mSystemsGenomicsPeer-reviewed journal article
Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures
Kellie A. HeomiD, Chatarin WangsanuwatiD, Lazarina V. ButkovichiD, Scott C. Tam, Annette R. RoweiD, Michelle Ann O'MalleyiD, Siddharth S. DeyiD
Abstract
Bacterial mRNA sequencing is inefficient due to the abundance of ribosomal RNA that is challenging to deplete. While commercial kits target rRNA from common bacterial species, they are frequently inefficient when applied to divergent species, including those from environmental isolates. Similarly, other methods typically employ large probe sets that tile the entire length of rRNAs; however, such approaches are infeasible when applied to many species. Therefore, we present EMBR-seq+, which requires fewer than ten oligonucleotides per rRNA by combining rRNA blocking primers with RNase H-mediated depletion to achieve rRNA removal efficiencies of up to 99% in diverse bacterial species. Further, in more complex microbial co-cultures between F. succinogenes strain UWB7 and anerobic fungi, EMBR-seq+ depleted both bacterial and fungal rRNA, with a 4-fold improvement in bacterial rRNA depletion compared to a commercial kit, thereby demonstrating that the method can be applied to non-model microbial mixtures. Notably, for microbes with unknown rRNA sequences, EMBR-seq+ enables rapid iterations in probe design without requiring to start experiments from total RNA. Finally, efficient depletion of rRNA enabled systematic quantification of the reprogramming of the bacterial transcriptome when cultured in the presence of the anerobic fungi Anaeromyces robustus or Caecomyces churrovis. We observed that F. succinogenes strain UWB7 downregulated several lignocellulose-degrading carbohydrate-active enzymes in the presence of anerobic gut fungi, suggesting close interactions between two cellulolytic species that specialize in different aspects of biomass breakdown. Thus, EMBR-seq+ enables efficient, cost-effective and rapid quantification of the transcriptome to gain insights into non-model microbial systems.
- organism: bacteria (other)
- assay: metagenomics
- research focus: variant calling
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: experimental assay
- Citations
- 6
- FWCI
- 0.53
- Field percentile
- top 43%
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