Genomic Comparison of Two Family-Level Groups of the Uncultivated NAG1 Archaeal Lineage from Chemically and Geographically Disparate Hot Springs.

Recent progress based on single-cell genomics and metagenomic investigations of archaea in a variety of extreme environments has led to significant advances in our understanding of the diversity, evolution, and metabolic potential of archaea, yet the vast majority of archaeal diversity remains undersampled. In this work, we coordinated single-cell genomics with metagenomics in order to construct a near-complete genome from a deeply branching uncultivated archaeal lineage sampled from Great Boiling Spring (GBS) in the U.S. Great Basin, Nevada. This taxon is distantly related (distinct families) to an archaeal genome, designated "Novel Archaeal Group 1" (NAG1), which was extracted from a metagenome recovered from an acidic iron spring in Yellowstone National Park (YNP). We compared the metabolic predictions of the NAG1 lineage to better understand how these archaea could inhabit such chemically distinct environments. Similar to the NAG1 population previously studied in YNP, the NAG1 population from GBS is predicted to utilize proteins as a primary carbon source, ferment simple carbon sources, and use oxygen as a terminal electron acceptor under oxic conditions. However, GBS NAG1 populations contained distinct genes involved in central carbon metabolism and electron transfer, including nitrite reductase, which could confer the ability to reduce nitrite under anaerobic conditions. Despite inhabiting chemically distinct environments with large variations in pH, GBS NAG1 populations shared many core genomic and metabolic features with the archaeon identified from YNP, yet were able to carve out a distinct niche at GBS.

Single-Cell-Genomics-Facilitated Read Binning of Candidate Phylum EM19 Genomes from Geothermal Spring Metagenomes.

The vast majority of microbial life remains uncatalogued due to the inability to cultivate these organisms in the laboratory. This "microbial dark matter" represents a substantial portion of the tree of life and of the populations that contribute to chemical cycling in many ecosystems. In this work, we leveraged an existing single-cell genomic data set representing the candidate bacterial phylum "Calescamantes" (EM19) to calibrate machine learning algorithms and define metagenomic bins directly from pyrosequencing reads derived from Great Boiling Spring in the U.S. Great Basin. Compared to other assembly-based methods, taxonomic binning with a read-based machine learning approach yielded final assemblies with the highest predicted genome completeness of any method tested. Read-first binning subsequently was used to extract Calescamantes bins from all metagenomes with abundant Calescamantes populations, including metagenomes from Octopus Spring and Bison Pool in Yellowstone National Park and Gongxiaoshe Spring in Yunnan Province, China. Metabolic reconstruction suggests that Calescamantes are heterotrophic, facultative anaerobes, which can utilize oxidized nitrogen sources as terminal electron acceptors for respiration in the absence of oxygen and use proteins as their primary carbon source. Despite their phylogenetic divergence, the geographically separate Calescamantes populations were highly similar in their predicted metabolic capabilities and core gene content, respiring O2, or oxidized nitrogen species for energy conservation in distant but chemically similar hot springs.