PtrR (YneJ) is a novelE. colitranscription factor regulating the putrescine stress response and glutamate utilization

Abstract

Although polyamines, such as putrescine (Ptr), induce envelope stress for bacteria, they are important as nitrogen and carbon sources. Ptr utilization in Escherichia coli involves protein glutamylation, and glutamate stands at a crossroads between catabolism and anabolism. This communication reports that the transcription factor YneJ, here renamed PtrR, is involved in the regulation of a small regulatory RNA gene, fnrS, and an operon, yneIHGF, encoding succinatesemialdehyde dehydrogenase, Sad (YneI), glutaminase, GlsB (YneH), and several other genes.The yneI promoter is activated during putrescine utilization under nitrogen/carbon starvation conditions, and we show that PtrR is important for the putrescine stress response. It is also a repressor of fnrS gene expression, involved in the cascade regulation of mRNA synthesis for the marA and sodB genes, involved in antibiotic responses. PtrR transcriptional regulation of fnrS leads to a regulatory cascade induced by this small RNA that affects mRNA levels of ompF and the multidrug resistance regulator, MarA. We propose that PtrR functions as a dual activator/repressor, and that its regulation is important for the responses to different stress conditions involving L-glutamine/L-glutamate and putrescine utilization.

A multi-scale transcriptional regulatory network knowledge base forEscherichia coli

“…PRECISE elucidated the regulons for three previously uncharacterized TFs (YieP, YiaJ/PlaR, and YdhB/AdnB), and expanded the regulons of three known TFs (MetJ, CysB, and KdgR) (Sastry et al, 2019). Many of these regulatory interactions were confirmed through DNA-binding profiles (Rodionova et al, 2020a(Rodionova et al, , 2020bSastry et al, 2019). Furthermore, three novel regulons were predicted from iModulons derived from a microarray dataset (Sastry et al, 2021a).…”

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

“…iModulons exhibit significant overlap with classically defined regulons, allowing for their direct association to one or more known transcriptional regulators. In addition, iModulons have been used to discover new regulons or to refine existing regulons by adding new genes and removing false regulatory interactions ( 12 – 15 ). This is an advantage over traditional gene set enrichment analysis, which requires predefined gene sets that may not be accurate.…”

“…iModulons have been successfully identified for additional species and applied to disentangle the transcriptional trajectory of a Bacillus subtilis sporulation time course ( 18 ) and identify medium-specific transcriptional responses in Staphylococcus aureus ( 19 ). Since iModulons often contain genes of unknown function, one can formulate hypotheses to discover these gene functions in different organisms ( 14 , 15 , 18 ). iModulons thus provide both mechanistic understanding and a guide to discovery.…”

Machine Learning Uncovers a Data-Driven Transcriptional Regulatory Network for the Crenarchaeal Thermoacidophile Sulfolobus acidocaldarius

“…Furthermore, the condition-dependent activity levels of each iModulon correspond to the activity of the underlying genetic signals and regulators. Despite the difference in approach (i.e., data analytics vs. direct molecular methods), iModulons recapitulate many known regulons from the literature, and have accurately predicted new genetic targets for regulators ( Sastry et al, 2019 ; Poudel et al, 2020 ; Rychel et al, 2020 ) and elucidated gene functions ( Rodionova et al, 2020 , 2021 ). This top-down approach allows for an unbiased method for reconstructing the TRN of prokaryotic organisms of interest, including archaea.…”