Prediction of novel non-coding RNAs relevant for the growth of Pseudomonas putida in a bioreactor

• Published in: Microbiology (Society for General Microbiology) 2020-02, Vol.166 (2), p.149-156
• Main Authors: Pobre, Vânia, Graça-Lopes, Gil, Saramago, Margarida, Ankenbauer, Andreas, Takors, Ralf, Arraiano, Cecília M, Viegas, Sandra C
• Format: Article
• Language: English
• Subjects: Bioreactors - microbiology; Gene Expression Regulation, Bacterial; Genome, Bacterial - genetics; Pseudomonas putida - genetics; Pseudomonas putida - growth & development; Pseudomonas putida - metabolism; Pseudomonas putida - physiology; RNA, Bacterial - classification; RNA, Bacterial - genetics; RNA, Bacterial - metabolism; RNA, Untranslated - classification; RNA, Untranslated - genetics; RNA, Untranslated - metabolism; Sequence Analysis, RNA; Stress, Physiological
• ISSN: 1350-0872; 1465-2080
• DOI: 10.1099/mic.0.000875

is a micro-organism with great potential for industry due to its stress-endurance traits and easy manipulation of the metabolism. However, optimization is still required to improve production yields. In the last years, manipulation of bacterial small non-coding RNAs (ncRNAs) has been recognized as an effective tool to improve the production of industrial compounds. So far, very few ncRNAs are annotated in beyond the generally conserved. In the present study, was cultivated in a two-compartment scale-down bioreactor that simulates large-scale industrial bioreactors. We performed RNA-Seq of samples collected at distinct locations and time-points to predict novel and potentially important ncRNAs for the adaptation of to bioreactor stress conditions. Instead of using a purely genomic approach, we have rather identified regions of putative ncRNAs with high expression levels using two different programs (Artemis and sRNA detect). Only the regions identified with both approaches were considered for further analysis and, in total, 725 novel ncRNAs were predicted. We also found that their expression was not constant throughout the bioreactor, showing different patterns of expression with time and position. This is the first work focusing on the ncRNAs whose expression is triggered in a bioreactor environment. This information is of great importance for industry, since it provides possible targets to engineer more effective strains for large-scale production.