التفاصيل البيبلوغرافية
| العنوان: |
Minimisation of metabolic networks defines a new functional class of genes |
| المؤلفون: |
Giorgio Jansen, Tanda Qi, Vito Latora, Grigoris D. Amoutzias, Daniela Delneri, Stephen G. Oliver, Giuseppe Nicosia |
| المصدر: |
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024) |
| بيانات النشر: |
Nature Portfolio, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Science |
| مصطلحات موضوعية: |
Science |
| الوصف: |
Abstract Construction of minimal metabolic networks (MMNs) contributes both to our understanding of the origins of metabolism and to the efficiency of biotechnological processes by preventing the diversion of flux away from product formation. We have designed MMNs using a novel in silico synthetic biology pipeline that removes genes encoding enzymes and transporters from genome-scale metabolic models. The resulting minimal gene-set still ensures both viability and high growth rates. The composition of these MMNs has defined a new functional class of genes termed Network Efficiency Determinants (NEDs). These genes, whilst not essential, are very rarely eliminated in constructing an MMN, suggesting that it is difficult for metabolism to be re-routed to obviate the need for such genes. Moreover, the removal of NED genes from an MMN significantly reduces its global efficiency. Bioinformatic analyses of the NED genes have revealed that not only do these genes have more genetic interactions than the bulk of metabolic genes but their protein products also show more protein-protein interactions. In yeast, NED genes are predominantly single-copy and are highly conserved across evolutionarily distant organisms. These features confirm the importance of the NED genes to the metabolic network, including why they are so rarely excluded during minimisation. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2041-1723 |
| Relation: |
https://doaj.org/toc/2041-1723 |
| DOI: |
10.1038/s41467-024-52816-2 |
| URL الوصول: |
https://doaj.org/article/8ab333ea3ee945a3b246aaf74a5e8aa1 |
| رقم الانضمام: |
edsdoj.8ab333ea3ee945a3b246aaf74a5e8aa1 |
| قاعدة البيانات: |
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