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DNAzyme 10-23 - Based Nanomachines for Nucleic Acid Recognition

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Flipping DNA to generate and regulate microbial consortia.

Rohini Ramadas¹, Mukund Thattai

¹National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India.

|October 28, 2009

Summary

Engineers can create synthetic microbial consortia with diverse phenotypes using programmed genetic changes. This method allows for stable maintenance and regulation of multiple microbial types for applications in biosynthesis and therapy.

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Area of Science:

Synthetic biology
Microbial ecology
Bioengineering

Background:

Microbial communities are crucial in natural ecosystems and have emerging bioengineering applications.
Synthetic microbial consortia offer potential in biosynthesis and therapeutic live-cell microbicide strategies.
Phenotypic diversity within consortia can enhance immune evasion in therapeutic applications.

Purpose of the Study:

To investigate a method for generating synthetic microbial consortia with regulated phenotypic diversity.
To explore programmed genetic interconversions as a mechanism for controlling microbial populations.
To develop a theoretical framework for analyzing the evolution of microbial consortia.

Main Methods:

Developed a theoretical model analyzing microbial populations evolving on a graph of genotypes.
Genotypes represented ordered combinations of DNA elements (promoters, genes, terminators).
Genotypic interconversions were modeled using a recombinase-driven DNA segment inversion mechanism.

Main Results:

The steady-state proportion of each genotype is influenced by its growth advantage and connectivity.
Multiple phenotypes, with identical or distinct growth rates, can be indefinitely maintained.
The proportion of phenotypes can be regulated by adjusting the rate of DNA flipping.

Conclusions:

Recombinase-based genetic constructs can be used to generate synthetic microbial consortia.
The developed graph-theoretic framework aids in adapting these constructs for diverse applications.
This approach provides a method for controlling phenotypic diversity in engineered microbial communities.