The continental subsurface houses a major portion of life’s abundance and diversity, yet little is known about viruses infecting microbes that reside there. Here, we use a combination of metagenomics and virus-targeted direct-geneFISH (virusFISH) to show that highly abundant carbon-fixing organisms of the uncultivated genus Candidatus Altiarchaeum are frequent targets of previously unrecognized viruses in the deep subsurface. Analysis of CRISPR spacer matches display resistances of Ca. Altiarchaea against eight predicted viral clades, which show genomic relatedness across continents but little similarity to previously identified viruses. Based on metagenomic information, we tag and image a putatively viral genome rich in protospacers using fluorescence microscopy. VirusFISH reveals a lytic lifestyle of the respective virus and challenges previous predictions that lysogeny prevails as the dominant viral lifestyle in the subsurface. CRISPR development over time and imaging of 18 samples from one subsurface ecosystem suggest a sophisticated interplay of viral diversification and adapting CRISPR-mediated resistances of Ca. Altiarchaeum. We conclude that infections of primary producers with lytic viruses followed by cell lysis potentially jump-start heterotrophic carbon cycling in these subsurface ecosystems.
Highlights d Thousands of diverse viruses encode genes that manipulate organic sulfur metabolism d Infection in the presence of sulfide increases bacteriophage production d Engineered phage T7 retains cysteine synthase (cysK) over multiple generations d These viruses can influence human gut dysbiosis, microbiomes, and biogeochemistry
Resolving bacterial and archaeal genomes from metagenomes has revolutionized our understanding of Earth’s biomes, yet producing high quality genomes from assembled fragments has been an ever-standing problem. While automated binning software and their combination produce prokaryotic bins in high-throughput, their manual refinement has been slow and sometimes difficult. Here, we present uBin, a GUI-based, standalone bin refiner that runs on all major operating platforms and was specifically designed for educational purposes. When applied to the public CAMI dataset, refinement of bins was able to improve 78.9% of bins by decreasing their contamination. We also applied the bin refiner as a standalone binner to public metagenomes from the International Space Station and demonstrate the recovery of near-complete genomes, whose replication indices indicate active proliferation of microbes in Earth’s lower orbit. uBin is an easy to install software for bin refinement, binning of simple metagenomes and communication of metagenomic results to other scientists and in classrooms. The software is open source and available under https://github.com/ProbstLab/uBin.
Resolving bacterial and archaeal genomes from metagenomes has revolutionized our understanding of Earth's biomes yet producing high-quality genomes from assembled fragments has been an ever-standing problem. While automated binning software and their combination produce prokaryotic bins in high throughput, their manual refinement has been slow, sometimes difficult or missing entirely facilitating error propagation in public databases. Here, we present uBin, a GUI-based, standalone bin refiner that runs on all major operating platforms and was additionally designed for educational purposes. When applied to the public CAMI dataset, refinement of bins using GC content, coverage and taxonomy was able to improve 78.9% of bins by decreasing their contamination. We also applied the bin refiner as a standalone binner to public metagenomes from the International Space Station and demonstrate the recovery of near-complete genomes, whose replication indices indicate the active proliferation of microbes in Earth's lower orbit. uBin is an easy to instal software for bin refinement, binning of simple metagenomes and communication of metagenomic results to other scientists and in classrooms. The software and its helper scripts are open source and available under https://github.com/ProbstLab/uBin.
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