Engineers learning how to program DNA molecules are at the cutting edge of what may be the next great technological revolution, adding to the steam engine, the industrial revolution, and the computer age. And they’re doing it with intelligent design.

Welcome to the labs of Caltech’s Molecular Programming Project (MPP), where scientists are building machinery, software, and art out of DNA molecules. A fascinating article about the work at MPP in Caltech’s magazine Engineering and Science describes what they have already achieved, and what they hope to accomplish.¹ Readers will see little if any use to which evolutionary theory is being put here, yet great enthusiasm for nano-design, despite the fact that Caltech (like most secular universities) treats Darwinian evolution as a given.

In fact, let’s dispense right up front with the only mention of evolution in the article: “computer technology has been evolving faster than anyone ever anticipated.” Wait a minute; by “evolution” there they mean intelligent design. Let’s try this one: “Biology has exploited that inherent essence of nature to do what biology wants to do: to reproduce, to evolve, to build really complex animals, and to build brains.” Hold on; that’s not Darwinian evolution either, that’s a personification of “Biology” as designer substitute. Other than a mention of “galactic evolution” (which is a law-driven process unrelated to Darwin’s notion of progress by unguided contingencies), “evolution” is strangely absent in this article, even though it uses other biological terms some 32 times. Word searches for “evol-” are more likely to turn up “revolution,” as in “technological revolution,” while searches for “bio-” yield the trendy neologism, “bioengineering.”
One of the leading protagonists is Paul Rothemund, a computer scientist who illustrates that one need not have more than a bachelor’s degree to advance science. A Senior Research Associate at the MPP, Rothemund and colleagues have developed ways to assemble DNA molecules into building blocks akin to Lincoln Logs that snap together. A few years ago, he pioneered “DNA Origami,” a way to create arbitrary shapes out of DNA, including smiley faces, maps of the world, snowflakes, and messages in English text. More recently, Rothemund and grad student Sungwook Woo have expanded the possibilities by refining the edges of the blocks with 16 different shapes: a kind of code. This allows for an exponential increase in the complexity of shapes that can be built, all the way from logic circuits to self-assembling nanobots. Notice how he draws on a familiar “watchmaker” analogy in his machine-language description:

In addition to enabling larger structures, these techniques could ease us past a sticking point on the way to a full-on, sci-fi, self-assembling nanobot: the problem of moving parts. “A human-scale analogy would be to take all the parts for a car, paint them with glue, throw them in a bag, shake it, and have a working car pop out,” Rothemund says. But DNA base-pair binding makes for a very powerful molecular adhesive — your car’s motor wouldn’t run and the wheels wouldn’t turn. Even the wipers would be stuck to the windshield. “We think that we will be able to design stacking bonds in which the parts of a nanomachine will be able to self-assemble and then slide freely past each other,” he continues. “The parts won’t look exactly like interlocking log walls, but they will work on the same basic principle.”

With a brilliant analogy, Rothemund points to another advantage of molecular architecture: ultra-fine precision. Does his analogy suggest that whales are intelligently designed? Sounds like it to us.

Compare a whale and a submarine, he explains. Both are about the same size, and both propel themselves underwater. A submarine is made up of relatively large pieces — steel panels and pipes, screws and bolts. But a whale’s internal structure extends all the way down to the arrangement of the individual protein molecules in its cells. In other words, a chunk of whale has a lot more going on than an equal-sized chunk of submarine.

Even so, building the parts is not enough. Another level of design is required to create a car or a nanobot: intelligently designed software. That, too, can be programmed into DNA, as the next “bioengineer” explains. Here’s the lead-up to his story (notice again the “design” language):

In order to make these parts self-assemble, however, each one has to know exactly where it’s going and how it fits into the grand design. And this is a problem: say you had several thousand unique shapes at your disposal — that’s still not enough to orchestrate the spontaneous coalescence of a piece of human-scale technology. “If we wanted to self-assemble a cell phone, origami won’t do it,” says Erik Winfree (PhD ’98), a computer scientist and director of the MPP. “But algorithmic processes could.”

It’s intuitive that “algorithmic processes” are intelligently designed. Earlier last year, Winfree and his colleagues succeeded in programming DNA into software that can calculate the square roots of integers up to 15 (find a natural process that can do that). It took 74 pre-programmed DNA molecules to create the logic circuit able to solve this simple math problem. Even so, it could not yield decimal precision; that’s “a bit beyond its capacity at the moment,” and it required a 10-hour wait for the answer.

Nevertheless, these baby steps are akin to the initial work of James Watt or Michael Faraday that started small and changed the world. Molecular programming is repeating the history of the computer revolution: first you program with bits, then with assembly language, then with high-level languages, then with objects and modular architecture. One thing DNA computing has over silicon chips is the ability to control other molecules. Rothemund explains:

“Molecular computers, no matter how simple, can be used to control other molecular phenomena.” No silicon computer has this power, but it’s DNA’s natural role. “The whole process of embryonic development is controlled by a molecular computer performing logical operations — ‘If X then Y, but only if A hasn’t happened.’ And even though it doesn’t solve anything we’d recognize as a computationally difficult problem, its computation serves to make a very complicated object.”

This means that “natural” embryonic development is teaching bioengineers how to control moving parts. Some MPP experiments have succeeded in programming “motive power” into molecular machines that can “walk” down tracks. (Does that sound familiar? Ever heard of dynein and kinesin in living cells?) Richard Murray is designing algorithms with feedback loops to mimic homeostasis — keeping dynamic systems within prescribed tolerances. “Since feedback is also crucial to biology — it’s how your body regulates your blood-sugar levels, for instance — he’s applying control-system principles to molecular programming.” Winfree and his team have already jumped beyond simple algorithms to neural network designs that mimic the brain. Others like Niles Pierce are working on “molecular instruments” that can search out and destroy cancer cells.

Will we have molecular apps on molecular smartphones some day? Wait and see. MPP team member Shuki Brook envisions a day when ordinary citizens can program apps using modular algorithms running on DNA computers, without having to understand biology, just like they design web pages, write documents, and create smartphone apps without knowing anything about silicon chips.

“The possibilities,” Pierce says, “are essentially endless.” And in this Caltech article about the MPP, a “quintessential engineering activity,” the connection between engineering and biology is seamless. Embryonic development is, after all, the execution of a molecular algorithm: “a powerful computing language already exists in the form of DNA molecules, which encode all the information any organism needs to develop, grow, and reproduce, whether it’s a bacterium, an elephant, or a towering redwood.” The bioengineers at MPP believe their work will provide insights into the design of life itself — in ways we cannot yet imagine — ways that may require new concepts and a new language. Molecular programming forces scientists to think of life in design terms:

Although the MPP is informed by the computer revolution, it’s rooted in aspirations to understand how life works. “Understanding biological systems is the most important challenge for the next 100 years,” says Bruck, whose background is electrical engineering, but who now focuses his research on computing with biological circuits. “If you compare our world to anything else in the universe, based on what we know so far, we have life here and not anywhere else. That’s the most precious thing we have here, and we still don’t understand it.”

Design-based science is leaving Darwin in the dust. “The difference between the MPP and what other people are doing with nanotechnology and biotechnology is that we’re trying to think in terms of information science,” Murray said. “For a computer scientist like Winfree, the MPP is about the idea that information is the essence of nature,” author Marcus Y. Woo explained; “that life is driven by the programming power of DNA.” There may well come a day when human-designed molecular algorithms become indistinguishable from “natural” ones. If so, natural selection — or any other theory of unguided causes — would become incoherent.

The intelligent design movement may now take a bow and say, “We told you so.” We said the DNA code and its algorithms are analogues to computer software; now the latecomers are catching on. We said intelligent design makes predictions and leads to testable conclusions. We said that codes upon codes in hierarchical networks are best explained by intelligent causes rather than undirected processes like mutation and natural selection. We said that intelligent design is a fruitful scientific theory. We said information is a fundamental property of life and the universe.
Now the light has dawned. In spite of their metaphysical preconceptions, Caltech scientists are demonstrating all this.

Literature Cited
1. Marcus Y. Woo, “Programming Molecular Apps.” Engineering & Science, Winter 2012, pp. 27-33. This quarterly magazine does an exemplary job of bringing complex ideas down to an educated layman’s level with helpful analogies and colorful descriptions.