微生物生态研究中基于BIOLOG方法的数据分析

BIOLOG微平板法作为一种方便快速的微生物检验技术,已广泛应用于环境微生物检测,微生物生态研究等方面,发挥着越来越重要的作用。该方法可以获得关于微生物群落碳源利用能力的大量数据,反映出关于微生物活性的丰富信息。然而大量的数据也对解释和分析提出了挑战,分析了应用于BIOLOG产生数据的统计分析方法,对常用的AWCD值计算,多样性指数计算,主成分分析(PCA),聚类分析,相关、回归等方法深入探讨,阐述各自的功能、不足以及在应用中容易出现的问题。另外也对一些不常见的方法,如非参数多元分析(Non-Parametric version of MANOVA/Permutation version of MANOVA)、动力学参数分析、多元回归树、典范对应分析等也进行了讨论。通过对不同方法应用目标和原理的分析论述了各自优缺点,对微生物研究中基于BIOLOG方法数据分析的选择应用提供参考。     

氨基酸对青稞酒酿造微生物群落演替及风味代谢的驱动

【背景】环境因素是微生物生长代谢的重要驱动因素,因此,解析其对白酒酿造过程中微生物群落演替的影响对青稞酒的可控化生产具有重要作用。氨基酸作为微生物生长代谢的重要营养底物以及环境因素,其对微生物群落演替的作用尚不明确。【目的】揭示环境因素对青稞酒发酵过程中微生物群落演替及风味代谢的驱动作用。【方法】通过气相色谱-质谱联用技术对比检测肚里黄和瓦蓝两种青稞原料酿造青稞酒过程中风味物质变化情况;采用高通量扩增子测序及多元统计分析比较两种青稞酒醅中微生物群落结构特征;结合蒙特卡洛置换检验确定环境因素对微生物的影响;通过模拟发酵对以上研究结果进行验证。【结果】肚里黄青稞酒醅中酯类化合物的含量及其发酵后期乳酸杆菌相对丰度和氨基酸含量显著低于瓦蓝酒醅(P<0.05);通过生物信息学分析发现,环境因素中游离氨基酸是青稞酒发酵过程微生物群落演替重要的推动因素,且乳酸杆菌相对丰度与游离氨基酸呈显著相关;模拟发酵实验证实了特定氨基酸不足会影响乳酸杆菌生长。【结论】揭示了青稞酒发酵过程中游离氨基酸对微生物群落组装的驱动作用,进而影响青稞酒的风味品质,为青稞酒的可控发酵提供理论基础。     

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。     

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。     

五大连池新期火山熔岩台地不同植被类型土壤微生物群落的功能多样性

土壤微生物群落是陆地生态系统的重要生物活性成分,其结构和功能多样性直接影响到系统的碳、氮等生态过程,微生物群落功能多样性与地上植被类型变化密切相关,开展植被类型对土壤微生物群落功能多样性的影响研究具有重要意义。以五大连池新期火山熔岩台地苔藓、草本、灌丛、矮曲林、针阔混交林5种典型植被类型为对象,利用BIOLOG微孔板法研究不同演替阶段植被类型土壤微生物群落功能多样性特征。结果表明：不同植被类型土壤微生物群落功能多样性存在显著差异。平均颜色变化率（AWCD）随培养时间延长而逐渐增加,大小顺序为：苔藓 > 针阔混交林 > 矮曲林 > 草本 > 灌丛。灌丛土壤微生物多样性指数与其他植被类型间差异显著。主成分分析结果表明,主成分1和主成分2分别能解释变量方差的56.24%和29.59%,不同植被类型下土壤微生物的碳源利用格局差异主要是由氨基酸类和带磷基糖类引起,二者合计解释总变异量的47.51%。冗余分析表明,速效磷、铵态氮、C：N和pH对微生物功能多样性具有显著的影响,羧酸类、氨基酸类、酯类和胺类的降解更易受到环境因素的影响。研究结果为进一步探讨植被类型与土壤微生物之间在植被演替过程中的关系提供参考。     

农业土壤微生物基因与群落多样性研究进展

介绍了群落基因组多样性、结构多样性与功能多样性相互关系的研究方法 ,重点论述了近年来农业土壤微生物群落遗传、结构与功能多样性的研究进展。同时总结了耕作措施和养分管理对农业土壤微生物群落多样性的影响 ,提出微生物序列分析、比较基因组学和微生物芯片技术与传统研究技术结合将有助于对微生物群落结构与功能和生物与环境因素对土壤微生物群落影响的深刻理解     

日偏食对乌鲁木齐空气微生物群落功能多样性的影响

为了了解日偏食对空气微生物群落碳代谢的影响,利用BIOLOG指纹图谱方法分析日偏食前后乌鲁木齐空气微生物群落碳代谢功能多样性的变化。结果表明,日偏食当天空气微生物的碳源代谢能力高于其他几天。微生物群落多样性指数方差分析显示,当天(2009年7月22日)Shannon-Wiener多样性指数最高;主成分分析表明对碳源利用起分异作用的主要是羧酸类物质。日偏食会影响乌鲁木齐空气微生物群落功能多样性。     

文峪河上游河岸林群落环境梯度格局和演替过程

以文峪河上游河岸林为研究对象,通过对群落建群种的DCA排序和物种关联分析进行生态种组划分,阐明了河岸林群落建群种各生态种组之间的生态演替功能差异,结合对样地和生态适应性功能组的DCA排序结果,分析了河岸林群落空间分布的环境梯度格局及其影响因素,基于以上分析,构建了研究地区河岸林群落演替过程,揭示了环境梯度格局对河岸林群落演替的控制作用。通过研究,文峪河上游河岸林群落生态适应性功能组比群落在排序空间上具有更好的分异性,采用生态适应性功能组更有利于分析群落的时空关系;研究地区河岸林群落9个建群种划分为阳性喜湿先锋型、阳性中生演替型、耐阴喜湿演替后期型和阳性中生逃避型4个生态种组;研究地区海拔梯度、河岸带坡度和河谷型共同决定了河岸林群落的分布格局,河岸带坡度和河谷型实际反映的是河岸带水文状况对河岸林群落时空格局的控制作用;根据生态适应性功能组和生态种组构建了研究地区河岸林群落演替模型,不同的海拔及其相应的河谷型具有明显不同的演替过程。     

基于SOM的野生秤锤树群落的空间分布和环境解释

本文采用自组织特征映射网络(self-organizing map, SOM)对南京老山野生秤锤树(Sinojackia xylocarpa)群落进行数量分类和排序, 分析了其与环境因子之间的关系。结果表明: (1) SOM将秤锤树野生群落的100个样方划分为5个群丛类型, 分类结果在空间上反映了秤锤树野生群落的演替变化趋势, 各群丛的群落结构和物种组成存在差异且群丛界限明显, 可较好地进行排序与分类的环境解释。(2)通过环境因子梯度的可视化方法, 确定了海拔、坡位和土壤厚度是影响该地区秤锤树生长和分布的主要因子, 同时也揭示了以不同优势种为代表的各群丛和环境因子的关系。(3) SOM可以摆脱许多定量技术的限制性假设, 使得神经网络对于群落生态特征及探索群落和环境相互关系具有良好展现力; SOM群落生态数据具有更高的映射能力, 进行群落分类以及较少程度的排序的潜力, 将有利于不同群落类型的分类和管理, 对于濒危植物保护具有重要意义。     

暖温带针阔叶林下土壤微生物区系群落特征及其动态研究

实施森林分类经营导致土壤微生物生态的变化,是保护区生态环境监测的任务之一。结合甘肃天水小陇山土壤微生物多年调研资料,在总结针叶林和阔叶林下微生物群落特征的基础上,比较了阔叶林转化为针叶林后土壤微生物的动态。结果表明:1暖温带阔叶林土壤微生物数量和分布特征的生态幅较小,针叶林较大;2针阔林下土壤微生物群落优势菌属相同,但针叶林的优势属葡萄球菌属(Staphylococcus)及稀有菌属头孢霉属(Cephalosporium)在阔叶林未出现,阔叶林常见属交链孢霉属(Alternaria)在针叶林未出现;3暖温带阔叶林土壤微生物多样性指数均大于针叶林,针、阔叶林下功能菌群类型且其数量排序基本一致;4阔叶林转变为针叶林后,对不同时期土壤微生物群落的数量、分布、种属组成、多样性和功能菌群等特征的全面分析认为,土壤微生物逐步适应了地上植被的变化,即微生物与环境关系的建立与地上植被类型的关系更密切。     

Interpreting 16S rDNA T-RFLP Data: Application of Self-Organizing Maps and Principal Component Analysis to Describe Community Dynamics and Convergence

Interpreting the large amount of data generated by rapid profiling techniques, such as T-RFLP, DGGE, and DNA arrays, is a difficult problem facing microbial ecologists. This study compares the ability of two very different ordination methods, principal component analysis (PCA) and self-organizing map neural networks (SOMs), to analyze 16S-DNA terminal restriction-fragment length polymorphism (T-RFLP) profiles from microbial communities in glucose-fed methanogenic bioreactors during startup and changes in operational parameters. Our goal was not only to identify which samples were similar, but also to decipher community dynamics and describe specific phylotypes, i.e., phylogenetically similar organisms, that behaved similarly in different reactors. Fifteen samples were taken over 56 volume changes from each of two bioreactors inoculated from river sediment (S2) and anaerobic digester sludge (M3) and from a well-established control reactor (R1). PCA of bacterial T-RFLP profiles indicated that both the S2 and M3 communities changed rapidly during the first nine volume changes, and then became relatively stable. PCA also showed that an HRT of 8 or 6 days had no effect on either reactor communtity, while an HRT of 2 days changed community structure significantly in both reactors. The SOM clustered the terminal restriction fragments according to when each fragment was most abundant in a reactor community, resulting in four clearly discernible groups. Thirteen fragments behaved similarly in both reactors, eight of which composed a significant proportion of the microbial community as judged by the relative abundance of the fragment in the T-RFLP profiles. Six Bacteria terminal restriction fragments shared between the two communities matched cloned 16S rDNA sequences from the reactors related to Spirochaeta, Aminobacterium, Thermotoga, and Clostridium species. Convergence also occurred within the acetoclastic methanogen community, resulting in a predominance of Methanosarcina siciliae-related organisms. The results demonstrate that both PCA and SOM analysis are useful in the analysis of T-RFLP data; however, the SOM was better at resolving patterns in more complex and variable data than PCA ordination.     

StatFingerprints: a friendly graphical interface program for processing and analysis of microbial fingerprint profiles

Molecular fingerprint methods are widely used to compare microbial communities in various habitats. The free program StatFingerprints can import, process, and display fingerprint profiles and perform numerous statistical analyses on them, and also estimate diversity indexes. StatFingerprints works with the free program R, providing an environment for statistical computing and graphics. No programming knowledge is required to use StatFingerprints, thanks to its friendly graphical user interface. StatFingerprints is useful for analysing the effect of a controlled factor on the microbial community and for establishing the relationships between the microbial community and the parameters of its environment. Multivariate analyses include ordination, clustering methods and hypothesis-driven tests like 50-50 multivariate analysis of variance, analysis of similarity or similarity percentage procedure and the program offers the possibility of plotting ordinations as a three-dimensional display.     

Community-Level Physiological Profiles of Cloacal Microbes in Songbirds (Order: Passeriformes): Variation Due to Host Species, Host Diet, and Habitat

The relationship between microorganisms and birds has received increased attention recently. The state of knowledge of this relationship, however, is based largely on examination of sick or dead birds, and knowledge of the prevalence and community structure and function of microbes in healthy wild populations is limited. Using carbon substrate utilization profiles, microbial communities were examined in 91 cloacal samples from 14 species within apparently healthy summer and winter passerine populations. Within each season, gradient lengths and eigenvalues from ordination analyses suggested that many samples differed in their carbon substrate utilization and several had very different communities. Cloacal microbe carbon utilization profiles were distinguishable among host species, season-specific diet, and study site in the ordination analyses. However, these patterns were only observed for the analysis of the summer data set. The results of this study support the idea that the avian host’s microbial community, relative to carbon substrate utilization, is related to host diet. Previously, this pattern had only been reported for potential pathogens isolated from the avian cloaca. Study site–specific patterns in the ordination analysis suggest that environmental conditions at a particular study site may influence cloacal microbial communities in birds. Results of this study indicate that examination of community-level physiological profiles may be a useful technique for distinguishing among avian cloacal samples, similar to that already established for discriminating aqueous and soil samples. Future studies that correlate microbe physiological profiles to condition-based indices of avian hosts may be most useful for eventually using the profile as an indicator of environmental conditions experienced by hosts.     

Reconstructing community relationships: the impact of sampling error, ordination approach, and gradient length

Effectively summarizing complex community relationships is an important feature in studies such as biodiversity, global change, and invasion ecology. The reliability of such community summaries depends on the degree of sampling variability that is present in the data, the structure of the data, and the choice of ordination method, but the relative importance of these factors is not understood. We compared the validity of results from different ordination methods by applying five levels of sampling error to a simulated coenoplane model at two gradient lengths using two types of data (abundance and presence–absence). The multivariate methods we compared were correspondence analysis (CA), detrended correspondence analysis (DCA), non-metric multidimensional scaling (NMDS), principal component analysis (PCA) and principal coordinates analysis (PCoA). Our results showed CA and PCA using presence–absence data were the most successful methods regardless of sampling error and gradient length, closely followed by the other methods using presence–absence data. With abundance data, PCA and CA were the most successful approaches with the short and long gradients, respectively. Approaches based on PCoA and NMDS using abundance data did not perform well regardless of the choice of distance measure used in the analysis. Both of these methods, along with the PCA using abundance data, were strongly affected by the longer gradient, leading to more distorted results.     

排序法在植物群落与环境关系研究中的应用述评

自然环境对植物的影响主要表现在气候、水文、土壤及地形方面。大尺度上,气候类型明显影响植物的带状分布与物种空间格局;中小尺度上,土壤、水文、地形以及三者的交互作用影响植物生长必需的环境与资源条件,并对植物群落物种多样性起决定性作用。多元数量分析是研究植物群落生态关系的重要方法,在揭示植物群落与环境关系方面起到关键作用。排序法作为数量分析的重要手段,经常在植物生态学研究中扮演重要角色,尤其是在植物群落分布以及群落结构方面的应用已形成一种趋势。主要从植物群落分布以及群落结构的角度综述了当今排序法的应用,分析了面临的主要问题,并提出了未来可能发展方向,以期为今后排序方法的选择应用提供参考。     

排序和广义线性模型与广义可加模型在植物种与环境关系研究中的应用

排序和广义线性模型(Generalized Linear Model,GLM)与广义可加模型(Goneralized Additive Model,GAM)是研究植物种与环境间关系的重要方法。基于线性模型的排序方法应限定于环境梯度较短的植被数据。而基于单峰模型的排序方法更适用于梯度较长的情况。PCA、CA／RA系列和CCA系列是常用的排序方法。同时进行环境数据和植被数据分析的CCA系列,能清楚地得出植物种与环境间的关系。CCA改进后的DCCA和PCCA,是现今较理想的排序方法。GLM和GAM实质上是用环境变量的高阶多项式来拟合植物种与环境变量的关系。GLM和GAM扩展了植物种与环境变量之间的关系模型,能深入地探讨植物种与环境间的关系。GLM主要是模型决定的,而GAM主要取决于原始数据。一般来说,排序能得出研究区域的主要环境梯度,提供了物种聚集和植物群落的概略描述。GLM与GAM对于深入研究单个植物种与环境间的关系具有优势。在实际研究中,两种方法结合使用能互补不足。     

广西英罗港红树植物群落的非线性排序

采用主分量分析 (PCA)、无偏主分量 (DPC)和非度量多维调节 (NMDS)等方法对广西英罗港 2 2个红树植物群落样地进行了排序。PCA和 DPC分析结果表明 ,取样数据具有明显的非线性结构。通过 NMDS分析 ,得到二维 NMDS排序格局 ,它能较好地反映了红树植物群落与环境因子之间的相互关系。     

Analysis of T-RFLP data using analysis of variance and ordination methods: a comparative study

The analysis of T-RFLP data has developed considerably over the last decade, but there remains a lack of consensus about which statistical analyses offer the best means for finding trends in these data. In this study, we empirically tested and theoretically compared ten diverse T-RFLP datasets derived from soil microbial communities using the more common ordination methods in the literature: principal component analysis (PCA), nonmetric multidimensional scaling (NMS) with Sørensen, Jaccard and Euclidean distance measures, correspondence analysis (CA), detrended correspondence analysis (DCA) and a technique new to T-RFLP data analysis, the Additive Main Effects and Multiplicative Interaction (AMMI) model. Our objectives were i) to determine the distribution of variation in T-RFLP datasets using analysis of variance (ANOVA), ii) to determine the more robust and informative multivariate ordination methods for analyzing T-RFLP data, and iii) to compare the methods based on theoretical considerations. For the 10 datasets examined in this study, ANOVA revealed that the variation from Environment main effects was always small, variation from T-RFs main effects was large, and variation from T-RF × Environment (T × E) interactions was intermediate. Larger variation due to T × E indicated larger differences in microbial communities between environments/treatments and thus demonstrated the utility of ANOVA to provide an objective assessment of community dissimilarity. The comparison of statistical methods typically yielded similar empirical results. AMMI, T-RF-centered PCA, and DCA were the most robust methods in terms of producing ordinations that consistently reached a consensus with other methods. In datasets with high sample heterogeneity, NMS analyses with Sørensen and Jaccard distance were the most sensitive for recovery of complex gradients. The theoretical comparison showed that some methods hold distinct advantages for T-RFLP analysis, such as estimations of variation captured, realistic or minimal assumptions about the data, reduced weight placed on rare T-RFs, and uniqueness of solutions. Our results lead us to recommend that method selection be guided by T-RFLP dataset complexity and the outlined theoretical criteria. Finally, we recommend using binary or relativized peak height data with soil-based T-RFLP data for ordination-based exploratory microbial analyses.     

16S rRNA基因在微生物生态学中的应用

16S rRNA(Small subunit ribosomal RNA)基因是对原核微生物进行系统进化分类研究时最常用的分子标志物(Biomarker),广泛应用于微生物生态学研究中。近些年来随着高通量测序技术及数据分析方法等的不断进步,大量基于16S rRNA基因的研究使得微生物生态学得到了快速发展,然而使用16S rRNA基因作为分子标志物时也存在诸多问题,比如水平基因转移、多拷贝的异质性、基因扩增效率的差异、数据分析方法的选择等,这些问题影响了微生物群落组成和多样性分析时的准确性。对当前使用16S rRNA基因分析微生物群落组成和多样性的进展情况做一总结,重点讨论当前存在的主要问题以及各种分析方法的发展,尤其是与高通量测序技术有关的实验和数据处理问题。