Survey Of Microbial Communities Research Articles

Abundance and Diversity of the Phototrophic Microbial Mat Communities of Sulphur Mountain Banff Springs and Their Significance to the Endangered Snail, <i>Physella johnsoni</i>

Seasonal population fluctuations and diversity of anoxygenic phototrophs and cyanobacteria at the Sulphur Mountain thermal springs, Banff, Canada were investigated and compared to drastic population changes of the endangered snail Physella johnsoni. The microbial community revealed new species of anoxygenic phototrophic bacteria with novel spectral and morphological characteristics. Major mat-forming organisms included densely growing Thiothrix-like species, oxygenic phototrophs of the genera Spirulina, Oscillatoria, and Phormidium and purple nonsulfur bacteria Rhodobacter, Rhodopseudomonas and Rhodomicrobium. Aerobic anoxygenic phototrophs comprised a significant portion, upwards of 9.6 × 104 CFU/cm2 of mat or 18.9% of total aerobic heterotrophic isolates, while PNSB and purple sulfur bacteria were quantified at maximum abundance of 3.2 × 105 and 2.0 × 106 CFU/cm2 of mat, respectively. Photosynthetic activity revealed incredibly productive carbon fixation rates, averaging 40.5 mg C/cm2/day at one studied spring system. A temporal mismatch was observed for mat area and available organics to the fluctuation of P. johnsoni population in a tracking inertia manner. Mat chlorophyll a content appeared directly proportional to snail numbers making it an appropriate indicator of population. This survey of the Sulphur springs microbial communities suggests that phototrophic species are among the main determinants to the proliferation of P. johnsoni.

A general species delimitation method with applications to phylogenetic placements.

Motivation: Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and Markov Chain Monte Carlo sampling, and can therefore only be applied to small datasets.Results: We introduce the Poisson tree processes (PTP) model to infer putative species boundaries on a given phylogenetic input tree. We also integrate PTP with our evolutionary placement algorithm (EPA-PTP) to count the number of species in phylogenetic placements. We compare our approaches with popular OTU-picking methods and the General Mixed Yule Coalescent (GMYC) model. For de novo species delimitation, the stand-alone PTP model generally outperforms GYMC as well as OTU-picking methods when evolutionary distances between species are small. PTP neither requires an ultrametric input tree nor a sequence similarity threshold as input. In the open reference species delimitation approach, EPA-PTP yields more accurate results than de novo species delimitation methods. Finally, EPA-PTP scales on large datasets because it relies on the parallel implementations of the EPA and RAxML, thereby allowing to delimit species in high-throughput sequencing data.Availability and implementation: The code is freely available at www.exelixis-lab.org/software.html.Contact: Alexandros.Stamatakis@h-its.orgSupplementary information: Supplementary data are available at Bioinformatics online.

Distribution-Based Clustering: Using Ecology To Refine the Operational Taxonomic Unit

16S rRNA sequencing, commonly used to survey microbial communities, begins by grouping individual reads into operational taxonomic units (OTUs). There are two major challenges in calling OTUs: identifying bacterial population boundaries and differentiating true diversity from sequencing errors. Current approaches to identifying taxonomic groups or eliminating sequencing errors rely on sequence data alone, but both of these activities could be informed by the distribution of sequences across samples. Here, we show that using the distribution of sequences across samples can help identify population boundaries even in noisy sequence data. The logic underlying our approach is that bacteria in different populations will often be highly correlated in their abundance across different samples. Conversely, 16S rRNA sequences derived from the same population, whether slightly different copies in the same organism, variation of the 16S rRNA gene within a population, or sequences generated randomly in error, will have the same underlying distribution across sampled environments. We present a simple OTU-calling algorithm (distribution-based clustering) that uses both genetic distance and the distribution of sequences across samples and demonstrate that it is more accurate than other methods at grouping reads into OTUs in a mock community. Distribution-based clustering also performs well on environmental samples: it is sensitive enough to differentiate between OTUs that differ by a single base pair yet predicts fewer overall OTUs than most other methods. The program can decrease the total number of OTUs with redundant information and improve the power of many downstream analyses to describe biologically relevant trends.

The PAMPA datasets: a metagenomic survey of microbial communities in Argentinean pampean soils

BackgroundSoil is among the most diverse and complex environments in the world. Soil microorganisms play an essential role in biogeochemical cycles and affect plant growth and crop production. However, our knowledge of the relationship between species-assemblies and soil ecosystem processes is still very limited. The aim of this study was to generate a comprehensive metagenomic survey to evaluate the effect of high-input agricultural practices on soil microbial communities.ResultsWe collected soil samples from three different areas in the Argentinean Pampean region under three different types of land uses and two soil sources (bulk and rhizospheric). We extracted total DNA from all samples and also synthetized cDNA from rhizospheric samples. Using 454-FLX technology, we generated 112 16S ribosomal DNA and 14 16S ribosomal RNA amplicon libraries totaling 1.3 M reads and 36 shotgun metagenome libraries totaling 17.8 million reads (7.7 GB). Our preliminary results suggested that water availability could be the primary driver that defined microbial assemblages over land use and soil source. However, when water was not a limiting resource (annual precipitation >800 mm) land use was a primary driver.ConclusionThis was the first metagenomic study of soil conducted in Argentina and our datasets are among the few large soil datasets publicly available. The detailed analysis of these data will provide a step forward in our understanding of how soil microbiomes respond to high-input agricultural systems, and they will serve as a useful comparison with other soil metagenomic studies worldwide.

A Unique Signal Distorts the Perception of Species Richness and Composition in High-Throughput Sequencing Surveys of Microbial Communities: a Case Study of Fungi in Indoor Dust

Sequence-based surveys of microorganisms in varied environments have found extremely diverse assemblages. A standard practice in current high-throughput sequence (HTS) approaches in microbial ecology is to sequence the composition of many environmental samples at once by pooling amplicon libraries at a common concentration before processing on one run of a sequencing platform. Biomass of the target taxa, however, is not typically determined prior to HTS, and here, we show that when abundances of the samples differ to a large degree, this standard practice can lead to a perceived bias in community richness and composition. Fungal signal in settled dust of five university teaching laboratory classrooms, one of which was used for a mycology course, was surveyed. The fungal richness and composition in the dust of the nonmycology classrooms were remarkably similar to each other, while the mycology classroom was dominated by abundantly sporulating specimen fungi, particularly puffballs, and appeared to have a lower overall richness based on rarefaction curves and richness estimators. The fungal biomass was three to five times higher in the mycology classroom than the other classrooms, indicating that fungi added to the mycology classroom swamped the background fungi present in indoor air. Thus, the high abundance of a few taxa can skew the perception of richness and composition when samples are sequenced to an even depth. Next, we used in silico manipulations of the observed data to confirm that a unique signature can be identified with HTS approaches when the source is abundant, whether or not the taxon identity is distinct. Lastly, aerobiology of indoor fungi is discussed.Electronic supplementary materialThe online version of this article (doi:10.1007/s00248-013-0266-4) contains supplementary material, which is available to authorized users.

A 454 Survey Reveals the Community Composition and Core Microbiome of the Common Bed Bug (Cimex lectularius) across an Urban Landscape

Elucidating the spatial dynamic and core constituents of the microbial communities found in association with arthropod hosts is of crucial importance for insects that may vector human or agricultural pathogens. The hematophagous Cimex lectularius (Hemiptera: Cimicidae), known as the human bed bug, has made a recent resurgence in North America, as well as worldwide, potentially owing to increased travel, climate change and resistance to insecticides. A comprehensive survey of the bed bug microbiome has not been performed to date, nor has an assessment of the spatial dynamics of its microbiome. Here we present a survey of internal and external bed bug microbial communities by amplifying the V4–V6 hypervariable region of the 16S rDNA gene region followed by 454 Titanium sequencing using 31 individuals from eight distinct collection locations obtained from residences in Cincinnati, OH. Across all samples, 97% of the microbial community is made up of two dominant OTUs, previously identified as the α-proteobacterium Wolbachia and an unnamed γ-proteobacterium from the Enterobacteriaceae. Microbial communities varied among host locations for measures of community diversity and exhibited structure according to collection location. This broad survey represents the most in-depth assessment, to date, of the microbes that associate with bed bugs.

The role of biogeography in shaping diversity of the intestinal microbiota in house mice

The microbial communities inhabiting the mammalian intestinal tract play an important role in diverse aspects of host biology. However, little is known regarding the forces shaping variation in these communities and their influence on host fitness. To shed light on the contributions of host genetics, transmission and geography to diversity in microbial communities between individuals, we performed a survey of intestinal microbial communities in a panel of 121 house mice derived from eight locations across Western Europe using pyrosequencing of the bacterial 16S rRNA gene. The host factors studied included population structure estimated by microsatellite loci and mitochondrial DNA, genetic distance and geography. To determine whether host tissue (mucosa)-associated communities display properties distinct from those of the lumen, both the caecal mucosa and contents were examined. We identified Bacteroides, Robinsoniella and Helicobacter as the most abundant genera in both the caecal content and mucosa-associated communities of wild house mice. Overall, we found geography to be the most significant factor explaining patterns of diversity in the intestinal microbiota, with a comparatively weaker influence of host population structure and genetic distance. Furthermore, the influence of host genetic distance was limited to the mucosa communities, consistent with this environment being more intimately coupled to the host.

Next Generation Sequencing to Define Prokaryotic and Fungal Diversity in the Bovine Rumen

A combination of Sanger and 454 sequences of small subunit rRNA loci were used to interrogate microbial diversity in the bovine rumen of 12 cows consuming a forage diet. Observed bacterial species richness, based on the V1–V3 region of the 16S rRNA gene, was between 1,903 to 2,432 species-level operational taxonomic units (OTUs) when 5,520 reads were sampled per animal. Eighty percent of species-level OTUs were dominated by members of the order Clostridiales, Bacteroidales, Erysipelotrichales and unclassified TM7. Abundance of Prevotella species varied widely among the 12 animals. Archaeal species richness, also based on 16S rRNA, was between 8 and 13 OTUs, representing 5 genera. The majority of archaeal OTUs (84%) found in this study were previously observed in public databases with only two new OTUs discovered. Observed rumen fungal species richness, based on the 18S rRNA gene, was between 21 and 40 OTUs with 98.4–99.9% of OTUs represented by more than one read, using Good’s coverage. Examination of the fungal community identified numerous novel groups. Prevotella and Tannerella were overrepresented in the liquid fraction of the rumen while Butyrivibrio and Blautia were significantly overrepresented in the solid fraction of the rumen. No statistical difference was observed between the liquid and solid fractions in biodiversity of archaea and fungi. The survey of microbial communities and analysis of cross-domain correlations suggested there is a far greater extent of microbial diversity in the bovine rumen than previously appreciated, and that next generation sequencing technologies promise to reveal novel species, interactions and pathways that can be studied further in order to better understand how rumen microbial community structure and function affects ruminant feed efficiency, biofuel production, and environmental impact.

The phylogenetic Kantorovich-Rubinstein metric for environmental sequence samples.

It is now common to survey microbial communities by sequencing nucleic acid material extracted in bulk from a given environment. Comparative methods are needed that indicate the extent to which two communities differ given data sets of this type. UniFrac, which gives a somewhat ad hoc phylogenetics-based distance between two communities, is one of the most commonly used tools for these analyses. We provide a foundation for such methods by establishing that, if we equate a metagenomic sample with its empirical distribution on a reference phylogenetic tree, then the weighted UniFrac distance between two samples is just the classical Kantorovich-Rubinstein, or earth mover's, distance between the corresponding empirical distributions. We demonstrate that this Kantorovich-Rubinstein distance and extensions incorporating uncertainty in the sample locations can be written as a readily computable integral over the tree, we develop L(p) Zolotarev-type generalizations of the metric, and we show how the p-value of the resulting natural permutation test of the null hypothesis 'no difference between two communities' can be approximated by using a Gaussian process functional. We relate the L(2)-case to an analysis-of-variance type of decomposition, finding that the distribution of its associated Gaussian functional is that of a computable linear combination of independent [Formula: see text] random variables.

Microbial community profiles in intercellular fluid of rice

Plants harbor microorganisms that are thought to stimulate plant defense systems or promote plant growth. Individual species in these intercellular microbial communities are often not sufficiently abundant to be easily described, although some endophytic microorganisms amenable to culture have been characterized. To better understand the microbial population of plants, we collected intercellular fluid (IF) from leaf blades and sheaths of rice and subsequently isolated DNA from the IF. Denaturing gradient gel electrophoresis (DGGE) analysis of 16S and 18S rDNA fragments amplified from IF DNA by PCR indicated that these band patterns were distinguishable from those of a leaf surface-wash fluid (SF). Analysis of a set of rDNA fragments amplified from IF DNA of rice with different genotypes, paddies or growth stages for the primary survey of overall microbial community in the IF suggested that this approach is suitable for analyzing microbial diversity in the IF from various plant samples. Actually, comparative analysis of amplified rDNA fragments of rice and other five plant species indicated that the microbial diversity in IF is likely to vary substantially among plant species. We can also use sequence analysis of 16S rDNA fragments amplified from rice IF DNA to identify species including unculturable bacteria and proteobacteria and Xanthomonas and 18S rDNA fragments to identify Tilletiaria anomala, Tilletia iowensis, Ustilago maydis and unculturable eukaryotes. Thus, IF DNA analysis seems to be a good tool to further study the microbial ecology of plants.

Ironing out the wrinkles in the rare biosphere through improved OTU clustering

Deep sequencing of PCR amplicon libraries facilitates the detection of low-abundance populations in environmental DNA surveys of complex microbial communities. At the same time, deep sequencing can lead to overestimates of microbial diversity through the generation of low-frequency, error-prone reads. Even with sequencing error rates below 0.005 per nucleotide position, the common method of generating operational taxonomic units (OTUs) by multiple sequence alignment and complete-linkage clustering significantly increases the number of predicted OTUs and inflates richness estimates. We show that a 2% single-linkage preclustering methodology followed by an average-linkage clustering based on pairwise alignments more accurately predicts expected OTUs in both single and pooled template preparations of known taxonomic composition. This new clustering method can reduce the OTU richness in environmental samples by as much as 30–60% but does not reduce the fraction of OTUs in long-tailed rank abundance curves that defines the rare biosphere.

Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.

The carnivorous bladderwort (Utricularia, Lentibulariaceae): a system inflates

Carnivorous plants inhabit nutrient-poor environments, where prominent targets of prey capture are organic nitrogen and phosphorus. Some carnivorous plants also acquire carbon from their victims. A new report focusing on Utricularia, the bladderwort, demonstrates that carbon assimilated from photosynthesis is paradoxically secreted into the trapping environment, where it may help to support a mutualistic bacterial community. This bacterial community may also secrete allelochemicals that attract microcrustaceans which bear a strong overt resemblance to bladderwort traps. Furthermore, Utricularia and its sister genus Genlisea share anomalous molecular evolutionary features, such as highly increased rates of nucleotide substitution and dynamic evolution of genome size, from approximately 60-1500 megabases depending on the species or even population. A mechanistic hypothesis, based on the mutagenic action of reactive oxygen species (ROS) is proposed to underlie these phenomena, involving error-prone repair at the level of DNA bases and double-strand breaks. It is argued that these plants are prime candidates for further research on the complexities of plant physiology associated with carnivory, metagenomic surveys of trap microbial communities, novel plant nitrogen/nutrient utilization pathways, the ecology of prey attraction, whole-plant and trap comparative development, and, finally, evolution of the minimal angiosperm genome.

Effect of PCR amplicon size on assessments of clone library microbial diversity and community structure

PCR-based surveys of microbial communities commonly use regions of the small-subunit ribosomal RNA (SSU rRNA) gene to determine taxonomic membership and estimate total diversity. Here we show that the length of the target amplicon has a significant effect on assessments of microbial richness and community membership. Using operational taxonomic unit (OTU)- and taxonomy-based tools, we compared the V6 hypervariable region of the bacterial SSU rRNA gene of three amplicon libraries of c. 100, 400 and 1000 base pairs (bp) from each of two hydrothermal vent fluid samples. We found that the smallest amplicon libraries contained more unique sequences, higher diversity estimates and a different community structure than the other two libraries from each sample. We hypothesize that a combination of polymerase dissociation, cloning bias and mispriming due to secondary structure accounts for the differences. While this relationship is not linear, it is clear that the smallest amplicon libraries contained more different types of sequences, and accordingly, more diverse members of the community. Because divergent and lower abundant taxa can be more readily detected with smaller amplicons, they may provide better assessments of total community diversity and taxonomic membership than longer amplicons in molecular studies of microbial communities.

Changes in microbial community structure in the wake of Hurricanes Katrina and Rita

Hurricanes have the potential to alter the structures of coastal ecosystems and generate pathogen-laden floodwaters thatthreaten public health. To examine the impact of hurricanes on urban systems, we compared microbial community structures in samples collected after Hurricane Katrina and before and after Hurricane Rita. We extracted environmental DNA and sequenced small-subunit rRNA (SSU rRNA) gene clone libraries to survey microbial communities in floodwater, water, and sediment samples collected from Lake Charles, Lake Pontchartrain, the 17th Street and Industrial Canals in New Orleans, and raw sewage. Correspondence analysis showed that microbial communities associated with sediments formed one cluster while communities associated with lake and Industrial Canal water formed a second. Communities associated with water from the 17th Street Canal and floodwaters collected in New Orleans showed similarity to communities in raw sewage and contained a number of sequences associated with possible pathogenic microbes. This suggests that a distinct microbial community developed in floodwaters following Hurricane Katrina and that microbial community structures as a whole might be sensitive indicators of ecosystem health and serve as "sentinels" of water quality in the environment.

RrnDB: documenting the number of rRNA and tRNA genes in bacteria and archaea

A dramatic exception to the general pattern of single-copy genes in bacterial and archaeal genomes is the presence of 1–15 copies of each ribosomal RNA encoding gene. The original version of the Ribosomal RNA Database (rrnDB) cataloged estimates of the number of 16S rRNA-encoding genes; the database now includes the number of genes encoding each of the rRNAs (5S, 16S and 23S), an internally transcribed spacer region, and the number of tRNA genes. The rrnDB has been used largely by microbiologists to predict the relative rate at which microbial populations respond to favorable growth conditions, and to interpret 16S rRNA-based surveys of microbial communities. To expand the functionality of the rrnDB (http://ribosome.mmg.msu.edu/rrndb/index.php), the search engine has been redesigned to allow database searches based on 16S rRNA gene copy number, specific organisms or taxonomic subsets of organisms. The revamped database also computes average gene copy numbers for any collection of entries selected. Curation tools now permit rapid updates, resulting in an expansion of the database to include data for 785 bacterial and 69 archaeal strains. The rrnDB continues to serve as the authoritative, curated source that documents the phylogenetic distribution of rRNA and tRNA genes in microbial genomes.

Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers

The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.

Diversity of bacterial communities in container habitats of mosquitoes.

We investigated the bacterial diversity of microbial communities in water-filled, human-made and natural container habitats of the mosquitoes Aedes aegypti and Aedes albopictus in suburban landscapes of New Orleans, Louisiana in 2003. We collected water samples from three classes of containers, including tires (n = 12), cemetery urns (n = 23), and miscellaneous containers that included two tree holes (n = 19). Total genomic DNA was extracted from water samples, and 16S ribosomal DNA fragments (operational taxonomic units, OTUs) were amplified by PCR and separated by denaturing gradient gel electrophoresis (DGGE). The bacterial communities in containers represented diverse DGGE-DNA banding patterns that were not related to the class of container or to the local spatial distribution of containers. Mean richness and evenness of OTUs were highest in water samples from tires. Bacterial phylotypes were identified by comparative sequence analysis of 90 16S rDNA DGGE band amplicons. The majority of sequences were placed in five major taxa: Alpha-, Beta- and Gammaproteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and an unclassified group; Proteobacteria and Bacteroidetes were the predominant heterotrophic bacteria in containers. The bacterial communities in human-made containers consisted mainly of undescribed species, and a phylogenetic analysis based on 16S rRNA sequences suggested that species composition was independent of both container type and the spatial distribution of containers. Comparative PCR-based, cultivation-independent rRNA surveys of microbial communities associated with mosquito habitats can provide significant insight into community organization and dynamics of bacterial species.

A COMPARISON OF TAXON CO-OCCURRENCE PATTERNS FOR MACRO- AND MICROORGANISMS

We examine co-occurrence patterns of microorganisms to evaluate community assembly "rules". We use methods previously applied to macroorganisms, both to evaluate their applicability to microorganisms and to allow comparison of co-occurrence patterns observed in microorganisms to those found in macroorganisms. We use a null model analysis of 124 incidence matrices from microbial communities, including bacteria, archaea, fungi, and algae, and we compare these results to previously published findings from a meta-analysis of almost 100 macroorganism data sets. We show that assemblages of microorganisms demonstrate nonrandom patterns of co-occurrence that are broadly similar to those found in assemblages of macroorganisms. These results suggest that some taxon co-occurrence patterns may be general characteristics of communities of organisms from all domains of life. We also find that co-occurrence in microbial communities does not vary among taxonomic groups or habitat types. However, we find that the degree of co-occurrence does vary among studies that use different methods to survey microbial communities. Finally, we discuss the potential effects of the undersampling of microbial communities on our results, as well as processes that may contribute to nonrandom patterns of co-occurrence in both macrobial and microbial communities such as competition, habitat filtering, historical effects, and neutral processes.

Taxa–area relationships for microbes: the unsampled and the unseen

The recent observation of a power-law relationship, S proportional A(z), between number of taxa, S, and area, A, for microbial eukaryotes and bacteria suggests that this is one of the few generic relationships in ecology, applicable to plants, animals and microbes. However, the rate of increase in the number of species with area varies from approximately the fourth (z = 0.26) to as little as the 50th root (z = 0.0019) in microbes. This is an enormous range for which no quantitative explanation has been proffered. We show by sampling from synthetic populations that the disparity between sample and community sizes in microbial community surveys means z can be considerably underestimated and accrual of rare taxa with increasing area will not be detectable. Significant microbial taxa-area relationships will only be observed when changes in community structure within samples correlate with area. Thus, the very low z values observed recently cannot be used as the sole evidence in support of any particular community theory of community assembly. More generally, this suggests that our search for patterns and laws in the microbial world will be profoundly influenced and, potentially distorted by the sample sizes that are typical of microbial community surveys.