A LIVING ALTERNATIVE TO MATHEMATICAL HEURISTICS

Microbial computation uses the abilities of microorganisms, mainly bacteria and slime molds, to do calculations that would normally be done by machines. Microorganisms have been genetically changed or created by synthetic biology to be able to interpret input and create output through logical circuits. In real life examples of microbial computation, quorum sensing and chemotaxis are being used by microorganisms as a form of computational ability. Physarum polycephalum, for example, has shown how its network of protoplasmic tubes can be used to physically represent solutions to optimization problems . In addition, it has been shown that synthetic biochips engineered microbial colonies can count events, execute Boolean logic, and adjust to their surroundings. By using physiological processes for these types of computations, they end up having low energy requirements, are highly parallel in nature, and self-replicate. Examples of how microbial computations mimic algorithms used in programming include chemical gradient signaling, nutrient driven spatial growth, and stigmergy where microorganisms provide environmental signals to other microorganisms to help in future actions upon that same environment. Using integrated microbial units that consist of shape, genetic control, and metabolic feedback, they serve as an encoder to encode data and can process via morphological computation and give analytical output. Advancements in synthetic biology have provided the foundation for bio circuits with more accurate and scalable capabilities, through the uses of DNA computing and logic gates based on CRISPR technology. Smart therapies, biosensing and diagnostics are just a few of the potential uses for these bio-circuits. Despite these advancements, several challenges persist including slow processing times, inconsistent results and difficulty scaling complexity. In the future bio-hybrid computing will fuse electronic and microbiological systems to create flexible, low power platforms to solve real world problems in logistics, robotics and medicine. In essence, microbial computation redefines intelligence as an emergent quality of life; therefore, microbial computation presents a physical and sustainable approach to traditional computing systems.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-13
DOI
https://doi.org/10.5281/zenodo.18995838
Primary Topic
Slime Mold and Myxomycetes Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A LIVING ALTERNATIVE TO MATHEMATICAL HEURISTICS

Reshma Banu S, Prannesh U R,Mahenthiran R, Sudha S S
Zenodo (CERN European Organization for Nuclear Research)
Slime Mold and Myxomycetes Research
article

A LIVING ALTERNATIVE TO MATHEMATICAL HEURISTICS

Reshma Banu S, Prannesh U R,Mahenthiran R, Sudha S S
article en

Abstract

Microbial computation uses the abilities of microorganisms, mainly bacteria and slime molds, to do calculations that would normally be done by machines. Microorganisms have been genetically changed or created by synthetic biology to be able to interpret input and create output through logical circuits. In real life examples of microbial computation, quorum sensing and chemotaxis are being used by microorganisms as a form of computational ability. Physarum polycephalum, for example, has shown how its network of protoplasmic tubes can be used to physically represent solutions to optimization problems . In addition, it has been shown that synthetic biochips engineered microbial colonies can count events, execute Boolean logic, and adjust to their surroundings. By using physiological processes for these types of computations, they end up having low energy requirements, are highly parallel in nature, and self-replicate. Examples of how microbial computations mimic algorithms used in programming include chemical gradient signaling, nutrient driven spatial growth, and stigmergy where microorganisms provide environmental signals to other microorganisms to help in future actions upon that same environment. Using integrated microbial units that consist of shape, genetic control, and metabolic feedback, they serve as an encoder to encode data and can process via morphological computation and give analytical output. Advancements in synthetic biology have provided the foundation for bio circuits with more accurate and scalable capabilities, through the uses of DNA computing and logic gates based on CRISPR technology. Smart therapies, biosensing and diagnostics are just a few of the potential uses for these bio-circuits. Despite these advancements, several challenges persist including slow processing times, inconsistent results and difficulty scaling complexity. In the future bio-hybrid computing will fuse electronic and microbiological systems to create flexible, low power platforms to solve real world problems in logistics, robotics and medicine. In essence, microbial computation redefines intelligence as an emergent quality of life; therefore, microbial computation presents a physical and sustainable approach to traditional computing systems.

Zenodo (CERN European Organization for Nuclear Research)
Responsible consumption and production
Openalex Percentile: Top 23%
Slime Mold and Myxomycetes Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.