Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures.

IMPORTANCE: Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities. Therefore, we developed EMBR-seq+, a method that requires fewer than 10 short oligonucleotides per rRNA to achieve up to 99% rRNA depletion in diverse bacterial species. Finally, EMBR-seq+ resulted in a deeper view of the transcriptome, enabling systematic quantification of how microbial interactions result in altering the transcriptional state of bacteria within co-cultures.

Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion.

BACKGROUND: RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification. RESULTS: EMBR-seq results in 90% of the sequenced RNA molecules from an E. coli culture deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq uses a single or a few oligonucleotides per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits for bacterial rRNA depletion, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA. CONCLUSIONS: EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.

Nature's recyclers: anaerobic microbial communities drive crude biomass deconstruction.

Microbial communities within anaerobic ecosystems have evolved to degrade and recycle carbon throughout the earth. A number of strains have been isolated from anaerobic microbial communities, which are rich in carbohydrate active enzymes (CAZymes) to liberate fermentable sugars from crude plant biomass (lignocellulose). However, natural anaerobic communities host a wealth of microbial diversity that has yet to be harnessed for biotechnological applications to hydrolyze crude biomass into sugars and value-added products. This review highlights recent advances in 'omics' techniques to sequence anaerobic microbial genomes, decipher microbial membership, and characterize CAZyme diversity in anaerobic microbiomes. With a focus on the herbivore rumen, we further discuss methods to discover new CAZymes, including those found within multi-enzyme fungal cellulosomes. Emerging techniques to characterize the interwoven metabolism and spatial interactions between anaerobes are also reviewed, which will prove critical to developing a predictive understanding of anaerobic communities to guide in microbiome engineering.