ArticleNature chemical biology2023
Engineered bacterial swarm patterns as spatial records of environmental inputs.
Article in Nature chemical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Engineered E. coli swarming for binary and analog input recording.Molecular systems biology · 2026Article
- Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- The 2025 motile active matter roadmap.Journal of physics. Condensed matter : an Institute of Physics journal · 2025Review
- Uptake and leakage rates differentially shape community arrangement and composition of microbial consortia.The ISME journal · 2025Article
- Framework nucleic acid strategy enables closer microbial contact for programming short-range interaction.Science advances · 2024Article
- Engineering Microbial Consortia as Living Materials: Advances and Prospectives.ACS synthetic biology · 2024Review
- VirB11, a traffic ATPase, mediated flagella assembly and type IV pilus morphogenesis to control the motility and virulence of Xanthomonas albilineans.Molecular plant pathology · 2024Article
- Advances and challenges in programming pattern formation using living cells.Current opinion in chemical biology · 2022Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A diverse array of bacteria species naturally self-organize into durable macroscale patterns on solid surfaces via swarming motility-a highly coordinated and rapid movement of bacteria powered by flagella. Engineering swarming is an untapped opportunity to increase the scale and robustness of coordinated synthetic microbial systems. Here we engineer Proteus mirabilis, which natively forms centimeter-scale bullseye swarm patterns, to 'write' external inputs into visible spatial records. Specifically, we engineer tunable expression of swarming-related genes that modify pattern features, and we develop quantitative approaches to decoding. Next, we develop a dual-input system that modulates two swarming-related genes simultaneously, and we separately show that growing colonies can record dynamic environmental changes. We decode the resulting multicondition patterns with deep classification and segmentation models. Finally, we engineer a strain that records the presence of aqueous copper. This work creates an approach for building macroscale bacterial recorders, expanding the framework for engineering emergent microbial behaviors.
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Registered trials
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