微生物生态研究中BIOLOG方法数据分析及R语言实现

微生物生态研究中,对微生物群落结构、群落特征以及其与环境因素的关系的揭示,一直受到广泛关注;适当的数据分析方法有助于更清晰地刻画微生物群落结构特征,明确其与环境因素的关系。结合实例,对微生物生态研究中基于BIOLOG微平板技术的数据分析方法进行梳理,分别介绍数据读取整理、特征指数计算、非限制性排序、限制性排序、聚类分析、环境向量拟合、蒙特尔检验等常用数据操作及生态分析方法;针对不同方法结论,结合研究目标和生态理论给出具有统计学意义的解释,并评价不同方法特点及适用场景;分析过程以R语言实现,并提供全部代码。结果表明,BIOLOG方法产生数据能从多个角度表征微生物群落功能特征,并结合环境指标梯度进行分析;但BIOLOG数据可能不满足正态性分布,在基于正态分布的分析前应提前进行检验;排序分析时应慎用主成分分析,可优先采用其他基于距离矩阵的排序方法;R语言能够简化BIOLOG数据读取及操作,易于完成各类统计分析。本研究能够对微生物生态研究者科学选择应用统计分析方法、提高数据处理效率提供直接参考。     

恩诺沙星对土壤微生物群落功能多样性的影响

为了评价恩诺沙星(enrofloxacin)对土壤微生物群落的影响,借助BIOLOG检测法比较了不同浓度恩诺沙星影响下的土壤微生物的群落特征。结果表明,各添加药物组与空白对照组的土壤微生物群落代谢多样性差异显著(P<0.05),空白对照组土壤微生物在BIOLOG微平板上的平均每孔颜色变化率(AWCD)和微生物代谢多样性指数(丰富度和多样性)显著高于添加药物组;药物显著影响微生物群落对BIOLOG微平板中碳源的利用能力,较低浓度的恩诺沙星(0.01μg/g)就显著影响了土壤微生物群落对α-Ketobutyric Acid、L-Phenylalanine、1-Erythritol、D-Xylose等碳源的利用代谢能力(P<0.05),且土壤微生物群落利用各类碳源的能力随药物浓度加大而降低。由此可见,恩诺沙星在土壤中残留时对土壤微生物的影响不容忽视。     

微生物应用于纳米生物合成技术研究进展

基于发展纳米材料"绿色合成技术"重要性,生物合成纳米材料已成为纳米合成技术研究热点。微生物具有廉价、易培养、繁殖快等优点被应用于多种纳米材料的生物合成研究,成为生物合成纳米材料的重要生物类群。本文综述了细菌、放线菌、酵母菌以及真菌等微生物应用于纳米生物合成技术的发展;着重评述了纳米材料微生物合成生物方法、纳米材料微生物合成相关机制、纳米材料形貌和尺寸微生物调控合成方法以及应用研究进展;并对纳米材料微生物合成技术未来发展趋势进行了展望。     

微生物组大数据管理与分析

高通量技术的迅猛发展促使微生物生态学研究获得了重大突破,掀起了元基因组学(Metagenomics)研究的热潮。元基因组学通常被定义为对未培养的环境样本中微生物群体的DNA序列分析。随着微生物组学数据的日益剧增,微生物大数据的高效管理与分析越来越受到研究者的关注。如何从海量的微生物组数据中挖掘出具有科研价值的数据信息并应用于实际问题成为当前的研究热点。目前已有很多计算生物学程序工具及数据库用于元基因组数据的分析与管理。本文主要综述了随着高通量测序技术的进步,国际上主要的微生物组计划及微生物组数据平台,如人类微生物组项目(human microbiome project,HMP)、地球微生物组项目(earth microbiome project,EMP)、欧盟的肠道微生物组计划(metagenomics of human intestinal tract,MetaHIT)、MG-RAST、i Microbe、整合微生物组(integration microbial genomes,IMG)以及EBI Metagenomics等;介绍了微生物数据分析的主要流程与工具;提出了建设多源异构的微生物生态数据管理与分析系统的必要性。     

青岛市不同功能区冬季空气微生物群落代谢与多样性特征

选取青岛市5个功能区(市区街道、海滨区域、饮用水源地、垃圾填埋场和人工湿地污水处理系统),采用SAS ISO100空气浮游菌采样器于2013年冬季采集空气微生物样品,应用BIOLOG方法分析空气微生物群落代谢功能多样性,阐明群落代谢与环境相关性。结果表明,不同功能区空气微生物群落碳源代谢强度存在差异,代谢稳定时,海滨区域和饮用水源地样品平均光密度值(AWCD)分别为0.302、0.210,而人工湿地、市区街道及垃圾填埋场分别为0.063、0.025和0.034,海滨区域和饮用水源地空气微生物群落碳源代谢强度明显高于其他功能区。不同功能区空气微生物群落Shannon指数和Simpson指数接近,但海滨区域和饮用水源地Mc Intosh指数明显高于其他功能区。海滨区域和饮用水源地空气微生物群落碳源代谢类型丰富,代谢水平高,人工湿地、市区街道和垃圾填埋场碳源代谢类型单一,代谢水平低。5个功能区空气微生物群落碳源代谢差异呈现区域性,分异代谢差异的主要是羧酸类碳源。风速、温度、湿度等非生物因素对空气微生物群落碳源代谢具有不同程度影响,且不同功能区主导非生物因素存在差异。BIOLOG方法可以提供大量多维数据,能够分析样品间微生物群落碳源代谢差异,客观、全面表征空气微生物群落碳源代谢多样性特征,是研究空气微生物群落功能多样性较理想的方法之一。     

一种基于BIOLOG代谢指纹分析的油气微生物勘探新方法

【目的】建立基于土壤微生物群落生理功能代谢的油气微生物勘探新方法。【方法】采集新疆玛北油气藏区浅层地表土壤样品45份,非油气藏区样品25份,利用BIOLOG微平板,测定微生物群落代谢活性,采用判别分析模型判断油气藏区微生物异常。【结果】从95种碳源中,筛选到10种能够体现油气藏区与非油气藏区土壤微生物群落结构差异的典型碳源,利用判别函数对试验及对照区进行回判,油气藏区判别正确率为97.8%,非油藏区判别正确率为100%,总判别正确率为98.6%。【结论】BIOLOG技术能高效准确的用于油气藏初步勘测。     

PCR-DGGE技术及其在植物微生态研究中的应用

植物中微生物种类较为丰富,在植物微生态系统中发挥重要作用.变性梯度凝胶电泳(denaturing gradient gel electrophoresis,DGGE)技术作为研究微生物物种多样性和种群动态变化的分子检测工具之一,广泛应用于植物微生物群落多样性和群落动态变化研究中.概述了DGGE技术的原理,及其在植物微生物生态学中的应用以及在该领域研究中导致DGGE偏差的因素和相应解决方法,对DGGE检测结果的分析提供参考,为进一步研究植物微生物相互作用提供帮助.     

北京9个典型板栗园土壤碳代谢微生物多样性特征

土壤微生物多样性与土壤质量存在密切联系,也是目前的研究热点。从北京板栗主产区采取9个典型板栗园表层(0—20cm)土壤,采用BIOLOG生态微平板(BIOLOG Eco PlateTM)分析土壤微生物碳代谢群结构,旨在了解不同板栗园土壤微生物碳代谢功能群结构的特点与差异。结果表明:9个土壤可分为3组:(1)1,6,9号土壤、(2)2,5,7号土壤、(3)3,4,8号土壤。组内土壤微生物碳代谢功能群结构相似,而每组之间有显著性的差异。其中,1,6,9号土壤利用D-羟基丁二酸等7种基质的微生物比较多;而利用葡萄糖-1-磷酸盐等14种基质的微生物比较少,2,5,7号土壤与1,6,9号土壤正好相反,3,4,8号土壤与1,6,9号土壤的相似之处表现在代谢D-羟基丁二酸等7种基质的微生物也比较多,而代谢i-赤藻糖醇、D-木糖、2-羟基安息香酸等基质的微生物比较少。但是,目前对于土壤微生物碳代谢功能群多样性在土壤可持续利用中的作用与意义,特别是与土壤CNP等生物化学过程之间的关系还不清楚。     

微生物微培养系统研究现状与展望

微生物培养是微生物学的起源和根本,成功的微生物培养是进行后续研究的重要前提与基础。但是,微生物培养操作不仅耗费了科研人员大量的精力和时间,还存在着极大的人为误差。近年来,容量小、高通量、模块化、可操作性良好并可进行在线检测的微生物微培养系统得到了微生物学领域的广泛关注。文中介绍了应用于微生物学领域的微培养系统,并按系统构成分类讨论了微生物微培养系统的发展、应用和展望。     

基于高通量测序技术的微生物检测数据分析方法

高通量测序技术的发展正在逐渐改变诸多生物学领域的研究方法.为应对突发疫情以及新发未知微生物威胁的需求,微生物鉴定技术逐渐从传统的物理化学方法及核酸杂交等分子水平方法进一步走向利用无需培养的测序数据进行快速分析检测.随之而来的是对高通量数据分析在精度及速度的要求.基于高通量测序数据的微生物检测数据分析方法在近些年得到了快速的发展.本文分析了目前基于高通量测序数据的微生物检测数据分析方法,对其数据分析的处理流程和计算方法进行了研究,比较了各个微生物检测数据分析方法的特点及适用场景.最后结合本实验室工作总结微生物检测数据分析方法在实际应用中可能遇到的问题,希望对该应用领域的研究有一定的参考意义.     

Polyphasic characterization of a suite of bacterial isolates capable of degrading 2,4-D

To develop a better understanding of the ecological aspects of microbial biodegradation, it is important to assess the phenotypic and biochemical diversity of xenobiotic degrading organisms. Forty-six bacterial isolates capable of degrading 2,4-dichlorophenoxyacetic acid (2,4-D) and representing several geographically distinct locations were characterized and placed into taxonomic groups based on the results of several independent analyses. The isolates were characterized based on Gram's reaction, colony morphology, cell morphology, fatty acid methyl ester (FAME) fingerprints, carbon substrate oxidation patterns (BIOLOG), DNA homology to whole-plasmid probes and repetitive extragenic palindromic (REP) fingerprints. Attempts to group organisms taxonomically based on colony morphology and cell morphology were largely unsuccessful. Both FAME and BIOLOG analyses were generally unable to provide reliable genus or species identifications of these environmental isolates by comparison of fingerprints or substrate use patterns to existing data bases. Modification of the standard protocols for these analyses, however, allowed taxonomic grouping of the isolates and the construction of new data bases, comprised solely of 2,4-D-degrading organisms, against which future novel isolates can be compared. Independent cluster analysis of the FAME and BIOLOG data shows that the isolates can be segregated into five taxonomic classes. The collection of 2,4-D-degrading isolates was also separated into five classes based on DNA homology to whole-plasmid probes obtained from individual isolates. REP analysis allowed isolates that likely represent the same (or very similar) organism(s) to be identified and grouped. Each of the analyses used represents a mechanistically different means of classifying organisms, yet the taxonomic groupings obtained by several of the methods (FAME, BIOLOG, DNA homology, and to some degree, REP analysis) were in good agreement. This indicates that the features discriminated by these different methods represent fundamental characteristics that determine phylogenetic groups of bacteria. Correspondence to: W.E. Holben.     

非培养方法在土壤微生物生态学研究中的应用

由于有相当数量的土壤微生物是目前不可培养的,因此利用传统培养技术来研究土壤微生物,不仅费时费力,所得到的结果可能和真实的情况相差甚远。近年来发展了三类不需培养的方法来研究土壤微生物的种类和数量,这些方法大体上分为生物化学、生理学和分子生物学三类。生物化学方法主要根据细胞膜磷脂酸(PLFA)的种类和数量来判定微生物的多样性;BIOLOG微量板分析系统是生理学方法的代表,它主要是根据土样细胞悬液对95种单一碳源的利用模式来说明群落结构的变化;分子生物学方法是发展应用最广的方法。基本步骤是提取土壤的总DNA,然后用通用引物或选择性高的引物来扩增16SrRNA基因。由于对扩增产物分析方法的不同,该方法又可分为PCR-DGGE,PCR-RFLP等。最近在PCR-RFLP基础上发展起来的T—RFLP分析方法,将微生物的多样性分析工作同RDP(ribosomal database project)数据库结合,充分利用了Internet的数据资源共享的优势,具有分辨率高,可实现自动化等优点。是未来土壤微生物生态学研究的有力工具。     

土壤微生物生态学研究中的非培养方法

土壤微生物种类和数量是评价土壤健康质量的重要指标之一。然而环境中90%以上的微生物不能够通过传统的培养基培养方法获得。最近发展起来的分析方法如磷脂脂肪酸(PLFA)、BIOLOG微孔板和分子生物学的方法可从不同方面对土壤微生物群落进行更为详尽的分析。论文就土壤微生物生态学研究中使用的主要方法进行了综述。     

微生物宏基因组数据分析方法研究进展

随着测序技术的迅速发展,人们对宏基因组的研究逐渐深入。通过宏基因组学对微生物群落的测序和分析,以理解微生物组成与环境之间的相互作用。微生物宏基因组的分析摆脱了传统研究中微生物分离培养的技术限制,并获得了微生物群落的相对丰度和群落的功能等信息。用于微生物数据分析的工具和软件较多,对于研究者选择合适的分析方法具有一定困难。概述了微生物宏基因组分析方法的流程,总结了分析中常用的工具及软件,为研究者快速筛选分析方法,揭示数据背后的生物学意义提供参考。     

Data transformations in the analysis of community-level substrate utilization data from microplates

BIOLOG EcoPlates provide one method for determination of functional diversity indices and community-level physiological profiling of microbial populations based on carbon substrate utilization. In this study, the effect of data transformation on BIOLOG EcoPlate data derived from wetland mesocosms and biofiltration systems was examined. Homoscedasticity, normality, and the number of linear correlations between variables were quantified and evaluated for data that had been transformed using either Taylor or logarithmic transforms. Subsequent multivariate analysis was implemented using the untransformed, Taylor transformed and logarithmic transformed data sets. The effect of data transformation and its effect on principle component analysis are presented. The transforms are shown to help increase homogeneity of variance, increase normality of the data, and increase the number of significant linear correlations for the data. Separate principle component analyses and ordinations of the data showed the transforms to be well suited to this type of data and in particular illustrate the ability of the logarithmic transform to reduce the influence of high leverage or outlying observations on the overall analysis and its robustness in terms of treating data from different ecological systems. Although BIOLOG EcoPlates were used in this study to illustrate the use of transformations on multivariate data, the techniques described may be employed on similar microplate data. In addition, if homoscedasticity, normality and the number of linear correlations within a data set are not evaluated and the possibility of transforming the data, using the Taylor, logarithmic or another transform, is not considered, erroneous analysis and misleading conclusions may be attained when performing multivariate analysis on microplate data.     

Analysis of BIOLOG GN Substrate Utilization Patterns by Microbial Communities

BIOLOG GN plates are increasingly used to characterize microbial communities by determining the ability of the communities to oxidize various carbon sources. Studies were done to determine whether the BIOLOG GN plate assay accurately reflects the catabolic potential of the inoculum used. To gain insight into which populations of microbial communities contribute to the BIOLOG patterns, denaturing gradient gel electrophoresis and temperature gradient gel electrophoresis (TGGE) were used to assess the diversity of ribotypes in the inocula and individual wells of BIOLOG plates following incubation. These studies were done with microbial communities from the rhizosphere of potatoes and an activated sludge reactor fed with glucose and peptone. TGGE analyses of BIOLOG wells inoculated with cell suspensions from the potato rhizosphere revealed that, compared with the inoculum, there was a decrease in the number of 16S rRNA gene fragments obtained from various wells, as well as a concomitant loss of populations that had been numerically dominant in the inoculum. The dominant fragments in TGGE gels could be assigned to the gamma subclass of the class Proteobacteria, suggesting that fast-growing bacteria adapted to high substrate concentrations were numerically dominant in the wells and may have been primarily responsible for the patterns of substrate use that were observed. Similarly, the community structure changed in wells inoculated with cells from activated sludge; one or more populations were enriched, but all dominant populations of the inoculum could be detected in at least one well. This study showed that carbon source utilization profiles obtained with BIOLOG GN plates do not necessarily reflect the functional potential of the numerically dominant members of the microbial community used as the inoculum.     

Comparison of microbial and meiofaunal community analyses for determining impact of heavy metal contamination

The impact of long-term heavy metal contamination on soil communities was assessed by a number of methods. These included plate counts of culturable bacteria, community level physiological profiling (CLPP) by analysis of the utilization of multiple carbon sources in BIOLOG plates, community fatty acid methyl ester (C-FAME) profiling and dehydrogenase enzyme activity measurements. These approaches were complemented with microscopic assessments of the diversity of the nematode community. Samples from two sites with different histories of heavy-metal input were assessed. Major differences in microbial and meiofaunal parameters were observed both between and within the sites. There was a large degree of congruence between each of the microbiological approaches. In particular, one sample appeared to be distinguished by a reduction in culturable bacteria (especially pseudomonads), limited response to carbon sources in CLPP, and major differences in extracted fatty acid profiles. The use of multivariate analysis to examine the relationship between microbial and physicochemical measurements revealed that CLPP and plate counts were useful for determining the gross effect of metals on soil microbial communities, whereas proportions of metal-resistant bacteria and dehydrogenase activity differentiated between the two sites. Copper and zinc concentrations and pH all showed significant correlation with the microbial parameters. Nematode community structure was affected to a greater extent by soil pH than by metal content, but the within-site rankings were the same as those achieved for microbiological analyses. The use of these methods for field evaluation of the impact of industrial pollution may be possible provided care is taken when interpreting the data.     

Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization

The BLOLOG redox technology based on tetrazolium dye reduction as an indicator of sole-carbon-source utilization was evaluated as a rapid, community-level method to characterize and classify heterotrophic microbial communities. Direct incubation of whole environmental samples (aquatic, soil, and rhizosphere) in BIOLOG plates containing 95 separate carbon sources produced community-dependent patterns of sole-carbon-source utilization. Principal-component analysis of color responses quantified from digitized images of plates revealed distinctive patterns among microbial habitats and spatial gradients within soil and estuarine sites. Correlation of the original carbon source variables to the principal components gives a functional basis to distinctions among communities. Intensive spatial and temporal analysis of microbial communities with this technique can produce ecologically relevant classifications of heterotrophic microbial communities.     

Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions

Constrained ordination methods aims at finding an environmental gradient along which the species abundances are maximally separated. The species response functions, which describe the expected abundance as a function of the environmental score, are according to the ecological fundamental niche theory only meaningful if they are bell-shaped. Many classical model-based ordination methods, however, use quadratic regression models without imposing the bell-shape and thus allowing for meaningless U-shaped response functions. The analysis output (e.g. a biplot) may therefore be potentially misleading and the conclusions are prone to errors. In this paper we present a log-likelihood ratio criterion with a penalisation term to enforce more bell-shaped response shapes. We report the results of a simulation study and apply our method to metagenomics data from microbial ecology.