596588 Efficient and Cost-Effective Bacterial mRNA Sequencing from Low Input Samples through Ribosomal RNA Depletion (Industry Candidate)

Wednesday, November 18, 2020
Food, Pharmaceutical & Bioengineering Division (15) (PreRecorded+)
Chatarin Wangsanuwat1,2, Kellie Heom1,2, Estella Liu1, Michelle O'Malley1,2 and Siddharth S. Dey1,2,3, (1)Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, (2)Center for Bioengineering, University of California, Santa Barbara, Santa Barbara, CA, (3)Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA

RNA sequencing provides 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 prevents efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Further, bacterial cells frequently contain 100-fold lower RNA than mammalian cells. Therefore, samples derived from non-cultivable and non-model bacterial species can have limiting starting amounts of total RNA, necessitating efficient amplification of small quantities of RNA. To overcome these limitations, we report EMBR-Seq (Enrichment of mRNA by Blocked rRNA Sequencing), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification, resulting in greater than 80% of the sequenced molecules 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 employs a single oligonucleotide per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to commercial kits, we show that EMBR-Seq successfully quantifies the transcriptome from 500-fold lower starting total RNA. Thus, EMBR-Seq provides an efficient and cost-effective approach to measure global gene expression profiles from low input bacterial samples.

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