Using artificial systems to explore the ecology and evolution of symbioses

Momeni, Babak; Chen, Chi‐Chun; Hillesland, Kristina L.; Waite, Adam James; Shou, Wenying

doi:10.1007/s00018-011-0649-y

Cited by 78 publications

(77 citation statements)

References 146 publications

(188 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As an alternative, synthetic microbial communities (cocultures) have been developed in which two or more species are cultivated together under laboratory conditions. Cocultures preserve core aspects of natural systems while offering greater practical experimental control (Shou et al, 2007;Hillesland and Stahl, 2010;Summers et al, 2010;Harcombe, 2010;Momeni et al, 2011;Hom and Murray, 2014;Mee et al, 2014). They are also more amenable to modeling than are natural systems and facilitate the development, experimental testing and refining of models for predicting community behavior (Zomorrodi and Segrè, 2015;Johns et al, 2016;Lindemann et al, 2016;Widder et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Microbial mutualism dynamics governed by dose-dependent toxicity of cross-fed nutrients

et al. 2016

View full text Add to dashboard Cite

Microbial interactions, including mutualistic nutrient exchange (cross-feeding), underpin the flow of energy and materials in all ecosystems. Metabolic exchanges are difficult to assess within natural systems. As such, the impact of exchange levels on ecosystem dynamics and function remains unclear. To assess how cross-feeding levels govern mutualism behavior, we developed a bacterial coculture amenable to both modeling and experimental manipulation. In this coculture, which resembles an anaerobic food web, fermentative Escherichia coli and photoheterotrophic Rhodopseudomonas palustris obligately cross-feed carbon (organic acids) and nitrogen (ammonium). This reciprocal exchange enforced immediate stable coexistence and coupled species growth. Genetic engineering of R. palustris to increase ammonium cross-feeding elicited increased reciprocal organic acid production from E. coli, resulting in culture acidification. Consequently, organic acid function shifted from that of a nutrient to an inhibitor, ultimately biasing species ratios and decreasing carbon transformation efficiency by the community; nonetheless, stable coexistence persisted at a new equilibrium. Thus, disrupting the symmetry of nutrient exchange can amplify alternative roles of an exchanged resource and thereby alter community function. These results have implications for our understanding of mutualistic interactions and the use of microbial consortia as biotechnology.

show abstract

Section: Introductionmentioning

confidence: 99%

Microbial mutualism dynamics governed by dose-dependent toxicity of cross-fed nutrients

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Mutualism results from coevolution of the two partners leading, ultimately, to cooperation. Intermediate evolutionary stages, however, can be detrimental to one or the other partner and it is unclear which driving forces govern the evolution of mutualism, ensure its maintenance in present systems and its adaptation to environmental challenges (Momeni et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Experimental evolution of nodule intracellular infection in legume symbionts

et al. 2013

View full text Add to dashboard Cite

Soil bacteria known as rhizobia are able to establish an endosymbiosis with legumes that takes place in neoformed nodules in which intracellularly hosted bacteria fix nitrogen. Intracellular accommodation that facilitates nutrient exchange between the two partners and protects bacteria from plant defense reactions has been a major evolutionary step towards mutualism. Yet the forces that drove the selection of the late event of intracellular infection during rhizobium evolution are unknown. To address this question, we took advantage of the previous conversion of the plant pathogen Ralstonia solanacearum into a legume-nodulating bacterium that infected nodules only extracellularly. We experimentally evolved this draft rhizobium into intracellular endosymbionts using serial cycles of legume-bacterium cocultures. The three derived lineages rapidly gained intracellular infection capacity, revealing that the legume is a highly selective environment for the evolution of this trait. From genome resequencing, we identified in each lineage a mutation responsible for the extracellular-intracellular transition. All three mutations target virulence regulators, strongly suggesting that several virulence-associated functions interfere with intracellular infection. We provide evidence that the adaptive mutations were selected for their positive effect on nodulation. Moreover, we showed that inactivation of the type three secretion system of R. solanacearum that initially allowed the ancestral draft rhizobium to nodulate, was also required to permit intracellular infection, suggesting a similar checkpoint for bacterial invasion at the early nodulation/root infection and late nodule cell entry levels. We discuss our findings with respect to the spread and maintenance of intracellular infection in rhizobial lineages during evolutionary times.

show abstract

“…This work can be easily extended to understand how can CDG evolve hybrid architectures, with different symbiotic relationships and reproduction rates. References [16,112,86], may act as an inspiration to futher the work.…”

Section: Future Workmentioning

confidence: 99%

Studying network morphology in common developmental genomes

Antonakopoulos

2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

View full text Add to dashboard Cite

Developmental biology seeks to understand how organisms are constructed. Development is a set of very complex processes involving a coded program as the organisms' genome. This genome describes how to build the organism, but not how the organism will look like. The zygote (the initial single cell), will eventually develop into a trillion cell organism. This extraordinary phenomenon has been an inspiration to the world of Computer Science and Artificial Life and has led to the creation of Artificial Embryogeny (AE). Artificial Embryogeny is a sub-discipline of evolutionary computation (EC) in which a phenotype undergoes a developmental phase. The number of AE systems currently being developed investigate mainly how principal biological processes and mechanisms can be exploited in the artificial world.One approach that utilize the phase of biological development in artificial systems is called Artificial Development (AD) where the genotype (genetic representation) contain a similar set of instructions -as in the biological organisms case -called generative program or developmental encoding. Therefore, the process of development comprise to actually execute those instructions and deal with the highly parallel interactions between them and the structure they create.On the other hand, nature uses the same fundamental machinery and almost the same genetic information to create vastly different creatures. A study reveals that about 99% of mouse genomes have direct counterparts in humans with cats having 90% of their homologous genes identical to humans. How is it possible for nature to use a vast majority of the same genetic representation in the DNA but still be able to develop such distant species? It was found that a common regulator gene can control the formation of many of the internal organs in both nematodes and vertebrates. Therefore, the very same gene can initiate the process of formation and define its outcome, for example, an intestine or a muscle cell.This thesis investigates how to design an Artificial Embryogeny by using the same genetic information to develop a class of computational architectures or different computational architectures. The result of this investigation has given rise to the Common Developmental Genomes (CDG). The computational architectures targeted, have a common characteristic of being sparsely-connected networks, with each node acting as a simple computational unit. Such computational architectures are cellular automata and boolean networks, artificial neural networks and cellular neural networks.The approach followed includes the following steps: a. investigate which architectures are suitable for development with such a model, b. describe a common developmental approach that can handle the targeted architectures, c. define how genetic information can be exploited by the developmental process, so as to develop these architectures and d. identify a suitable genome representation to ensure that different structures can be developed and achieved. The target architectures chos...

show abstract

Using artificial systems to explore the ecology and evolution of symbioses

Cited by 78 publications

References 146 publications

Microbial mutualism dynamics governed by dose-dependent toxicity of cross-fed nutrients

Microbial mutualism dynamics governed by dose-dependent toxicity of cross-fed nutrients

Experimental evolution of nodule intracellular infection in legume symbionts

Studying network morphology in common developmental genomes

Contact Info

Product

Resources

About