Matthew Griffin, award winning Futurist working between the dates of 2020 and 2070, is described as “The Adviser behind the Advisers” and a “Young Kurzweil.” Regularly featured in the global press, including BBC, CNBC, Discovery and RT, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew sits on several boards and his recent work includes mentoring Lunar XPrize teams, building the first generation of biological computers and re-envisioning global education with the G20, and helping the world’s largest manufacturers ideate the next 20 years of intelligent devices and machines. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Bain & Co, BCG, BOA, Blackrock, Bentley, Credit Suisse, Dell EMC, Dentons, Deloitte, Du Pont, E&Y, HPE, Huawei, JPMorgan Chase, KPMG, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, UBS, and many more.
WHY THIS MATTERS IN BRIEF
You could argue that DNA is actually the oldest programming language on Earth, and today we’re starting to learn how to write and program it in new ways to create new a completely new class of living, biological computers.
Hot on the heels of a breakthrough that saw a team in the US store a movie in the DNA of a living E.coli bacterium, and then retrieve and replay it, researchers in the US have developed a DNA based Biological computer that works inside living bacterial cells and tells them what to do, according to a report published recently in Nature. Composed of Ribonucleic Acid (RNA), the new “Ribocomputer” can not only survive in the bacterium E. coli, but it can also respond to a dozen different inputs making it the most complex biological computer to date.
“We’ve developed [a biological computer] that controls how cells behave,” says Alexander Green, an engineer at Arizona State University, who developed the technology with colleagues at Harvard University.
“The [bacterial] cells go about their normal business, replicating and sensing what’s going on in their environments, but they’ve also got this computational machinery in them that we’ve instructed them to [synthesise],” he says, and the new biological circuit works just like a digital one, it receives an input and makes a logic-based decision, using AND, OR, and NOT operations, but instead of the inputs and outputs being voltage signals, they are the presence or absence of specific chemicals or proteins.
The process begins with the design of a DNA strand that codes for all the logic the system will need. The researchers then inserted the synthesised DNA into E. coli bacteria as part of a plasmid, which is a ring of DNA that can replicate itself as it floats around in the cell, that served as a template for the biological computer’s machinery. The cell’s molecular machinery then translated the DNA into RNA, essentially copying the DNA code onto a different molecule, which could then be used by the cell.
This RNA then linked up with the cell’s ribosome and instructed it to produce a protein specified in the RNA’s code. But here’s where the system behaves like a computer though rather than just a genetically engineered organism – the RNA only does its job when it receives an input that activates it. That’s because the engineered RNA contains codes not just for a protein, but also for logic functions. The logic portions must receive the right inputs in order to activate the RNA in a way that allows the ribosome to use it to produce the circuit’s output, or in this case a protein that glows.
“Those switches are kind of the equivalent of your first transistors,” says Green, “they are devices we can build into more complex things.”
Green’s team was able to arrange multiple biological transistors, which they call “toehold switches,” together, that then formed what the researchers called the “gate RNA”, which is a kind of molecular logic circuit.
The inputs, in Green’s demonstration, were strands of RNA added to the cells after the plasmid containing the “gate RNA” code has already been inserted. These input RNAs paired up with those of the codes of the ribocomputer’s gate RNA. A match between the input RNA and the gate RNA freed the strand so that when it encountered a ribosome, it could tell the cellular machinery to produce the florescence protein, which was easy to see when the system worked, because the E. coli lit up.
In their most complex biocomputer design, they built in enough switches to generate a 12-input circuit made up of 5 AND gates, 5 ORs, and 2 NOTs.
“There’s a million ways you can fail at this thing,” he says, “in the cell everything is interacting with everything else and there are a million ways those interactions could flip the switch on accident.”
Green’s team succeeded in overcoming this by using a combination of algorithms that predict how an RNA molecule folds, along with deep insight into which RNA structures might perform the computations, Lucks says.
“It’s the greatest number of inputs in a circuit that a cell has been able to process,” adds Green, “to be able to analyse those signals and make a decision is the big advance here.”
In the past previous work using DNA and proteins to build biological circuits has seen relatively modest success. The best of those circuits have functioned only in test tubes, rather than in living, replicating cells, or they weren’t able to process as much information in such a compact space as the ribocomputer. For example, last year Microsoft researchers reported a method for DNA computing using an origami-style structure. The design enabled faster computation than other equivalent DNA circuits, but it wouldn’t work inside a living cell.
Christopher Voigt at MIT has also created software that automates the design of DNA circuits for living cells, and last year demonstrated its capabilities, but those designs couldn’t handle as many inputs as the new biocomputer and they also required more DNA to encode.
Green says he hopes the field of biocomputing will pick up speed now.
“We’re like 70 years behind where things are in electrical engineering,” he says, “the first transistor was invented in 1947, and once we get the infrastructure for building biological circuits right then hopefully we’ll have similar growth.”
Green says he envisions biocomputers like these being used in diagnostic devices that detect and kill viruses, or in cellular devices programmed to break down environmental toxins, and all that’s just for starters, and before they revolutionise the field of computing.
“You could upload a biological circuit into the cells in the body to protect against viruses or prevent cancer from developing,” he says, “that is, the biocomputer would be part of your own cells. If the body is attacked by cancerous or viral materials, cells could be programmed to shut down or synthesize a drug or summon the immune system into action, instead of allowing the disease to spread.”
As developments in this space continue to gather pace it’s highly likely that one day we could see the creation of living computers that not only store and process information but also replicate themselves, and if even just a part of that vision is realised then the world as we know it will never be the same again.
However, if biocomputers aren’t your thing then fear not, there are plenty of other types of new, ultra-powerful computer platforms emerging that make today’s computers look lame, including Chemical, DNA, Liquid, Neuromorphic, Photonic and Quantum computers, take your pick – they’re all awesome!