Operon Structure Inference in Clostridium beijerinckii NRRL B-589 using RNA-Seq

Operon Structure Inference in Clostridium beijerinckii NRRL B-589 using RNA-Seq

Paper in proceedings (conference paper)

Current operon structure inference relies on the utilization of online tools that provide predictions based on knowledge of the intergenic distance of neighboring genes as well as the functional relationships of their protein products. This approach is not sufficient for an accurate inference of operon structure as no information regarding co-expression of genes is considered. Moreover, such predictions are cumbersome in non-model organisms as relationships among their proteins are not known. The combination of wet lab data and data from web services using database searches can, however, greatly improve in silico inference of operon structure in individual bacterial or archaeal genomes. Current research in biotechnology is aimed mostly at non-model organisms for their various phenotypic traits. An example can be found in the strain Clostridium beijerinckii NRRL B-598, a non-model butanol producer whose phenotype still needs to be explained on the molecular level. We used the complete genome sequence of the strain (available from the NCBI GenBank database under the accession no. CP011966.3) and predicted the operon structure for its 5,442 total genes using the online tool, Operon-mapper. Subsequently, we took 3,351 predicted operons and verified their co-expression using data from our previous transcriptomic studies. These included 36 samples of genome-wide transcriptomes of the strain, under various conditions, gathered using RNA-Seq technology. Finally, we were able to adjust predicted operons according to their co-expression.

Current operon structure inference relies on the utilization of online tools that provide predictions based on knowledge of the intergenic distance of neighboring genes as well as the functional relationships of their protein products. This approach is not sufficient for an accurate inference of operon structure as no information regarding co-expression of genes is considered. Moreover, such predictions are cumbersome in non-model organisms as relationships among their proteins are not known. The combination of wet lab data and data from web services using database searches can, however, greatly improve in silico inference of operon structure in individual bacterial or archaeal genomes. Current research in biotechnology is aimed mostly at non-model organisms for their various phenotypic traits. An example can be found in the strain Clostridium beijerinckii NRRL B-598, a non-model butanol producer whose phenotype still needs to be explained on the molecular level. We used the complete genome sequence of the strain (available from the NCBI GenBank database under the accession no. CP011966.3) and predicted the operon structure for its 5,442 total genes using the online tool, Operon-mapper. Subsequently, we took 3,351 predicted operons and verified their co-expression using data from our previous transcriptomic studies. These included 36 samples of genome-wide transcriptomes of the strain, under various conditions, gathered using RNA-Seq technology. Finally, we were able to adjust predicted operons according to their co-expression.

Clostridium beijerinckii; bioinformatics; functional annotation

Clostridium beijerinckii; bioinformatics; functional annotation

SCHWARZEROVÁ, J.; MUSILOVÁ, J.; JUREČKOVÁ, K.; BRANSKÁ, B.; PROVAZNÍK, I.; PATÁKOVÁ, P.; SEDLÁŘ, K.

2022

30.09.2021

978-80-88307-08-2

8th International Conference on Chemical Technology

284

289

6

http://hdl.handle.net/