Biological computing is a promising field with potential applications, yet past engineered
genetic circuits for logic gates have suffered from excessive complexity, cumbersome
operation, and reliance on multiple input substances.
To overcome these issues, we decided not to confine computation within cells. Therefore, we
created the LOGIC project, proposing an in vitro logic computing
system based on bacterial quorum sensing and spatial diffusion, including lightweight adders
and
a light-induced QS molecular degradation system.
We have also developed LOGIC Toolkit, which provides new methods for the next generation of
iGEMers and researchers to explore biological computing.
Introduction
Engineering biological systems capable of computation has long been a goal of biology, which can
be applied in fields such as biosafety or environmental monitoring, or as a basic component in
computer construction. [1]
Background
In binary addition, the circuit consists of several basic logic gates:
AND gate:
Outputs 1 only when both inputs are 1.
Input A
Input B
Output (A AND B)
0
0
0
0
1
0
1
0
0
1
1
1
OR gate:
Outputs 1 as long as one input is 1.
Input A
Input B
Output (A OR B)
0
0
0
0
1
1
1
0
1
1
1
1
XOR gate:
Outputs 1 when the two inputs are different.
Input A
Input B
Output (A XOR B)
0
0
0
0
1
1
1
0
1
1
1
0
A binary adder consists of a half-adder and full-adders (Figure 1). The half-adder is used to process
the first bit calculation, while the full-adder is used to process the second and higher bit
calculations. By connecting the half-adder and full-adder in series, binary addition can be
achieved.
Figure 1. Half-Adder & Full-Adder
Biological computing is the process of using cells to simulate the above logic gates and adders.
Current biological computing
scheme
To date, the most common paradigm in biological computing has been to engineer logic circuits into
gene regulatory networks within cells.[2][3][4]
However, this method requires complex genetic circuits to achieve logic gate functions, and it's
complexity is constrained by the number of available orthogonal components and metabolic burden. In
addition, each new function requires extensive genetic engineering, which makes the system
inflexible.
Figure 2. Constructing multiple logic gates in
single cells using
regulatory elements of the bacterial type III secretion system (T3SS). [2]
Figure 3. Constructing hierarchical AND gates
within a single cell
to mimick the electronic combination lock.[3]
Figure 4. Implementing the Sierpinski Triangle
in bacterial
colonies using logic gates (XOR gates). [4]
Our Solution
Logic Gates & Adders
Through computational and experimental evidence, it has been proven that a single modular colony
Through computational and experimental evidence, it has been proven that a single modular colony
can perform simple digital logic operations.[1] By combining
multiple colonies, complex adders can be constructed, thereby eliminating the need for further
genetic editing of bacteria. We utilized quorum-sensing systems to implement dual- or multi-input
logic gates, which were then assembled into half-adders and full-adders for binary addition,
ultimately producing the computational output.
The computational system constructed using this method is highly lightweight and flexible,
offering a new approach to biological computing. There are two basic genetic circuits used to
perform logical calculations: high-pass and band-pass.[1]
High-pass: Downstream gene expression is activated when the
concentration of the signal molecules exceeds the threshold.
Band-pass: Downstream gene expression is activated when the
concentration of the signal molecules is within a specific range.
We will use these two basic circuits to construct the half-adder and full-adder.
Spatial Computation
Figure 5. OR gate and AND gate implementation
through spatial
configuration
With "high-pass" and other engineered bacteria, we can now proceed to construct logic
gates. Unlike conventional logic gates, LOGIC operates as a form of spatial computation: the
input is defined by the local concentration of AHL molecules, while the output is reported
through the fluorescence intensity of sfGFP.
The characteristic of a “high-pass” colony is that it requires the AHL input concentration to
reach a certain threshold before producing an output. It is easy to imagine that the closer the
AHL input point is to the processor colony, the higher AHL concentration produced at the
high-pass colony.
For easy understanding, we now roughly classify AHL input points by their distance from the
engineered bacteria into “nearby AHL input points” and “far AHL input points”. For a “high-pass”
engineered processor bacterium, if we provide two “nearby AHL input points”, then a signal at
just one input point is sufficient to activate the “high-pass” bacterium—clearly, this
constitutes an OR gate. Similarly, if we provide the “high-pass” with two “far AHL input
points”,
constitutes an OR gate. Similarly, if we provide the “high-pass” with two “far AHL input
points”,
it is easy to see that only when both input points carry AHL signals will the “high-pass”
bacterium be activated, yielding an AND gate (Figure 6)!
Figure 6. Full-adder implementation with three
inputs and two
outputs
By employing "high-pass" and "band-pass" composite module combined with spatially configured
input,
we can achieve a series of logic gates including OR, AND and XOR, among others. Under
multi-input
and multi-output conditions, more complex logic functions can be realized. For example, a
full-adder
By employing "high-pass" and "band-pass" composite module combined with spatially configured
input,
we can achieve a series of logic gates including OR, AND and XOR, among others. Under
multi-input
and multi-output conditions, more complex logic functions can be realized. For example, a
full-adder
can be readily implemented using three inputs and two outputs, with the results mediated
by one “band-pass” and one “high-pass” composite module (Figure 7).
This provides the foundational components for computing arbitrary logic functions and building
biological computers. What's more, effective signal transmission between colonies is also
needed. After constructing the logic gate colonies and the connector colonies, we can then build
a binary adder.
Orthogonal Systems
Figure 7. The role of orthogonal AHL molecular
systems
Perhaps you have already noticed that spatial computation imposes strict requirements on the
distances and spatial arrangement between AHL signal input points and downstream engineered
bacteria—for example, preventing spatial crosstalk among inputs and outputs, and ensuring
that the distance between the engineered bacteria and the AHL input sources is appropriate.
As the complexity of logic computation increases, the system complexity rises
sharply. To raise the upper limit of our biological circuits' complexity within limited
space while maintaining signal accuracy, we employed orthogonal AHL molecular systems.[5]
Degradation Modules
Figure 8. Schematic diagram of light-controlled
components
After constructing the computation in space, we further aimed to achieve temporally
sustained and repeatable computation.
Revisiting our project LOGIC, the current design cannot support our adder to perform multiple
rounds of addition. To enable multi-round operations, the existing computational state must be
reset—i.e., residual AHL in the agar and the fluorescence used as the output signal need to be
cleared.
To provide controllable and timely clearing and resetting of computational results, we designed
an opto-degradation module. To degrade residual AHL molecules, we employed the
quorum-sensing-molecules-degrading enzyme AiiA[6], and fused it
with the blue-light-responsive photoreceptor domain VVD, enabling light-controlled regulation of
its enzymatic activity.[7] For the fluorescence outputs, we add
a protein degradation tag based on the AsLOV2 protein to fluorescent reporters, enabling
light-inducible degradation of the fluorescent signal.[8]
LOGIC Toolkit
To facilitate understanding and application of LOGIC, we digitized experimental data and performed
curve fitting for both diffusion dynamics and cellular responses. By characterizing the diffusion
field and cellular response, we can design input spatial patterns that yield specific logic outputs.
We also developed visualization software based on the fitted curves to facilitate understanding of
LOGIC and predict outcomes. Additionally, to minimize operational artifacts, we designed and and
build a software-driven precision positioning hardware device. Finally, we integrated the components
and tools developed during experimentation into the LOGIC toolkit.
Figure 9.(A) Orthogonal AHL
biosensors and diffusion-response
mapping. (B) Logic gate modules. (C) Light-induced
degradation. (D) Modeling method of spatial
computation. (E) Software for visualization and debugging. (F)
Hardware for easier colony
localization.
Fedorec, A. J. H., Treloar, N. J., Wen, K. Y., Dekker, L., Ong, Q. H., Jurkeviciute, G., Lyu,
E., Rutter, J. W., Zhang, K. J. Y., Rosa, L., Zaikin, A., & Barnes, C. P. (2024). Emergent
digital bio-computation through spatial diffusion and engineered bacteria. Nature
Communications, 15(1). https://doi.org/10.1038/s41467-024-49264-3
Moon, T. S., Lou, C., Tamsir, A., Stanton, B. C., & Voigt, C. A. (2012). Genetic programs
constructed from layered logic gates in single cells. Nature, 491(7423), 249–253. https://doi.org/10.1038/nature11516
Jonkergouw, C., Savola, P., Osmekhina, E., Van Strien, J., Batys, P., & Linder, M. B. (2023).
Exploration of chemical diversity in intercellular quorum sensing signalling systems in
prokaryotes. Angewandte Chemie International Edition, 63(2). https://doi.org/10.1002/anie.202314469
Han, T., Chen, Q., & Liu, H. (2016). Engineered photoactivatable genetic switches based on the
bacterium phage T7 RNA polymerase. ACS Synthetic Biology, 6(2), 357–366. https://doi.org/10.1021/acssynbio.6b00248
Tague, N., Coriano-Ortiz, C., Sheets, M. B., & Dunlop, M. J. (2023). Light-inducible protein
degradation in E. coli with the LOVdeg tag. eLife, 12. https://doi.org/10.7554/elife.87303
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