Humans love telling things what to do. Anything we can establish, predict, and control — from computers to factories — we can program to get reliable, useful results. Biotechnology has matured to the point where scientists increasingly regard living cells as programmable, but not everyone agrees with using that term. By tinkering with and editing their genes to create all kinds of useful new products, molecules, chemicals and materials at scale, leaders in this field of synthetic biology promise to fundamentally reinvent the way we make things, driven by new and emerging techniques for editing DNA and the seemingly limitless productive potential of biology.
Companies like Zymergen, Amyris
Living things, from the simplest cells all the way up to complex organisms, have already been industrialized. Animal agriculture is an obvious example, or yeasts, which are thrown into gigantic vats where they produce essential chemicals like citric acid at vast scales. But what if those yeasts’ genes could be edited so that they instead produced, for instance, a precious mineral, or a pharmaceutically useful molecule? What if the cells of a cow could be re-coded to produce a constant supply of pure filet mignon?
The imagination can run wild with this idea: feed the right instructions into a cell — or billions of them — and produce new chemicals or non-toxic dyes, purify water, make more efficient bioreactors, who knows what else. For all the excitement and promise, as these ideas and techniques become more widespread and sophisticated, disagreement is also emerging over the question: Can we really claim to program life like software? Should we? And what does that even mean?
To some, programming biology offers the opportunity to provide unparalleled material and economic abundance for the entire planet, while also improving our role as stewards of Spaceship Earth, giving us fewer reason to dig up fossil fuels or produce poisonous chemicals to manufacture the things we need and love. Others see the whole notion as little more than a faulty analogy, even a counterproductive mischaracterization that risks treating life as something much less complex and mysterious than it truly is. Climate change is just one example of how such attitudes may lead us astray. As is often the case, insight can be found in the spaces between these points of view.
The ‘Black Box’ of Biology
In recent history, humans have learned a great deal about the inner workings of living cells. Industry is now looking to innovate by interfacing with these inner workings directly, applying the logic of computation by using powerful new tools like CRISPR to edit individual genes. Human understanding of the living systems that these technologies unlock for us is still in its infancy, but they are already being put to productive use. The mRNA technology behind the COVID-19, for example, fosters immunity by directly rewriting cells’ instructions for producing proteins. If that’s not programming, what is it?
Key to the idea of programming biology is the fact that living systems run on code, DNA, which rather than ones and zeroes we interpret as A’s, C’s, T’s, and G’s. It’s a language that humans can read and are even learning to write, but we cannot yet do so fluently. By way of analogy, we can work with words and short phrases, but not full sentences, let alone paragraphs, or chapters. Changing just one letter in a genetic sequence may produce results that are good, bad, or undetectable, and very often the outcome doesn’t follow logical expectations.
Almost none of this is true of computer code, which humans understand at a fundamental level because, well, we invented it. Some argue that, for this reason, we can never truly program biology in a meaningful sense. No matter what measures we take to control it, they remind us, “life finds a way” to undermine or break out of the boxes we build around them (not always to such dramatic effect as Jurassic Park). In digital programming, predictability is key. There’s little use for a spreadsheet app that unexpectedly changes a number value every now and then. Yet one thing we can say for sure about life is that it is not predictable. In fact, evolution is powered by unpredictability, genetic mutation having contributed much of the dazzling variety of life on Earth.
At the same time, we regularly build and use complex systems of significantly limited predictability. Airplanes, traffic systems, computer networks, all are made up of so many smaller, predictable parts that their behavior is only predictable up to a point, always capable of doing something that no one sees coming. For anyone who doesn’t know its inner workings, even a perfectly constructed computer could be called a ‘black box’: we know what goes in and what comes out, without understanding what’s happening inside. Something similar could be said of the current relationship to biology.
Luckily for biotechnology, the path to progress may not require a complete grasp on the code of life. Deeper knowledge and abilities can be attained by embracing the inevitable margins of mystery that come from working with living systems. Feeding new genetic code into a cell with an expected result, while also being open to the unexpected, could be called programming, or perhaps prodding, posing a question to nature herself. While this may not be as reliable or efficient as drafting code for a computer program, the upside is that the answers are often surprising, and sometimes relate to questions that weren’t even asked. That’s how innovation happens, and it sets biology apart from any other ‘programmable’ domain in some exciting ways.
In industry, there is not the luxury of waiting for a full grasp of the complex systems that evolution has dreamt up over the last four billion years before they can be put to use. The imperative to hit milestones and deliver useful, scalable, and ultimately marketable products leaves no option except to find the most direct path to the best and most useful outcomes. Accepting the reality of working with unpredictability means building mostly predictable systems that can tolerate the many unexpected — but often useful — behaviors of nature. Once those processes are within the realm of repeatability accepted by traditional computation or manufacturing processes, the distinction becomes less important.
The complexity of biology is cause for humility, but also enthusiasm. There is an opportunity in biotechnology to learn and even harness processes and abilities that no one could never invent, let alone fully understand. We didn’t invent the chicken, for example, and certainly don’t understand all its working parts, what’s going on in its mind when we feed them, or what the chain of events that converts grains into an egg that can produce an entire new chicken. But they offer us so much value, reliably and at scale, that they might as well be considered advanced technology. The question of whether gene editing and coding living systems amounts to ‘programming’, then, is largely semantic. It’s also secondary to the real question: what will be done with these new and ever-improving abilities? In trying to understand the fundamental workings of biology, so long as we are finding ways of improving our quality of life and the health of the planet, it shouldn’t really matter what word we use to describe it.