Title |
Historical contingency and the gradual evolution of metabolic properties in central carbon and genome-scale metabolisms
|
---|---|
Published in |
BMC Systems Biology, April 2014
|
DOI | 10.1186/1752-0509-8-48 |
Pubmed ID | |
Authors |
Aditya Barve, Sayed-Rzgar Hosseini, Olivier C Martin, Andreas Wagner |
Abstract |
A metabolism can evolve through changes in its biochemical reactions that are caused by processes such as horizontal gene transfer and gene deletion. While such changes need to preserve an organism's viability in its environment, they can modify other important properties, such as a metabolism's maximal biomass synthesis rate and its robustness to genetic and environmental change. Whether such properties can be modulated in evolution depends on whether all or most viable metabolisms - those that can synthesize all essential biomass precursors - are connected in a space of all possible metabolisms. Connectedness means that any two viable metabolisms can be converted into one another through a sequence of single reaction changes that leave viability intact. If the set of viable metabolisms is disconnected and highly fragmented, then historical contingency becomes important and restricts the alteration of metabolic properties, as well as the number of novel metabolic phenotypes accessible in evolution. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 20% |
Ireland | 1 | 20% |
Switzerland | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 60% |
Members of the public | 2 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Portugal | 1 | 2% |
Germany | 1 | 2% |
Netherlands | 1 | 2% |
France | 1 | 2% |
Brazil | 1 | 2% |
Canada | 1 | 2% |
Singapore | 1 | 2% |
United States | 1 | 2% |
Unknown | 48 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 25% |
Student > Ph. D. Student | 11 | 20% |
Student > Master | 6 | 11% |
Professor | 5 | 9% |
Student > Doctoral Student | 4 | 7% |
Other | 11 | 20% |
Unknown | 5 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 25 | 45% |
Biochemistry, Genetics and Molecular Biology | 10 | 18% |
Social Sciences | 2 | 4% |
Computer Science | 2 | 4% |
Chemistry | 2 | 4% |
Other | 6 | 11% |
Unknown | 9 | 16% |