Transforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiTransforming cells into AutomataBased on the following papers● [1] Engineering Life: Building a FAB for Biology – David Baker, GeorgeChurch,Jim Collins, Drew Endy, Joseph Jacobson, Jay Keasling, Paul Modrich,ChristinaSmolke and Ron Weiss● [2]Genetic Circuit Building Blocks for Cellular Computation, Communications,andSignal Processing – Ron Weiss, Subhayu Basu, Sara Hooshangi, AbigailKalmbach, David Karig, Rishabh Mehreja and Ilka NetravaliAdditional References● Slides of Michael Fisher● http://wikipedia.enIntroductionBiological Systems Engineering (BSE) is a broad-based engineering disciplinewith additional emphasis on biology and chemistry. It is not to be confused with Biomed-ical Engineering and it is not necessarily Genetic Engineering, although the line betweenthe two is sometimes blurred. The discipline focuses on environmentally sound, sustain-able engineering solutions to meet societies’ needs. Biological Systems Engineering is abroad and growing engineering field that integrates the expertise of fundamental engi-neering fields with expertise from non-engineering disciplines.Gene Network: A gene network (also called a Gene Regulatory Network (GRN) or ge-netic regulatory network,) is a collection of DNA segments in a cell which interact witheach other and with other substances in the cell, thereby governing the rates at whichgenes are transcribed into mRNA. Genes can be viewed as nodes in such a network, withinputbeing proteins such as transcription factors, and outputs being the level of geneexpression. The node itself can also be viewed as a function which can be obtained bycombining basic functions upon the inputs (such as and, nand, or gates in electronics).These functions perform information processing within the cell and determines its behav-ior. Now cells can be viewed as units that can perform computation, communications andsignal processing. In the area of genomic biology, single gene prespectives are becoming ncreasinglylimited for gaining insght into biological processes. Gene networks are important fr mak-ing progress in our understanding of the manners in which genes and molecules collec-tively form a biological system. For example, cells can be programed to detect high bloodsugar levels and are able to release insulin.Transforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiElectrical circuit vs Genetic circuitsElectrical Circuits Biological CircuitsBasic Building blocks Transistors GenesInputs 1=5 volts0=0 volts1= High protein concentration0=low protein concentrationLayout and Design On circuit boards con-nected by wiresIn a cell in an open environ-mentExecution Pattern Deterministic(All boards with the samelayout will perform in thesame way)Stochastic (cells programmedidentically and under the sameenvironmental conditions willvary in their behavior)Building Genetic circuits involve building a genetic component library, assembling theminto biocircuits, tuning the circuit and ints components till the desired output is reachedand checking the output by using a fluorescent protein as a reporter. The promoter is the regulatory region of the DNA upstream of the gene that promotestranscription. the florescent protein is used to determine if the final protein was produced.Transforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiBuilding blocksBefore programming cells and controlling their behavior, we need to establish a library ofwell defined components that serves as the building blocks of more complex systems. Not GateIn the above figure 0 indicates no input mRNA so the RNAp can transport through geneproducing output mRNA or output protein in other words. 1 indicates presence of inputmRNA so it hinders the RNAp through transport through the gene producing no outputprotein. Nand GateTransforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiNor GateBoth NOR and NAND gates can be used to form any type of gates. They are most popu-lar gates in processor design because of their versatility.Inputing Data and Detecting ConditionsWe input in form of repressors and inducer to detect the environmental conditionsusing the biological circuits. ● Inducer is a small molecule that binds to a specific area of the activator or repres-sor.● Activator is a DNA binding protein that regulates genes by increasing the rate oftranscription by attracting RNAp to the promoter.● Repressor is a DNA binding protein that regulates genes by derceasing the rate oftranscription by repelling RNAp from the promoter. For external interaction (inputing to the cell), we use IMPLIES gate and for cell-cell in-teraction, we use AND gate. In the below figure, when we have both inducer and repressor, the inducer changes therepressor making the RNAp to transport through the gene producing 1 as output.Transforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiImplies gateAnd GateTransforming cells into Automata CS374 Spring 2008 Lecture 15, 05/20/08Presenter: Michael Fisher Scribe: Aditya JamiIn the above figure, the two figures corresponds to 1 0 and 0 1 in the truth table. In thisconstruct, RNAp has a low affinity for the promoter and thus the basic transcription isminimal. When only activator is present, the output is still LOW, since the activator haslittle affinity for the operator without the corresponding inducer. The output is HIGH onlywhen the inducer binds the activator and changes its conformation, yielding complex in-ducer/activator that binds the promoter. So, both activators and repressors performs desig-nated work only when we have a inducer.An application of cell – cell communications is Quorum sensing. It allows us to deter-mine how many other cells there are in the surrounding area. Cells diffuse an inducer thatpermeates their own membrane. The inducer then permeates surrounding cell mem-branes. Decisions are then able to be made based on the concentration of the chemical. Cell-Cell communication schematics(1)Sender sends out inducers using metabolic pathways.(2)The small molecules diffuse outside the membrane and to the environment.(3)The signals then diffuses into neighboring cells.
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