Fungal Architectures and Logical Bacteria

Always had an interest in Fungi,  now connecting with computation?  Amazing thought.  On my list.  

Fungal Architectures and Logical Bacteria  By Karen Emslie

Commissioned by CACM Staff, June 15, 2023

Brain organoid seen through the microscope with neurons stained magenta.

Biological computers could outperform silicon-based machines, while consuming far less energy.

Biocomputing sits at the intersection of computer science, biology, and engineering. Researchers in the field seek to exploit the inherent molecular and chemical qualities of biological materials—including microorganisms like bacteria and fungi and cell components like DNA—to advance computing. Demonstrated and potential applications include performing computational tasks, data storage and retrieval, and the construction of novel hardware.

Proponents argue that biocomputing has advantages over conventional electronic methods. For example, the technology does not rely on fast-heating silicon microchips, making it more energy efficient, and many living materials have the useful ability to self-repair.

The origins of biocomputing date back to the 1990s, when Turing Award recipient and computer scientist Leonard Adleman demonstrated that DNA molecules could be encoded to carry out computational tasks. Recent developments in synthetic biology and nanobiotechnology have advanced the field by permitting the manipulation of biological materials on a nanoscale. Breakthroughs are happening globally and range from bacteria-driven functionalities to ongoing work on potentially disruptive technologies based on fungal mycelium—and human brain cells.

Bacterial devices

Bacteria are microorganisms that display behaviors—like gene expression and quorum sensing, a type of chemical communication—that can be genetically engineered to perform computing tasks.

Sangram Bagh and Rajkamal Srivastav, biophysicists at the Saha Institute of Nuclear Physics in Kolkata, India, have developed a logically reversible double Feynman gate using molecular engineered bacteria in an Artificial Neural Network (ANN) architecture. Their 3-input-3-output double Feynman logic gate using laboratory engineered, non-pathological E. coli cells is, say the researchers, the first realization of a double Feynman gate using living cells.

Bagh and Srivastav developed "cellular devices" by creating synthetic genetic networks inside E. coli and constructing a single-layer artificial network-type architecture with the engineered bacteria, which they describe as 'bactoneurons'. The double Feynman gates were generated when the bactoneurons were arranged in this architecture. The cellular devices' input signals were produced using extracellular chemicals, Bagh explains; "This input signal is like a zero or one. It is present or not, and then you get an output." The output, in this case, is the expression of three fluorescent proteins.

Other bacteria-driven biocomputing solutions are emerging: a team from the Walton Institute and the Tyndall National Institute in Ireland, and the University of Essex in the U.K., have proposed Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. Researchers at the Centro Nacional de Biotecnología (CSIC) and Complutense University of Madrid (UCM) in Spain and the Diego Portales University in Santiago, Chile, have shown "the possibility" of programming synthetic bacteria using a perceptron neural network. In Boston University´s Oliveira Lab, researchers are developing programmable microbial communities embedded in microfluidic devices.

Bacteria are single-celled and microscopic, but some biocomputing experiments are based on more complex living structures   ... '