Introducing DOTUR, a Computer Program for Defining Operational Taxonomic Units and Estimating Species Richness

Although copious qualitative information describes the members of the diverse microbial communities on Earth, statistical approaches for quantifying and comparing the numbers and compositions of lineages in communities are lacking. We present a method that addresses the challenge of assigning sequences to operational taxonomic units (OTUs) based on the genetic distances between sequences. We developed a computer program, DOTUR, which assigns sequences to OTUs by using either the furthest, average, or nearest neighbor algorithm for each distance level. DOTUR uses the frequency at which each OTU is observed to construct rarefaction and collector's curves for various measures of richness and diversity. We analyzed 16S rRNA gene libraries derived from Scottish and Amazonian soils and the Sargasso Sea with DOTUR, which assigned sequences to OTUs rapidly and reliably based on the genetic distances between sequences and identified previous inconsistencies and errors in assigning sequences to OTUs. An analysis of the two 16S rRNA gene libraries from soil demonstrated that they do not contain enough sequences to support a claim that they contain different numbers of bacterial lineages with statistical confidence (P > 0.05), nor do they contain enough sequences to provide a robust estimate of species richness when an OTU is defined as containing sequences that are no more than 3% different from each other. In contrast, the richness of OTUs at the 3% level in the Sargasso Sea collection began to plateau after the sampling of 690 sequences. We anticipate that an equivalent extent of sampling for soil would require sampling more than 10,000 sequences, almost 100 times the size of typical sequence collections obtained from soil.     

Toward a census of bacteria in soil

For more than a century, microbiologists have sought to determine the species richness of bacteria in soil, but the extreme complexity and unknown structure of soil microbial communities have obscured the answer. We developed a statistical model that makes the problem of estimating richness statistically accessible by evaluating the characteristics of samples drawn from simulated communities with parametric community distributions. We identified simulated communities with rank-abundance distributions that followed a truncated lognormal distribution whose samples resembled the structure of 16S rRNA gene sequence collections made using Alaskan and Minnesotan soils. The simulated communities constructed based on the distribution of 16S rRNA gene sequences sampled from the Alaskan and Minnesotan soils had a richness of 5,000 and 2,000 operational taxonomic units (OTUs), respectively, where an OTU represents a collection of sequences not more than 3% distant from each other. To sample each of these OTUs in the Alaskan 16S rRNA gene library at least twice, 480,000 sequences would be required; however, to estimate the richness of the simulated communities using nonparametric richness estimators would require only 18,000 sequences. Quantifying the richness of complex environments such as soil is an important step in building an ecological framework. We have shown that generating sufficient sequence data to do so requires less sequencing effort than completely sequencing a bacterial genome.     

Comparison of bacterial communities in the Solimões and Negro River tributaries of the Amazon River based on small subunit rRNA gene sequences

The microbiota of the Amazon River basin has been little studied. We compared the structure of bacterial communities of the Solim?es and Negro Rivers, the main Amazon River tributaries, based on analysis of 16S rRNA gene sequences. Water was sampled with a 3-L Van Dorn collection bottle; samples were collected at nine different points/depths totaling 27 L of water from each river. Total DNA was extracted from biomass retained by a 0.22-μm filter after sequential filtration of the water through 0.8- and 0.22-μm filters. The 16S rRNA gene was amplified by PCR, cloned and sequenced, and the sequences were analyzed with the PHYLIP and DOTUR programs to obtain the operational taxonomic units (OTUs) and to calculate the diversity and richness indices using the SPADE program. Taxonomic affiliation was determined using the naive Bayesian rRNA Classifier of the RDP II (Ribosomal Database Project). We recovered 158 sequences from the Solim?es River grouped into 103 OTUs, and 197 sequences from the Negro River library grouped into 90 OTUs by the DOTUR program. The Solim?es River was found to have a greater diversity of bacterial genera, and greater estimated richness of 446 OTUs, compared with 242 OTUs from the Negro River, as calculated by ACE estimator. The Negro River has less bacterial diversity, but more 16S rRNA gene sequences belonging to the bacterial genus Polynucleobacter were detected; 56 sequences from this genus were found (about 30% of the total sequences). We suggest that a more in-depth investigation be made to elucidate the role played by these bacteria in the river environment. These differences in bacterial diversity between Solim?es and Negro Rivers could be explained by differences in organic matter content and pH of the rivers.     

Divergence thresholds and divergent biodiversity estimates: can metabarcoding reliably describe zooplankton communities?

DNA metabarcoding is a promising method for describing communities and estimating biodiversity. This approach uses high‐throughput sequencing of targeted markers to identify species in a complex sample. By convention, sequences are clustered at a predefined sequence divergence threshold (often 3%) into operational taxonomic units (OTUs) that serve as a proxy for species. However, variable levels of interspecific marker variation across taxonomic groups make clustering sequences from a phylogenetically diverse dataset into OTUs at a uniform threshold problematic. In this study, we use mock zooplankton communities to evaluate the accuracy of species richness estimates when following conventional protocols to cluster hypervariable sequences of the V4 region of the small subunit ribosomal RNA gene (18S) into OTUs. By including individually tagged single specimens and “populations” of various species in our communities, we examine the impact of intra‐ and interspecific diversity on OTU clustering. Communities consisting of single individuals per species generated a correspondence of 59–84% between OTU number and species richness at a 3% divergence threshold. However, when multiple individuals per species were included, the correspondence between OTU number and species richness dropped to 31–63%. Our results suggest that intraspecific variation in this marker can often exceed 3%, such that a single species does not always correspond to one OTU. We advocate the need to apply group‐specific divergence thresholds when analyzing complex and taxonomically diverse communities, but also encourage the development of additional filtering steps that allow identification of artifactual rRNA gene sequences or pseudogenes that may generate spurious OTUs.     

利用小亚基核糖体RNA 技术分析温室黄瓜近根土壤古菌和真菌多样性

土壤古菌和真菌在温室生态系统是仅次于细菌的微生物,具有类似于细菌的重要生态功能。通过构建古菌16S rRNA和真菌18S rRNA基因克隆文库,分析温室黄瓜近根土壤古菌和真菌群落结构组成,为开发利用温室这一特殊的生态环境中丰富的微生物资源以及理解微生物与植物间的互作提供参考依据。采用研磨-冻融-溶菌酶-蛋白酶K-SDS热处理以及CTAB处理等理化方法,提取和纯化微生物总DNA,构建古菌16S rRNA和真菌18S rRNA基因克隆文库。利用DOTUR软件将古菌和真菌序列按照相似性97％的标准分成若干个可操作分类单元 (OTUs)。土壤古菌克隆文库主要包括泉古菌门和未分类的古菌两大类,并有少部分广域古菌类群,所有泉古菌均属于热变形菌纲,共45个OTUs;真菌克隆文库包括真菌门的大多数亚门真菌,共24个OTUs,未发现担子菌亚门真菌。古菌多样性比较丰富,且发现少量的广域古菌 (甲烷菌),这一情况可能与温室长期高温高湿,高有机质含量,土壤处于缺氧环境有关;土壤真菌的优势种群为子囊菌,占到土壤真菌的80％以上,这可能与绝大多数植物真菌性病害属于土传病害,通过菌丝体、菌核或子囊壳在土壤病残体中越冬有一定的关系。     

Global patterns of diversity and community structure in marine bacterioplankton

Because of their small size, great abundance and easy dispersal, it is often assumed that marine planktonic microorganisms have a ubiquitous distribution that prevents any structured assembly into local communities. To challenge this view, marine bacterioplankton communities from coastal waters at nine locations distributed world-wide were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes, used as operational taxonomic units (OTU). Our survey and analyses show that there were marked differences in the composition and richness of OTUs between locations. Remarkably, the global marine bacterioplankton community showed a high degree of endemism, and conversely included few cosmopolitan OTUs. Our data were consistent with a latitudinal gradient of OTU richness. We observed a positive relationship between the relative OTU abundances and their range of occupation, i.e. cosmopolitans had the largest population sizes. Although OTU richness differed among locations, the distributions of the major taxonomic groups represented in the communities were analogous, and all local communities were similarly structured and dominated by a few OTUs showing variable taxonomic affiliations. The observed patterns of OTU richness indicate that similar evolutionary and ecological processes structured the communities. We conclude that marine bacterioplankton share many of the biogeographical and macroecological features of macroscopic organisms. The general processes behind those patterns are likely to be comparable across taxa and major global biomes.     

Bacterial diversity at different depths in lead-zinc mine tailings as revealed by 16S rRNA gene libraries

Bacterial communities at 10 cm, 100 cm, and 200 cm depths in a 100-year-old lead-zinc tailing heap were evaluated by constructing 16S rRNA gene libraries. In total, 98 operational taxonomic units (OTUs) were identified from 193 clones at a 3% sequence difference level. The OTU number and species richness decreased with the depth. Species composition was significantly different between the three libraries. Fifty-seven percent of the examined clones were Acidobacteria and 27% belonged to Proteobacteria. Other sequences included Chloroflexi, Firmicutes, Chlamydiae, Actinobacteria, Gemmatimonadetes, Nitrospira, and three unclassified OTUs. Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Firmicutes, and Actinobacteria were mainly distributed in the rhizosphere of naturally colonizing plants; however, Deltaproteobacteria, Acidobacteria, and Chloroflexi tended to inhabit the deeper tailings (below the 100 cm-depth).     

Synthetic Statistical Approach Reveals a High Degree of Richness of Microbial Eukaryotes in an Anoxic Water Column

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.     

PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets

As 16S rRNA gene targeted massively parallel sequencing has become a common tool for microbial diversity investigations, numerous advances have been made to minimize the influence of sequencing and chimeric PCR artifacts through rigorous quality control measures. However, there has been little effort towards understanding the effect of multi-template PCR biases on microbial community structure. In this study, we used three bacterial and three archaeal mock communities consisting of, respectively, 33 bacterial and 24 archaeal 16S rRNA gene sequences combined in different proportions to compare the influences of (1) sequencing depth, (2) sequencing artifacts (sequencing errors and chimeric PCR artifacts), and (3) biases in multi-template PCR, towards the interpretation of community structure in pyrosequencing datasets. We also assessed the influence of each of these three variables on α- and β-diversity metrics that rely on the number of OTUs alone (richness) and those that include both membership and the relative abundance of detected OTUs (diversity). As part of this study, we redesigned bacterial and archaeal primer sets that target the V3-V5 region of the 16S rRNA gene, along with multiplexing barcodes, to permit simultaneous sequencing of PCR products from the two domains. We conclude that the benefits of deeper sequencing efforts extend beyond greater OTU detection and result in higher precision in β-diversity analyses by reducing the variability between replicate libraries, despite the presence of more sequencing artifacts. Additionally, spurious OTUs resulting from sequencing errors have a significant impact on richness or shared-richness based α- and β-diversity metrics, whereas metrics that utilize community structure (including both richness and relative abundance of OTUs) are minimally affected by spurious OTUs. However, the greatest obstacle towards accurately evaluating community structure are the errors in estimated mean relative abundance of each detected OTU due to biases associated with multi-template PCR reactions.     

Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.     

Distinct protistan assemblages characterize the euphotic zone and deep sea (2500 m) of the western North Atlantic (Sargasso Sea and Gulf Stream)

Protistan diversity was characterized at three locations in the western North Atlantic (Sargasso Sea and Gulf Stream) by sequencing 18S rRNA genes in samples from euphotic (< or = 125 m) and bathypelagic depths (2500 m). A total of 923 partial-length protistan sequences were analysed, revealing 324 distinct operational taxonomic units (OTUs) determined by an automated OTU-calling program set to 95% sequence similarity. Most OTUs were comprised of only one or two sequences suggesting a large but rare pool of protistan diversity. Many OTUs from both depth strata were associated with recently described novel alveolate and stramenopile lineages while many OTUs from the bathypelagic were affiliated with Acantharea, Polycystinea and Euglenozoa and were not observed in euphotic zone libraries. Protistan assemblages from the euphotic zone and the deep sea were largely composed of distinct OTUs; only 28 of the 324 protistan OTUs were detected in both shallow and deep sea clone libraries. The diversity of protistan assemblages in the deep sea was distinctly lower than the diversity of euphotic zone assemblages. Protistan assemblages from the Gulf Stream were the most diverse for either depth strata. Overall, protistan assemblages from different stations but comparable depths were more similar than the assemblages from different depths at the same station. These data suggest that particular groups of protistan OTUs formed distinct 'shallow' and 'deep-sea' assemblages across widely spaced oceanic locales.     

Synthetic statistical approach reveals a high degree of richness of microbial eukaryotes in an anoxic water column

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.     

Phylogenetic profiling of bacterial community from two intimately located sites in Balramgari,North-East coast of India

Microbial communities in coastal subsurface sediments play an important role in biogeochemical cycles. In this study microbial communities in tidal subsurface sediments of Balramgari in the state of Orissa, India were investigated using a culture independent approach. Two 16S rDNA cloned libraries were prepared from the closely located (100 m along the coast) subsurface sediment samples. Library I sediment samples had higher organic carbon content but lower sand percentage in comparison to Library II. A total of 310 clone sequences were used for DOTUR analysis which revealed 51 unique phylotypes or operational taxonomic units (OTUs) for both libraries. The OTUs were affiliated with 13 major lineages of domain bacteria including Proteobacteria (α, β, δ and λ), Acidobacteria, Actinobacteria, Cyanobacteria, Chloroflexi, Firmicutes, Verrucomicrobia, Bacteroidetes, Gemmatimonadetes and TM7. We encountered few pathogenic bacteria such as Aeromonas hydrophila and Ochrobactrum intermedium, in sediment from Library I. ∫-LIBSHUFF comparison depicts that the two libraries were significantly different communities. Most of the OTUs from both libraries possessed ≥85% to <97% similarity to RDP database sequences depicting the putative presence of new species, genera and phylum. This work revealed the complex and unique bacterial diversity from coastal habitat of Balramgari and shows that, in coastal habitat a variability of physical and chemical parameter has a prominent impact on the microbial community structure.     

Biogeography of pelagic bacterioplankton across an antagonistic temperature-salinity gradient in the Red Sea

The Red Sea is a unique marine ecosystem with contrasting gradients of temperature and salinity along its north-to-south axis. It is an extremely oligotrophic environment that is characterized by perpetual year-round water column stratification, high annual solar irradiation, and negligible riverine and precipitation inputs. In this study, we investigated whether the contemporary environmental conditions shape community assemblages by pyrosequencing 16S rRNA genes of bacteria in surface water samples collected from the northeastern half of this water body. A combined total of 1855 operational taxonomic units (OTUs) were recovered from the 'small-cell' and 'large-cell' fractions. Here, a few major OTUs affiliated with Cyanobacteria and Proteobacteria accounted for ～93% of all sequences, whereas a tail of 'rare' OTUs represented most of the diversity. OTUs allied to Surface 1a/b SAR11 clades and Prochlorococcus related to the high-light-adapted (HL2) ecotype were the most widespread and predominant sequence types. Interestingly, the frequency of taxa that are typically found in the upper mesopelagic zone was significantly elevated in the northern transects compared with those in the central, presumably as a direct effect of deep convective mixing in the Gulf of Aqaba and water exchange with the northern Red Sea. Although temperature was the best predictor of species richness across all major lineages, both spatial and environmental distances correlated strongly with phylogenetic distances. Our results suggest that the bacterial diversity of the Red Sea is as high as in other tropical seas and provide evidence for fundamental differences in the biogeography of pelagic communities between the northern and central regions.     

Helminth Colonization Is Associated with Increased Diversity of the Gut Microbiota

Soil-transmitted helminths colonize more than 1.5 billion people worldwide, yet little is known about how they interact with bacterial communities in the gut microbiota. Differences in the gut microbiota between individuals living in developed and developing countries may be partly due to the presence of helminths, since they predominantly infect individuals from developing countries, such as the indigenous communities in Malaysia we examine in this work. We compared the composition and diversity of bacterial communities from the fecal microbiota of 51 people from two villages in Malaysia, of which 36 (70.6%) were infected by helminths. The 16S rRNA V4 region was sequenced at an average of nineteen thousand sequences per samples. Helminth-colonized individuals had greater species richness and number of observed OTUs with enrichment of Paraprevotellaceae, especially with Trichuris infection. We developed a new approach of combining centered log-ratio (clr) transformation for OTU relative abundances with sparse Partial Least Squares Discriminant Analysis (sPLS-DA) to enable more robust predictions of OTU interrelationships. These results suggest that helminths may have an impact on the diversity, bacterial community structure and function of the gut microbiota.     

Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes

Operational taxonomic units (OTUs) are conventionally defined at a phylogenetic distance (0.03—species, 0.05—genus, 0.10—family) based on full-length 16S rRNA gene sequences. However, partial sequences (700 bp or shorter) have been used in most studies. This discord may affect analysis of diversity and species richness because sequence divergence is not distributed evenly along the 16S rRNA gene. In this study, we compared a set each of bacterial and archaeal 16S rRNA gene sequences of nearly full length with multiple sets of different partial 16S rRNA gene sequences derived therefrom (approximately 440-700 bp), at conventional and alternative distance levels. Our objective was to identify partial sequence region(s) and distance level(s) that allow more accurate phylogenetic analysis of partial 16S rRNA genes. Our results showed that no partial sequence region could estimate OTU richness or define OTUs as reliably as nearly full-length genes. However, the V1-V4 regions can provide more accurate estimates than others. For analysis of archaea, we recommend the V1-V3 and the V4-V7 regions and clustering of species-level OTUs at 0.03 and 0.02 distances, respectively. For analysis of bacteria, the V1-V3 and the V1-V4 regions should be targeted, with species-level OTUs being clustered at 0.04 distance in both cases.     

Local-scale spatial diversity patterns of ectomycorrhizal fungal communities in a subtropical pine-oak forest

This study aimed to analyze spatial patterns of soil ectomycorrhizal fungal (EMF) communities at the local scale in a subtropical pine-oak forest located in the Nearctic-Neotropical transition in central Mexico, to underpin biodiversity conservation strategies in forest fragments of this region. We used a spatially-explicit nested square sampling design with the same sampling representativeness at all scales and replicated three times. We detected 674 EMF OTUs within 19,200 m² and 65 OTUs on average per sample. Seventy percent of OTUs were detected in only 1–4 samples. Average community similarity was below 5%, showed minor change within 14 and 339 m distance and increased with the spatial grain used to compare the data. We found a high species-area relationship and beta diversity coefficients for soil fungi indicating that, at the local scale, increasing area by a constant factor of four represented an increase in OTU richness by a factor of two.     

A Comparison of Methods for Clustering 16S rRNA Sequences into OTUs

Recent studies of 16S rRNA sequences through next-generation sequencing have revolutionized our understanding of the microbial community composition and structure. One common approach in using these data to explore the genetic diversity in a microbial community is to cluster the 16S rRNA sequences into Operational Taxonomic Units (OTUs) based on sequence similarities. The inferred OTUs can then be used to estimate species, diversity, composition, and richness. Although a number of methods have been developed and commonly used to cluster the sequences into OTUs, relatively little guidance is available on their relative performance and the choice of key parameters for each method. In this study, we conducted a comprehensive evaluation of ten existing OTU inference methods. We found that the appropriate dissimilarity value for defining distinct OTUs is not only related with a specific method but also related with the sample complexity. For data sets with low complexity, all the algorithms need a higher dissimilarity threshold to define OTUs. Some methods, such as, CROP and SLP, are more robust to the specific choice of the threshold than other methods, especially for shorter reads. For high-complexity data sets, hierarchical cluster methods need a more strict dissimilarity threshold to define OTUs because the commonly used dissimilarity threshold of 3% often leads to an under-estimation of the number of OTUs. In general, hierarchical clustering methods perform better at lower dissimilarity thresholds. Our results show that sequence abundance plays an important role in OTU inference. We conclude that care is needed to choose both a threshold for dissimilarity and abundance for OTU inference.     

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.     

Metagenomic and small-subunit rRNA analyses reveal the genetic diversity of bacteria, archaea, fungi, and viruses in soil

Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.