ArticleNature communications2024
Advancing the scale of synthetic biology via cross-species transfer of cellular functions enabled by iModulon engraftment.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Transcriptional regulatory network differences between six industrialMetabolic engineering communications · 2026Article
- Review
- Disentangling factors affecting bacterial transcriptional regulatory network inference.iScience · 2026Article
- Roadmap for light interaction with biophotonic surfaces and their diverse applications.Journal of biomedical optics · 2026Article
- Dissecting host stress responses for predictable heterologous gene expression in E. coli.Nucleic acids research · 2026Article
- Article
- Transcriptional regulatory networks of the human gut symbiont Bacteroides thetaiotaomicron are uncovered using machine learning.Nucleic acids research · 2025Article
- Restructuring a Complex Genetic Function on Episomal Vectors inACS synthetic biology · 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
- Machine learning reveals the transcriptional regulatory network and circadian dynamics ofProceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Machine learning applied to large compendia of transcriptomic data has enabled the decomposition of bacterial transcriptomes to identify independently modulated sets of genes, such iModulons represent specific cellular functions. The identification of iModulons enables accurate identification of genes necessary and sufficient for cross-species transfer of cellular functions. We demonstrate cross-species transfer of: 1) the biotransformation of vanillate to protocatechuate, 2) a malonate catabolic pathway, 3) a catabolic pathway for 2,3-butanediol, and 4) an antimicrobial resistance to ampicillin found in multiple Pseudomonas species to Escherichia coli. iModulon-based engineering is a transformative strategy as it includes all genes comprising the transferred cellular function, including genes without functional annotation. Adaptive laboratory evolution was deployed to optimize the cellular function transferred, revealing mutations in the host. Combining big data analytics and laboratory evolution thus enhances the level of understanding of systems biology, and synthetic biology for strain design and development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.