Programming Biological Cells

1
Programming Biological Cells

• Ron Weiss, George Homsy, Radhika Nagpal
• Tom Knight, Gerald Sussman, Nick Papadakis
• MIT Artificial Intelligence Laboratory

2
Motivation

• Goal program biological cells
• Characteristics
• small (E.coli 1x2?m , 109/ml)
• self replicating
• energy efficient
• Potential applications
• smart drugs / medicine
• agriculture
• embedded systems

3
Approach
Outline

• Building biological digital circuits
• compute, connect gates, store values
• High-level programming issues

4
Compute Biological Inverter

• signal protein concentration level
• computation protein production decay

5
Inverter Behavior

• Simulation model based on l phage biochemistry

A

active gene
Z
time (x100 sec)
6
Connect Ring Oscillator

• Connected gates show oscillation, phase shift

A
B
C
time (x100 sec)
7
Memory RS Latch
time (x100 sec)
8
Microbial Circuit Design
logic circuit
genome
microbial circuit compiler
BioSPICE
protein DB

• Assigning proteins is hard.
• BioSPICE Simulate a colony of cells

9
BioSPICE

• Prototype protein level simulator
• intracellular circuits, intercellular
  communication

protein concentration
cell
Simulation snapshot
10
High Level Programming

• Requires a new paradigm
• colonies are amorphous
• cells multiply die often
• expose mechanisms cells can perform reliably
• Microbial programming language
• example pattern generation using aggregated
  behavior

11
Conclusions Future Work

• Biological digital gates are plausible
• Now
• Implement digital gates in E. coli
• Also
• Analyze robustness/sensitivity of gates
• Construct a protein kinetics database
• Study protein?protein interactions for faster
  logic circuits