BackgroundThe study of microbiomes using whole-metagenome shotgun sequencing enables the analysis of uncultivated microbial populations that may have important roles in their environments. Extracting individual draft genomes (bins) facilitates metagenomic analysis at the single genome level. Software and pipelines for such analysis have become diverse and sophisticated, resulting in a significant burden for biologists to access and use them. Furthermore, while bin extraction algorithms are rapidly improving, there is still a lack of tools for their evaluation and visualization.ResultsTo address these challenges, we present metaWRAP, a modular pipeline software for shotgun metagenomic data analysis. MetaWRAP deploys state-of-the-art software to handle metagenomic data processing starting from raw sequencing reads and ending in metagenomic bins and their analysis. MetaWRAP is flexible enough to give investigators control over the analysis, while still being easy-to-install and easy-to-use. It includes hybrid algorithms that leverage the strengths of a variety of software to extract and refine high-quality bins from metagenomic data through bin consolidation and reassembly. MetaWRAP’s hybrid bin extraction algorithm outperforms individual binning approaches and other bin consolidation programs in both synthetic and real data sets. Finally, metaWRAP comes with numerous modules for the analysis of metagenomic bins, including taxonomy assignment, abundance estimation, functional annotation, and visualization.ConclusionsMetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomic bins. The bin refinement and reassembly modules of metaWRAP consistently outperform other binning approaches. Each module of metaWRAP is also a standalone component, making it a flexible and versatile tool for tackling metagenomic shotgun sequencing data. MetaWRAP is open-source software available at https://github.com/bxlab/metaWRAP.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0541-1) contains supplementary material, which is available to authorized users.

The environment significantly influences the dynamic expression and assembly of all components encoded in the genome of an organism into functional biological networks. We have constructed a model for this process in Halobacterium salinarum NRC-1 through the data-driven discovery of regulatory and functional interrelationships among approximately 80% of its genes and key abiotic factors in its hypersaline environment. Using relative changes in 72 transcription factors and 9 environmental factors (EFs) this model accurately predicts dynamic transcriptional responses of all these genes in 147 newly collected experiments representing completely novel genetic backgrounds and environments-suggesting a remarkable degree of network completeness. Using this model we have constructed and tested hypotheses critical to this organism's interaction with its changing hypersaline environment. This study supports the claim that the high degree of connectivity within biological and EF networks will enable the construction of similar models for any organism from relatively modest numbers of experiments.

SignificanceIt has remained an unresolved question whether microorganisms recovered from the most arid environments on Earth are thriving under such extreme conditions or are just dead or dying vestiges of viable cells fortuitously deposited by atmospheric processes. Based on multiple lines of evidence, we show that indigenous microbial communities are present and temporally active even in the hyperarid soils of the Atacama Desert (Chile). Following extremely rare precipitation events in the driest parts of this desert, where rainfall often occurs only once per decade, we were able to detect episodic incidences of biological activity. Our findings expand the range of hyperarid environments temporarily habitable for terrestrial life, which by extension also applies to other planetary bodies like Mars.

Background:The study of microbiomes using whole-metagenome shotgun sequencing enables the analysis of uncultivated microbial populations that may have important roles in their environments. Extracting individual draft genomes (bins) facilitates metagenomic analysis at the single genome level. Software and pipelines for such analysis have become diverse and sophisticated, resulting in a significant burden for biologists to access and use them. Furthermore, while bin extraction algorithms are rapidly improving, there is still a lack of tools for their evaluation and visualization. Results:To address these challenges, we present metaWRAP, a modular pipeline software for shotgun metagenomic data analysis. MetaWRAP deploys state-of-the-art software to handle metagenomic data processing starting from raw sequencing reads and ending in metagenomic bins and their analysis. MetaWRAP is flexible enough to give investigators control over the analysis, while still being easy-to-install and easy-to-use. It includes hybrid algorithms that leverage the strengths of a variety of software to extract and refine high-quality bins from metagenomic data through bin consolidation and reassembly. MetaWRAP's hybrid bin extraction algorithm outperforms individual binning approaches and other bin consolidation programs in both synthetic and real datasets. Finally, metaWRAP comes with numerous modules for the analysis of metagenomic bins, including taxonomy assignment, abundance estimation, functional annotation, and visualization. Conclusions:MetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomic bins. The bin refinement and reassembly modules of metaWRAP consistently outperform other binning approaches. Each module of metaWRAP is also a standalone component, making it a flexible and versatile tool for tackling metagenomic shotgun sequencing data. MetaWRAP is open-source software available at https://github.com/ bxlab/metaWRAP.

The Atacama Desert is one of the oldest and driest deserts in the world, and its hyper-arid core is described as 'the most barren region imaginable'. We used a combination of high-throughput sequencing and microscopy methods to characterize the endolithic microbial assemblages of halite pinnacles (salt rocks) collected in several hyper-arid areas of the desert. We found communities dominated by archaea that relied on a single phylotype of Halothece cyanobacteria for primary production. A few other phylotypes of salt-adapted bacteria and archaea, including Salinibacter, Halorhabdus, and Halococcus were major components of the halite communities, indicating specific adaptations to the unique halite environments. Multivariate statistical analyses of diversity metrics clearly separated the halite communities from that of the surrounding soil in the Yungay area. These analyses also revealed distribution patterns of halite communities correlated with atmospheric moisture. Microbial endolithic communities from halites exposed to coastal fogs and high relative humidity were more diverse; their archaeal and bacterial assemblages were accompanied by a novel algae related to oceanic picoplankton of the Mamiellales. In contrast, we did not find any algae in the Yungay pinnacles, suggesting that the environmental conditions in this habitat might be too extreme for eukaryotic photosynthetic life.