Kinetic Modeling and Meta-Analysis of the Bacillus subtilis SigB Regulon during Spore Germination and Outgrowth

0541594 - MBÚ 2022 RIV CH eng J - Článek v odborném periodiku
Vohradský, Jiří - Schwarz, Marek - Ramaniuk, Olga - Ruiz-Larrabeiti, Olatz - Vaňková Hausnerová, Viola - Šanderová, Hana - Krásný, Libor
Kinetic Modeling and Meta-Analysis of the Bacillus subtilis SigB Regulon during Spore Germination and Outgrowth.
Microorganisms. Roč. 9, č. 1 (2021). E-ISSN 2076-2607
Grant CEP: GA MŠMT(CZ) LM2018131; GA MŠMT(CZ) EF16_013/0001777; GA ČR(CZ) GA20-12109S
Institucionální podpora: RVO:61388971
Klíčová slova: Bacillus subtilis * SigB * gene regulatory networks * computational modeling * promoter sequence analysis
Obor OECD: Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology
Impakt faktor: 4.926, rok: 2021
Způsob publikování: Open access
https://www.mdpi.com/2076-2607/9/1/112

The exponential increase in the number of conducted studies combined with the development of sequencing methods have led to an enormous accumulation of partially processed experimental data in the past two decades. Here, we present an approach using literature-mined data complemented with gene expression kinetic modeling and promoter sequence analysis. This approach allowed us to identify the regulon of Bacillus subtilis sigma factor SigB of RNA polymerase (RNAP) specifically expressed during germination and outgrowth. SigB is critical for the cell's response to general stress but is also expressed during spore germination and outgrowth, and this specific regulon is not known. This approach allowed us to (i) define a subset of the known SigB regulon controlled by SigB specifically during spore germination and outgrowth, (ii) identify the influence of the promoter sequence binding motif organization on the expression of the SigB-regulated genes, and (iii) suggest additional sigma factors co-controlling other SigB-dependent genes. Experiments then validated promoter sequence characteristics necessary for direct RNAP-SigB binding. In summary, this work documents the potential of computational approaches to unravel new information even for a well-studied system, moreover, the study specifically identifies the subset of the SigB regulon, which is activated during germination and outgrowth.
Trvalý link: http://hdl.handle.net/11104/0319132