Microbial Community Samples Research Articles

Comprehensive Meta-analysis of Ontology Annotated 16S rRNA Profiles Identifies Beta Diversity Clusters of Environmental Bacterial Communities.

Comprehensive mapping of environmental microbiomes in terms of their compositional features remains a great challenge in understanding the microbial biosphere of the Earth. It bears promise to identify the driving forces behind the observed community patterns and whether community assembly happens deterministically. Advances in Next Generation Sequencing allow large community profiling studies, exceeding sequencing data output of conventional methods in scale by orders of magnitude. However, appropriate collection systems are still in a nascent state. We here present a database of 20,427 diverse environmental 16S rRNA profiles from 2,426 independent studies, which forms the foundation of our meta-analysis. We conducted a sample size adaptive all-against-all beta diversity comparison while also respecting phylogenetic relationships of Operational Taxonomic Units(OTUs). After conventional hierarchical clustering we systematically test for enrichment of Environmental Ontology terms and their abstractions in all possible clusters. This post-hoc algorithm provides a novel formalism that quantifies to what extend compositional and semantic similarity of microbial community samples coincide. We automatically visualize significantly enriched subclusters on a comprehensive dendrogram of microbial communities. As a result we obtain the hitherto most differentiated and comprehensive view on global patterns of microbial community diversity. We observe strong clusterability of microbial communities in ecosystems such as human/mammal-associated, geothermal, fresh water, plant-associated, soils and rhizosphere microbiomes, whereas hypersaline and anthropogenic samples are less homogeneous. Moreover, saline samples appear less cohesive in terms of compositional properties than previously reported.

Cocopeat for Wastewater Treatment in the Developing World. II: Field Evaluation of Constructed Wetlands Packed with Cocopeat for Wastewater Treatment in Can Tho, Vietnam

AbstractCocopeat, a byproduct of coconut processing, was evaluated as a packing medium in vertical flow constructed wetlands for the treatment of septic tank effluent in the Mekong Delta of Vietnam. Vertical flow constructed wetlands are typically packed with gravel and then planted with ornamental plants. For this study, varying percentages of cocopeat were added to the gravel and the systems assessed for supplemental treatment efficiency. A secondary treatment step of gravel planters with ornamental plants was assessed for supplemental treatment efficiency. Removal efficiencies of nitrogen, phosphorus, coliform, and biological oxygen demand were measured. Microbial community samples were collected periodically in order to chronologically analyze community shifts within and between different wetland cells. Ammonium transformation and removal was greater than 95% in each wetland containing cocopeat throughout the course of the study. Ammonium concentrations were significantly higher in the effluent of the...

A flexible and economical barcoding approach for highly multiplexed amplicon sequencing of diverse target genes.

High throughput sequencing of phylogenetic and functional gene amplicons provides tremendous insight into the structure and functional potential of complex microbial communities. Here, we introduce a highly adaptable and economical PCR approach to barcoding and pooling libraries of numerous target genes. In this approach, we replace gene- and sequencing platform-specific fusion primers with general, interchangeable barcoding primers, enabling nearly limitless customized barcode-primer combinations. Compared to barcoding with long fusion primers, our multiple-target gene approach is more economical because it overall requires lower number of primers and is based on short primers with generally lower synthesis and purification costs. To highlight our approach, we pooled over 900 different small-subunit rRNA and functional gene amplicon libraries obtained from various environmental or host-associated microbial community samples into a single, paired-end Illumina MiSeq run. Although the amplicon regions ranged in size from approximately 290 to 720 bp, we found no significant systematic sequencing bias related to amplicon length or gene target. Our results indicate that this flexible multiplexing approach produces large, diverse, and high quality sets of amplicon sequence data for modern studies in microbial ecology.

Application of Meta‐Mesh on the analysis of microbial communities from human associated‐habitats

With the current fast accumulation of microbial community samples and related metagenomic sequencing data, data integration and analysis system is urgently needed for in‐depth analysis of large number of metagenomic samples (also referred to as “microbial communities”) of interest. Although several existing databases have collected a large number of metagenomic samples, they mostly serve as data repositories with crude annotations, and offer limited functionality for analysis. Moreover, the few available tools for comparative analysis in the literature could only support the comparison of a few pre‐defined set of metagenomic samples. To facilitate comprehensive comparative analysis on large amount of diverse microbial community samples, we have designed a Meta‐Mesh system for a variety of analyses including quantitative analysis of similarities among microbial communities and computation of the correlation between the meta‐information of these samples. We have used Meta‐Mesh for systematically and efficiently analyses on diverse sets of human associate‐habitat microbial community samples. Results have shown that Meta‐Mesh could serve well as an efficient data analysis platform for discovery of clusters, biomarker and other valuable biological information from a large pool of human microbial samples.

The sequential isolation of metabolites, RNA, DNA, and proteins from a single, undivided mixed microbial community sample

The sequential isolation of metabolites, RNA, DNA, and proteins from a single, undivided mixed microbial community sample

Comparison of Total DNA Extraction Methods for Microbial Community Form Polluted Soil

Abstract DNA isolation represents the basic and probably the most important step in molecular biology for microbial strains, and even more, for microbial community analyses. Despite the development of molecular protocols for DNA microbial community isolation, there are still many drawbacks dependent of samples composition, and even the commercially available genomic isolation kits have significant limitations in recovering high genomic DNA amounts, especially from soil samples. Our study is aiming to compare and optimize a total microbial community DNA isolation protocol from polluted soil samples, estimating the amount and the purity of genomic DNA per g of soil, versus time requirements for each protocol, taking under consideration that our soil samples have a high content of humic acids. We checked several protocols for total DNA extraction, CTAB based, including a specific Kit for Soil DNA Isolation Kit NorgenBiotek. We estimated the time needed for each protocol, the amount of the DNA per gram of polluted soil, proteins and RNA contamination grade, by spectrophotometric analysis, but also the grade of PCR amplification inhibition. The most efficient method for our soil samples with high content of humic acid, suitable for further molecular analyses was the total DNA microbial community sample retrieved from Sagova et al. (2008) based protocol, with several adjustments. This protocol will be valuable for molecular analysis on microbial community profiling from environmental samples, especially from polluted soils.

The sequential isolation of metabolites, RNA, DNA, and proteins from a single, undivided mixed microbial community sample

The sequential isolation of metabolites, RNA, DNA, and proteins from a single, undivided mixed microbial community sample

Potential Microorganisms for Prevention of Paraffin Precipitation in a Hypersaline Oil Reservoir

Based on 454 pyrosequencing of 16S rRNA gene amplicons, microbial communities in samples collected from seven wells, six of which had positive paraffin deposition reduction and one with negative paraffin deposition reduction upon a microbial treatment designed for the prevention of paraffin precipitation, were analyzed. Microbial communities’ structures were significantly different for the samples from the negative well and the positive wells. Microbes affiliated with Diaphorobacter belonging to β-Proteobacteria were predominant in the negative well, While γ-Proteobacteria-affiliated microbes of Pseudomonas and Enterobacter and Firmicute-affiliated Bacillus were shared and dominant in the positive wells. Microbes shared in the positive wells could be considered as potential candidates for investigations into microbial paraffin control. In addition, microbial activity of hydrocarbon-degradation and microbial products such as biosurfactants were proposed to be the main potential mechanisms for the microbial treatment for the prevention of paraffin precipitation.

Phylogeny-based classification of microbial communities

Next-generation sequencing coupled with metagenomics has led to the rapid growth of sequence databases and enabled a new branch of microbiology called comparative metagenomics. Comparative metagenomic analysis studies compositional patterns within and between different environments providing a deep insight into the structure and function of complex microbial communities. It is a fast growing field that requires the development of novel supervised learning techniques for addressing challenges associated with metagenomic data, e.g. sensitivity to the choice of sequence similarity cutoff used to define operational taxonomic units (OTUs), high dimensionality and sparsity of the data and so forth. On the other hand, the natural properties of microbial community data may provide useful information about the structure of the data. For example, similarity between species encoded by a phylogenetic tree captures the relationship between OTUs and may be useful for the analysis of complex microbial datasets where the diversity patterns comprise features at multiple taxonomic levels. Even though some of the challenges have been addressed by learning algorithms in the literature, none of the available methods take advantage of the inherent properties of metagenomic data. We proposed a novel supervised classification method for microbial community samples, where each sample is represented as a set of OTU frequencies, which takes advantage of the natural structure in microbial community data encoded by a phylogenetic tree. This model allows us to take advantage of environment-specific compositional patterns that may contain features at multiple granularity levels. Our method is based on the multinomial logistic regression model with a tree-guided penalty function. Additionally, we proposed a new simulation framework for generating 16S ribosomal RNA gene read counts that may be useful in comparative metagenomics research. Our experimental results on simulated and real data show that the phylogenetic information used in our method improves the classification accuracy. http://www.cs.ucr.edu/~tanaseio/metaphyl.htm.

GPU-Meta-Storms: computing the structure similarities among massive amount of microbial community samples using GPU

The number of microbial community samples is increasing with exponential speed. Data-mining among microbial community samples could facilitate the discovery of valuable biological information that is still hidden in the massive data. However, current methods for the comparison among microbial communities are limited by their ability to process large amount of samples each with complex community structure. We have developed an optimized GPU-based software, GPU-Meta-Storms, to efficiently measure the quantitative phylogenetic similarity among massive amount of microbial community samples. Our results have shown that GPU-Meta-Storms would be able to compute the pair-wise similarity scores for 10 240 samples within 20 min, which gained a speed-up of >17 000 times compared with single-core CPU, and >2600 times compared with 16-core CPU. Therefore, the high-performance of GPU-Meta-Storms could facilitate in-depth data mining among massive microbial community samples, and make the real-time analysis and monitoring of temporal or conditional changes for microbial communities possible. GPU-Meta-Storms is implemented by CUDA (Compute Unified Device Architecture) and C++. Source code is available at http://www.computationalbioenergy.org/meta-storms.html.

Tracking human sewage microbiome in a municipal wastewater treatment plant

Human sewage pollution is a major threat to public health because sewage always comes with pathogens. Human sewage is usually received and treated by wastewater treatment plants (WWTPs) to control pathogenic risks and ameliorate environmental health. However, untreated sewage that flows into water environments may cause serious waterborne diseases, as reported in India and Bangladesh. To examine the fate of the human sewage microbiome in a local municipal WWTP of Hong Kong, we used massively parallel sequencing of 16S rRNA gene to systematically profile microbial communities in samples from three sections (i.e., influent, activated sludge, and effluent) obtained monthly throughout 1 year. The results indicated that: (1) influent sewage bacterial profile reflected the human microbiome; (2) human gut bacterial community was the dominant force shaping influent sewage bacterial profile; (3) most human sewage bacteria could be effectively removed by the WWTP; (4) a total of 75 genera were profiled as potentially pathogenic bacteria, most of which were still present in the effluent although at a very low level; (5) a grouped pattern of bacterial community was observed among the same section samples but a dispersed pattern was found among the different section samples; and (6) activated sludge was less affected by the influent sewage bacteria, but it showed a significant impact on the effluent bacteria. All of these findings provide novel insights toward a mechanistic understanding of the fate of human sewage microbiome in the WWTP.

Two-stage microbial community experimental design

Microbial community samples can be efficiently surveyed in high throughput by sequencing markers such as the 16S ribosomal RNA gene. Often, a collection of samples is then selected for subsequent metagenomic, metabolomic or other follow-up. Two-stage study design has long been used in ecology but has not yet been studied in-depth for high-throughput microbial community investigations. To avoid ad hoc sample selection, we developed and validated several purposive sample selection methods for two-stage studies (that is, biological criteria) targeting differing types of microbial communities. These methods select follow-up samples from large community surveys, with criteria including samples typical of the initially surveyed population, targeting specific microbial clades or rare species, maximizing diversity, representing extreme or deviant communities, or identifying communities distinct or discriminating among environment or host phenotypes. The accuracies of each sampling technique and their influences on the characteristics of the resulting selected microbial community were evaluated using both simulated and experimental data. Specifically, all criteria were able to identify samples whose properties were accurately retained in 318 paired 16S amplicon and whole-community metagenomic (follow-up) samples from the Human Microbiome Project. Some selection criteria resulted in follow-up samples that were strongly non-representative of the original survey population; diversity maximization particularly undersampled community configurations. Only selection of intentionally representative samples minimized differences in the selected sample set from the original microbial survey. An implementation is provided as the microPITA (Microbiomes: Picking Interesting Taxa for Analysis) software for two-stage study design of microbial communities.

Development and validation of an experimental life support system for assessing the effects of global climate change and environmental contamination on estuarine and coastal marine benthic communities

An experimental life support system (ELSS) was constructed to study the interactive effects of multiple stressors on coastal and estuarine benthic communities, specifically perturbations driven by global climate change and anthropogenic environmental contamination. The ELSS allows researchers to control salinity, pH, temperature, ultraviolet radiation (UVR), tidal rhythms and exposure to selected contaminants. Unlike most microcosms previously described, our system enables true independent replication (including randomization). In addition to this, it can be assembled using commercially available materials and equipment, thereby facilitating the replication of identical experimental setups in different geographical locations. Here, we validate the reproducibility and environmental quality of the system by comparing chemical and biological parameters recorded in our ELSS with those prevalent in the natural environment. Water, sediment microbial community and ragworm (the polychaete Hediste diversicolor) samples were obtained from four microcosms after 57days of operation. In general, average concentrations of dissolved inorganic nutrients (NO3 (-) ; NH4 (+) and PO4 (-3) ) in the water column of the ELSS experimental control units were within the range of concentrations recorded in the natural environment. While some shifts in bacterial community composition were observed between in situ and ELSS sediment samples, the relative abundance of most metabolically active bacterial taxa appeared to be stable. In addition, ELSS operation did not significantly affect survival, oxidative stress and neurological biomarkers of the model organism Hediste diversicolor. The validation data indicate that this system can be used to assess independent or interactive effects of climate change and environmental contamination on benthic communities. Researchers will be able to simulate the effects of these stressors on processes driven by microbial communities, sediment and seawater chemistry and to evaluate potential consequences to sediment toxicity using model organisms such as Hediste diversicolor.

Quantification of the 16S-23S rRNA internal transcribed spacers of Burkholderia xenovorans strain LB400 using real-time PCR in soil samples

This study establishes a new real-time PCR assay (using SYBR Green™ detection) for the identification and the direct quantification of specific individual Burkholderia xenovorans strain LB400 from DNA samples of soil and sediment. Specific primers were designed to amplify a 190-bp fragment of the 16S-23S rRNA internal transcribed spacers (ITS) from LB400. The specificity of primers was evaluated using 21 strains. The detection limit of the real-time PCR was analysed on soil samples inoculated with LB400 and was of 6 copies (10(5) CFUg(-1) of dry sample). The 16S-23S rRNA ITS primers developed in this work for rapid quantification of LB400 were validated. The assay allowed the quantification of LB400 as pure strain and among the indigenous microbial community in samples of soil and sediment (105-day experiment).

Comparison of the catabolic activity and catabolic profiles of rhizospheric, gravel-associated and interstitial microbial communities in treatment wetlands

Microbial communities play a critical role in degrading organic contaminants in treatment wetlands; however, an understanding of the different roles played by rhizospheric, gravel-associated and interstitial microbial communities is deficient due to a lack of data directly comparing these microbial communities. Community level physiological profiling (CLPP) was used to compare the catabolic capabilities of rhizospheric, gravel-associated and interstitial microbial communities in vertical-flow planted and unplanted wetland mesocosms. Wetland mesocosms were decommissioned to gather microbial community samples associated with the roots and gravel bed media taken from the top (10 cm depth), middle (30 cm depth) and bottom (60 cm depth). The catabolic capabilities of the rhizospheric microbial communities were seen to be much greater than those of the gravel-associated communities. A decrease in catabolic capability was seen with increasing depth, suggesting that communities near the surface play a larger role in the degradation of carbon-based compounds. A general difference in catabolic profiles based on plant presence/absence was observed for the interstitial water and all gravel-associated samples at all depths, suggesting that the presence of roots within part of the mesocosm not only has a localized effect on the attached microbial population, but also on gravel-associated microbial communities throughout the mesocosms.

Mangrove microbial diversity and the impact of trophic contamination

Mangroves are threatened ecosystems that provide numerous ecosystem services, especially through their wide biodiversity, and their bioremediation capacity is a challenging question in tropical areas. In a mangrove in Mayotte, we studied the potential role of microbial biofilm communities in removing nutrient loads from pre-treated wastewater. Microbial community samples were collected from tree roots, sediments, water, and from a colonization device, and their structure and dynamics were compared in two areas: one exposed to sewage and the other not. The samples from the colonization devices accurately reflected the natural communities in terms of diversity. Communities in the zone exposed to sewage were characterized by more green algae and diatoms, higher bacteria densities, as well as different compositions. In the area exposed to sewage, the higher cell densities associated with specific diversity patterns highlighted adapted communities that may play a significant role in the fate of nutrients.

Non-destructive sampling of rock-dwelling microbial communities using sterile adhesive tape

Building stone provides a habitat for an array of microorganisms, many of which have been demonstrated to have a deleterious effect on the appearance and/or structural integrity of stone masonry. It is essential to understand the composition and structure of stone-dwelling (lithobiontic) microbial communities if successful stone conservation strategies are to be applied, particularly in the face of global environmental change. Ideally, the techniques used to sample such assemblages should be non-destructive due to the sensitive conservation status of many stone buildings. This paper quantitatively assesses the performance of sterile adhesive tape as a non-destructive sampling technique and compares the results of tape sampling with an alternative, destructive, sampling method. We used DNA fingerprinting (TRFLP) to characterise the algal, fungal and bacterial communities living on a stone slab. Our results demonstrate that tape sampling may be used to collect viable quantities of microbial DNA from environmental samples. This technique is ideally suited to the sampling of microbial biofilms, particularly when these communities are dominated by green algae. It provides a good approximation of total community diversity (i.e. the aggregate diversity of epilithic and endolithic communities). Tape sampling is straightforward, rapid and cost effective. When combined with molecular analytical techniques, this sampling method has the potential to make a major contribution to efforts to understand the structure of lithobiontic microbial communities and our ability to predict the response of such communities to future environmental change.

Impact Assessment of Pumping Parameters on Groundwater Bacterial Communities

Groundwater microbial community samples are traditionally collected using pumping techniques optimized for groundwater chemistry assessment, although the impact of groundwater pumping parameters on apparent bacterial community structures (BCSs) is not really known. We therefore studied the impact of pumping lift, flow regime, and tubing material on BCS, which were analyzed by terminal‐restriction fragment length polymorphism (T‐RFLP). Ruzicka dissimilarity coefficients were calculated between T‐RFLP profiles to assess disparities between BCS. Variations in pumping lift, flow regime, and tubing material did not affect the apparent BCS in experiments using a homogenous water system under laboratory conditions showing that the conditions within the tube had no detectable effect on BCS. However, pumping groundwater from aquifer monitoring wells at different flow rates in the field revealed a significant impact on the apparent BCS. Water samples collected from fine sediment were the most affected by the pumping flow rate.

A biomolecular isolation framework for eco-systems biology

Mixed microbial communities are complex, dynamic and heterogeneous. It is therefore essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single samples to facilitate meaningful data integration, analysis and modeling. We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin columns. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and biomedical research interest. The developed methodological framework lays the foundation for standardized molecular eco-systematic studies on a range of different microbial communities in the future.

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.