Being able to turn human cells into powerful, living computing systems will revolutionise computing, energy, and healthcare, along with a myriad of other industries.


Today’s computer hardware is about to get softer, a lot softer, after a research team in the US announced they’ve managed to engineer the DNA of living human cells to carry out complex computations, in short turning these human cells into Biological computers. While the group hasn’t put those modified cells to work in useful ways yet down the road the team behind them hope the new genetic programming technique will help improve Cancer therapies and give scientists the power to create “on demand tissues” that can replace worn out human body parts. And all that’s just for starters.


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Engineering cells to function like our regular logical computers isn’t new. In fact there are a few research teams around the world now that have announced interesting breakthroughs recently, from being able to store and retrieve movies in the DNA of living bacteria, creating biological logic gates, the basic components of today’s silicon based computers, and more recently, to creating a new programming language for living cells, and even turning an E. coli bacteria into a fully fledged biological computer.

As part of the growing interest in synthetic biology research teams around the world have been manipulating DNA for decades to make cells perform simple actions like lighting up when oxygen levels drop, and even grow into specific shapes, which one day could see us grow, for example, cities. To date though most of these experiments have been performed on E. coli and other bacteria because their genes are relatively easy to manipulate.

Naturally, over time scientists have tried to extend these experiments to mammalian cells in order to help them create the genetic circuitry that could help detect and treat human diseases, and possibly, one day, even help us create new types of bio-energy. But up until now efforts to construct large scale genetic circuits in mammalian cells have largely failed, because for complex circuits to work, the individual components, such as the turning on and off of different genes, must happen consistently.

Now, in order to get to the bottom of how they did it we’re going to have to go geek speak… The most common way to turn a gene on or off is by using proteins called transcription factors that bind to and regulate the expression of a specific gene, but the problem is these transcription factors “all behave slightly differently,” says Wilson Wong, a synthetic biologist at Boston University who helped create the new “mammalian” computer.


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To upgrade their DNA “switches,” Wong and his colleagues steered clear of transcription factors and instead switched human kidney cell genes on and off using scissor-like enzymes that selectively cut out snippets of DNA. These enzymes, known as DNA recombinases, recognise two target stretches of DNA, each between 30 to 50 or more base pairs long. When a recombinase finds its target DNA stretches, it cuts out any DNA in between, and stitches the severed ends of the double helix back together.

To design genetic circuits, Wong and his colleagues use the conventional cellular machinery that reads out a cell’s DNA, transcribes its genes into RNA, and then translates the RNA into proteins. This normal “Gene to Protein” operation is initiated by another DNA snippet, a promoter, that sits just upstream of a gene. When a promoter is activated, a molecule called RNA polymerase gets to work, marching down the DNA strand and producing an RNA until it reaches another DNA snippet, a termination sequence, that tells it to stop.

To make one of their simplest mammalian circuits Wong’s team inserted four extra snippets of DNA after a promoter. The main one produced green fluorescent protein (GFP), which lights up cells when it is produced. But in front of it was a termination sequence, flanked by two snippets that signalled the DNA recombinase. Wong and his team then inserted another gene in the same cell that made a modified recombinase, activated only when bound to a specific drug, without it, the recombinase wouldn’t cut the DNA.


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When the promoter upstream of the GFP gene was activated, the RNA polymerase ran headfirst into the termination sequence, stopped reading the DNA, and didn’t produce the fluorescent protein. But when the drug was added, the recombinase switched on and spliced out the termination sequence that was preventing the RNA polymerase from initiating production of GFP.

Voila, the cell lit up, and the new biological computer worked.

As if that feat weren’t enough, Wong and his colleagues also showed that by adding additional recombinases together with different target strands, they could build a wide variety of circuits, each designed to carry out a different logical operation. The approach worked so well that in all the team built over 110 different biological circuits, with a 97 percent success rate, as reported in in Nature Biotechnology.

As a further demonstration, they engineered human cells to produce a biological version of something called a Boolean logic lookup table. The circuit in this case has six different inputs, which can combine in different ways to execute one of 16 different logical operations.

“It’s exciting in that it represents another scale at which we can design mammalian genetic circuits,” says Timothy Lu, a synthetic biologist at MIT who wasn’t involved in the research.

The team dubbed the new tool with a catchy name, BLADE, which stands for “Boolean logic and arithmetic through DNA excision.”


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Although the current circuits are a proof of concept, both Lu and Wong say synthetic biologists want to use them to create new medical therapies. For example, scientists could engineer human T cells, which are the sentinels of our immune system, with genetic circuits that initiate a response to wipe out cancerous tumours when they detect the presence of two or three “biomarkers,” like this one, that are produced by cancer cells, Lu says. Another example being explored by Wong and others is to engineer stem cells so they develop into specific cell types when prompted by different signals. This could let synthetic biologists generate tissues on demand, such as insulin-producing β cells, or cartilage-producing chondrocytes. The possibilities are limitless, and almost any one of them could revolutionise healthcare.

As we continue to see researchers make progress in turning biology into tomorrow’s computing devices the promise the technology promises is too big for many people at this point to grasp, and at some point, like was also demonstrated recently, we, that is humans, will be the computing platform. If you think the world is strange and futuristic now, then hold onto your 3D printed hats, the next couple of decades are going to be even crazier.

About author

Matthew Griffin

Matthew Griffin, award winning Futurist and Founder of the 311 Institute, a global futures think tank working between the dates of 2020 and 2070, is described as "The Adviser behind the Advisers." Regularly featured on AP, CNBC, Discovery and RT, his 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 five 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 future. A rare talent Matthew sits on the Technology and Innovation Committee (TIAC) for Centrica, Europe’s largest utility company, and his recent work includes mentoring XPrize teams, building the first generation of biocomputers and re-inventing global education, and helping the world’s largest manufacturers envision, design and build the next 20 years of devices, smartphones and intelligent machines. Matthew's clients are the who’s who of industry and include 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, the USAF and many others.

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