ArticleNucleic acids research2022
Machine learning from Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators.
Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 40 citations in OpenAlex.
- Regulatory and metabolic control of microbial biosynthetic gene clusters.Communications biology · 2026Review
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- The transcriptional regulatory network of the Escherichia coli MG1655 reference strain.Nucleic acids research · 2026Article
- iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets.Nucleic acids research · 2025Article
- Thermodynamic modeling of RsmA - mRNA interactions capture novel direct binding across theFrontiers in molecular biosciences · 2025Article
- Machine-Learning Analysis of Streptomyces coelicolor Transcriptomes Reveals a Transcription Regulatory Network Encompassing Biosynthetic Gene Clusters.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Modulating bacterial function utilizing A knowledge base of transcriptional regulatory modules.Nucleic acids research · 2024Article
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.Nature communications · 2024Article
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- Identification ofVirulence · 2023Article
- A multi-scale expression and regulation knowledge base for Escherichia coli.Nucleic acids research · 2023Article
- Machine learning uncovers themSystems · 2023Article
- Transcriptome-wide marker gene expression analysis of stress-responsive sulfate-reducing bacteria.Scientific reports · 2023Article
- Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance.Cell reports · 2023Article
- The transcriptional regulators of virulence forGenes & diseases · 2023Review
- The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions.Research square · 2023Article
- Computationally Efficient Assembly of Pseudomonas aeruginosa Gene Expression Compendia.mSystems · 2023Article
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- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.bioRxiv : the preprint server for biology · 2023Article
- Imaging biofilms using fluorescenceFrontiers in cellular and infection microbiology · 2023Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
The transcriptional regulatory network (TRN) of Pseudomonas aeruginosa coordinates cellular processes in response to stimuli. We used 364 transcriptomes (281 publicly available + 83 in-house generated) to reconstruct the TRN of P. aeruginosa using independent component analysis. We identified 104 independently modulated sets of genes (iModulons) among which 81 reflect the effects of known transcriptional regulators. We identified iModulons that (i) play an important role in defining the genomic boundaries of biosynthetic gene clusters (BGCs), (ii) show increased expression of the BGCs and associated secretion systems in nutrient conditions that are important in cystic fibrosis, (iii) show the presence of a novel ribosomally synthesized and post-translationally modified peptide (RiPP) BGC which might have a role in P. aeruginosa virulence, (iv) exhibit interplay of amino acid metabolism regulation and central metabolism across different carbon sources and (v) clustered according to their activity changes to define iron and sulfur stimulons. Finally, we compared the identified iModulons of P. aeruginosa with those previously described in Escherichia coli to observe conserved regulons across two Gram-negative species. This comprehensive TRN framework encompasses the majority of the transcriptional regulatory machinery in P. aeruginosa, and thus should prove foundational for future research into its physiological functions.
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