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Evolution of resource cycling in ecosystems and individuals.

Crombach A, Hogeweg P - BMC Evol. Biol. (2009)

Bottom Line: If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics.In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling.By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands. anton.crombach@gmail.com

ABSTRACT

Background: Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned?

Results: We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves.

Conclusion: In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

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Overview of the model. A. Individuals and resources are placed on a grid (size 100×100). Individuals consist of a genome, from which a network is computed. They compete for reproduction into empty grid sites by processing resources. B. The resource is a bit string of length 64. Maximally the first 8 bits can be sensed by a network, which then produces a sequence of bits at its output. The output is matched to the original bit string, and the length of the correct sequence (matching the bit string from the leftmost bit) is the raw score of the individual, which in this example is 13. If the individual reproduces, the resource is rotated from right to left for 13 bits and placed back in the grid site. C. The effect of a few types of mutation on the genome (left) and the topology of the network (right). By default the parameter values for each type of mutation are: gene duplication 16·10-4, deletion 24·10-4, binding specificity 4·10-4, gene expression threshold 4·10-4, binding site duplication 4·10-4, deletion 10·10-4, innovation 1·10-4, binding specificity 4·10-4, weight 4·10-4. In order to balance the growth of the network, we apply a small penalty per gene and binding site of pen = 2.5·10-5.
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Figure 1: Overview of the model. A. Individuals and resources are placed on a grid (size 100×100). Individuals consist of a genome, from which a network is computed. They compete for reproduction into empty grid sites by processing resources. B. The resource is a bit string of length 64. Maximally the first 8 bits can be sensed by a network, which then produces a sequence of bits at its output. The output is matched to the original bit string, and the length of the correct sequence (matching the bit string from the leftmost bit) is the raw score of the individual, which in this example is 13. If the individual reproduces, the resource is rotated from right to left for 13 bits and placed back in the grid site. C. The effect of a few types of mutation on the genome (left) and the topology of the network (right). By default the parameter values for each type of mutation are: gene duplication 16·10-4, deletion 24·10-4, binding specificity 4·10-4, gene expression threshold 4·10-4, binding site duplication 4·10-4, deletion 10·10-4, innovation 1·10-4, binding specificity 4·10-4, weight 4·10-4. In order to balance the growth of the network, we apply a small penalty per gene and binding site of pen = 2.5·10-5.

Mentions: We describe our model from a high-level perspective first, followed by several sections covering the details. Central to the local and model is the processing of resources: organisms have to evolve their regulatory network such that they gain energy from nutrients in the environment. As depicted in Figure 1B, a resource is a bit string, and as an abstraction of metabolic activity an individual has to reproduce the bit string as a temporal output (expression) pattern of its gene regulatory network. We name this a "bite". The example in Figure 1B shows a bite of 13 bits. Next, this bite determines both the fitness of an individual and what waste product is left in the environment: the bite is cut from the left of the resource and re-attached at the right side, effectively rotating the resource bit string.


Evolution of resource cycling in ecosystems and individuals.

Crombach A, Hogeweg P - BMC Evol. Biol. (2009)

Overview of the model. A. Individuals and resources are placed on a grid (size 100×100). Individuals consist of a genome, from which a network is computed. They compete for reproduction into empty grid sites by processing resources. B. The resource is a bit string of length 64. Maximally the first 8 bits can be sensed by a network, which then produces a sequence of bits at its output. The output is matched to the original bit string, and the length of the correct sequence (matching the bit string from the leftmost bit) is the raw score of the individual, which in this example is 13. If the individual reproduces, the resource is rotated from right to left for 13 bits and placed back in the grid site. C. The effect of a few types of mutation on the genome (left) and the topology of the network (right). By default the parameter values for each type of mutation are: gene duplication 16·10-4, deletion 24·10-4, binding specificity 4·10-4, gene expression threshold 4·10-4, binding site duplication 4·10-4, deletion 10·10-4, innovation 1·10-4, binding specificity 4·10-4, weight 4·10-4. In order to balance the growth of the network, we apply a small penalty per gene and binding site of pen = 2.5·10-5.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2698886&req=5

Figure 1: Overview of the model. A. Individuals and resources are placed on a grid (size 100×100). Individuals consist of a genome, from which a network is computed. They compete for reproduction into empty grid sites by processing resources. B. The resource is a bit string of length 64. Maximally the first 8 bits can be sensed by a network, which then produces a sequence of bits at its output. The output is matched to the original bit string, and the length of the correct sequence (matching the bit string from the leftmost bit) is the raw score of the individual, which in this example is 13. If the individual reproduces, the resource is rotated from right to left for 13 bits and placed back in the grid site. C. The effect of a few types of mutation on the genome (left) and the topology of the network (right). By default the parameter values for each type of mutation are: gene duplication 16·10-4, deletion 24·10-4, binding specificity 4·10-4, gene expression threshold 4·10-4, binding site duplication 4·10-4, deletion 10·10-4, innovation 1·10-4, binding specificity 4·10-4, weight 4·10-4. In order to balance the growth of the network, we apply a small penalty per gene and binding site of pen = 2.5·10-5.
Mentions: We describe our model from a high-level perspective first, followed by several sections covering the details. Central to the local and model is the processing of resources: organisms have to evolve their regulatory network such that they gain energy from nutrients in the environment. As depicted in Figure 1B, a resource is a bit string, and as an abstraction of metabolic activity an individual has to reproduce the bit string as a temporal output (expression) pattern of its gene regulatory network. We name this a "bite". The example in Figure 1B shows a bite of 13 bits. Next, this bite determines both the fitness of an individual and what waste product is left in the environment: the bite is cut from the left of the resource and re-attached at the right side, effectively rotating the resource bit string.

Bottom Line: If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics.In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling.By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands. anton.crombach@gmail.com

ABSTRACT

Background: Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned?

Results: We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves.

Conclusion: In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

Show MeSH