Exploring the computing power of microbes that shapes the environment.

Area of Science:

• Microbiology
• Synthetic Biology
• Computational Biology

Background:

• Microbes function as physical computing systems, processing information via genetic and metabolic mechanisms.
• Microbial computations significantly impact environmental processes, including soil chemistry and atmospheric composition.
• The complexity of natural microbial information processing, including symbolic representation and algorithms, is not fully understood.

Purpose of the Study:

• To review and compare natural and synthetic microbial computations.
• To identify approaches for bridging the complexity gap between natural and synthetic systems.
• To emphasize the importance of formalizing microbial computation for advancing synthetic biology.

Main Methods:

• Review of existing literature on natural microbial computation.
• Analysis of synthetic biology tools and implemented genetic circuits (Boolean, sequential, analog, distributed).
• Focus on bacterial systems for examining natural and synthetic functions.

Main Results:

• Synthetic biology has enabled the creation of defined genetic circuits for computation in living cells.
• Current synthetic circuits are simpler than natural microbial computations.
• New strategies are emerging to increase the computational power of synthetic systems.

Conclusions:

• Understanding natural microbial computation is crucial for developing more sophisticated synthetic genetic circuitry.
• Formalizing the principles of microbial computation can guide future synthetic biology advancements.
• Bridging the gap between natural and synthetic microbial computing power is a key future direction.