Rare taxa have potential to make metabolic contributions in enhanced biological phosphorus removal ecosystems

Enhanced biological phosphorus removal (EBPR) relies on diverse but specialized microbial communities to mediate the cycling and ultimate removal of phosphorus from municipal wastewaters. However, little is known about microbial activity and dynamics in relation to process fluctuations in EBPR ecosystems. Here, we monitored temporal changes in microbial community structure and potential activity across each bioreactor zone in a pilot‐scale EBPR treatment plant by examining the ratio of small subunit ribosomal RNA (SSU rRNA) to SSU rRNA gene (rDNA) over a 120 day study period. Although the majority of operational taxonomic units (OTUs) in the EBPR ecosystem were rare, many maintained high potential activities based on SSU rRNA : rDNA ratios, suggesting that rare OTUs contribute substantially to protein synthesis potential in EBPR ecosystems. Few significant differences in OTU abundance and activity were observed between bioreactor redox zones, although differences in temporal activity were observed among phylogenetically cohesive OTUs. Moreover, observed temporal activity patterns could not be explained by measured process parameters, suggesting that other ecological drivers, such as grazing or viral lysis, modulated community interactions. Taken together, these results point towards complex interactions selected for within the EBPR ecosystem and highlight a previously unrecognized functional potential among low abundance microorganisms in engineered ecosystems.     

Semi-automated extraction of microbial DNA from feces for qPCR and phylogenetic microarray analysis

The human gastrointestinal tract (GI-tract) harbors a complex microbial ecosystem, largely composed of so far uncultured species, which can be detected only by using techniques such as PCR and by different hybridization techniques including phylogenetic microarrays. Manual DNA extraction from feces is laborious and is one of the bottlenecks holding up the application of microarray and other DNA-based techniques in large cohort studies. In order to enhance the DNA extraction step we combined mechanical disruption of microbial cells by repeated bead-beating (RBB) with two automated DNA extraction methods, KingFisher with InviMag Stool DNA kit (KF) and NucliSENS easyMAG (NeM). The semi-automated DNA extraction methods, RBB combined with either KF or NeM, were compared to the manual extraction method currently considered the most suited method for fecal DNA extraction by assessing the yield of 16S rRNA gene copies by qPCR and total microbiota composition by the HITChip, a phylogenetic microarray. Parallel DNA extractions from infant fecal samples by using the three methods showed that the KF and manual methods gave comparable yields of 16S rRNA gene copies as assessed by qPCR, whereas NeM showed a significantly lower yield. All three methods showed highly similar microbiota profiles in HITChip. Both KF and NeM were found to be suitable methods for DNA extraction from fecal samples after the mechanical disruption of microbial cells by bead-beating. The semi-automated methods could be performed in half of the time required for the manual protocol, while being comparable to the manual method in terms of reagent costs.     

Diversity of the human gastrointestinal tract microbiota revisited

Since the early days of microbiology, more than a century ago, representatives of over 400 different microbial species have been isolated and fully characterized from human gastrointestinal samples. However, during the past decade molecular ecological studies based on ribosomal RNA (rRNA) sequences have revealed that cultivation has been able only to access a small fraction of the microbial diversity within the gastrointestinal tract. The increasing number of deposited rRNA sequences calls for the setting up a curated database that allows handling of the excessive degree of redundancy that threatens the usability of public databases. The integration of data from cultivation-based studies and molecular inventories of small subunit (SSU) rRNA diversity, presented here for the first time, provides a systematic framework of the microbial diversity in the human gastrointestinal tract of more than 1000 different species-level phylogenetic types (phylotypes). Such knowledge is essential for the design of high-throughput approaches such as phylogenetic DNA microarrays for the comprehensive analysis of gastrointestinal tract microbiota at multiple levels of taxonomic resolution. Development of such approaches is likely to be pivotal to generating novel insights in microbiota functionality in health and disease.     

Assembly of the human intestinal microbiota

Complex microbial ecosystems occupy the skin, mucosa and alimentary tract of all mammals, including humans. Recent advances have highlighted the tremendous diversity of these microbial communities and their importance to host physiology, but questions remain about the ecological processes that establish and maintain the microbiota throughout life. The prevailing view, that the gastrointestinal microbiota of adult humans is a climax community comprised of the superior competitors for a stable set of niches, does not account for all of the experimental data. We argue here that the unique history of each community and intrinsic temporal dynamics also influence the structure of human intestinal communities.     

Rapid quantitative profiling of complex microbial populations

Diverse and complex microbial ecosystems are found in virtually every environment on earth, yet we know very little about their composition and ecology. Comprehensive identification and quantification of the constituents of these microbial communities—a ‘census’—is an essential foundation for understanding their biology. To address this problem, we developed, tested and optimized a DNA oligonucleotide microarray composed of 10 462 small subunit (SSU) ribosomal DNA (rDNA) probes (7167 unique sequences) selected to provide quantitative information on the taxonomic composition of diverse microbial populations. Using our optimized experimental approach, this microarray enabled detection and quantification of individual bacterial species present at fractional abundances of <0.1% in complex synthetic mixtures. The estimates of bacterial species abundance obtained using this microarray are similar to those obtained by phylogenetic analysis of SSU rDNA sequences from the same samples—the current ‘gold standard’ method for profiling microbial communities. Furthermore, probes designed to represent higher order taxonomic groups of bacterial species reliably detected microbes for which there were no species-specific probes. This simple, rapid microarray procedure can be used to explore and systematically characterize complex microbial communities, such as those found within the human body.     

Lactobacillus casei Abundance Is Associated with Profound Shifts in the Infant Gut Microbiome

Colonization of the infant gut by microorganisms over the first year of life is crucial for development of a balanced immune response. Early alterations in the gastrointestinal microbiota of neonates has been linked with subsequent development of asthma and atopy in older children. Here we describe high-resolution culture-independent analysis of stool samples from 6-month old infants fed daily supplements of Lactobacillus casei subsp. Rhamnosus (LGG) or placebo in a double-blind, randomized Trial of Infant Probiotic Supplementation (TIPS). Bacterial community composition was examined using a high-density microarray, the 16S rRNA PhyloChip, and the microbial assemblages of infants with either high or low LGG abundance were compared. Communities with high abundance of LGG exhibited promotion of phylogenetically clustered taxa including a number of other known probiotic species, and were significantly more even in their distribution of community members. Ecologically, these aspects are characteristic of communities that are more resistant to perturbation and outgrowth of pathogens. PhyloChip analysis also permitted identification of taxa negatively correlated with LGG abundance that have previously been associated with atopy, as well as those positively correlated that may prove useful alternative targets for investigation as alternative probiotic species. From these findings we hypothesize that a key mechanism for the protective effect of LGG supplementation on subsequent development of allergic disease is through promotion of a stable, even, and functionally redundant infant gastrointestinal community.     

Communities of Arbuscular Mycorrhizal Fungi Detected in Forest Soil Are Spatially Heterogeneous but Do Not Vary throughout the Growing Season

Despite the important ecosystem role played by arbuscular mycorrhizal fungi (AMF), little is known about spatial and temporal variation in soil AMF communities. We used pyrosequencing to characterise AMF communities in soil samples (n = 44) from a natural forest ecosystem. Fungal taxa were identified by BLAST matching of reads against the MaarjAM database of AMF SSU rRNA gene diversity. Sub-sampling within our dataset and experimental shortening of a set of long reads indicated that our approaches to taxonomic identification and diversity analysis were robust to variations in pyrosequencing read length and numbers of reads per sample. Different forest plots (each 10×10 m and separated from one another by 30 m) contained significantly different soil AMF communities, and the pairwise similarity of communities decreased with distance up to 50 m. However, there were no significant changes in community composition between different time points in the growing season (May-September). Spatial structure in soil AMF communities may be related to the heterogeneous vegetation of the natural forest study system, while the temporal stability of communities suggests that AMF in soil represent a fairly constant local species pool from which mycorrhizae form and disband during the season.     

2型糖尿病小鼠食道菌群的结构分析

人体内庞大的微生物群体对人体有着巨大的影响.越来越多的数据表明,肠道菌群与肥胖症、糖尿病等代谢性疾病的发生密切相关.食道菌群结构对研究胃肠道及整个消化 系统菌群结构至关重要.针对10只2型糖尿病模型小鼠及10只正常对照小鼠食道样本,进行变性梯度凝胶电泳（DGGE）和克隆测序分析食道菌群结构.结果发现,实验组小鼠与对照组小鼠食道菌群多样性指数与丰富度指数存在显著差异,均匀度指数无显著差 异.说明正常小鼠较2型糖尿病小鼠食道菌群种类及数量较大,优势菌种类及相对含量相似.测序结果显示,正常小鼠食道内含乳杆菌属细菌,而患病小鼠食道内不含乳杆菌属细菌或含量极低.提示乳杆菌属细菌与2型糖尿病密切相关,实验结果对研究糖尿病发病机理及并发症治疗有重要意义.     

Comparative metaproteomics and diversity analysis of human intestinal microbiota testifies for its temporal stability and expression of core functions

The human intestinal tract is colonized by microbial communities that show a subject-specific composition and a high-level temporal stability in healthy adults. To determine whether this is reflected at the functional level, we compared the faecal metaproteomes of healthy subjects over time using a novel high-throughput approach based on denaturing polyacrylamide gel electrophoresis and liquid chromatography-tandem mass spectrometry. The developed robust metaproteomics workflow and identification pipeline was used to study the composition and temporal stability of the intestinal metaproteome using faecal samples collected from 3 healthy subjects over a period of six to twelve months. The same samples were also subjected to DNA extraction and analysed for their microbial composition and diversity using the Human Intestinal Tract Chip, a validated phylogenetic microarray. Using metagenome and single genome sequence data out of the thousands of mass spectra generated per sample, approximately 1,000 peptides per sample were identified. Our results indicate that the faecal metaproteome is subject-specific and stable during a one-year period. A stable common core of approximately 1,000 proteins could be recognized in each of the subjects, indicating a common functional core that is mainly involved in carbohydrate transport and degradation. Additionally, a variety of surface proteins could be identified, including potential microbes-host interacting components such as flagellins and pili. Altogether, we observed a highly comparable subject-specific clustering of the metaproteomic and phylogenetic profiles, indicating that the distinct microbial activity is reflected by the individual composition.     

Characterization of the diversity and temporal stability of bacterial communities in human milk

Recent investigations have demonstrated that human milk contains a variety of bacterial genera; however, as of yet very little work has been done to characterize the full diversity of these milk bacterial communities and their relative stability over time. To more thoroughly investigate the human milk microbiome, we utilized microbial identification techniques based on pyrosequencing of the 16S ribosomal RNA gene. Specifically, we characterized the bacterial communities present in milk samples collected from 16 women at three time-points over four weeks. Results indicated that milk bacterial communities were generally complex; several genera represented greater than 5% of the relative community abundance, and the community was often, yet not always, stable over time within an individual. These results support the conclusion that human milk, which is recommended as the optimal nutrition source for almost all healthy infants, contains a collection of bacteria more diverse than previously reported. This finding begs the question as to what role this community plays in colonization of the infant gastrointestinal tract and maintaining mammary health.     

Comparative microbial diversity in the gastrointestinal tracts of food animal species

Molecular tools based on small subunit (SSU) rDNA gene sequencesoffer a powerful and rapid tool for the analysis of complexmicrobial communities found in the gastrointestinal tracts (GIT)of food animal species. Extensive comparative sequence analysisof SSU rRNA molecules representing a wide diversity of organismsshows that different regions of the molecule vary in sequenceconservation. Oligonucleotides complementing regions of universallyconversed SSU rRNA sequences are used as universal probes, whilethose complementing more variable regions of sequence are usefulas selective probes targeting species, genus, or phylogeneticgroups. Different approaches derive different information andthis is highly dependent on the type of target nucleic acidemployed and the conceptual and technical basis used for nucleicacid probe design. Generally these approaches can be dividedinto DNA-based methods employing empirically characterized probesand rRNA-based methods based on comparative sequence analysisfor design and interpretation of "rational" probes. Polymerasechain reaction (PCR) based techniques can also be applied tothe analysis of microbial communities in the GIT. Direct cloningof SSU rDNA genes amplified from these complex communities canbe used to determine the extent of diversity in these GIT communities.Denaturing gradient gel electrophoresis (DGGE) is another powerfultool for profiling microbial diversity of microbial communitiesin GI tracts. Sequence analysis of the excised DGGE ampliconscan then be used to presumptively identify predominant bacterialspecies. Examples of how these molecular approaches are beingused to study the microbial diversity of communities from steersfed different diets, swine fed probiotics, and Atlantic salmonfed aquaculture diets are presented.     

Microbiome analysis of dairy cows fed pasture or total mixed ration diets

Understanding rumen microbial ecology is essential for the development of feed systems designed to improve livestock productivity, health and for methane mitigation strategies from cattle. Although rumen microbial communities have been studied previously, few studies have applied next-generation sequencing technologies to that ecosystem. The aim of this study was to characterize changes in microbial community structure arising from feeding dairy cows two widely used diets: pasture and total mixed ration (TMR). Bacterial, archaeal and protozoal communities were characterized by terminal restriction fragment length polymorphism of the amplified SSU rRNA gene and statistical analysis showed that bacterial and archaeal communities were significantly affected by diet, whereas no effect was observed for the protozoal community. Deep amplicon sequencing of the 16S rRNA gene revealed significant differences in the bacterial communities between the diets and between rumen solid and liquid content. At the family level, some important groups of rumen bacteria were clearly associated with specific diets, including the higher abundance of the Fibrobacteraceae in TMR solid samples and members of the propionate-producing Veillonelaceae in pasture samples. This study will be relevant to the study of rumen microbial ecology and livestock feed management.     

Alignment-Independent Comparisons of Human Gastrointestinal Tract Microbial Communities in a Multidimensional 16S rRNA Gene Evolutionary Space

We present a novel approach for comparing 16S rRNA gene clone libraries that is independent of both DNA sequence alignment and definition of bacterial phylogroups. These steps are the major bottlenecks in current microbial comparative analyses. We used direct comparisons of taxon density distributions in an absolute evolutionary coordinate space. The coordinate space was generated by using alignment-independent bilinear multivariate modeling. Statistical analyses for clone library comparisons were based on multivariate analysis of variance, partial least-squares regression, and permutations. Clone libraries from both adult and infant gastrointestinal tract microbial communities were used as biological models. We reanalyzed a library consisting of 11,831 clones covering complete colons from three healthy adults in addition to a smaller 390-clone library from infant feces. We show that it is possible to extract detailed information about microbial community structures using our alignment-independent method. Our density distribution analysis is also very efficient with respect to computer operation time, meeting the future requirements of large-scale screenings to understand the diversity and dynamics of microbial communities.     

Alignment-independent comparisons of human gastrointestinal tract microbial communities in a multidimensional 16S rRNA gene evolutionary space

We present a novel approach for comparing 16S rRNA gene clone libraries that is independent of both DNA sequence alignment and definition of bacterial phylogroups. These steps are the major bottlenecks in current microbial comparative analyses. We used direct comparisons of taxon density distributions in an absolute evolutionary coordinate space. The coordinate space was generated by using alignment-independent bilinear multivariate modeling. Statistical analyses for clone library comparisons were based on multivariate analysis of variance, partial least-squares regression, and permutations. Clone libraries from both adult and infant gastrointestinal tract microbial communities were used as biological models. We reanalyzed a library consisting of 11,831 clones covering complete colons from three healthy adults in addition to a smaller 390-clone library from infant feces. We show that it is possible to extract detailed information about microbial community structures using our alignment-independent method. Our density distribution analysis is also very efficient with respect to computer operation time, meeting the future requirements of large-scale screenings to understand the diversity and dynamics of microbial communities.     

Functional composition of plant communities determines the spatial and temporal stability of soil microbial properties in a long‐term plant diversity experiment

Stable provisioning of ecosystem functions and services is crucial for human well‐being in a changing world. Two essential ecological components driving vital ecosystem functions in terrestrial ecosystems are plant diversity and soil microorganisms. In this study, we tracked soil microbial basal respiration and biomass over a time period of 12 years in a grassland biodiversity experiment (the Jena Experiment) and examined the role of plant diversity and plant functional group composition for the spatial and temporal stability of soil microbial properties (basal respiration and biomass) in bulk‐soil. Spatial and temporal stability were calculated as the inverse coefficient of variation (CV^?1) of soil microbial respiration and biomass measured from soil samples taken over space and time, respectively. We found that 1) plant species richness consistently increased soil microbial properties after a time lag of four years since the establishment of the experimental plots, 2) plant species richness had minor effects on the spatial stability of soil microbial properties, whereas 3) the functional composition of plant communities significantly affected spatial stability of soil microbial properties, with legumes and tall herbs reducing both the spatial stability of microbial respiration and biomass, while grasses increased the latter, and 4) the effect of plant diversity on temporal stability of soil microbial properties turned from being negative to neutral, suggesting that the recovery of soil microbial communities from former arable land‐use takes more than a decade. Our results highlight the importance of plant functional group composition for the spatial and temporal stability of soil microbial properties, and hence for microbially‐driven ecosystem processes, such as decomposition and element cycling, in temperate semi‐natural grassland.     

Integrating microbial ecology into ecosystem models: challenges and priorities

Microbial communities can potentially mediate feedbacks between global change and ecosystem function, owing to their sensitivity to environmental change and their control over critical biogeochemical processes. Numerous ecosystem models have been developed to predict global change effects, but most do not consider microbial mechanisms in detail. In this idea paper, we examine the extent to which incorporation of microbial ecology into ecosystem models improves predictions of carbon (C) dynamics under warming, changes in precipitation regime, and anthropogenic nitrogen (N) enrichment. We focus on three cases in which this approach might be especially valuable: temporal dynamics in microbial responses to environmental change, variation in ecological function within microbial communities, and N effects on microbial activity. Four microbially-based models have addressed these scenarios. In each case, predictions of the microbial-based models differ—sometimes substantially—from comparable conventional models. However, validation and parameterization of model performance is challenging. We recommend that the development of microbial-based models must occur in conjunction with the development of theoretical frameworks that predict the temporal responses of microbial communities, the phylogenetic distribution of microbial functions, and the response of microbes to N enrichment.     

Inferring dynamic signatures of microbes in complex host ecosystems

The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe will prove instrumental for future studies in this field.