Quantitatively partitioning microbial genomic traits among taxonomic ranks: implications for subsurface microbial communities
A comprehensive model coupling microbial traits to taxonomy would provide an invaluable tool for inferring microbial-environment and microbial-microbial interactions. In particular, these interactions are difficult to understand in many microbiomes, such as subsurface sediment communities, due to the prevalence of culture-resistant lineages. Quantifying how microbial traits relate to taxonomy has been difficult because canonical taxonomies such as the NCBI taxonomy continue to “reflect the current consensus in the systematic literature.” The recently-proposed taxonomy, the Genome Taxonomy Database (GTDB), incorporates only sequence homology of conserved genes and attempts to partition taxonomic ranks such that each rank implies the same amount of evolutionary distance, regardless of its position on the phylogenetic tree. This provides the first opportunity to completely separate taxonomy from traits, and therefore to quantify how taxonomic rank corresponds to traits across the microbial tree of life. We quantified the structure of clusters of orthologous groups functional categories (COG-FCs) relative abundances, a proxy for genomic traits, within the lineages of 13,735 cultured and uncultured microbial lineages from a custom-curated genome database. On average, 41.4% of the variation in COG-FC relative abundance is explained by taxonomic rank, with domain, phylum, class, order, family, and genus explaining, on average, 3.2%, 14.6%, 4.1%, 9.2%, 4.8%, and 5.5% of the variance, respectively (p<0.001 for all). We further used a variance component model to explore the relationship between taxonomic rank and variability of individual COG-FCs. We found that different taxonomic ranks had greater influence on specific COG-FC relative abundances; however, phylum had the greatest influence on average. Utilizing the average COG-FC compositions for individual genera, we extrapolated COG-FC compositions to global subsurface communities sampled with 16S amplicon sequencing. We note differences in COG-FC relative abundance, scaled by community structures, across different subsurface sediment environments. These results yield a more comprehensive understanding of the genomic composition across subsurface microbial communities. Authors: Taylor M. Royalty and Andrew D. Steen.
Taylor Royalty earned his B.S. in Biology from Western Carolina University and his M.S. in Atmospheric Science from North Carolina State University. He is currently working on his Ph.D. as a C-DEBI doctoral fellow with Dr. Andrew Steen at the University of Tennessee, Knoxville. His current research utilizes ‘omics’-based approaches to address questions related to theoretical and community microbial ecology, with an emphasis on subsurface microbial communities.