Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida
Abstract The genome-scale model of metabolism and gene expression (ME-model) for Pseudomonas putida KT2440, iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model, iPpu1676-ME significantly expands on gene expression, ma...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-025-00521-1 |
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| author | Juan D. Tibocha-Bonilla Vishant Gandhi Chloe Lieng Oriane Moyne Rodrigo Santibáñez-Palominos Karsten Zengler |
| author_facet | Juan D. Tibocha-Bonilla Vishant Gandhi Chloe Lieng Oriane Moyne Rodrigo Santibáñez-Palominos Karsten Zengler |
| author_sort | Juan D. Tibocha-Bonilla |
| collection | DOAJ |
| description | Abstract The genome-scale model of metabolism and gene expression (ME-model) for Pseudomonas putida KT2440, iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model, iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization in P. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus, iPpu1676-ME offers valuable insights into P. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism. |
| format | Article |
| id | doaj-art-ae0a3153aa7e43b9812382c86ffcb44d |
| institution | Kabale University |
| issn | 2056-7189 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj-art-ae0a3153aa7e43b9812382c86ffcb44d2025-08-20T03:48:18ZengNature Portfolionpj Systems Biology and Applications2056-71892025-05-011111910.1038/s41540-025-00521-1Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putidaJuan D. Tibocha-Bonilla0Vishant Gandhi1Chloe Lieng2Oriane Moyne3Rodrigo Santibáñez-Palominos4Karsten Zengler5Bioinformatics and Systems Biology Graduate Program, University of California, San DiegoDepartment of Bioengineering, University of California, San DiegoDepartment of Pediatrics, University of California, San DiegoDepartment of Pediatrics, University of California, San DiegoDepartment of Pediatrics, University of California, San DiegoDepartment of Bioengineering, University of California, San DiegoAbstract The genome-scale model of metabolism and gene expression (ME-model) for Pseudomonas putida KT2440, iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model, iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization in P. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus, iPpu1676-ME offers valuable insights into P. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism.https://doi.org/10.1038/s41540-025-00521-1 |
| spellingShingle | Juan D. Tibocha-Bonilla Vishant Gandhi Chloe Lieng Oriane Moyne Rodrigo Santibáñez-Palominos Karsten Zengler Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida npj Systems Biology and Applications |
| title | Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida |
| title_full | Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida |
| title_fullStr | Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida |
| title_full_unstemmed | Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida |
| title_short | Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida |
| title_sort | model of metabolism and gene expression predicts proteome allocation in pseudomonas putida |
| url | https://doi.org/10.1038/s41540-025-00521-1 |
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