Recent applications of molecular genetics to edaphic microbial communities of the McMurdo Dry Valleys and elsewhere have rejected a long-held belief that Antarctic soils contain extremely limited microbial diversity. The Inter-Valley Soil Comparative Survey aims to elucidate the factors shaping these unique microbial communities and their biogeography by integrating molecular genetic approaches with biogeochemical analyses. Although the microbial communities of Dry Valley soils may be complex, there is little doubt that the ecosystem's food web is relatively simple, and evidence suggests that physicochemical conditions may have the dominant role in shaping microbial communities. To examine this hypothesis, bacterial communities from representative soil samples collected in four geographically disparate Dry Valleys were analyzed using molecular genetic tools, including pyrosequencing of 16S rRNA gene PCR amplicons. Results show that the four communities are structurally and phylogenetically distinct, and possess significantly different levels of diversity. Strikingly, only 2 of 214 phylotypes were found in all four valleys, challenging a widespread assumption that the microbiota of the Dry Valleys is composed of a few cosmopolitan species. Analysis of soil geochemical properties indicated that salt content, alongside altitude and Cu²⁺, was significantly correlated with differences in microbial communities. Our results indicate that the microbial ecology of Dry Valley soils is highly localized and that physicochemical factors potentially have major roles in shaping the microbiology of ice-free areas of Antarctica. These findings hint at links between Dry Valley glacial geomorphology and microbial ecology, and raise previously unrecognized issues related to environmental management of this unique ecosystem.

Geothermal springs are model ecosystems to investigate microbial biogeography as they represent discrete, relatively homogenous habitats, are distributed across multiple geographical scales, span broad geochemical gradients, and have reduced metazoan interactions. Here, we report the largest known consolidated study of geothermal ecosystems to determine factors that influence biogeographical patterns. We measured bacterial and archaeal community composition, 46 physicochemical parameters, and metadata from 925 geothermal springs across New Zealand (13.9–100.6 °C and pH < 1–9.7). We determined that diversity is primarily influenced by pH at temperatures 70 °C. Further, community dissimilarity increases with geographic distance, with niche selection driving assembly at a localised scale. Surprisingly, two genera (Venenivibrio and Acidithiobacillus) dominated in both average relative abundance (11.2% and 11.1%, respectively) and prevalence (74.2% and 62.9%, respectively). These findings provide an unprecedented insight into ecological behaviour in geothermal springs, and a foundation to improve the characterisation of microbial biogeographical processes.

Factors governing large-scale spatio-temporal distribution of microorganisms remain unresolved, yet are pivotal to understanding ecosystem value and function. Molecular genetic analyses have focused on the influence of niche and neutral processes in determining spatial patterns without considering the temporal scale. Here, we use temporal phylogenetic analysis calibrated using microfossil data for a globally sampled desert cyanobacterium, Chroococcidiopsis, to investigate spatio-temporal patterns in microbial biogeography and evolution. Multilocus phylogenetic associations were dependent on contemporary climate with no evidence for distance-related patterns. Massively parallel pyrosequencing of environmental samples confirmed that Chroococcidiopsis variants were specific to either hot or cold deserts. Temporally scaled phylogenetic analyses showed no evidence of recent inter-regional gene flow, indicating populations have not shared common ancestry since before the formation of modern continents. These results indicate that global distribution of desert cyanobacteria has not resulted from widespread contemporary dispersal but is an ancient evolutionary legacy. This highlights the importance of considering temporal scales in microbial biogeography.

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.

Advances in the sequencing of DNA extracted from media such as soil and water offer huge opportunities for biodiversity monitoring and assessment, particularly where the collection or identification of whole organisms is impractical. However, there are myriad methods for the extraction, storage, amplification and sequencing of DNA from environmental samples.