Computational Identification of Small RNAs in Clostridium Acetobutylicum and Prediction of mRNA Targets
Yili Chen, Dinesh Indurthi, Shawn Jones, and Eleftherios Terry Papoutsakis. Dept. of Chemical Engineering & Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way, Newark, DE 19711
Small non-coding bacterial RNAs (sRNAs) have been found in genomes of many model organisms. Many studies show that sRNAs play important regulatory roles in a variety of cellular processes in bacteria. Clostridium acetobutylicum is a gram-positive, rodshaped anaerobe that produces acetone, butanol and ethanol through fermentation of a variety of carbon sources. It regained interest for potential use in vehicle biofuel production. However, the transcriptional regulation of C. acetobutylicum has not been well understood and sRNA regulation is ignored in previous studies. We predicted sRNAs and their mRNA targets in C. acetobutylicum ATCC 824 with various computational approaches. The non-coding sRNAs were predicted in the intergenic regions of C. acetobutylicum ATCC 824 genome using an integrated computational method, sRNAPredict2. The prediction was followed by Q-RT-PCR and Northern blot validation. The mRNA targets of the validated sRNAs were then predicted by searching in the genome for strong sRNA-mRNA duplexes based on sequence match and the hybrid profile prediction. In summary, 133 sRNAs were predicted, 117 on the chromosome and 16 on the plasmid. Experiments verified the expression of 7 out of 15 randomly selected putative sRNAs. The study identified a group of highly conserved sRNAs that are associated with 16S Ribosomal RNA in genomic location. The high expression level of these sRNAs suggests their potentially important regulation function in C. acetobutylicum.