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Historical contingency and the gradual evolution of metabolic properties in central carbon and genome-scale metabolisms.

Barve A, Hosseini SR, Martin OC, Wagner A - BMC Syst Biol (2014)

Bottom Line: Where this is not the case, alternative essential metabolic pathways consisting of multiple reactions are responsible, but such pathways are not common.Metabolism is thus highly evolvable, in the sense that its properties could be fine-tuned by successively altering individual reactions.Historical contingency does not strongly restrict the origin of novel metabolic phenotypes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Evolutionary Biology and Environmental Sciences, University of Zurich, Bldg, Y27, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland. andreas.wagner@ieu.uzh.ch.

ABSTRACT

Background: 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.

Results: We here computationally explore two vast spaces of possible metabolisms to ask whether viable metabolisms are connected. We find that for all but the simplest metabolisms, most viable metabolisms can be transformed into one another by single viability-preserving reaction changes. Where this is not the case, alternative essential metabolic pathways consisting of multiple reactions are responsible, but such pathways are not common.

Conclusions: Metabolism is thus highly evolvable, in the sense that its properties could be fine-tuned by successively altering individual reactions. Historical contingency does not strongly restrict the origin of novel metabolic phenotypes.

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Related in: MedlinePlus

The number of viable metabolisms V(n) decreases as the number of reactions n decreases. (A) The vertical axis (note the logarithmic scale) shows the number of genotypes, and the horizontal axis shows the number n of reactions in a potential metabolism. Black circles represent the number of genotypes in genotype space Ω(n) (regardless of viability), grey circles show the number of potential metabolisms viable on glucose, whereas the blue circles denote the number of potential metabolisms viable on all 10 carbon sources. (B) The vertical axis (note the logarithmic scale) shows the fraction /V(n)/ //Ω(n)/. The grey circles show the fraction of genotypes viable on glucose relative to the number of possible metabolisms, whereas the blue circles denote the fraction of genotypes viable on 10 carbon sources relative to the number of possible metabolisms. Note that viable genotypes become extremely rare as the number of reactions in a metabolism decreases. Data for both figures is based on all viable metabolisms for each n (Additional file 3 and Additional file 8).
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Figure 1: The number of viable metabolisms V(n) decreases as the number of reactions n decreases. (A) The vertical axis (note the logarithmic scale) shows the number of genotypes, and the horizontal axis shows the number n of reactions in a potential metabolism. Black circles represent the number of genotypes in genotype space Ω(n) (regardless of viability), grey circles show the number of potential metabolisms viable on glucose, whereas the blue circles denote the number of potential metabolisms viable on all 10 carbon sources. (B) The vertical axis (note the logarithmic scale) shows the fraction /V(n)/ //Ω(n)/. The grey circles show the fraction of genotypes viable on glucose relative to the number of possible metabolisms, whereas the blue circles denote the fraction of genotypes viable on 10 carbon sources relative to the number of possible metabolisms. Note that viable genotypes become extremely rare as the number of reactions in a metabolism decreases. Data for both figures is based on all viable metabolisms for each n (Additional file 3 and Additional file 8).

Mentions: Figure 1A shows the number of viable metabolisms V(n) (grey circles), together with the number of all metabolisms (black circles, Ω(n) = ) as a function of the number n of reactions. Note the logarithmic vertical axis. The number of viable metabolisms has a maximum at n = 37 with a total of 2.39 x 108 metabolisms, while the minimum size of a viable metabolism, i.e., the smallest n such that V(n) > 0 is 23 (Additional file 3). This means that at least 23 reactions are required to synthesize all 13 biomass precursors on glucose. There are three such smallest metabolisms, one of which is shown in Additional file 4. Figure 1B expresses V(n) as a fraction of the number of metabolisms Ω(n) (grey circles), and shows that this fraction decreases with decreasing n. This means that random sampling is much less likely to yield a viable metabolism for small than for large metabolisms. For the smallest n with viable metabolisms (n = 23), the three viable potential metabolisms correspond to a fraction 10-14 of all metabolisms of size 23. The largest viable metabolism contains all n = 51 reactions.


Historical contingency and the gradual evolution of metabolic properties in central carbon and genome-scale metabolisms.

Barve A, Hosseini SR, Martin OC, Wagner A - BMC Syst Biol (2014)

The number of viable metabolisms V(n) decreases as the number of reactions n decreases. (A) The vertical axis (note the logarithmic scale) shows the number of genotypes, and the horizontal axis shows the number n of reactions in a potential metabolism. Black circles represent the number of genotypes in genotype space Ω(n) (regardless of viability), grey circles show the number of potential metabolisms viable on glucose, whereas the blue circles denote the number of potential metabolisms viable on all 10 carbon sources. (B) The vertical axis (note the logarithmic scale) shows the fraction /V(n)/ //Ω(n)/. The grey circles show the fraction of genotypes viable on glucose relative to the number of possible metabolisms, whereas the blue circles denote the fraction of genotypes viable on 10 carbon sources relative to the number of possible metabolisms. Note that viable genotypes become extremely rare as the number of reactions in a metabolism decreases. Data for both figures is based on all viable metabolisms for each n (Additional file 3 and Additional file 8).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4022055&req=5

Figure 1: The number of viable metabolisms V(n) decreases as the number of reactions n decreases. (A) The vertical axis (note the logarithmic scale) shows the number of genotypes, and the horizontal axis shows the number n of reactions in a potential metabolism. Black circles represent the number of genotypes in genotype space Ω(n) (regardless of viability), grey circles show the number of potential metabolisms viable on glucose, whereas the blue circles denote the number of potential metabolisms viable on all 10 carbon sources. (B) The vertical axis (note the logarithmic scale) shows the fraction /V(n)/ //Ω(n)/. The grey circles show the fraction of genotypes viable on glucose relative to the number of possible metabolisms, whereas the blue circles denote the fraction of genotypes viable on 10 carbon sources relative to the number of possible metabolisms. Note that viable genotypes become extremely rare as the number of reactions in a metabolism decreases. Data for both figures is based on all viable metabolisms for each n (Additional file 3 and Additional file 8).
Mentions: Figure 1A shows the number of viable metabolisms V(n) (grey circles), together with the number of all metabolisms (black circles, Ω(n) = ) as a function of the number n of reactions. Note the logarithmic vertical axis. The number of viable metabolisms has a maximum at n = 37 with a total of 2.39 x 108 metabolisms, while the minimum size of a viable metabolism, i.e., the smallest n such that V(n) > 0 is 23 (Additional file 3). This means that at least 23 reactions are required to synthesize all 13 biomass precursors on glucose. There are three such smallest metabolisms, one of which is shown in Additional file 4. Figure 1B expresses V(n) as a fraction of the number of metabolisms Ω(n) (grey circles), and shows that this fraction decreases with decreasing n. This means that random sampling is much less likely to yield a viable metabolism for small than for large metabolisms. For the smallest n with viable metabolisms (n = 23), the three viable potential metabolisms correspond to a fraction 10-14 of all metabolisms of size 23. The largest viable metabolism contains all n = 51 reactions.

Bottom Line: Where this is not the case, alternative essential metabolic pathways consisting of multiple reactions are responsible, but such pathways are not common.Metabolism is thus highly evolvable, in the sense that its properties could be fine-tuned by successively altering individual reactions.Historical contingency does not strongly restrict the origin of novel metabolic phenotypes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Evolutionary Biology and Environmental Sciences, University of Zurich, Bldg, Y27, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland. andreas.wagner@ieu.uzh.ch.

ABSTRACT

Background: 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.

Results: We here computationally explore two vast spaces of possible metabolisms to ask whether viable metabolisms are connected. We find that for all but the simplest metabolisms, most viable metabolisms can be transformed into one another by single viability-preserving reaction changes. Where this is not the case, alternative essential metabolic pathways consisting of multiple reactions are responsible, but such pathways are not common.

Conclusions: Metabolism is thus highly evolvable, in the sense that its properties could be fine-tuned by successively altering individual reactions. Historical contingency does not strongly restrict the origin of novel metabolic phenotypes.

Show MeSH
Related in: MedlinePlus