The birth of biocomputing (on paper)

Read an article this past week discussing how researchers in Barcelona Spain have constructed a biological computing device on paper (see Biocomputer built with cells printed on paper). Their research was written up in a Nature Article (see 2D printed multi-cellular devices performing digital or analog computations).

We’ve written about DNA computing and storage before (see DNA IT …, DNA Computing… posts and our GBoS podcast on DNA storage…). But this technology takes all that to another level.

2-bit_ALU (from
2-bit_ALU (from

The challenges with biological computing previously had been how to perform the input processing and output within a single cell or when using multiple cells for computations, how to wire the cells together to provide the combinational logic required for the circuit.

The researchers in Spain seemed to have solved the wiring problems by using diffusion across a porous surface (like paper) to create a carrier signal (wire equivalent) and having cell groups at different locations along this diffusion path either enhance or block that diffusion, amplify/reduce that diffusion or transform that diffusion into something different

Analog (combinatorial circuitry types of) computation for this biocomputer are performed based on the location of sets of cells along this carrier signal. So spatial positioning is central to the device and the computation it performs. Not unlike digital or combinatorial circuitry, different computations can be performed just by altering the position along the wire (carrier signal) that gates (cells) are placed.

Their process seems to start with designing multiple cell groups to provide the processing desired, i.e., enhancing, blocking, transforming of the diffusion along the carrier signal, etc. Once they have the cells required to transform the diffusion process along the carrier signal, they then determine the spatial layout for the cells to be used in the logical circuit to perform the computation desired. Then they create a stamp which has wells (or indentations) which can be filled in with the cells required for the computation. Then they fill these wells with cells and nutrients for their operation and then stamp the circuit onto a porous surface.

The carrier signal the research team uses is a small molecule, the bacterial 3OC6HSL acyl homoserine lactone (AHL) which seems to be naturally used in a sort of biologic quorum sensing. And the computational cells produce an enzyme that enhances or degrades the AHL flow along the carrier signal. The AHL diffuses across the paper and encounters these computational cells along the way and compute whatever it is that’s required to be computed. At some point a cell transforms AHL levels to something externally available

They created:

  • Source cells (Sn) that take a substance as input (say mercury) and converts this into AHL
  • .Gate cells (M) that provide a switch on the solution of AHL difusing across the substrate.
  • Carrier reporter cells (CR) which can be used to report on concentrations of AHL.

The CR cells produce green florescent reporter proteins (GFP). Moreover, each gate cell expresses red florescent reporter proteins (RFP) as well for sort of a diagnostic tap into its individual activity.

Mapping of a general transistor architecture on a cellular printed pattern obtained using a stamping template. Similar to the transistor architecture, the cellular pattern is composed of three main components: source (S1 cells), gate (M cells) that responds to external inputs and a drain (CR cells) as the final output responding to the presence of the carrying signal (CS). b Stamping template used to create the circuit made of PLA with a layer of synthetic fibre (green). Cellular inks (yellow) are in their corresponding containers. Before stamping, the synthetic fibre is soaked with the different cell types. Finally, the stamping template is pressed against the paper surface, depositing all cells. c Circuit response. In the absence of external input, i.e. arabinose, the CS encoded in the production of AHL molecules by S1 cells diffuses along the surface, inducing GFP expression in reporter cells CR. In the presence of 10−3 M arabinose (Ara), the modulatory element Mara produces the AHL cleaving enzyme Aiia, which degrades the CS. Error bars are the standard deviation (SD) of three independent experiments. Data are presented as mean values ± SD. Experiments are performed on paper strips. The average fold change is 5.6x. d Photography of the device. Source data are provided as a Source Data file.

Using S, M and CR cells they are able to create any type of gate needed. This includes OR, AND, NOR and XNOR gates and just about any truth table needed. With this level of logic they could potentially implement any analog circuit on a piece of paper (if it was big enough).

a Schematic representation of the multi-branch implementation of a truth table. bImplementation of different logic gates. A schematic representation of the cells used in each paper strip and their corresponding distance points is given (Left). Gates with two sources of S1 (OR and XNOR gates) are circuits carrying two branches, while the other gates (NOR and AND gates) can be implemented with just one branch. Input concentrations are Ara = 10−3 M and aTc = 10−6 M. M+aTc and MaTc are, respectively, positive and negative modulatory cells responding to aTc. M+ara and Mara are, respectively, positive and negative modulatory cells responding to arabinose. S1 cells produce AHL constitutively and CR are the reporter cells. Error bars are the standard deviation (SD) of three independent experiments. The average fold change has been obtained from the mean of ON and OFF states from each circuit. OR gate 14.31x, AND gate 6.21x, NOR gate 6.58x, XNOR gate 5.6x. Source data are provided as a Source Data file.

As we learn in circuits class, any digital logic can be reduced to one of a few gates, such as NAND or NOR.

As an example of uses of the biocomputing, they implemented a mercury level sensing device. Once the device is dipped in a solution with mercury, the device will display a number of green florescent dots indicating the mercury levels of the solution

The bio-logical computer can be stamped onto any surface that supports agent diffusion, even flexible surfaces such as paper. The process can create a single use bio-logic computer, sort of smart litmus paper that could be used once and then recycled.

The computational cells stay “alive” during operation by metabolizing nutrients they were stamped with. As the biocomputer uses biological cells and paper (or any flexible diffusible substrate) as variable inputs and cells can be reproduced ad-infinitum for almost no cost, biocomputers like this can be made very inexpensively and once designed (and the input cells and stamp created) they can be manufactured like a printing press churns out magazines.


Now I’d like to see some sort of biological clock capability that could be used to transform this combinatorial logic into digital logic. And then combine all this with DNA based storage and I think we have all the parts needed for a biological, ARM/RISC V/POWER/X86 based server.

And a capacitor would be a nice addition, then maybe they could design a DRAM device.

Its one off nature, or single use will be a problem. But maybe we can figure out a way to feed all the S, M, and CR cells that make up all the gates (and storage) for the device. Sort of supplying biological power (food) to the device so that it could perform computations continuously.

Ok, maybe it will be glacially slow (as diffusion takes time). We could potentially speed it up by optimizing the diffusion/enzymatic processes. But it will never be the speed of modern computers.

However, it can be made very cheap, and very height dense. Just imagine a stack of these devices 40in tall that would potentially consist of 4000-8000 or more processing elements with immense amounts of storage. And slowness may not be as much of a problem.

Now if we could just figure out how to plug it into an ethernet network, then we’d have something.

Photo credit(s):

  • 2 Bit alu from Wikipedia
  • Figures 1 & 3 from Nature article 2D printed multi-cellular devices performing digital and analog computation

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