TITLE:
Improved Method for Isolation of Microbial RNA from Biofuel Feedstock for Metatranscriptomics
AUTHORS:
Hailan Piao, Lye Meng Markillie, David E. Culley, Roderick I. Mackie, Matthias Hess
KEYWORDS:
RNA Extraction; Biofuels; CAZymes; Metatranscriptomics; Systems Microbiology; Microbial Ecology
JOURNAL NAME:
Advances in Microbiology,
Vol.3 No.1,
March
28,
2013
ABSTRACT: Metatranscriptomics—gene express profiling via DNA sequencing—is a powerful tool to identify genes that are actively expressed and might contribute to the phenotype of individual organisms or the phenome (the sum of several phenotypes) of a microbial community. Furthermore, metatranscriptome studies can result in extensive catalogues of genes that encode for enzymes of industrial relevance. In both cases, a major challenge for generating a high quality metatranscriptome is the extreme lability of RNA and its susceptibility to ubiquitous RNAses. The microbial community (the microbiome) of the cow rumen efficiently degrades lignocelullosic biomass, generates significant amounts of methane, a greenhouse gas twenty times more potent than carbon dioxide, and is of general importance for the physiological wellbeing of the host animal. Metatranscriptomes of the rumen microbiome from animals kept under different conditions and from various types of rumen-incubated biomass can be expected to provide new insights into these highly interesting phenotypes and subsequently provide the framework for an enhanced understanding of this socioeconomically important ecosystem. The ability to isolate large amounts of intact RNA will significantly facilitate accurate transcript annotation and expression profiling. Here we report a method that combines mechanical disruption with chemical homogenization of the sample material and consistently yields 1 mg of intact RNA from 1 g of rumen-incubated biofuel feedstock. The yield of total RNA obtained with our method exceeds the RNA yield achieved with previously reported isolation techniques, which renders RNA isolated with the method presented here as an ideal starting material for metatranscriptomic analyses and other molecular biology applications that require significant amounts of starting material.