Sunok Jeon

Polymerase chain reaction primers miss half of rRNA microbial diversity.

The rRNA approach is the principal tool to study microbial diversity, but it has important biases. These include polymerase chain reaction (PCR) primers bias, and relative inefficiency of DNA extraction techniques. Such sources of potential undersampling of microbial diversity are well known, but the scale of the undersampling has not been quantified. Using a marine tidal flat bacterial community as a model, we show that even with unlimited sampling and sequencing effort, a single combination of PCR primers/DNA extraction technique enables theoretical recovery of only half of the richness recoverable with three such combinations. This shows that different combinations of PCR primers/DNA extraction techniques recover in principle different species, as well as higher taxa. The majority of earlier estimates of microbial richness seem to be underestimates. The combined use of multiple PCR primer sets, multiple DNA extraction techniques, and deep community sequencing will minimize the biases and recover substantially more species than prior studies, but we caution that even this—yet to be used—approach may still leave an unknown number of species and higher taxa undetected.

Protistan microbial observatory in the Cariaco Basin, Caribbean. I. Pyrosequencing vs Sanger insights into species richness

Microbial diversity and distribution are topics of intensive research. In two companion papers in this issue, we describe the results of the Cariaco Microbial Observatory (Caribbean Sea, Venezuela). The Basin contains the largest body of marine anoxic water, and presents an opportunity to study protistan communities across biogeochemical gradients. In the first paper, we survey 18S ribosomal RNA (rRNA) gene sequence diversity using both Sanger- and pyrosequencing-based approaches, employing multiple PCR primers, and state-of-the-art statistical analyses to estimate microbial richness missed by the survey. Sampling the Basin at three stations, in two seasons, and at four depths with distinct biogeochemical regimes, we obtained the largest, and arguably the least biased collection of over 6000 nearly full-length protistan rRNA gene sequences from a given oceanographic regime to date, and over 80 000 pyrosequencing tags. These represent all major and many minor protistan taxa, at frequencies globally similar between the two sequence collections. This large data set provided, via the recently developed parametric modeling, the first statistically sound prediction of the total size of protistan richness in a large and varied environment, such as the Cariaco Basin: over 36 000 species, defined as almost full-length 18S rRNA gene sequence clusters sharing over 99% sequence homology. This richness is a small fraction of the grand total of known protists (over 100 000–500 000 species), suggesting a degree of protistan endemism.

Protistan microbial observatory in the Cariaco Basin, Caribbean. II. Habitat specialization

This is the second paper in a series of three that investigates eukaryotic microbial diversity and taxon distribution in the Cariaco Basin, Venezuela, the oceans largest anoxic marine basin. Here, we use phylogenetic information, multivariate community analyses and statistical richness predictions to test whether protists exhibit habitat specialization within defined geochemical layers of the water column. We also analyze spatio-temporal distributions of protists across two seasons and two geographic sites within the basin. Non-metric multidimensional scaling indicates that these two basin sites are inhabited by distinct protistan assemblages, an observation that is supported by the minimal overlap in observed and predicted richness of sampled sites. A comparison of parametric richness estimations indicates that protistan communities in closely spaced—but geochemically different—habitats are very dissimilar, and may share as few as 5% of total operational taxonomic units (OTUs). This is supported by a canonical correspondence analysis, indicating that the empirically observed OTUs are organized along opposing gradients in oxidants and reductants. Our phylogenetic analyses identify many new clades at species to class levels, some of which appear restricted to specific layers of the water column and have a significantly nonrandom distribution. These findings suggest many pelagic protists are restricted to specific habitats, and likely diversify, at least in part due to separation by geochemical barriers.

Environmental rRNA inventories miss over half of protistan diversity

BackgroundThe main tool to discover novel microbial eukaryotes is the rRNA approach. This approach has important biases, including PCR discrimination against certain rRNA gene species, which makes molecular inventories skewed relative to the source communities. The degree of this bias has not been quantified, and it remains unclear whether species missed from clone libraries could be recovered by increasing sequencing efforts, or whether they cannot be detected in principle. Here we attempt to discriminate between these possibilities by statistically analysing four protistan inventories obtained using different general eukaryotic PCR primers.ResultsWe show that each PCR primer set-specific clone library is not a sample from the community diversity but rather from a fraction of this diversity. Therefore, even sequencing such clone libraries to saturation would only recover that fraction, which, according to the parametric models, varies between 17 ± 4% to 49 ± 10%, depending on the set of primers. The pooled data is thus qualitatively richer than individual libraries, even if normalized to the same sequencing effort.ConclusionThe use of a single pair of primers leads to significant underestimation of the true community richness at all levels of taxonomic hierarchy. The majority of available protistan rRNA gene surveys likely sampled less than half of the target diversity, and might have completely missed the rest. The use of multiple PCR primers reduces this bias but does not necessarily eliminate it.

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

ABSTRACT 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 communitys 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.

A novel archaeal group in the phylum Crenarchaeota found unexpectedly in an eukaryotic survey in the Cariaco Basin

Archaea have been found in many more diverse habitats than previously believed due in part to modern molecular approaches to discovering microbial diversity. We report here an unexpected expansion of the habitat diversity of the Archaea in the Cariaco Basin we found using a primer set designed for 18S eukaryotic rDNA sequence analysis. The results presented here expand the originally identified 9 archaeal clones reported in this environment using bacterial/archaeal primers to 152 archaeal clones: 67 (18 OTU) of these clones were found at a depth of 900 m of station A while 71 (9 OTU) of them were at a depth of between 300∼335 m of station B&C depending upon which location the samples were taken. We used three phylogenetic analysis methods and detected 20 phylotypes belonging to a single previously unreported group distantly related to the Crenarchaeota. Also, we determined that the original nine sequences did not fall into any of the known phyla of the Archaea suggesting that they may represent a novel group within the Kingdom Archaea. Thus, from these two studies, we suggest that Archaea in the Cariaco Basin could be unique; however, further studies using archaeal-specific primers and the design of new primers as well as the systematic use of several different primer combinations may improve the chances of understanding the archeal diversity in the Cariaco Basin.

Deep-Sea Microbial Eukaryotes in Anoxic, Microoxic, and Sulfidic Environments

Dr. Virginia Edgcomb is a research associate in the department of geology and geophysics at the Woods Hole Oceanographic Institution (WHOI), Woods Hole, MA. She received her Ph.D. from the University of Delaware (department of biology) in 1997. As postdoctoral researcher, she spent 3 years at the Marine Biological Laboratory where she was involved in studies of early eukaryotic evolution and of microbial diversity at hydrothermal vents, followed by 2 years at WHOI where she studied the tolerance of several marine prokaryotes to extreme conditions found at hydrothermal vents. Her current research interests include microbial ecology of microoxic and anoxic environments, and diversity and evolution of protists.