2026/07/16 by Marian Shaw, Sadhya Garg, Julia Kirby +5 · 1 voice
Biochemistry, Genetics and Molecular Biology · #Bacterial Genetics and Biotechnology #Bacterial biofilms and quorum sensing #Gene Regulatory Network Analysis
paper · pdf · doi:10.1038/s44320-026-00232-7
openalex publication_date 2026/07/16 · openalex created_date 2026/07/17 · openalex updated_date 2026/07/23
Many bacterial species form self-organized macroscale patterns through swarming. Despite its extensive genetic tractability, Escherichia coli remains underexplored for robust, applied control of swarming. Here we develop a set of E. coli strains that generate centimeter-scale swarming patterns to spatially record environmental inputs. Specifically, we modulate the expression of swarming-related genes in response to chemical and optical signals, reshaping baseline swarm patterns in analog or binary-like fashions. To decode bacterial patterns across space and time, we develop scalable computational methods incorporating feature extraction, regression, and deep-learning models. Time-lapse imaging reveals that colonies record inputs dynamically, enabling early-stage classification. This work establishes a strategy for spatial information recording in E. coli and expands the toolkit for programming emergent microbial behaviors at macroscopic scales.