Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities.

An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.     

Serial analysis of ribosomal sequence tags (SARST): a high-throughput method for profiling complex microbial communities

Two decades of culture-independent studies have confirmed that microbial communities represent the most complex and concentrated pool of phylogenetic diversity on the planet. There remains a need for innovative molecular tools that can further our knowledge of microbial diversity and its functional implications. We present the method and application of serial analysis of ribosomal sequence tags (SARST) as a novel tool for elucidating complex microbial communities, such as those found in soils and sediments. Serial analysis of ribosomal sequence tags uses a series of enzymatic reactions to amplify and ligate ribosomal sequence tags (RSTs) from bacterial small subunit rRNA gene (SSU rDNA) V1-regions into concatemers that are cloned and sequenced. This approach offers a significant increase in throughput over traditional SSU rDNA clone libraries, as up to 20 RSTs are obtained from each sequencing reaction. To test SARST and measure the bias associated with this approach, RST libraries were prepared from a defined mixture of pure cultures and from duplicate arctic soil DNA samples. The actual RST distribution reflected the theoretical composition of the original defined mixture. Data from duplicate soil libraries (1345 and 1217 RSTs, with 525 and 505 unique RSTs, respectively) indicated that replication provides a strongly correlated RST profile (r(2) = 0.80) and division-level distribution of RSTs (r(2) = 0.99). Using sequence data from abundant soil RSTs, we designed specific primers that successfully amplified a larger portion of the SSU rDNA for further phylogenetic analysis. These results suggest that SARST is a powerful approach for reproducible high-throughput profiling of microbial diversity amenable to medical, industrial or environmental microbiology applications.     

Metabolic profiling as a means of characterizing plant-associated microbial communities

Abstract Microbial communities from leaf and root habitats associated with sugar beet ( Beta vulgaris ) were characterized according to their capacity to metabolize a range of 95 sole carbon sources available in a commercial assay, GN-BIOLOG MicroPlates. Metabolic profiling was assessed as a method for evaluating perturbation of microbial communities of glasshouse-grown sugar beet inoculated with a genetically modified microorganism. This technique has allowed microbial communities, colonising the immature leaves of treated and untreated plants to be differentiated, although no differences were observed when plants inoculated with genetically modified microorganisms and unmodified inoculated plants were compared. As plants developed and differentiated, the carbon utilization patterns observed allowed communities to be grouped according to the habitat from which they were isolated, irrespective of treatment. These studies demonstrate that the genetically modified microorganism, introduced as a seed dressing colonised developing immature tissue throughout the 231-day study but did not disrupt the natural succession of microbial communities in glasshouse-grown sugar beet plants.     

A(r)Ray of hope in analysis of the function and diversity of microbial communities

The vast majority of microorganisms in the environment remain uncultured, and their existence is known only from sequences retrieved by PCR. As a consequence, our understanding of the ecological function of dominant microbial populations in the environment is limited. We will review microbial diversity studies and show that these may have moved from an extreme underestimation to a potentially severe overestimation of diversity. The latter results from a simple PCR-generated artifact: the cloning of heteroduplex molecules followed by Escherichia coli mismatch repair, which may generate an exponential increase in observed sequence diversity. However, simple modifications to current PCR amplification protocols minimize such artifactual sequences and may bring within our reach estimation of bacterial diversity in environmental samples. Such estimates may spur new culture-independent approaches based on genomic and microarray technology, allowing correlation of phylogenetic identity with the ecological function of unculturable organisms. In particular, we are developing a DNA microarray that enables identification of individual populations active in utilization of specific organic substrates. The array consists of 16S and 23S rDNA-targeted oligonucleotides and is hybridized to RNA extracted from samples incubated with (14)C-labeled organic substrates. Populations that metabolize the substrate can be identified by the radiolabel incorporated in their rRNA after only one to two cell doublings, ensuring realistic preservation of community structure. Thus, the microarray approach may provide a powerful means to link microbial community structure with in situ function of individual populations.     

Phylogeny-guided (meta)genome mining approach for the targeted discovery of new microbial natural products

Genomics-based methods are now commonplace in natural products research. A phylogeny-guided mining approach provides a means to quickly screen a large number of microbial genomes or metagenomes in search of new biosynthetic gene clusters of interest. In this approach, biosynthetic genes serve as molecular markers, and phylogenetic trees built with known and unknown marker gene sequences are used to quickly prioritize biosynthetic gene clusters for their metabolites characterization. An increase in the use of this approach has been observed for the last couple of years along with the emergence of low cost sequencing technologies. The aim of this review is to discuss the basic concept of a phylogeny-guided mining approach, and also to provide examples in which this approach was successfully applied to discover new natural products from microbial genomes and metagenomes. I believe that the phylogeny-guided mining approach will continue to play an important role in genomics-based natural products research.     

Considering external information to improve the phylogenetic comparison of microbial communities: a new approach based on constrained Double Principal Coordinates Analysis (cDPCoA)

The use of next‐generation sequencing technologies is revolutionizing microbial ecology by allowing a deep phylogenetic coverage of tens to thousands of samples simultaneously. Double Principal Coordinates Analysis (DPCoA) is a multivariate method, developed in community ecology, able to integrate a distance matrix describing differences among species (e.g. phylogenetic distances) in the analysis of a species abundance matrix. This ordination technique has been used recently to describe microbial communities taking into account phylogenetic relatedness. In this work, we extend DPCoA to integrate the information of external variables measured on communities. The constrained Double Principal Coordinates Analysis (cDPCoA) is able to enforce a priori classifications to retrieve subtle differences and (or) remove the effect of confounding factors. We describe the main principles of this new approach and demonstrate its usefulness by providing application examples based on published 16S rRNA gene data sets.     

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.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Biotypic diversity in greenbug (Hemiptera: Aphididae): characterizing new virulence and host associations

Biotypic diversity of the greenbug, Schizaphis graminum (Rondani) (Hemiptera: Aphididae), was assessed among populations collected from cultivated wheat, Triticum aestivum L., and sorghum, Sorghum bicolor (L.) Moench, and their associated noncultivated grass hosts. Greenbugs were collected during May through August 2002 from 30 counties of Kansas, Nebraska, Oklahoma, and Texas. Discounting the presumptive biotype A, five of the remaining nine letter-designated greenbug biotypes were collected; however, biotypes C, F, J, and K were not detected. Biotypes E and I exhibited the greatest host range and were the only biotypes collected in all four states. Sixteen greenbug clones, collected from eight plant species, exhibited unique biotype profiles. Eleven were collected from noncultivated grasses, three from wheat, and two from sorghum. The most virulent biotypes were collected from noncultivated hosts. The great degree of biotypic diversity among noncultivated grasses supports the contention that the greenbug species complex is composed of host-adapted races that diverged on grass species independently of, and well before, the advent of modern agriculture.     

Nested PCR-denaturing gradient gel electrophoresis approach to determine the diversity of sulfate-reducing bacteria in complex microbial communities

Here, we describe a three-step nested-PCR-denaturing gradient gel electrophoresis (DGGE) strategy to detect sulfate-reducing bacteria (SRB) in complex microbial communities from industrial bioreactors. In the first step, the nearly complete 16S rRNA gene was amplified using bacterial primers. Subsequently, this product was used as a template in a second PCR with group-specific SRB primers. A third round of amplification was conducted to obtain fragments suitable for DGGE. The largest number of bands was observed in DGGE patterns of products obtained with primers specific for the Desulfovibrio-Desulfomicrobium group, indicating a large diversity of these SRBs. In addition, members of other phylogenetic SRB groups, i.e., Desulfotomaculum, Desulfobulbus, and Desulfococcus-Desulfonema-Desulfosarcina, were detected. Bands corresponding to Desulfobacterium and Desulfobacter were not detected in the bioreactor samples. Comparative sequence analysis of excised DGGE bands revealed the identity of the community members. The developed three-step PCR-DGGE strategy is a welcome tool for studying the diversity of sulfate-reducing bacteria.     

Novel approach using substrate-mediated radiolabelling of RNA to link metabolic function with the structure of microbial communities

A novel concept was developed applying radioisotope-labelled substrate incorporation into the biomass. The resulting radiolabelled RNA was used both as an indicator of activity and as a template for gaining structural and functional information about a substrate-utilizing microbial community. Sequences of PCR products are separated via cloning or using molecular fingerprinting techniques. Nucleic acids from predominant clones or the whole molecular fingerprinting pattern are transferred to a membrane and hybridized with the radiolabelled sample RNA. Scanning of the hybridized blots for radioactivity indicates the members involved in the utilization of the substrate. This novel 'random walk' approach using radioisotope probing was evaluated in a model community experiment.     

Microbial phylogeny and diversity: Small subunit ribosomal RNA sequence analysis and beyond

Small subunit ribosomal RNA (16S rRNA) gene sequence analysis is used for the identification and classification of prokaryotes. In addition, sequencing of 16S rRNA genes amplified directly from the environment is used to estimate microbial diversity. The presence of mosaicism, intra-genomic heterogeneity and the lack of a universal threshold sequence identity value limit 16S rRNA-based phylogenetic analysis. PCR-amplification bias and cloning bias can also result in an inaccurate representation of the microbial diversity. In this review, recently reported complexities of 16S rRNA gene sequence analyses and the requirement of additional tools for microbial phylogeny and diversity analyses are discussed.     

Cyanobacterial diversity in natural and artificial microbial mats of Lake Fryxell (McMurdo Dry Valleys,Antarctica): a morphological and molecular approach

Currently, there is no consensus concerning the geographic distribution and extent of endemism in Antarctic cyanobacteria. In this paper we describe the phenotypic and genotypic diversity of cyanobacteria in a field microbial mat sample from Lake Fryxell and in an artificial cold-adapted sample cultured in a benthic gradient chamber (BGC) by using an inoculum from the same mat. Light microscopy and molecular tools, including 16S rRNA gene clone libraries, denaturing gradient gel electrophoresis, and sequencing, were used. For the first time in the study of cyanobacterial diversity of environmental samples, internal transcribed spacer (ITS) sequences were retrieved and analyzed to complement the information obtained from the 16S rRNA gene. Microscopy allowed eight morphotypes to be identified, only one of which is likely to be an Antarctic endemic morphotype. Molecular analysis, however, revealed an entirely different pattern. A much higher number of phylotypes (15 phylotypes) was found, but no sequences from Nodularia and Hydrocoryne, as observed by microscopy, were retrieved. The 16S rRNA gene sequences determined in this study were distributed in 11 phylogenetic lineages, 3 of which were exclusively Antarctic and 2 of which were novel. Collectively, these Antarctic sequences together with all the other polar sequences were distributed in 22 lineages, 9 of which were exclusively Antarctic, including the 2 novel lineages observed in this study. The cultured BGC mat had lower diversity than the field mat. However, the two samples shared three morphotypes and three phylotypes. Moreover, the BGC mat allowed enrichment of one additional phylotype. ITS sequence analysis revealed a complex signal that was difficult to interpret. Finally, this study provided evidence of molecular diversity of cyanobacteria in Antarctica that is much greater than the diversity currently known based on traditional microscopic analysis. Furthermore, Antarctic endemic species were more abundant than was estimated on the basis of morphological features. Decisive arguments concerning the global geographic distribution of cyanobacteria should therefore incorporate data obtained with the molecular tools described here.     

The use of gene probes in the rapid analysis of natural microbial communities

Summary Hybridization probes produced from DNA sequences have proven to be a powerful tool in the rapid and sensitive analysis of natural microbial communities. By using function-specific probes, such as those identifying genes coding for photosynthesis, the potential a microbial community has for performing a given function may be rapidly determined. Gene probes have also been used in the identification and isolation of a specific catabolic genotype in less than one-fourth the time required for the conventional culture enrichment technique. Species-specific probes constructed from portions of genes coding for ribosomal RNA have been used for the rapid identification and enumeration of bacterial species in environmental samples. The use of reassociation kinetics as a measure of community diversity and complexity is also discussed. The successful application of this technique to community analysis may reduce the time required from 1 year, for conventional analysis, to 2 weeks.     

Changes in coral microbial communities in response to a natural pH gradient

Surface seawater pH is currently 0.1 units lower than pre-industrial values and is projected to decrease by up to 0.4 units by the end of the century. This acidification has the potential to cause significant perturbations to the physiology of ocean organisms, particularly those such as corals that build their skeletons/shells from calcium carbonate. Reduced ocean pH could also have an impact on the coral microbial community, and thus may affect coral physiology and health. Most of the studies to date have examined the impact of ocean acidification on corals and/or associated microbiota under controlled laboratory conditions. Here we report the first study that examines the changes in coral microbial communities in response to a natural pH gradient (mean pH_T 7.3–8.1) caused by volcanic CO₂ vents off Ischia, Gulf of Naples, Italy. Two Mediterranean coral species, Balanophyllia europaea and Cladocora caespitosa, were examined. The microbial community diversity and the physiological parameters of the endosymbiotic dinoflagellates (Symbiodinium spp.) were monitored. We found that pH did not have a significant impact on the composition of associated microbial communities in both coral species. In contrast to some earlier studies, we found that corals present at the lower pH sites exhibited only minor physiological changes and no microbial pathogens were detected. Together, these results provide new insights into the impact of ocean acidification on the coral holobiont.