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Scrambling Signal Modularity in Bottom-up Assembled Synthetic Pseudomonas Consortia Reveals Robust Information
Monica Chu1,2,3, Eric VanArsdale1,2,3, Divya Muthusamy1,2,3
1Fischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, United States.
Synthetic microbial communities can convey messages effectively even when their signaling pathways are rearranged. This research explores robust bacterial communication for diverse applications.
Area of Science:
- Microbial Ecology
- Synthetic Biology
- Bacterial Communication
Background:
- Synthetic microbial communities offer potential in health, agriculture, environment, and biomanufacturing.
- Bacterial signaling is crucial for intercellular information transfer and collective behavior in microbial consortia.
- Complex communication involves multiple signals, disruptors, species, and environmental constraints.
Purpose of the Study:
- To investigate the robustness of molecular information transfer in a synthetic microbial consortium.
- To demonstrate that scrambled signaling pathways can still effectively convey intended messages.
- To provide a framework for designing signaling processes in assembled microbial communities.
Main Methods:
- Assembled a synthetic consortium of several *Pseudomonas* species.
- Utilized two signaling molecules: phloroglucinol (redox-active metabolite) and 3-oxo-C12 acylhomoserine lactone (quorum sensing signal).
- Investigated intraconversion and signal transduction among community members.
Main Results:
- Demonstrated that genetic and organizational scrambling of a multisignal pathway did not impede message conveyance.
- Showed that the order of signal reception, transduction, and transmission can be rearranged with minimal impact.
- Found the messaging structure to be remarkably robust within the consortial context.
Conclusions:
- The molecular messaging system in synthetic microbial consortia can be highly resilient to structural changes.
- This work provides a conceptual framework for engineering robust information transfer in synthetic communities.
- Findings are inspired by rhizospheric molecular signaling mechanisms.
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