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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 (Δ 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.

Predicting Selective RNA Processing and Stabilization Operons in Clostridium spp.