Spontaneous reaction silencing in metabolic optimization.
Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we pre...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2008-12-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC2582435?pdf=render |
| _version_ | 1819231782751436800 |
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| author | Takashi Nishikawa Natali Gulbahce Adilson E Motter |
| author_facet | Takashi Nishikawa Natali Gulbahce Adilson E Motter |
| author_sort | Takashi Nishikawa |
| collection | DOAJ |
| description | Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical nonoptimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function. |
| first_indexed | 2024-12-23T11:50:26Z |
| format | Article |
| id | doaj.art-7f7b0ecd8e1e4bf99c3ab2a099d65c42 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-23T11:50:26Z |
| publishDate | 2008-12-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-7f7b0ecd8e1e4bf99c3ab2a099d65c422022-12-21T17:48:13ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582008-12-01412e100023610.1371/journal.pcbi.1000236Spontaneous reaction silencing in metabolic optimization.Takashi NishikawaNatali GulbahceAdilson E MotterMetabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical nonoptimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.http://europepmc.org/articles/PMC2582435?pdf=render |
| spellingShingle | Takashi Nishikawa Natali Gulbahce Adilson E Motter Spontaneous reaction silencing in metabolic optimization. PLoS Computational Biology |
| title | Spontaneous reaction silencing in metabolic optimization. |
| title_full | Spontaneous reaction silencing in metabolic optimization. |
| title_fullStr | Spontaneous reaction silencing in metabolic optimization. |
| title_full_unstemmed | Spontaneous reaction silencing in metabolic optimization. |
| title_short | Spontaneous reaction silencing in metabolic optimization. |
| title_sort | spontaneous reaction silencing in metabolic optimization |
| url | http://europepmc.org/articles/PMC2582435?pdf=render |
| work_keys_str_mv | AT takashinishikawa spontaneousreactionsilencinginmetabolicoptimization AT nataligulbahce spontaneousreactionsilencinginmetabolicoptimization AT adilsonemotter spontaneousreactionsilencinginmetabolicoptimization |