Universal computing by DNA origami robots in a living animal

Yes, they can build circuits. See the supplementary materials, which also contain all the how-tos (ProTip: although most journal articles are behind paywalls, the materials & methods stuff is often freely accessible, at least for the Nature and Science journal families. It's also often a lot easier to read and understand for the lay person who isn't already familiar with the field in questions, assuming that your interest is more in the engineering than the science end - I see many papers whose theoretical validity I am incompetent to assess, but whose experimental process I am able to understand.) http://www.nature.com/nnano/journal/vaop/ncurrent/extref/nna...

EDIT: I spoke too soon. Section 6 of the supplementary material, which explores the idea of building more complex circuits and the scaling issues therewith, is unfortunately missing right now. I notified the authors and I'm sure that will be fixed soon. Meanwhile, here's what they say in the paper:

The architectures described here are capable of processing two input bits at most. However, the outputs from two 'processors’ can be relayed to a third and increase the processing capacity (limited by the possible number of unique gate-key systems that can be designed). Importantly, the scaling of our design is linear rather than logarithmic, with errors in robot activation propagating in the order of the root sum square of the number of unique robot types in a system (Supplementary Note 6). Figure 4 presents a schematic of a hypothetical 4-input bit architecture for an imaginary task of controlling three therapeutic molecules simultaneously, where only the number of robots comprising the system limits its capacity. The basic concept we describe can be scaled plausibly to exceed the capacity of older 8-bit computers such as a Commodore 64 or Atari 800, which many of us had experience of as children.

WTF |8-.

Where you get that stuff: the robots are designed with CADnano, which is free software: http://cadnano.org/ and programmed with Visual DSD, a free project from Microsoft: http://boson.research.microsoft.com/webdna/ and http://research.microsoft.com/en-us/projects/dna/manual.pdf

(isn't it nice that 'webDNA actually means DNA programming on the web' instead of some marketing department BS?) The raw material DNA strands are available from commercial suppliers.

IO is currently done by fluorospectroscopy, which is very common in experimental biology - you make compounds that flouresce inside the cell, then pull out some blood/do a biopsy/chop up the host if it's something very primitive and measure the degree of flourescence. So your unit testing is basically probabilistic rather than deterministic.

There's course material on this kind of thing at http://www.dna.caltech.edu/courses/cs191/index.html

From wikipedia:

>DNA computing is fundamentally similar to parallel computing in that it takes advantage of the many different molecules of DNA to try many different possibilities at once.[11] For certain specialized problems, DNA computers are faster and smaller than any other computer built so far. Furthermore, particular mathematical computations have been demonstrated to work on a DNA computer. As an example, DNA molecules have been utilized to tackle the assignment problem.[12] Aran Nayebi[13] has provided a general implementation of Strassen's matrix multiplication algorithm on a DNA computer, although there are problems with scaling. In addition, Caltech researchers have created a circuit made from 130 unique DNA strands, which is able to calculate the square root of numbers up to 15.

Perhaps it can be used in nanobots. Also being slow isn't necessarily a disadvantage if it could be made much cheaper. Biology can rapidly self-replicate out of everyday materials. It can also run efficiently on chemical energy and even sunlight. Though these likely don't apply to this research, just biocomputers in general.

That's always the best choice. Here's the paper itself: http://life-sciences.biu.ac.il/files/life-sciences/media/nna...

Searching on the title and appending 'filetype:pdf' for Google will often return a preprint or a copy from the authors' institutional website.

As for the content - wow, amazing work. I'm no biotechnologist but this seems like the gateway to an algorithmic approach to medicine. I wonder if it could be turned around to measure intra-cellular processes and send out signals by producing nonreactive chemical tracers...oh yes, it's addressed on page 4.

How long before we see biological botnets? Fascinating stuff.

It will then find some way to sit on itself while you're working on it.