Diffuse flow environments within basalt- and sediment-based hydrothermal vent ecosystems harbor specialized microbial communities

Hydrothermal vents differ both in surface input and subsurface geochemistry. The effects of these differences on their microbial communities are not clear. Here, we investigated both alpha and beta diversity of diffuse flow-associated microbial communities emanating from vents at a basalt-based hydrothermal system along the East Pacific Rise (EPR) and a sediment-based hydrothermal system, Guaymas Basin. Both Bacteria and Archaea were targeted using high throughput 16S rRNA gene pyrosequencing analyses. A unique aspect of this study was the use of a universal set of 16S rRNA gene primers to characterize total and diffuse flow-specific microbial communities from varied deep-sea hydrothermal environments. Both surrounding seawater and diffuse flow water samples contained large numbers of Marine Group I (MGI) Thaumarchaea and Gammaproteobacteria taxa previously observed in deep-sea systems. However, these taxa were geographically distinct and segregated according to type of spreading center. Diffuse flow microbial community profiles were highly differentiated. In particular, EPR dominant diffuse flow taxa were most closely associated with chemolithoautotrophs, and off axis water was dominated by heterotrophic-related taxa, whereas the opposite was true for Guaymas Basin. The diversity and richness of diffuse flow-specific microbial communities were strongly correlated to the relative abundance of Epsilonproteobacteria, proximity to macrofauna, and hydrothermal system type. Archaeal diversity was higher than or equivalent to bacterial diversity in about one third of the samples. Most diffuse flow-specific communities were dominated by OTUs associated with Epsilonproteobacteria, but many of the Guaymas Basin diffuse flow samples were dominated by either OTUs within the Planctomycetes or hyperthermophilic Archaea. This study emphasizes the unique microbial communities associated with geochemically and geographically distinct hydrothermal diffuse flow environments

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

The observed relative abundances of all error-free sequence in the equal-abundance <i>iv</i>-SCs (V3V4E: red; V6E: blue).

<p>The pool of error-free sequences for V6E (14,761 reads) was resampled 10,000 times with replacement to match the number of V3V4E error-free sequences (4,609 reads) and used to calculate 95% confidence intervals for V6E.</p

Summary statistics for chimera-check of <i>iv</i>-SCs.

<p>Summary statistics for chimera-check of <i>iv</i>-SCs.</p

Spearman rank (ρ) and log-log transformed Pearson (<i>r</i>) correlation coefficients of relative abundances of corresponding sequences in P and T <i>iv</i>-SCs.

<p>Spearman rank (ρ) and log-log transformed Pearson (<i>r</i>) correlation coefficients of relative abundances of corresponding sequences in P and T <i>iv</i>-SCs.</p

Spearman rank (ρ) and log-log transformed Pearson (<i>r</i>) correlation coefficients of error-free sequences with their respective theoretical frequencies.

<p>The pools of error-free sequences for V6P and V6T (33,804 and 39,978 reads respectively) were resampled 10,000 times with replacement to match the numbers of V3V4P and V3V4T error-free sequences (5,424 and 6,607 reads respectively). The correlation coefficients for each bootstrap were calculated and presented as means and 95% confidence intervals. The bootstrapping <i>p</i> values (testing the V6x correlation coefficients as higher than the V3V4x equivalents) were 0.814 (ρ) and 0.152 (<i>r</i>) for resampled V6P vs. V3V4P and <0.001 (ρ and <i>r</i>) for resampled V6T vs. V3V4T.</p