Aggregation of Sponge Cells - The Journal of Biological Chemistry
Programming Biological Cells
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Programming Biological Cells Ron Weiss, George Homsy, Radhika Nagpal rweiss,ghomsy,radhi @ai.mit.edu MIT Laboratory for Computer Science and Artificial Intelligence It appears that biological organisms can be harnessed as substrates for computation. Biological cells possess important characteristics, such as energy efficiency, self- reproduction, and miniature scale, that make them attractive for many applications. Examples include embedded intelli- gence in materials, sensing, smart medicine, and nanoscale fabrication. Vast numbers of programmed cells executing in parallel will enable cheap computation. This abstract argues that individual cells are programmable, and presents a pro- gramming paradigm for colonies of cells. Cellular Gates A fundamental chemical process in the cell is the production of proteins from genes encoded in the DNA. The cell per- forms important regulatory activities through DNA-binding proteins that repress the production of specific proteins. [2] proposes using this regulatory mechanism to implement dig- ital logic inverters. This idea can be extended to construct complex digital logic, making the cell a self-contained com- putational unit. Microbial circuit design creates a biological digital circuit using a small set of basic gates and a database of protein ki- netic rates. To prevent interference between the gates, a dif- ferent protein is used for each unique signal. Therefore, the number of proteins needed to implement a circuit is propor- tional to the complexity of the circuit. The design process requires searching the database and assigning suitable pro- teins to each gate, where the dynamic characteristics of the gate may differ depending on the proteins chosen. The basic gates must be robust enough to function with a wide variety of kinetically different proteins. Figure 1: Genes and Proteins of a Biological
Transcript of Programming Biological Cells
Programming Biological CellsRon Weiss, George Homsy, Radhika Nagpal
rweiss,ghomsy,radhi @ai.mit.edu
MIT Laboratory for Computer Science and Artificial Intelligence
It appears that biological organisms can be harnessedas substrates for computation. Biological cells possessimportant characteristics, such as energy efficiency, self-reproduction, and miniature scale, that make them attractivefor many applications. Examples include embedded intelli-gence in materials, sensing, smart medicine, and nanoscalefabrication. Vast numbers of programmed cells executing inparallel will enable cheap computation. This abstract arguesthat individual cells are programmable, and presents a pro-gramming paradigm for colonies of cells.
Cellular GatesA fundamental chemical process in the cell is the productionof proteins from genes encoded in the DNA. The cell per-forms important regulatory activities through DNA-bindingproteins that repress the production of specific proteins. [2]proposes using this regulatory mechanism to implement dig-ital logic inverters. This idea can be extended to constructcomplex digital logic, making the cell a self-contained com-putational unit.
Microbial circuit design creates a biological digital circuitusing a small set of basic gates and a database of protein ki-netic rates. To prevent interference between the gates, a dif-ferent protein is used for each unique signal. Therefore, thenumber of proteins needed to implement a circuit is propor-tional to the complexity of the circuit. The design processrequires searching the database and assigning suitable pro-teins to each gate, where the dynamic characteristics of thegate may differ depending on the proteins chosen. The basicgates must be robust enough to function with a wide varietyof kinetically different proteins.
Figure 1: Genes and Proteins of a Biological Latch
We are currently implementing a digital abstraction in E.coli bacteria. A model of the chemical dynamics of digitallogic was developed using characteristics of known proteinsencoded by the lambda-phage virus. Several basic gateshave been designed, such as a biological RS-latch for storingstate. The latch uses two input proteins for and ,and cross couples the output proteins and to maintain
Authors are advised by Gerry Sussman, Hal Abelson, and Tom Knight,and are supported by DARPA under contract number N00014-96-1-1228administered by ONR.
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Figure 2: Dynamic Behavior of a Biological Latch
state (Figure 1). The simulated dynamic behavior of thisgate shows that a biological RS-latch is plausible (Figure 2).In parallel with the modeling effort we are building a ringoscillator in the lab, creating the first bacterial digital circuit.
Programming a Colony of CellsIndividual biological cells have limited computational ca-pacity and frequently fail. However, by programming largecolonies of cells that execute in parallel and coordinatingtheir actions through intercellular communication, signifi-cant computational power can be achieved. The goal ofthe Amorphous Computing project [1] is to develop novelparadigms for programming such substrates.
The Microbial Colony Language is a programmingparadigm simple enough for biological cells, yet expressiveenough to implement interesting applications. The languageexposes programming mechanisms that biological cells canperform reliably. The program for a single cell comprisesevent-triggered rules, boolean state, boolean operations, andlimited range chemical diffusion for communication. Wehave implemented protein-level and language-level simula-tors that model cell colonies executing microbial programs.Simulations show that these programs can produce largescale pattern generation and coordinated group behavior.
The endeavor to create programmable biological systemsis only a first step toward expanding the role and nature ofcomputation beyond traditional applications.
References
[1] Abelson, Knight, and Sussman. Amorphous computing.White paper, October 1995.
[2] Knight and Sussman. Cellular gate technology. In Un-conventional Models of Computation, 1997.
