Introducing SONS, a tool for operational taxonomic unit-based comparisons of microbial community memberships and structures

The recent advent of tools enabling statistical inferences to be drawn from comparisons of microbial communities has enabled the focus of microbial ecology to move from characterizing biodiversity to describing the distribution of that biodiversity. Although statistical tools have been developed to compare community structures across a phylogenetic tree, we lack tools to compare the memberships and structures of two communities at a particular operational taxonomic unit (OTU) definition. Furthermore, current tests of community structure do not indicate the similarity of the communities but only report the probability of a statistical hypothesis. Here we present a computer program, SONS, which implements nonparametric estimators for the fraction and richness of OTUs shared between two communities.     

毛竹种植对土壤细菌和真菌群落结构及多样性的影响

为揭示天然林改为毛竹林过程中土壤微生物变化规律,在浙江省湖州市安吉县和长兴县两地选择不同种植历史的粗放经营毛竹林,分层采集0～20和20～40 cm的混合土壤样品,应用PCR-DGGE技术分析土壤细菌和真菌群落结构及多样性变化.结果表明: 在马尾松林改种毛竹林或毛竹林入侵杂灌阔叶林形成毛竹纯林过程中,土壤细菌和真菌的群落结构均发生明显变化,且细菌结构对毛竹种植的响应更敏感;随着毛竹生长时间的延长,表层土壤细菌群落表现出抵抗干扰、最后向改种毛竹之前状态恢复的趋势.毛竹种植时间、样地和土层均对土壤细菌和真菌多样性产生显著影响,其中样地和土层的影响明显大于种植时间.土壤性质和细菌、真菌结构的冗余分析结果表明,不同地点、不同土层驱动土壤微生物结构随时间变化的主要因子没有一致规律,且第1、2轴对样地变化的解释率大多低于65.0%,说明除本研究分析的5个土壤化学指标外,可能还有其他土壤理化性质共同驱动微生物结构的变化.     

Microbial biogeography of drinking water: patterns in phylogenetic diversity across space and time

In this study, we collected water from different locations in 32 drinking water distribution networks in the Netherlands and analysed the spatial and temporal variation in microbial community composition by high‐throughput sequencing of 16S rRNA gene amplicons. We observed that microbial community compositions of raw source and processed water were very different for each distribution network sampled. In each network, major differences in community compositions were observed between raw and processed water, although community structures of processed water did not differ substantially from end‐point tap water. End‐point water samples within the same distribution network revealed very similar community structures. Network‐specific communities were shown to be surprisingly stable in time. Biofilm communities sampled from domestic water metres varied distinctly between households and showed no resemblance to planktonic communities within the same distribution networks. Our findings demonstrate that high‐throughput sequencing provides a powerful and sensitive tool to probe microbial community composition in drinking water distribution systems. Furthermore, this approach can be used to quantitatively compare the microbial communities to match end‐point water samples to specific distribution networks. Insight in the ecology of drinking water distribution systems will facilitate the development of effective control strategies that will ensure safe and high‐quality drinking water.     

A unifying quantitative framework for exploring the multiple facets of microbial biodiversity across diverse scales

Recent developments of molecular tools have revolutionized our knowledge of microbial biodiversity by allowing detailed exploration of its different facets and generating unprecedented amount of data. One key issue with such large datasets is the development of diversity measures that cope with different data outputs and allow comparison of biodiversity across different scales. Diversity has indeed three components: local (α), regional (γ) and the overall difference between local communities (β). Current measures of microbial diversity, derived from several approaches, provide complementary but different views. They only capture the β component of diversity, compare communities in a pairwise way, consider all species as equivalent or lack a mathematically explicit relationship among the α, β and γ components. We propose a unified quantitative framework based on the Rao quadratic entropy, to obtain an additive decomposition of diversity (γ = α + β), so the three components can be compared, and that integrate the relationship (phylogenetic or functional) among Microbial Diversity Units that compose a microbial community. We show how this framework is adapted to all types of molecular data, and we highlight crucial issues in microbial ecology that would benefit from this framework and propose ready‐to‐use R‐functions to easily set up our approach.     

DNA barcoding to map the microbial communities: current advances and future directions

During the last two decades, the DNA barcode development towards microbial community has increased dramatically. DNA barcode development is related to error-free and quick species identification which aid in understanding the microbial biodiversity, as well as the diseases related to microbial species. Here, we seek to evaluate the so-called barcoding initiatives for the microbial communities and the emerging trends in this field. In this paper, we describe the development of DNA marker-based DNA barcoding system, comparison between routine species identification and DNA barcode, and microbial biodiversity and DNA barcode for microbial communities. Two major topics, such as the molecular diversity of viruses and barcode for viruses have been discussed at the same time. We demonstrate the current status and the maker of DNA barcode for bacteria, algae, fungi, and protozoa. Furthermore, we argue about the promises, limitations, and present and future challenges of microbial barcode development.     

Phylogenetic and functional metagenomic profiling for assessing microbial biodiversity in environmental monitoring

Decisions guiding environmental management need to be based on a broad and comprehensive understanding of the biodiversity and functional capability within ecosystems. Microbes are of particular importance since they drive biogeochemical cycles, being both producers and decomposers. Their quick and direct responses to changes in environmental conditions modulate the ecosystem accordingly, thus providing a sensitive readout. Here we have used direct sequencing of total DNA from water samples to compare the microbial communities of two distinct coastal regions exposed to different anthropogenic pressures: the highly polluted Port of Genoa and the protected area of Montecristo Island in the Mediterranean Sea. Analysis of the metagenomes revealed significant differences in both microbial diversity and abundance between the two areas, reflecting their distinct ecological habitats and anthropogenic stress conditions. Our results indicate that the combination of next generation sequencing (NGS) technologies and bioinformatics tools presents a new approach to monitor the diversity and the ecological status of aquatic ecosystems. Integration of metagenomics into environmental monitoring campaigns should enable the impact of the anthropogenic pressure on microbial biodiversity in various ecosystems to be better assessed and also predicted.     

Soil Functional Operating Range Linked to Microbial Biodiversity and Community Composition Using Denitrifiers as Model Guild

Soil microorganisms are key players in biogeochemical cycles. Yet, there is no consistent view on the significance of microbial biodiversity for soil ecosystem functioning. According to the insurance hypothesis, declines in ecosystem functioning due to reduced biodiversity are more likely to occur under fluctuating, extreme or rapidly changing environmental conditions. Here, we compare the functional operating range, a new concept defined as the complete range of environmental conditions under which soil microbial communities are able to maintain their functions, between four naturally assembled soil communities from a long-term fertilization experiment. A functional trait approach was adopted with denitrifiers involved in nitrogen cycling as our model soil community. Using short-term temperature and salt gradients, we show that the functional operating range was broader and process rates were higher when the soil community was phylogenetically more diverse. However, key bacterial genotypes played an important role for maintaining denitrification as an ecosystem functioning under certain conditions.     

Soil fungal communities are compositionally resistant to drought manipulations – Evidence from culture-dependent and culture-independent analyses

Current environmental change predictions forecast intensified drought conditions. It is becoming increasingly evident that plant communities are sensitive to drought and that soil-inhabiting microbial communities vary along precipitation gradients. However, the drought sensitivity of microbial communities in general and that of soil fungi in particular remains unclear, even though understanding their responses to adverse environmental conditions is vital for better understanding of ecosystem service provisioning. We sampled soils at two sites with established experiments that imposed extreme, chronic drought to assess fungal community responses. We analyzed fungal communities using both culture-dependent and -independent tools and MiSeq-sequenced communities from colony forming units (CFU-PCR) on a drought simulating medium and from environmental DNA (ePCR), to compare the conclusions derived from these two methods. Our data from the two approaches consistently indicate that the composition of fungal communities is not affected by the drought treatment, whereas – based on the CFU-PCR but not ePCR data – their richness and diversity increased under drought conditions at the more mesic of the two sites. Further, based on the direct comparisons of CFU-PCR and ePCR, we estimate that more than 10% of the fungal community and more than 20% of the ascomycetes were culturable. We conclude that although recent research indicates that plant and bacterial communities respond to drought, fungal community responses are more variable, particularly in experiments that impose chronic drought under field conditions.     

Accessing the soil metagenome for studies of microbial diversity

Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome.     

Statistical methods for characterizing diversity of microbial communities by analysis of terminal restriction fragment length polymorphisms of 16S rRNA genes

The analysis of terminal restriction fragment length polymorphisms (T-RFLP) of 16S rRNA genes has proven to be a facile means to compare microbial communities and presumptively identify abundant members. The method provides data that can be used to compare different communities based on similarity or distance measures. Once communities have been clustered into groups, clone libraries can be prepared from sample(s) that are representative of each group in order to determine the phylogeny of the numerically abundant populations in a community. In this paper methods are introduced for the statistical analysis of T-RFLP data that include objective methods for (i) determining a baseline so that 'true' peaks in electropherograms can be identified; (ii) a means to compare electropherograms and bin fragments of similar size; (iii) clustering algorithms that can be used to identify communities that are similar to one another; and (iv) a means to select samples that are representative of a cluster that can be used to construct 16S rRNA gene clone libraries. The methods for data analysis were tested using simulated data with assumptions and parameters that corresponded to actual data. The simulation results demonstrated the usefulness of these methods in their ability to recover the true microbial community structure generated under the assumptions made. Software for implementing these methods is available at http://www.ibest.uidaho.edu/tools/trflp_stats/index.php.     

Comparative analysis of yellow microbial communities growing on the walls of geographically distinct caves indicates a common core of microorganisms involved in their formation

Morphologically similar microbial communities that often form on the walls of geographically distinct limestone caves have not yet been comparatively studied. Here, we analysed phylotype distribution in yellow microbial community samples obtained from the walls of distinct caves located in Spain, Czech Republic and Slovenia. To infer the level of similarity in microbial community membership, we analysed inserts of 474 16S rRNA gene clones and compared those using statistical tools. The results show that the microbial communities under investigation are composed solely of Bacteria. The obtained phylotypes formed three distinct groups of operational taxonomic units (OTUs). About 60% of obtained sequences formed three core OTUs common to all three sampling sites. These were affiliated with actinobacterial Pseudonocardinae (30-50% of sequences in individual sampling site libraries), but also with gammaproteobacterial Chromatiales (6-25%) and Xanthomonadales (0.5-2.0%). Another 7% of sequences were common to two sampling sites and formed eight OTUs, while the remaining 35% were site specific and corresponded mostly to OTUs containing single sequences. The same pattern was observed when these data were compared with sequence data available from similar studies. This comparison showed that distinct limestone caves support microbial communities composed mostly of phylotypes common to all sampling sites.     

Predicting the responsiveness of soil biodiversity to deforestation: a cross‐biome study

The consequences of deforestation for aboveground biodiversity have been a scientific and political concern for decades. In contrast, despite being a dominant component of biodiversity that is essential to the functioning of ecosystems, the responses of belowground biodiversity to forest removal have received less attention. Single‐site studies suggest that soil microbes can be highly responsive to forest removal, but responses are highly variable, with negligible effects in some regions. Using high throughput sequencing, we characterize the effects of deforestation on microbial communities across multiple biomes and explore what determines the vulnerability of microbial communities to this vegetative change. We reveal consistent directional trends in the microbial community response, yet the magnitude of this vegetation effect varied between sites, and was explained strongly by soil texture. In sandy sites, the difference in vegetation type caused shifts in a suite of edaphic characteristics, driving substantial differences in microbial community composition. In contrast, fine‐textured soil buffered microbes against these effects and there were minimal differences between communities in forest and grassland soil. These microbial community changes were associated with distinct changes in the microbial catabolic profile, placing community changes in an ecosystem functioning context. The universal nature of these patterns allows us to predict where deforestation will have the strongest effects on soil biodiversity, and how these effects could be mitigated.     

Spatial heterogeneity of eukaryotic microbial communities in an unstudied geothermal diatomaceous biological soil crust: Yellowstone National Park, WY, USA

Knowledge of microbial communities and their inherent heterogeneity has dramatically increased with the widespread use of high-throughput sequencing technologies, and we are learning more about the ecological processes that structure microbial communities across a wide range of environments, as well as the relative scales of importance for describing bacterial communities in natural systems. Little work has been carried out to assess fine-scale eukaryotic microbial heterogeneity in soils. Here, we present findings from a bar-coded 18S rRNA survey of the eukaryotic microbial communities in a previously unstudied geothermal diatomaceous biological soil crust in Yellowstone National Park, WY, USA, in which we explicitly compare microbial community heterogeneity at the particle scale within soil cores. Multivariate analysis of community composition showed that while subsamples from within the same soil core clustered together, community dissimilarity between particles in the same core was high. This study describes a novel soil microbial environment and also adds to our growing understanding of microbial heterogeneity and the scales relevant to the study of soil microbial communities.     

环境选择和扩散限制驱动温带森林土壤细菌群落的构建

环境选择和扩散限制是生态系统中生物群落构建的两个基本过程,而两者相对作用的大小因研究尺度、群落属性和类型等有所不同.目前对温带亚高山森林土壤微生物群落构建的驱动因子和机制尚缺乏了解.本文利用PCR-DGGE技术研究庞泉沟自然保护区内5种典型森林包括华北落叶松林、青杄林、白杄林、油松林以及桦树林的6个森林土壤细菌群落(Lp MC1、Lp MC2、Pw MC、Pm MC、Pt MC、BMC)的结构特征及其影响因素,分析细菌群落结构与环境因子的相关性,以及土壤因子、植被和空间因素对细菌群落结构的影响.结果表明:研究区各样地土壤细菌群落的结构和生物多样性具有显著差异,低海拔落叶松和油松土壤细菌群落多样性较高(20条带),白杄林土壤细菌群落(13条带)多样性最低,高海拔落叶松土壤细菌群落多样性最高;土壤环境因子,如pH、土壤含水量、总碳、总氮、土壤有机质、速效磷以及土壤酶活性与土壤细菌群落多样性和结构显著相关;样地土壤细菌群落的beta多样性与群落的空间距离呈显著相关,表明扩散限制对群落结构具有一定的影响;方差分解分析结果显示,6个样地细菌群落结构的驱动因素大小依次为土壤因子(0.27)、空间因素(0.19)和植被(0.15);将区域土壤微生物作为"源群落",微宇宙试验结果显示,土壤因子是细菌群落结构形成的主要驱动力(0.35),同时源群落丰富的物种多样性对微宇宙土壤细菌群落结构具有显著影响.总之,在局域尺度下,环境选择对温带森林土壤细菌群落结构动态和多样性发挥主导作用,地理距离对群落结构具有显著影响,即确定性过程和随机过程共同决定局域森林土壤细菌群落结构,前者占主导地位.对于土壤细菌群落而言,扩散群落的组成和结构受到源群落的多样性特征和环境因子的双重影响.     

Termite Hindguts and the Ecology of Microbial Communities in the Sequencing Age

Advances in high‐throughput nucleic acid sequencing have improved our understanding of microbial communities in a number of ways. Deeper sequence coverage provides the means to assess diversity at the resolution necessary to recover ecological and biogeographic patterns, and at the same time single‐cell genomics provides detailed information about the interactions between members of a microbial community. Given the vastness and complexity of microbial ecosystems, such analyses remain challenging for most environments, so greater insight can also be drawn from analysing less dynamic ecosystems. Here, we outline the advantages of one such environment, the wood‐digesting hindgut communities of termites and cockroaches, and how it is a model to examine and compare both protist and bacterial communities. Beyond the analysis of diversity, our understanding of protist community ecology will depend on using statistically sound sampling regimes at biologically relevant scales, transitioning from discovery‐based to experimental ecology, incorporating single‐cell microbiology and other data sources, and continued development of analytical tools.     

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.     

Diversity and assembly patterns of activated sludge microbial communities: A review

Understanding diversity and assembly patterns of microbial communities in activated sludge (AS) is pivotal for addressing fundamental ecological questions and wastewater treatment engineering. Recent applications of molecular methods especially high-throughput sequencing (HTS) have led to the explosion of information about AS community diversity, including the identification of uncultured taxa, and characterization of low-abundance but environmentally important populations such as antibiotic resistant bacteria and pathogens. Those progresses have facilitated the leverage of ecological theories in describing AS community assembly. The lognormal species abundance curve has been applied to estimate AS microbial richness. Taxa-area and taxa-time relationships (TAR and TTR) have been observed for AS microbial communities. Core AS microbial communities have been identified. Meanwhile, the roles of both deterministic and stochastic processes in shaping AS community structures have been examined. Nonetheless, it remains challenging to define tempo-spatial scales for reliable identification of community turnover, and find tight links between AS microbial structure and wastewater treatment plant (WWTP) functions. To solve those issues, we expect that future research will focus on identifying active functional populations in AS using omics- methods integrated with stable-isotope probing (SIP) with the development of bioinformatics tools. Developing mathematic models to understand AS community structures and utilize information on AS community to predict the performance of WWTPs will also be vital for advancing knowledge of AS microbial ecology and environmental engineering.     

The influence of the invasive shrub, Lonicera maackii, on leaf decomposition and microbial community dynamics

Amur honeysuckle (Lonicera maackii) is an exotic invasive shrub that is rapidly expanding into forests of eastern North America. This species forms a dense forest understory, alters tree regeneration, negatively affects herb-layer biodiversity, and alters ecosystem function. In a second-growth forest in central Kentucky, we examined the timing and production of leaf litter and compared litter chemistry, decay rates, and microbial community colonization of Amur honeysuckle to that of two native trees, white ash (Fraxinus americana) and hickory (Carya spp.). The distribution of Amur honeysuckle was clumped, allowing us to compare differences in decomposition under and away from Amur honeysuckle shrubs. Amur honeysuckle leaf litter had significantly higher nitrogen, lower C:N, and lower lignin than the other species, and decomposition rates were greater than 5×?faster. Despite the much higher rate of Amur honeysuckle decomposition compared with the native species (p?<?0.0001), decomposition of all species was significantly slower (p?=?0.0489) in sites located under Amur honeysuckle shrubs. Nitrogen concentration increased through time in decomposing Amur honeysuckle litter; however, total mass of N rapidly declined. We found the initial microbial community on leaf litter of Amur honeysuckle was distinct from two native species and although all microbial communities changed through time, the microbial community of Amur honeysuckle remained distinct from native communities. In summary, a distinct microbial community that may originate on Amur honeysuckle leaves prior to senescence could explain the rapid decay rates.     

塔里木荒漠河岸林不同生境群落物种多度分布格局

为解释塔里木荒漠河岸林群落构建和物种多度分布格局形成的机理, 本文以塔里木荒漠河岸林2个不同生境(沙地、河漫滩) 4 ha固定监测样地为研究对象, 基于两样地物种调查数据, 采用统计模型(对数级数模型、对数正态模型、泊松对数正态分布模型、Weibull分布模型)、生态位模型(生态位优先占领模型、断棍模型)和中性理论模型(复合群落零和多项式模型、Volkov模型)拟合荒漠河岸林群落物种多度分布, 并用K-S检验与赤池信息准则(AIC)筛选最优拟合模型。结果表明: (1)随生境恶化(土壤水分降低), 植物物种多度分布曲线变化减小, 群落物种多样性、多度和群落盖度降低, 常见种数减少。(2)选用的3类模型均可拟合荒漠河岸林不同生境群落物种多度分布格局, 统计模型和中性理论模型拟合效果均优于生态位模型。复合群落零和多项式模型对远离河岸的干旱沙地生境拟合效果最好; 对数正态模型和泊松对数正态模型对洪水漫溢的河漫滩生境拟合效果最优; 中性理论模型与统计模型无显著差异。初步推断中性过程在荒漠河岸林群落构建中发挥着主导作用, 但模型拟合结果只能作为推断群落构建过程的必要非充分条件, 不能排除生态位过程的潜在作用。