The considerable microbial diversity of soils and key role in biogeochemical cycling have led to growing interest in their global distribution and the impact that environmental change might have at the regional level. In the broadest study of Arctic soil bacterial communities to date, we used high-throughput DNA sequencing to investigate the bacterial diversity from 200 independent Arctic soil samples from 43 sites. We quantified the impact of spatial and environmental factors on bacterial community structure using variation partitioning analysis, illustrating a nonrandom distribution across the region. pH was confirmed as the key environmental driver structuring Arctic soil bacterial communities, while total organic carbon (TOC), moisture and conductivity were shown to have little effect. Specialist taxa were more abundant in acidic and alkaline soils while generalist taxa were more abundant in acidoneutral soils. Of the 48 147 bacterial taxa, a core microbiome composed of only 13 taxa that were ubiquitously distributed and present within 95% of samples was identified, illustrating the high potential for endemism in the region. Overall, our results demonstrate the importance of spatial and edaphic factors on the structure of Arctic soil bacterial communities.

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Comprehensive mapping of environmental microbiomes in terms of their compositional features remains a great challenge in understanding the microbial biosphere of the Earth. It bears promise to identify the driving forces behind the observed community patterns and whether community assembly happens deterministically. Advances in Next Generation Sequencing allow large community profiling studies, exceeding sequencing data output of conventional methods in scale by orders of magnitude. However, appropriate collection systems are still in a nascent state. We here present a database of 20,427 diverse environmental 16S rRNA profiles from 2,426 independent studies, which forms the foundation of our meta-analysis. We conducted a sample size adaptive all-against-all beta diversity comparison while also respecting phylogenetic relationships of Operational Taxonomic Units(OTUs). After conventional hierarchical clustering we systematically test for enrichment of Environmental Ontology terms and their abstractions in all possible clusters. This post-hoc algorithm provides a novel formalism that quantifies to what extend compositional and semantic similarity of microbial community samples coincide. We automatically visualize significantly enriched subclusters on a comprehensive dendrogram of microbial communities. As a result we obtain the hitherto most differentiated and comprehensive view on global patterns of microbial community diversity. We observe strong clusterability of microbial communities in ecosystems such as human/mammal-associated, geothermal, fresh water, plant-associated, soils and rhizosphere microbiomes, whereas hypersaline and anthropogenic samples are less homogeneous. Moreover, saline samples appear less cohesive in terms of compositional properties than previously reported.

Effective and sensitive monitoring of human pathogenic bacteria in municipal wastewater treatment is important not only for managing public health risk related to treated wastewater reuse, but also for ensuring proper functioning of the treatment plant. In this study, three different 16S rRNA gene molecular analysis methodologies were employed to screen bacterial pathogens in samples collected at three different stages of an activated sludge plant. Overall bacterial diversity was analyzed using next generation sequencing (NGS) on the Illumina MiSeq platform, as well as PCR-DGGE followed by band sequencing. In addition, a microdiversity analysis was conducted using PCR-DGGE, targeting Escherichia coli. Bioinformatics analysis was performed using QIIME protocol by clustering sequences against the Human Pathogenic Bacteria Database. NGS data were also clustered against the Greengenes database for a genera-level diversity analysis. NGS proved to be the most effective approach screening the sequences of 21 potential human bacterial pathogens, while the E. coli microdiversity analysis yielded one (O157:H7 str. EDL933) out of the two E. coli strains picked up by NGS. Overall diversity using PCR-DGGE did not yield any pathogenic sequence matches even though a number of sequences matched the NGS results. Overall, sequences of Gram-negative pathogens decreased in relative abundance along the treatment train while those of Gram-positive pathogens increased.

Recycling of wood ash from energy production may counteract soil acidification and return essential nutrients to soils. However, wood ash amendment affects soil physicochemical parameters that control composition and functional expression of the soil microbial community. Here, we applied total RNA sequencing to simultaneously assess the impact of wood ash amendment on the active soil microbial communities and the expression of functional genes from all microbial taxa. Wood ash significantly affected the taxonomic (rRNA) as well as functional (mRNA) profiles of both agricultural and forest soil. Increase in pH, electrical conductivity, dissolved organic carbon and phosphate were the most important physicochemical drivers for the observed changes. Wood ash amendment increased the relative abundance of the copiotrophic groups Chitinonophagaceae (Bacteroidetes) and Rhizobiales (Alphaproteobacteria) and resulted in higher expression of genes involved in metabolism and cell growth. Finally, total RNA sequencing allowed us to show that some groups of bacterial feeding protozoa increased concomitantly to the enhanced bacterial growth, which shows their pivotal role in the regulation of bacterial abundance in soil.