mSystems (Feb 2021)
Transcription Inhibitors with XRE DNA-Binding and Cupin Signal-Sensing Domains Drive Metabolic Diversification in <italic toggle="yes">Pseudomonas</italic>
Abstract
ABSTRACT Transcription factors (TFs) are instrumental in the bacterial response to new environmental conditions. They can act as direct signal sensors and subsequently induce changes in gene expression leading to physiological adaptation. Here, by combining transcriptome sequencing (RNA-seq) and cistrome determination (DAP-seq), we studied a family of eight TFs in Pseudomonas aeruginosa. This family, encompassing TFs with XRE-like DNA-binding and cupin signal-sensing domains, includes the metabolic regulators ErfA, PsdR, and PauR and five so-far-unstudied TFs. The genome-wide delineation of their regulons identified 39 regulatory interactions with genes mostly involved in metabolism. We found that the XRE-cupin TFs are inhibitors of their neighboring genes, forming local, functional units encoding proteins with functions in condition-specific metabolic pathways. Growth phenotypes of isogenic mutants highlighted new roles for PauR and PA0535 in polyamines and arginine metabolism. The phylogenetic analysis of this family of regulators across the bacterial kingdom revealed a wide diversity of such metabolic regulatory modules and identified species with potentially higher metabolic versatility. Numerous genes encoding uncharacterized XRE-cupin TFs were found near metabolism-related genes, illustrating the need of further systematic characterization of transcriptional regulatory networks in order to better understand the mechanisms of bacterial adaptation to new environments. IMPORTANCE Bacteria of the Pseudomonas genus, including the major human pathogen Pseudomonas aeruginosa, are known for their complex regulatory networks and high number of transcription factors, which contribute to their impressive adaptive ability. However, even in the most studied species, most of the regulators are still uncharacterized. With the recent advances in high-throughput sequencing methods, it is now possible to fill this knowledge gap and help the understanding of how bacteria adapt and thrive in new environments. By leveraging these methods, we provide an example of a comprehensive analysis of an entire family of transcription factors and bring new insights into metabolic and regulatory adaptation in the Pseudomonas genus.
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