This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology

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Computational discovery and RT-PCR validation of novel Burkholderia conserved and Burkholderia pseudomallei unique sRNAs

Jia-Shiun Khoo12, Shiao-Fei Chai1, Rahmah Mohamed1, Sheila Nathan13 and Mohd Firdaus-Raih1*

Author Affiliations

1 School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia

2 Codon Genomics SB, Jalan Bandar 18, Pusat Bandar Puchong, Selangor Darul Ehsan, Malaysia

3 Malaysia Genome Institute, Jalan Bangi Lama, 43000 Kajang, Malaysia

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BMC Genomics 2012, 13(Suppl 7):S13  doi:10.1186/1471-2164-13-S7-S13

Published: 13 December 2012



The sRNAs of bacterial pathogens are known to be involved in various cellular roles including environmental adaptation as well as regulation of virulence and pathogenicity. It is expected that sRNAs may also have similar functions for Burkholderia pseudomallei, a soil bacterium that can adapt to diverse environmental conditions, which causes the disease melioidosis and is also able to infect a wide variety of hosts.


By integrating several proven sRNA prediction programs into a computational pipeline, available Burkholderia spp. genomes were screened to identify sRNA gene candidates. Orthologous sRNA candidates were then identified via comparative analysis. From the total prediction, 21 candidates were found to have Rfam homologs. RT-PCR and sequencing of candidate sRNA genes of unknown functions revealed six putative sRNAs which were highly conserved in Burkholderia spp. and two that were unique to B. pseudomallei present in a normal culture conditions transcriptome. The validated sRNAs include potential cis-acting elements associated with the modulation of methionine metabolism and one B. pseudomallei-specific sRNA that is expected to bind to the Hfq protein.


The use of the pipeline developed in this study and subsequent comparative analysis have successfully aided in the discovery and shortlisting of sRNA gene candidates for validation. This integrated approach identified 29 B. pseudomallei sRNA genes - of which 21 have Rfam homologs and 8 are novel.