Predicting Selective RNA Processing and Stabilization Operons in Clostridium spp.

In selective RNA processing and stabilization (SRPS) operons, stem-loops (SLs) located at the 3 '-UTR region of selected genes can control the stability of the corresponding transcripts and determine the stoichiometry of the operon. Here, for such operons, we developed a computational approach named SLOFE (stem-loop free energy) that identifies the SRPS operons and predicts their transcript- and protein-level stoichiometry at the whole-genome scale using only the genome sequence via the minimum free energy (Delta G) of specific SLs in the intergenic regions within operons. As validated by the experimental approach of differential RNA-Seq, SLOFE identifies genome-wide SRPS operons in Clostridium cellulolyticum with 80% accuracy and reveals that the SRPS mechanism contributes to diverse cellular activities. Moreover, in the identified SRPS operons, SLOFE predicts the transcript- and protein-level stoichiometry, including those encoding cellulosome complexes, ATP synthases, ABC transporter family proteins, and ribosomal proteins. Its accuracy exceeds those of existing in silico approaches in C. cellulolyticum, Clostridium acetobutylicum, Clostridium thermocellum, and Bacillus subtilis. The ability to identify genome-wide SRPS operons and predict their stoichiometry via DNA sequence in silico should facilitate studying the function and evolution of SRPS operons in bacteria.

Automated summary

The computational approach SLOFE can identify SRPS operons and predict their stoichiometry at a genome-wide scale using only DNA sequence, achieving an 80% accuracy in identifying SRPS operons in Clostridium cellulolyticum. SLOFE predicts transcript- and protein-level stoichiometry in operons encoding cellulosome complexes, ATP synthases, ABC transporter family proteins, and ribosomal proteins, surpassing existing in silico approaches in several bacteria species.