Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes. Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages.

High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With metatran- scriptomics, it is possible to interrogate the transcriptomes of multiple organisms si- multaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe rela- tionships between gene expression levels and community characteristics. How- ever, metatranscriptomic data sets contain a rich suite of additional information that is just beginning to be explored. Here, we focus on antisense expression in meta- transcriptomics, discuss the different computational strategies for handling it, and highlight the strengths but also potentially detrimental effects on downstream anal- ysis and interpretation. We also analyzed the antisense transcriptomes of multiple genomes and metagenome-assembled genomes (MAGs) from five different data sets and found high variability in the levels of antisense transcription for individual spe- cies, which were consistent across samples. Importantly, we challenged the concep- tual framework that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from the combined effect of unknown biological and technical factors. Antisense transcription can be highly informative, including techni- cal details about data quality and novel insight into the biology of complex micro- bial communities.

We report eight genomes from representatives of the phylum Acidobacteriasubdivisions 1 and 3, isolated from soils. The genome sizes range from 4.9 to 6.7 Mb. Genomic analysis reveals putative genes for low- and high-affinity respiratory oxygen reductases, high-affinity hydrogenases, and the capacity to use a diverse collection of carbohydrates.