Microarray analysis of defined Mycobacterium tuberculosis populations using RNA amplification strategies
Medical Microbiology, Centre for Infection, Division of Cellular & Molecular Medicine, St. George's University of London, Cranmer Terrace, Tooting, London, UK
BMC Genomics 2008, 9:94 doi:10.1186/1471-2164-9-94Published: 25 February 2008
The amplification of bacterial RNA is required if complex host-pathogen interactions are to be studied where the recovery of bacterial RNA is limited. Here, using a whole genome Mycobacterium tuberculosis microarray to measure cross-genome representation of amplified mRNA populations, we have investigated two approaches to RNA amplification using different priming strategies. The first using oligo-dT primers after polyadenylation of the bacterial RNA, the second using a set of mycobacterial amplification-directed primers both linked to T7 polymerase in vitro run off transcription.
The reproducibility, sensitivity, and the representational bias introduced by these amplification systems were examined by contrasting expression profiles of the amplified products from inputs of 500, 50 and 5 ng total M. tuberculosis RNA with unamplified RNA from the same source. In addition, as a direct measure of the effectiveness of bacterial amplification for identifying biologically relevant changes in gene expression, a model M. tuberculosis system of microaerophilic growth and non-replicating persistence was used to assess the capability of amplified RNA microarray comparisons. Mycobacterial RNA was reproducibly amplified using both methods from as little as 5 ng total RNA (~equivalent to 2 × 105 bacilli). Differential gene expression patterns observed with unamplified RNA in the switch from aerobic to microaerophilic growth were also reflected in the amplified expression profiles using both methods.
Here we describe two reproducible methods of bacterial RNA amplification that will allow previously intractable host-pathogen interactions during bacterial infection to be explored at the whole genome level by RNA profiling.