Optogenetic Bio-Electronic Sensing for Real-Time Molecular Communication
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Solution Overview
Problem
Existing molecular communication (MC) networks built entirely of biological components face significant limitations due to processing and propagation delays, limited computational capabilities, and the need for complex algorithms, requiring time-consuming and error-prone human intervention for post-processing.
Innovation Solution
A hybrid bio-electronic framework that utilizes biological components for sensing and offloads processing and computation to traditional electronic systems using optogenetics and electronics, integrating biosensors with an external light stimulus to control cellular processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If molecular communication networks are built entirely of biological components, then the system maintains natural sensing capabilities, but processing and propagation delays increase and computational capabilities are limited
Solution Approach 1:
The system is divided into two functional segments: biological components (microbes with biosensors) that perform sensing, and electronic components that perform processing and communication. This segmentation allows each part to excel at its specialized function, resolving the contradiction between maintaining natural sensing capabilities and reducing processing delays.
Solution Approach 2:
An intermediary interface is introduced between the biological sensing components and electronic processing components. This interface enables seamless data transfer from the biological domain to the electronic domain, allowing fast electronic processing while preserving the advantages of biological sensing.
2Adaptability or versatility
If molecular communication networks use biological components, then the system can sense environmental conditions, but computational capabilities are limited and complex algorithms require human intervention
Solution Approach 1:
The system separates sensing functions (performed by versatile biological components) from computational functions (performed by electronic systems). This allows the biological components to maintain their adaptability and versatility in sensing while electronic systems handle complex computational algorithms, eliminating the need for manual post-processing.
3Adaptability or versatility
If molecular communication networks are fully biological, then the system maintains natural molecular transceivers, but network scalability and throughput are limited
Solution Approach 1:
The system segments communication functions into biological sensing (maintaining natural transceiver properties) and electronic communication (enabling high-speed data transmission). This segmentation allows the network to scale effectively and achieve high throughput by leveraging the strengths of both biological and electronic communication systems.
4Measurement precision
If molecular communication networks use biological components, then the system can detect stimulus molecules, but post-processing requires time-consuming and error-prone human intervention
Solution Approach 1:
An electronic intermediary system is introduced that automatically processes data from biological sensors in real-time. This intermediary performs detection, analysis, and communication functions electronically, eliminating the need for manual post-processing while preserving the high detection precision of biological sensors.
Solution Approach 2:
The system implements automated self-processing where electronic components continuously analyze and interpret data from biological sensors without human intervention. This self-service capability maintains detection precision while dramatically improving processing efficiency and eliminating human error.
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
Enables efficient, real-time biological sensing and communication by simplifying computation and communication complexity, enhancing network scalability, throughput, and reducing engineering burdens, while maintaining the innate sensing capabilities of biological systems.
Implementation Method 1
each region comprises an optogenetic system to generate, upon interacting with the at least one light beam, a plurality of biosensors
Implementation Method 2
a light detector configured to detect light received from one or more of the plurality of regions and generate an electrical signal
Data Source
AI summary
Devices, systems and methods for biological sensing and communication using optogenetics and electronics are described. One example method includes generating a light beam incident on multiple regions in a device, wherein each region comprises an optogenetic system to generate, upon interacting with the light beam, biosensors, wherein an interaction between the biosensors and stimulus molecules in each region is associated with a threshold for a production of an output molecule or an alteration of an output property of the output molecule, the biosensors, or the stimulus molecules, wherein the production or the alteration is based on a value associated with an information source, detecting an output received from one or more of the multiple regions corresponding to the output molecule or the output property in that region, and generating an electric signal associated therewith, and processing the electrical signal to determine the value associated with the information source.