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Summary: Photosynthetic bacteria are abundant in alkaline, terrestrial hot springs and there is a long history of research on phototrophs in Yellowstone National Park (YNP). Hot springs provide a framework to examine the ecophysiology of phototrophs in situ because they provide natural gradients of geochemistry, pH and temperature. Phototrophs within the Cyanobacteria and Chloroflexi groups are frequently observed in alkaline hot springs. Decades of research has determined that temperature constrains Cyanobacteria in alkaline hot springs, but factors that constrain the distribution of phototrophic Chloroflexi remain unresolved. Using a combination of 16S rRNA gene sequencing and photoassimilation microcosms, we tested the hypothesis that temperature would constrain the activity and composition of phototrophic Cyanobacteria and Chloroflexi. We expected diversity and rates of photoassimilation to decrease with increasing temperature. We report 16S rRNA amplicon sequencing along with carbon isotope signatures and photoassimilation from 45 to 72°C in two alkaline hot springs. We find that Roseiflexus, Chloroflexus (Chloroflexi) and Leptococcus (Cyanobacteria) operational taxonomic units (OTUs) have distinct distributions with temperature. This distribution suggests that, like phototrophic Cyanobacteria, temperature selects for specific phototrophic Chloroflexi taxa. The richness of phototrophic Cyanobacteria decreased with increasing temperature along with a decrease in oxygenic photosynthesis, whereas Chloroflexi richness and rates of anoxygenic photosynthesis did not decrease with increasing temperature, even at temperatures approaching the upper limit of photosynthesis (~72–73°C). Our carbon isotopic data suggest an increasing prevalence of the 3‐hydroxypropionate pathway with decreasing temperature coincident with photoautotrophic Chloroflexi. Together these results indicate temperature plays a role in defining the niche space of phototrophic Chloroflexi (as has been observed for Cyanobacteria), but other factors such as morphology, geochemistry, or metabolic diversity of Chloroflexi, in addition to temperature, could determine the niche space of this highly versatile group. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]