Modeling bacterial species abundance from small community surveys

Soil contamination with antibiotics in a typical peri-urban area in eastern China: Seasonal variation, risk assessment, and microbial responses

The prevalence and persistence of antibiotics in soils has become an emerging environmental issue and an increasing threat to soil security and global public health. The problem is more severe in areas undergoing rapid urbanization; however, the ecological risks of antibiotics, seasonal variability, and associated soil microbial responses in peri-urban soils have not been well-explored. The seasonal soil sampling campaigns were conducted in a typical peri-urban watershed in eastern China to investigate distribution of antibiotics. The results demonstrated higher mean concentrations of most antibiotic compounds in winter than in summer in peri-urban soils. The seasonal variations of norfloxacin, enrofloxacin, and ciprofloxacin were more significant than those of other antibiotics, due to their higher migration ability and bioavailability. An ecological risk assessment demonstrated that chlortetracycline, ciprofloxacin, doxycycline, and ofloxacin can pose high risks to soil microorganisms. Furthermore, the coexistence of multiple antibiotics obviously poses higher risks than individual compounds. A redundancy analysis demonstrated that tetracyclines mainly showed negative correlations with Firmicutes and Chloroflexi, and quinolones showed obviously negative correlations with Acidobacteria, Gemmatimonadetes, and Nitrospirae, suggesting potential inhibition from antibiotics on biological activities or biodegradation processes. However, the persistence of antibiotics in soil results in a significant decrease in bacterial diversity and a change in dominant species. Our results provide an overview of the seasonal variability of antibiotics and the associated effects on bacterial communities in peri-urban soils. The results can provide scientific guidance on decreasing soil contamination with antibiotics to enhance soil security in similar areas.

A new framework to accurately quantify soil bacterial community diversity from DGGE

Denaturing gradient gel electrophoresis (DGGE) has been and remains extensively used to assess and monitor the effects of various treatments on soil bacterial communities. Considering only abundant phylotypes, the diversity estimates produced by this technique have been proven to be uncorrelated to true community diversity. The aim of this paper was to develop a framework to estimate a community's true diversity from DGGE. Developed using in silico DGGE profiles generated from published pyrosequencing datasets, this framework elongates the rank-abundance distributions (RADs) drawn by band quantification using the peak-to-signal ratio (PSR) parameter, which was proven to be related to bacterial richness. The ability to compare DGGE-based diversity estimates to the true diversity of communities led to a unique opportunity to identify potential pitfalls when analyzing DGGE gels with commercial analysis software programs and gain insight into the process of DNA band clustering in the profiles. Bacterial diversity was compared through richness, Shannon, and Simpson's 1/D indices. Intermediate results demonstrated that, even though commercial gel analysis software programs were unable to produce consistent results throughout all samples, a newly developed Matlab-based framework unraveled the dominance profiles of communities from band quantification. Elongating these partial RADs using the PSRs extracted from the DGGE profiles chiefly made it possible to accurately estimate the true diversity of communities. For all the samples analyzed, the estimated Shannon and Simpson's 1/D were accurate at ±10 %. Richness estimations were less accurate, ranging from -11 to 31 % of the expected values. The framework showed great potential to study the structure and diversity of soil bacterial communities.

Horizon-specific bacterial community composition of German grassland soils, as revealed by pyrosequencing-based analysis of 16S rRNA genes

The diversity of bacteria in soil is enormous, and soil bacterial communities can vary greatly in structure. Here, we employed a pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to characterize the overall and horizon-specific (A and B horizons) bacterial community compositions in nine grassland soils, which covered three different land use types. The entire data set comprised 752,838 sequences, 600,544 of which could be classified below the domain level. The average number of sequences per horizon was 41,824. The dominant taxonomic groups present in all samples and horizons were the Acidobacteria, Betaproteobacteria, Actinobacteria, Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Chloroflexi, Firmicutes, and Bacteroidetes. Despite these overarching dominant taxa, the abundance, diversity, and composition of bacterial communities were horizon specific. In almost all cases, the estimated bacterial diversity (H') was higher in the A horizons than in the corresponding B horizons. In addition, the H' was positively correlated with the organic carbon content, the total nitrogen content, and the C-to-N ratio, which decreased with soil depth. It appeared that lower land use intensity results in higher bacterial diversity. The majority of sequences affiliated with the Actinobacteria, Bacteroidetes, Cyanobacteria, Fibrobacteres, Firmicutes, Spirochaetes, Verrucomicrobia, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria were derived from A horizons, whereas the majority of the sequences related to Acidobacteria, Chloroflexi, Gemmatimonadetes, Nitrospira, TM7, and WS3 originated from B horizons. The distribution of some bacterial phylogenetic groups and subgroups in the different horizons correlated with soil properties such as organic carbon content, total nitrogen content, or microbial biomass.

Assessment of phylogenetic diversity of bacterial microflora in drinking water using serial analysis of ribosomal sequence tags

We examined chlorinated drinking water samples from three different surface water treatment plants for bacterial 16S rDNA diversity using the serial analysis of V6 ribosomal sequence tag (SARST-V6) method. A considerable degree of diversity was observed in each sample, with an estimated richness ranging from 173 to 333 phylotypes. The community structure shows that there are differences in bacterial evenness between sampled sites. The taxonomic composition of the microbial communities was found to be dominated by members of the Proteobacteria (57.2-77.4%), broadly distributed among the classes Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Deltaproteobacteria. Additionally, a large proportion of sequences (6.3-36.5%) were found to be distantly related to database sequences of unknown phylogenetic affiliation. Given the apparent significance of this bacterial group in drinking water, a 16S rDNA analysis was performed and confirmed their presence and phylogeny. Notwithstanding the potential under-representation of certain bacterial phyla using the SARST-V6 primer pairs, as revealed by a refined computer algorithm, our results suggest that 16S rDNA corresponding to a variety of eubacterial groups can be detected in finished drinking water, suggesting that this water may contain a higher level of bacterial diversity than previously observed.

Extensive phylogenetic analysis of a soil bacterial community illustrates extreme taxon evenness and the effects of amplicon length, degree of coverage, and DNA fractionation on classification and ecological parameters

To thoroughly investigate the bacterial community diversity present in a single composite sample from an agricultural soil and to examine potential biases resulting from data acquisition and analytical approaches, we examined the effects of percent G+C DNA fractionation, sequence length, and degree of coverage of bacterial diversity on several commonly used ecological parameters (species estimation, diversity indices, and evenness). We also examined variation in phylogenetic placement based on multiple commonly used approaches (ARB alignments and multiple RDP tools). The results demonstrate that this soil bacterial community is highly diverse, with 1,714 operational taxonomic units demonstrated and 3,555 estimated (based on the Chao1 richness estimation) at 97% sequence similarity using the 16S rRNA gene. The results also demonstrate a fundamental lack of dominance (i.e., a high degree of evenness), with 82% of phylotypes being encountered three times or less. The data also indicate that generally accepted cutoff values for phylum-level taxonomic classification might not be as applicable or as general as previously assumed and that such values likely vary between prokaryotic phyla or groups.

Evidence from GC-TRFLP that bacterial communities in soil are lognormally distributed

The Species Abundance Distribution (SAD) is a fundamental property of ecological communities and the form and formation of SADs have been examined for a wide range of communities including those of microorganisms. Progress in understanding microbial SADs, however, has been limited by the remarkable diversity and vast size of microbial communities. As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD. We have used a novel approach to characterize the SAD of bacterial communities by coupling genomic DNA fractionation with analysis of terminal restriction fragment length polymorphisms (GC-TRFLP). Examination of a soil microbial community through GC-TRFLP revealed 731 bacterial operational taxonomic units (OTUs) that followed a lognormal distribution. To recover the same 731 OTUs through analysis of DNA sequence data is estimated to require analysis of 86,264 16S rRNA sequences. The approach is examined and validated through construction and analysis of simulated microbial communities in silico. Additional simulations performed to assess the potential effects of PCR bias show that biased amplification can cause a community whose distribution follows a power-law function to appear lognormally distributed. We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models. Our analysis supports use of the lognormal as the null distribution for studying the SAD of bacterial communities as for plant and animal communities.

Endolithic Microbial Ecosystems

The endolithic environment, the pore space in rocks, is a ubiquitous microbial habitat and an interface between biology and geology. Photosynthesis-based endolithic communities inhabit the outer centimeters of rocks exposed to the surface, and offer model systems for microbial ecology, geobiology, and astrobiology. Endolithic ecosystems are among the simplest microbial ecosystems known and as such provide tractable models for testing ecological hypotheses. Such hypotheses have been difficult to test because microbial ecosystems are extraordinarily diverse. We review here recent culture-independent, ribosomal RNA-based studies that evaluate hypotheses about endolithic ecosystems, and provide insight for understanding general principles in microbial ecology. Comparison of endolithic communities supports the principle that patterns of microbial diversity are governed by similar principles observed in macroecological systems. Recent results also explore geobiological processes that shape the current biosphere and potentially provide clues to life's history on Earth and where to seek life elsewhere in the Solar System.

Serial analysis of rRNA genes and the unexpected dominance of rare members of microbial communities

The accurate description of a microbial community is an important first step in understanding the roles of its components in ecosystem function. A method for surveying microbial communities termed serial analysis of rRNA genes (SARD) is described here. Through a series of molecular cloning steps, short DNA sequence tags are recovered from the fifth variable (V5) region of the prokaryotic 16S rRNA genes from microbial communities. These tags are ligated to form concatemers comprised of 20 to 40 tags which are cloned and identified by DNA sequencing. Four agricultural soil samples were profiled with SARD to assess the method's utility. A total of 37,008 SARD tags comprising 3,127 unique sequences were identified. A comparison of duplicate profiles from one soil genomic DNA preparation revealed that the method was highly reproducible. The large numbers of singleton tags, together with nonparametric richness estimates, indicated that a significant amount of sequence tag diversity remained undetected with this level of sampling. The abundance classes of the observed tags were scale-free and conformed to a power law distribution. Numerically, the majority of the total tags observed belonged to abundance classes that were each present at less than 1% of the community. Over 99% of the unique tags individually made up less than 1% of the community. Therefore, from either a numerical or diversity standpoint, taxa with low abundance comprised a significant proportion of the microbial communities examined and could potentially make a large contribution to ecosystem function. SARD may provide a means to explore the ecological roles of these rare members of microbial communities in qualitative and quantitative terms.

What is the extent of prokaryotic diversity?

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term 'diversity' may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in 'real life'. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet.

Phylogenetic comparisons of bacterial communities from serpentine and nonserpentine soils

I present the results of a culture-independent survey of soil bacterial communities from serpentine soils and adjacent nonserpentine comparator soils using a variety of newly developed phylogenetically based statistical tools. The study design included site-based replication of the serpentine-to-nonserpentine community comparison over a regional scale ( approximately 100 km) in Northern California and Southern Oregon by producing 16S rRNA clone libraries from pairs of samples taken on either side of the serepentine-nonserpentine edaphic boundary at three geographical sites. At the division level, the serpentine and nonserpentine communities were similar to each other and to previous data from forest soils. Comparisons of both richness and Shannon diversity produced no significant differences between any of the libraries, but the vast majority of phylogenetically based tests were significant, even with only 50 sequences per library. These results suggest that most samples were distinct, consisting of a collection of lineages generally not found in other samples. The pattern of results showed that serpentine communities tended to be more similar to each other than they were to nonserpentine communities, and these differences were at a lower taxonomic scale. Comparisons of two nonserpentine communities generally showed differences, and some results suggest that the geographical site may control community composition as well. These results show the power of phylogenetic tests to discern differences between 16S rRNA libraries compared to tests that discard DNA data to bin sequences into operational taxonomic units, and they stress the importance of replication at larger scales for inferences regarding microbial biogeography.

Diversity of Planctomycetes in soil in relation to soil history and environmental heterogeneity

Members of the Planctomycetes, which were once thought to occur primarily in aquatic environments, have been discovered in soils on five continents, revealing that these Bacteria are a widespread and numerically abundant component of microbial communities in soil. We examined the diversity of Planctomycetes in soil samples obtained from experimental plots at an agricultural site in order to assess the extent of Planctomycetes diversity in soil, to determine whether management effects such as past land cover and compost addition affected the composition of the Planctomycetes community, and to determine whether the observations made could provide insight into the ecological distribution of these organisms. Analysis of Planctomycetes 16S rRNA gene sequences revealed a total of 312 +/- 35 unique phylotypes in the soil at the site examined. The majority of these Planctomycetes sequences were unique, and the sequences had phylogenetic affiliations that included all major lineages in the Planctomycetaceae, as well as several novel groups of deeply divergent Planctomycetes. Both soil management history and compost amendment had significant effects on the Planctomycetes diversity, and variations in soil organic matter, Ca2+ content, and pH were associated with variations in the Planctomycetes community composition. In addition, Planctomycetes richness increased in proportion to the area sampled and was correlated with the spatial heterogeneity of nitrate, which was associated with the soil management history at the orchard site examined. This report provides the first systematic assessment of the diversity of Planctomycetes in soil and also provides evidence that the diversity of this group increases with area as defined by the general power law description of the taxon-area relationship.

Denaturing gradient electrophoresis (DGE) and single-strand conformation polymorphism (SSCP) molecular fingerprintings revisited by simulation and used as a tool to measure microbial diversity

The exact extent of microbial diversity remains unknowable. Nevertheless, fingerprinting patterns [denaturing gradient electrophoresis (DGE), single-strand conformation polymorphism (SSCP)] provide an image of a microbial ecosystem and contain diversity data. We generated numerical simulation fingerprinting patterns based on three types of distribution (uniform, geometric and lognormal) with a range of units from 10 to 500,000. First, simulated patterns containing a diversity of around 1000 units or more gave patterns similar to those obtained in experiments. Second, the number of bands or peaks saturated quickly to about 35 and were unrelated to the degree of diversity. Finally, assuming lognormal distribution, we used an estimator of diversity on in silico and experimental fingerprinting patterns. Results on in silico patterns corresponded to the simulation inputs. Diversity results in experimental patterns were in the same range as those obtained from the same DNA sample in molecular inventories. Thus, fingerprinting patterns contain extractable data about diversity although not on the basis of a number of bands or peaks, as is generally assumed to be the case.

Only a few fungal species dominate highly diverse mycofloras associated with the common reed

Plants are naturally colonized by many fungal species that produce effects ranging from beneficial to pathogenic. However, how many of these fungi are linked with a single host plant has not been determined. Furthermore, the composition of plant-associated fungal communities has not been rigorously determined. We investigated these essential issues by employing the perennial wetland reed Phragmites australis as a model. DNA extracted from roots, rhizomes, stems, and leaves was used for amplification and cloning of internal transcribed spacer rRNA gene fragments originating from reed-associated fungi. A total of 1,991 clones from 15 clone libraries were differentiated by restriction fragment length polymorphism analyses into 345 operational taxonomical units (OTUs). Nonparametric estimators for total richness (Chao1 and ACE) and also a parametric log normal model predicted a total of about 750 OTUs if the libraries were infinite. Sixty-two percent of the OTUs sequenced were novel at a threshold of 3%. Several of these OTUs represented undocumented fungal species, which also included higher taxonomic levels. In spite of the high diversity of the OTUs, the mycofloras of vegetative organs were dominated by just a few typical fungi, which suggested that competition and niche differentiation influence the composition of plant-associated fungal communities. This suggestion was independently supported by the results of nested PCR assays specifically monitoring two OTUs over 3 years, which revealed significant preferences for host habitat and host organ.

Estimating bacterial diversity from clone libraries with flat rank abundance distributions

There are a number of parametric and non-parametric methods for estimating diversity. However all such methods employ either the proportional abundance of the most abundant taxon in a sample or require that a specific taxon is sampled more than once. Consequently, the available methods for estimating diversity cannot be applied to samples consisting entirely of singletons, which might be characteristic of some hyperdiverse communities. Here we present a non-parametric method that estimates the probability that a given number of unique taxa would be sampled from a community with a particular diversity. We have applied this approach to a well known data set of 100 unique clones from a sample of Amazonian soil (Borneman and Triplett (1997) Appl Environ Microbiol 63: 2647-2653) and determine the probability that this observation would be made from an environment of a given diversity. On this basis we can state this observation would be very unlikely (P = 0.006) if the soil diversity was less than 10(3), and quite unlikely (P = 0.6) if the diversity was less than 10(4), and probable (P = 0.95) if the diversity was about 10(5). There are essentially no contestable assumptions in our method. Thus we are able to offer almost unequivocal evidence that the bacterial diversity, of at least soils, is very large and a method that may be used to interpret samples consisting entirely of singletons from other hyperdiverse communities.