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

Abstract

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.

FIG 1

Flow chart of the progression of data analysis, showing (left to right) sample collection; sequencing of single-cell genomes and reference GenBank genomes (stars) and metagenomes (circles); nucleotide trimer frequency calculation; MLP model training; and read-binning, assembly, and postassembly analyses (annotation, metabolic reconstruction, and estimation of genome completeness). The MLP pipeline (top and right) subsequently was conducted on all geographic sites analyzed in this study.

FIG 2

Comparison of Calescamantes assemblies. The total numbers of predicted proteins (black) and KEGG orthologs (KO) (purple) are shown in parentheses. Best reciprocal BLASTP hits using an E value cutoff of ≤1E−15 were calculated between all analyzed assemblies. (A) Comparison of predicted proteins in the GBS SAG coassembly (dark gray) compared to the GBS MLP metagenome assembly (light blue). (B) Venn diagram of GBS MLP metagenome assembly (light blue), the Octopus Spring MLP metagenome assembly (yellow), and the Gongxiaoshe MLP metagenome assembly (red). Unique genes had no BLAST hit to any other assembly. (C) Number of shared protein-coding regions between the incomplete Calescamantes assembly from Bison Pool and other assembled genomes (E value of ≤1E−15).

FIG 3

Maximum-likelihood phylogeny based on partial 16S rRNA genes (953 bp) representing all sequenced members within the Calescamantes phylum (≥85% identity), as well as members of other well-known bacterial phyla. Hot spring locations from which Calescamantes sequences were obtained are shown on the right. Black dots indicate bootstrap values of ≥90, and white dots indicate values of ≥50. The SAG coassembly and MLP assembly 16S rRNA gene sequences are shown together on the same branch, as they were 100% identical. 16S rRNA gene sequences from Cole et al. (23), which branch as a close sister to the SAG/MLP 16S rRNA gene (99.2 to 100% identical), were not included in the phylogeny due to their short length (200 to 400 bp). The scale bar indicates 0.05 substitutions per site. Sequences originating from MLP assemblies (MLP), SAGs, and/or amplified 16S rRNA gene clone libraries (Clone) are indicated in parentheses.

FIG 4

Schematic diagram of the core metabolic potential of Calescamantes populations analyzed from GBS, GXS, and Octopus Spring (OS). GBS-specific genes are shaded green, GBS- and OS-specific genes are shaded blue, and GXS-specific genes are shaded red.