Engineered Bacteria Swarm Patterns for Environmental Information Encoding

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Solution Overview

Problem

Current methods in synthetic biology for recording environmental information require DNA sequencing, which is limiting, and the unique swarming behavior of bacteria like Proteus mirabilis has not been engineered for biotechnological applications such as recording environmental conditions.

Innovation Solution

Engineered bacteria with exogenous inducible promoters controlling swarming motility genes, regulated by environmental parameters, produce visible patterns that can be analyzed using machine learning models to detect spatiotemporal changes, allowing for non-sequencing information recording.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If DNA sequencing methods are used for information recovery, then information can be recorded and retrieved, but the process becomes complex and time-consuming

Engineering Contradiction:

Improveinformation recoveryVSAvoidsequencing time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The patent creates visual copies of information through bacterial swarm patterns that can be directly observed and analyzed. Instead of storing information in DNA sequences that require sequencing, the system encodes environmental information into visible spatial patterns that serve as direct readable copies, eliminating the need for time-consuming sequencing processes

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces the mechanical/chemical DNA sequencing process with an optical observation system. Machine learning models analyze visual images of bacterial swarm patterns to decode information, substituting the complex DNA sequencing machinery with simpler optical detection and computational analysis

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If traditional bacterial observation methods are used, then simple patterns can be observed, but complex spatiotemporal information cannot be encoded

Engineering Contradiction:

Improveenvironmental information encodingVSAvoidpattern analysis complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent changes the parameters of bacterial behavior by using inducible promoters that respond to environmental conditions. This causes bacteria to alter their swarm patterns in response to specific environmental parameters, encoding information into the spatial and temporal characteristics of the patterns without requiring complex analysis devices

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent introduces machine learning models as intermediaries between the bacterial swarm patterns and the observer. These models automatically analyze complex visual patterns and extract encoded environmental information, bridging the gap between simple bacterial behavior and complex information retrieval

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of information

If bacterial swarming behavior is left natural, then simple colony growth occurs, but controlled pattern formation for information recording is not achieved

Engineering Contradiction:

Improveinformation recording capabilityVSAvoidgenetic engineering complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent enables bacteria to serve themselves as information recording devices. By engineering bacteria with environmental sensors and inducible promoters, the bacteria automatically detect and record environmental conditions through their own swarming behavior, eliminating the need for external recording equipment

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent performs preliminary genetic engineering of bacteria before deployment. The bacteria are pre-equipped with environmental sensing capabilities and inducible promoters that will automatically respond to environmental conditions during the experiment, preparing the information recording system in advance

Inventive Principle:

Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enables the detection of environmental changes by analyzing visual patterns formed by bacteria, providing a novel method for encoding and decoding environmental information without the need for DNA sequencing, with high accuracy and utility in biotechnological applications.

Implementation Method 1

bacteria are transgenic in nature and comprise at least one exogenous inducible promoter that controls at least one gene related to swarming motility exhibited by the bacteria

Methodology Applied

Scientific EffectInducible promoter regulation:

Implementation Method 2

Many bacterial species form complex spatial patterns on solid agar surfaces via swarming motility, a flagella-powered rapid coordinated movement of bacteria across a surface

Methodology Applied

Scientific EffectSwarming motility:

Implementation Method 3

detecting differences between observed and expected swarm patterns using macroscopic images of the swarm patterns and one or more trained machine learning models

Methodology Applied

Scientific EffectImage pattern recognition: Image Processing

Data Source

PatentUS20250002903A1Engineering Bacteria Swarm Patterns for Spatiotemporal Information Encoding

Publication Date: 2025.01.02 THE TRUSTEES OF COLUMBIA UNIV IN THE CITY OF NEW YORK

AI summary

Encoding environmental parameters by modulating swarm patterns of bacteria on substrates and correlating spatiotemporal changes in the environmental parameters to changes in swarm patterns using one or more trained machine learning models.