As technology and biology converge, a new era of computing is emerging, marked by the rise of biological computers.

These systems leverage the unique properties of biological molecules and cells to perform computational tasks, offering a paradigm shift from traditional silicon-based computing.

In this article, we will explore the concept of biocomputing, outline its various types, and delve into groundbreaking biocomputing platforms such as FinalSpark and Trumpet, which are leading the way in this exciting field.

What is Biocomputing?

Biocomputing refers to the use of biological materials and processes to perform computational functions [1].

Unlike traditional computers, which rely on electronic circuits made from silicon to process information, biocomputers use biological molecules like DNA, RNA, proteins, or even entire cells to execute logical operations and store data.

The goal of biocomputing is not only to replicate the capabilities of electronic computers but also to exploit the unique properties of biological systems [2], such as self-repair, adaptability, and energy efficiency.

Advantages of Biocomputers over Electronic Computers

Biological computers offer several advantages over traditional computing systems. For example, they can operate in environments that would be hostile to electronic devices, such as within the human body.

This makes them particularly promising for medical applications, where they could be used for tasks like monitoring health conditions, delivering drugs, or even repairing tissues.

Moreover, biocomputing systems have the potential to be far more energy-efficient than their electronic counterparts, as they can operate using the energy naturally produced by biological processes.

Types of Biocomputing

Biocomputing can be broadly classified into several types, based on the nature of the biological materials used and the approach taken to perform computations. These include:

DNA Computing

DNA computing is perhaps the most well-known form of biocomputing. It uses the molecular structure of DNA to encode and process information [3].

DNA molecules can store vast amounts of data, and their ability to undergo specific chemical reactions allows for the execution of complex logical operations.

For instance, a biocomputer using DNA might solve a computational problem by synthesizing a large number of DNA strands, each representing a potential solution, and then using biochemical reactions to eliminate incorrect answers.

Applications

DNA computing has been used in experimental setups to solve mathematical problems, crack codes, and perform searches within large datasets [3]. Its potential in medical diagnostics, such as detecting genetic diseases, is also being explored.

RNA Computing

RNA computing operates on principles similar to DNA computing but uses RNA molecules instead [4].

RNA has the advantage of being able to carry out additional functions, such as catalyzing chemical reactions (like ribozymes) or regulating gene expression, making it a versatile tool in biological computers.

Applications

RNA-based systems are being investigated for their potential in developing smart therapeutics, where they could be used to detect disease markers in cells and trigger appropriate responses, such as the production of therapeutic proteins [5].

Protein-Based Computing

Protein-based computing utilizes proteins as the primary computational elements.

Proteins, with their vast array of functions and ability to undergo complex conformational changes, can be harnessed to perform logic operations and store information. This approach often involves designing synthetic proteins or using natural proteins that change their structure or activity in response to specific signals [6].

Applications

This type of biocomputing could be used in developing sensors that detect and respond to environmental changes, such as pH or temperature, or in creating biocomputers that can perform complex calculations within living cells.

Cellular Computing

Cellular computing involves using whole cells, often genetically engineered, to perform computations.

These cells can be programmed to respond to environmental stimuli by activating or repressing specific genes, producing outputs like fluorescence or the synthesis of certain molecules.

Applications

Cellular biocomputers have potential applications in synthetic biology, where they could be used to create organisms with new capabilities, such as producing drugs in response to disease signals or breaking down pollutants in the environment.

Notable Biocomputing Platforms

FinalSpark’s Biocomputing Platform

FinalSpark has emerged as a leader in the development of biocomputers that integrate living brain tissue with electronic hardware.

Their platform leverages lab-grown brain organoids—clusters of neurons derived from human stem cells—wired into silicon chips to create hybrid systems that are incredibly energy-efficient [7, 8].

Energy Efficiency: FinalSpark’s biological computers are up to 100,000 times more energy-efficient than traditional silicon-based systems. This is achieved by using the natural energy processes of neurons, which only require small amounts of biochemical energy to function.

Learning and Adaptation: The neurons in FinalSpark’s biocomputers are trained using a reward mechanism involving dopamine, mimicking the way human brains learn. This allows the system to adapt and improve its performance over time, much like a human learning a new skill.

Applications: While still in the developmental stages, FinalSpark’s platform is being explored for applications in artificial intelligence, where it could be used to train AI models more efficiently. The potential for these systems to reduce the energy consumption of AI processes is significant, especially given the growing environmental concerns surrounding data centers and computational power.

Trumpet Biocomputing Platform

The Trumpet platform, developed by researchers at the University of Minnesota, represents a novel approach to biological computing.

Officially named the Transcriptional RNA Universal Multi-Purpose GatE PlaTform, Trumpet is a non-living molecular system that uses biological enzymes to perform DNA-based computations [9, 10].

Logical Operations: Trumpet is capable of performing all universal Boolean logic gates (NAND, NOT, NOR, AND, and OR), which are the building blocks of digital computing. These gates can be combined to create more complex circuits, enabling the platform to perform sophisticated computational tasks.

Signal Amplification: One of Trumpet’s key innovations is its ability to amplify signals, a challenge in previous molecular computing systems. This amplification makes it possible to detect and interpret the outputs of the system more reliably, which is crucial for practical applications.

Stability and Reliability: Unlike biological computers that use living cells, Trumpet’s non-living nature makes it more stable and less prone to the issues that arise from cellular processes, such as metabolic changes or evolutionary pressures. This stability enhances the platform’s reliability, making it suitable for long-term applications.

Applications: Trumpet’s potential applications are vast, ranging from medical implants that repair nerve damage to advanced prosthetics controlled by molecular circuits. The platform could also be used in early disease detection, where biological circuits are designed to recognize and respond to specific biomarkers, such as those associated with cancer or diabetes.

Theranostics: Trumpet is particularly promising in the field of theranostics, where it could be used to create devices that both diagnose and treat conditions within the body [11]. For example, a Trumpet-based circuit could detect low insulin levels in a diabetic patient and trigger the production of insulin, offering a new approach to managing chronic diseases.

Conclusion

The development of biological computers marks a significant milestone in the evolution of computing.

By harnessing the unique properties of biological molecules and systems, biocomputing platforms like FinalSpark and Trumpet are pushing the boundaries of what is possible in both technology and medicine.

As these platforms continue to evolve, they hold the promise of revolutionizing a wide range of fields, from artificial intelligence to personalized medicine, offering new solutions to some of the most pressing challenges of our time.

References

[1] Biocomputation: Moving Beyond Turing with Living Cellular Computers. Communications of the ACM: https://dl.acm.org/doi/full/10.1145/3635470

[2] Pathways to cellular supremacy in biocomputing. Nature Communications: https://www.nature.com/articles/s41467-019-13232-z

[3] Concept, Development and Applications of DNA Computation. Fundamental Research: https://www.sciencedirect.com/science/article/pii/S2667325823002352

[4] Synthetic RNA-based logic computation in mammalian cells. Nature Communications: https://www.nature.com/articles/s41467-018-07181-2

[5] mRNA-based therapeutics: powerful and versatile tools to combat diseases. Signal Transduction and Targeted Therapy: https://www.nature.com/articles/s41392-022-01007-w

[6] A noncommutative combinatorial protein logic circuit controls cell orientation in nanoenvironments. Applied Sciences and Engineering: https://www.science.org/doi/10.1126/sciadv.adg1062

[7] FinalSpark Neuroplatform: https://finalspark.com/neuroplatform/

[8] Open and remotely accessible Neuroplatform for research in wetware computing. Frontiers in Artificial Intelligence: https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2024.1376042/full

[9] Trumpet platform: http://trumpet.bio/build/

[10] Trumpet is an operating system for simple and robust cell-free biocomputing. Nature Communications: https://www.nature.com/articles/s41467-023-37752-x

[11] The Trumpet biocomputing platform heralds a new path for medicine. News and Events (U. of Minnesota): https://twin-cities.umn.edu/news-events/trumpet-biocomputing-platform-heralds-new-path-medicine