Bacterial artificial chromosome fingerprint arrays for the differentiation of transcriptomic differences in...

Although microarray technology has become more widespread as a discovery tool for bacterial pathogenesis, it remains a method available only to laboratories with access to expensive equipment and costly analysis software. Mycobacterium tuberculosis, the causative agent for tuberculosis (TB), afflicts one-third of the global population, and kills between 2 and 3 million people per year. While the majority of cases of TB occur in developing areas of the world, facilities in these regions may not be able to support microarray analysis. Additionally, a major limitation of microarrays is that only genes on the array are being assayed. With acquired virulence and drug resistance in microbes, a method less dependent on a predetermined list of gene targets is advantageous. We present a method of expression analysis based on bacterial artificial chromosomes (BACs) that can be applied with standard laboratory equipment and free analysis software. This technique, bacterial artificial chromosome fingerprint arrays (BACFA), was developed and utilised to identify expression differences between intracellular strains of M. tuberculosis, one virulent (H37Rv) and one attenuated (H37Ra). Southern blots of restriction-enzyme digested BAC fragments were sequentially hybridised with strain-specific cDNA probes to generate expression profiles that were used to isolate expression differences in broth grown and intracellular bacteria. Repeat comparisons of intracellular profiles via BACFA identified genomic regions differentially expressed by the two strains. Quantitative real-time PCR was used to assess the genes located in these fragments in order to confirm or deny the differential regulation of genes. In total, we identified six genes that were differentially regulated between strains inside the host cell (pks2, aceE, Rv1571, and frdBCD). We report that BACFA is an effective technique in the expression analysis of bacteria and can be considered complementary to the high-throughput analysis offered by microarrays.