丰富,不同植被下土壤细菌和古菌多样性和群落结构存在显著差异。     

从土壤中提取DNA用于PCR扩增

设计、比较了5种直接从土壤中提取DNA的方法。实验结果表明这5种方法都可以从土壤中提取到长度大于15kb的DNA片段,但在不同方法间DNA的产量存在很大差异;初提的土壤DNA经进一步提纯后均可用于PCR反应,利用细菌16S rRNA基因和抗菌肽Shiva-1基因的引物都得到了相应的目的产物。其中方法5提取DNA产量最高,无明显降解,且重复性好,是一种从小量土壤样品中直接提取DNA的理想方法。     

流溪河生态公益林下土壤细菌多样性

【背景】森林土壤细菌多样性在一定程度上是衡量森林质量的重要指标之一,土壤细菌群落结构组成及变化能够反映森林生态系统的结构和功能,在森林生态系统物质养分循环中发挥着重要的作用。【目的】以广州市流溪河国家森林公园3种不同密度林分生态公益林的土壤为研究对象,分析不同密度林分类型对土壤细菌群落结构的影响,探讨不同林分密度土壤养分和土壤细菌的分布规律,为退化生态系统的恢复、合理利用公益林土壤资源、维护地力及提高公益林生态系统生产力和服务功能提供参考。【方法】选择高密度林分(HD)、中密度林分(MD)、低密度林分(LD)3种林分类型,采用"S"形取样法采集土壤样品,提取土壤微生物总DNA,采用Illumina MiSeq高通量测序技术对16S rRNA基因进行序列测定,利用R语言和SPSS21.0等软件分析林分密度对细菌多样性及群落结构的影响。【结果】高林分密度土壤肥力状况较中低林分密度高;不同林分密度下土壤细菌多样性指数、丰富度指数略有差异,中密度林分指数最高;流溪河区域土壤细菌多样性较高,变形菌门和酸杆菌门是主要类群。【结论】流溪河生态公益林土壤细菌具有丰富的多样性,以变形菌门和酸杆菌门为主;林分密度对土壤细菌的多样性、丰富度及其群落结构产生明显影响;流溪河区域中密度林分(1 800-2 200株/hm2)更适合土壤细菌的繁衍生息;土壤的肥力状况受林分密度、灌木杂草的影响;16SrRNA基因的基因组异质性会导致对细菌多样性的过高估计。     

茶园土壤微生物总DNA不同提取方法的比较

传统的微生物分离培养方法,在反映茶园土壤微生物基因信息上有很大的局限性,因此,目前逐步被分子生态学的方法替代,而获得高质量、大片段、无偏好的土壤微生物总DNA则是茶园土壤微生物分子生态学研究的基础.本文采用SDS高盐法、变性剂加SDS高盐法、脱腐SDS高盐法、CTAB法和Krsek改进法5种土壤微生物DNA提取方法分别从茶园土壤微生物中提取总DNA,并对5种方法提取的DNA的片段大小、质量和产量进行了综合评价.结果表明,Krsek改进法提取到的DNA片段最大(>23 kb)、纯度最高(OD260/OD280>1.70;OD260/OD230>1.35)、产量较高(>34.50μg/g dry soil)且不需纯化就可以用于PCR扩增和RFLP分析.因此,Krsek改进法是一种高效、可靠且适合于茶园土壤微生物分子生态学研究的DNA提取方法.     

新疆一号冰川土壤细菌多样性的研究

应用变性梯度凝胶电泳（DGGE）技术分离PCR扩增的16SrDNA来研究土壤微生物的多样性。直接从新疆一号冰川不同海拔高度的土壤样品中提取总DNA。用两套细菌通用引物分别扩增16SrDNA的V3和V6／V9高变区的特异性片段,PCR产物进行DGGE分析。PCR—DGGE图谱表明,PCR产物经DGGE检测到的条带清晰且分离效果好。结果表明,PCR—DGGE是一种快速研究微生物群落结构的有效方法。     

Effect of Freeze-Thaw Cycles on Bacterial Communities of Arctic Tundra Soil

The effect of freeze-thaw (FT) cycles on Arctic tundra soil bacterial community was studied in laboratory microcosms. FT-induced changes to the bacterial community were followed over a 60-day period by terminal restriction fragment length polymorphism (T-RFLP) profiles of amplified 16S rRNA genes and reverse transcribed 16S rRNA. The main phylotypes of the active, RNA-derived bacterial community were identified using clone analysis. Non-metric multidimensional scaling ordination of the T-RFLP profiles indicated some shifts in the bacterial communities after three to five FT cycles at −2, −5, and −10°C as analyzed both from the DNA and rRNA. The dominating T-RFLP peaks remained the same, however, and only slight variation was generally detected in the relative abundance of the main T-RF sizes of either DNA or rRNA. T-RFLP analysis coupled to clone analysis of reverse transcribed 16S rRNA indicated that the initial soil was dominated by members of Bacteroidetes, Acidobacteria, Alpha-, Beta-, and Gammaproteobacteria. The most notable change in the rRNA-derived bacterial community was a decrease in the relative abundance of a Betaproteobacteria-related phylotype after the FT cycles. This phylotype decreased, however, also in the control soil incubated at constant +5°C suggesting that the decrease was not directly related to FT sensitivity. The results indicate that FT caused only minor changes in the bacterial community structure.     

Community Structure Analyses Are More Sensitive to Differences in Soil Bacterial Communities than Anonymous Diversity Indices

Changes in the diversity and structure of soil microbial communities may offer a key to understanding the impact of environmental factors on soil quality in agriculturally managed systems. Twenty-five years of biodynamic, bio-organic, or conventional management in the DOK long-term experiment in Switzerland significantly altered soil bacterial community structures, as assessed by terminal restriction fragment length polymorphism (T-RFLP) analysis. To evaluate these results, the relation between bacterial diversity and bacterial community structures and their discrimination potential were investigated by sequence and T-RFLP analyses of 1,904 bacterial 16S rRNA gene clones derived from the DOK soils. Standard anonymous diversity indices such as Shannon, Chao1, and ACE or rarefaction analysis did not allow detection of management-dependent influences on the soil bacterial community. Bacterial community structures determined by sequence and T-RFLP analyses of the three gene libraries substantiated changes previously observed by soil bacterial community level T-RFLP profiling. This supported the value of high-throughput monitoring tools such as T-RFLP analysis for assessment of differences in soil microbial communities. The gene library approach also allowed identification of potential management-specific indicator taxa, which were derived from nine different bacterial phyla. These results clearly demonstrate the advantages of community structure analyses over those based on anonymous diversity indices when analyzing complex soil microbial communities.     

Community structure analyses are more sensitive to differences in soil bacterial communities than anonymous diversity indices

Changes in the diversity and structure of soil microbial communities may offer a key to understanding the impact of environmental factors on soil quality in agriculturally managed systems. Twenty-five years of biodynamic, bio-organic, or conventional management in the DOK long-term experiment in Switzerland significantly altered soil bacterial community structures, as assessed by terminal restriction fragment length polymorphism (T-RFLP) analysis. To evaluate these results, the relation between bacterial diversity and bacterial community structures and their discrimination potential were investigated by sequence and T-RFLP analyses of 1,904 bacterial 16S rRNA gene clones derived from the DOK soils. Standard anonymous diversity indices such as Shannon, Chao1, and ACE or rarefaction analysis did not allow detection of management-dependent influences on the soil bacterial community. Bacterial community structures determined by sequence and T-RFLP analyses of the three gene libraries substantiated changes previously observed by soil bacterial community level T-RFLP profiling. This supported the value of high-throughput monitoring tools such as T-RFLP analysis for assessment of differences in soil microbial communities. The gene library approach also allowed identification of potential management-specific indicator taxa, which were derived from nine different bacterial phyla. These results clearly demonstrate the advantages of community structure analyses over those based on anonymous diversity indices when analyzing complex soil microbial communities.     

Links between plant and rhizoplane bacterial communities in grassland soils, characterized using molecular techniques

Molecular analysis of grassland rhizosphere soil has demonstrated complex and diverse bacterial communities, with resultant difficulties in detecting links between plant and bacterial communities. These studies have, however, analyzed "bulk" rhizosphere soil, rather than rhizoplane communities, which interact most closely with plants through utilization of root exudates. The aim of this study was to test the hypothesis that plant species was a major driver for bacterial rhizoplane community composition on individual plant roots. DNA extracted from individual roots was used to determine plant identity, by analysis of the plastid tRNA leucine (trnL) UAA gene intron, and plant-related bacterial communities. Bacterial communities were characterized by analysis of PCR-amplified 16S rRNA genes using two fingerprinting methods: terminal restriction fragment length polymorphisms (T-RFLP) and denaturing gradient gel electrophoresis (DGGE). Links between plant and bacterial rhizoplane communities could not be detected by visual examination of T-RFLP patterns or DGGE banding profiles. Statistical analysis of fingerprint patterns did not reveal a relationship between bacterial community composition and plant species but did demonstrate an influence of plant community composition. The data also indicated that topography and other, uncharacterized, environmental factors are important in driving bacterial community composition in grassland soils. T-RFLP had greater potential resolving power than DGGE, but findings from the two methods were not significantly different.     

Community Structure of Actively Growing Bacterial Populations in Plant Pathogen Suppressive Soil

The bacterial community in soil was screened by using various molecular approaches for bacterial populations that were activated upon addition of different supplements. Plasmodiophora brassicae spores, chitin, sodium acetate, and cabbage plants were added to activate specific bacterial populations as an aid in screening for novel antagonists to plant pathogens. DNA from growing bacteria was specifically extracted from the soil by bromodeoxyuridine immunocapture. The captured DNA was fingerprinted by terminal restriction fragment length polymorphism (T-RFLP). The composition of the dominant bacterial community was also analyzed directly by T-RFLP and by denaturing gradient gel electrophoresis (DGGE). After chitin addition to the soil, some bacterial populations increased dramatically and became dominant both in the total and in the actively growing community. Some of the emerging bands on DGGE gels from chitin-amended soil were sequenced and found to be similar to known chitin-degrading genera such as Oerskovia, Kitasatospora, and Streptomyces species. Some of these sequences could be matched to specific terminal restriction fragments on the T-RFLP output. After addition of Plasmodiophora spores, an increase in specific Pseudomonads could be observed with Pseudomonas-specific primers for DGGE. These results demonstrate the utility of microbiomics, or a combination of molecular approaches, for investigating the composition of complex microbial communities in soil.     

Links between Plant and Rhizoplane Bacterial Communities in Grassland Soils, Characterized Using Molecular Techniques

Molecular analysis of grassland rhizosphere soil has demonstrated complex and diverse bacterial communities, with resultant difficulties in detecting links between plant and bacterial communities. These studies have, however, analyzed “bulk” rhizosphere soil, rather than rhizoplane communities, which interact most closely with plants through utilization of root exudates. The aim of this study was to test the hypothesis that plant species was a major driver for bacterial rhizoplane community composition on individual plant roots. DNA extracted from individual roots was used to determine plant identity, by analysis of the plastid tRNA leucine (trnL) UAA gene intron, and plant-related bacterial communities. Bacterial communities were characterized by analysis of PCR-amplified 16S rRNA genes using two fingerprinting methods: terminal restriction fragment length polymorphisms (T-RFLP) and denaturing gradient gel electrophoresis (DGGE). Links between plant and bacterial rhizoplane communities could not be detected by visual examination of T-RFLP patterns or DGGE banding profiles. Statistical analysis of fingerprint patterns did not reveal a relationship between bacterial community composition and plant species but did demonstrate an influence of plant community composition. The data also indicated that topography and other, uncharacterized, environmental factors are important in driving bacterial community composition in grassland soils. T-RFLP had greater potential resolving power than DGGE, but findings from the two methods were not significantly different.     

A novel strategy to extract specific phylogenetic sequence information from community T-RFLP

Cultivation-independent analyses of soil microbial community structures are frequently used to describe microbiological soil characteristics. Semi-automated terminal restriction fragment length polymorphism (T-RFLP) analyses yield high-resolution genetic profiles of highly diverse soil microbial communities and hold great potential for use in routine soil quality monitoring. A serious limitation of T-RFLP analyses has been the inability to reliably affiliate observed terminal restriction fragments (T-RF) to phylogenetic groups. In the study presented here, we were able to overcome this limitation of T-RFLP. With a combination of adapter ligation, fragment size selection, and re-amplification with adapter site specific PCR, we were able to isolate a T-RF-fraction of a narrow size-range containing a T-RF that was significantly more abundant in heavy metal amended soils. Cloning the size-selected T-RF fraction allowed for the efficient isolation of clones containing this specific T-RF. Sequence determination and phylogenetic inference in RDP-II affiliated the sequence to unclassified cyanobacteria. Specific primer design and PCR amplification from bulk soil DNA allowed for independent confirmation of the results from bacterial T-RFLP and T-RF cloning. Our results show that specific T-RFs can be efficiently isolated and identified, and that the adapter ligation approach holds great potential for genetic profiling and for identification of community components of interest.     

Bacterial communities in Arctic fjelds of Finnish Lapland are stable but highly pH-dependent

The seasonal and spatial variations of microbial communities in Arctic fjelds of Finnish Lapland were studied. Phospholipid fatty acid analysis (PLFA) and terminal restriction fragment analysis (T-RFLP) of amplified 16S rRNA genes were used to assess the effect of soil conditions and vegetation on microbial community structures along different altitudes of two fjelds, Saana and Jehkas. Terminal restriction fragments were additionally analysed from c. 160 cloned sequences and isolated bacterial strains and matched with those of soil DNA samples. T-RFLP and PLFA analyses indicated relatively similar microbial communities at various altitudes and under different vegetation of the two fjelds. However, soil pH had a major influence on microbial community composition. Members of the phylum Acidobacteria dominated especially in the low pH soils (pH 4.6-5.2), but above pH 5.5, the relative amount of terminal restriction fragments corresponding to acidobacterial clones was substantially lower. Both T-RFLP and PLFA analysis indicated stable microbial communities as the DNA and fatty acid profiles were similar in spring and late summer samples sampled over 3 years. These results indicate that differences in microbial community composition could be explained primarily by variation in the bedrock materials that cause variation in the soil pH.     

Use of the T-RFLP technique to assess spatial and temporal changes in the bacterial community structure within an agricultural soil planted with transgenic and non-transgenic potato plants

The aim of this study was to examine whether the terminal restriction fragment length polymorphism (T-RFLP) analysis represents an appropriate technique for monitoring highly diverse soil bacterial communities, i.e. to assess spatial and/or temporal effects on bacterial community structure. The T-RFLP method, a recently described fingerprinting technique, is based on terminal restriction fragment length polymorphisms between distinct small-subunit rRNA gene sequence types. This technique permits an automated quantification of the fluorescence signal intensities of the individual terminal restriction fragments (T-RFs) in a given community fingerprint pattern. The indigenous bacterial communities of three soil plots located within an agricultural field of 110 m(2) were compared. The first site was planted with non-transgenic potato plants, while the other two were planted with transgenic GUS and Barnase/Barstar potato plants, respectively. Once prior to planting and three times after planting, seven parallel samples were taken from each of the three soil plots. The T-RFLP analysis resulted in very complex but highly reproducible community fingerprint patterns. The percentage abundance values of defined T-RFs were calculated for the seven parallel samples of the respective soil plot. A multivariate analysis of variance was used to test T-RFLP data sets for significant differences. The statistical treatments clearly revealed spatial and temporal effects, as well as spacextime interaction effects, on the structural composition of the bacterial communities. T-RFs which showed the highest correlations to the discriminant factors were not those T-RFs which showed the largest single variations between the seven-sample means of individual plots. In summary, the T-RFLP technique, although a polymerase chain reaction-based method, proved to be a suitable technique for monitoring highly diverse soil microbial communities for changes over space and/or time.