Acidobacteria are ubiquitous and abundant members of soil bacterial communities. However, an ecological understanding of this important phylum has remained elusive because its members have been difficult to culture and few molecular investigations have focused exclusively on this group. We generated an unprecedented number of acidobacterial DNA sequence data using pyrosequencing and clone libraries (39 707 and 1787 sequences, respectively) to characterize the relative abundance, diversity and composition of acidobacterial communities across a range of soil types. To gain insight into the ecological characteristics of acidobacterial taxa, we investigated the large-scale biogeographic patterns exhibited by acidobacterial communities, and related soil and site characteristics to acidobacterial community assemblage patterns. The 87 soils analyzed by pyrosequencing contained more than 8600 unique acidobacterial phylotypes (at the 97% sequence similarity level). One phylotype belonging to Acidobacteria subgroup 1, but not closely related to any cultured representatives, was particularly abundant, accounting for 7.4% of bacterial sequences and 17.6% of acidobacterial sequences, on average, across the soils. The abundance of Acidobacteria relative to other bacterial taxa was highly variable across the soils examined, but correlated strongly with soil pH (R=−0.80, P<0.001). Soil pH was also the best predictor of acidobacterial community composition, regardless of how the communities were characterized, and the relative abundances of the dominant Acidobacteria subgroups were readily predictable. Acidobacterial communities were more phylogenetically clustered as soil pH departed from neutrality, suggesting that pH is an effective habitat filter, restricting community membership to progressively more narrowly defined lineages as pH deviates from neutrality.

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.