CS374 Fall 2006 October 17, 2006 Transforming Cells into Automata - Scribed by Rashmi Raj Transforming Cells into Automata Based On The Following Papers: 1. Engineering Life: Building a FAB for Biology – David Baker, George Church, Jim Collins, Drew Endy, Joseph Jacobson, Jay Keasling, Paul Modrich, Christina Smolke and Ron Weiss 2. Genetic Circuit Building Blocks for Cellular Computation, Communications, and Signal Processing – Ron Weiss, Subhayu Basu, Sara Hooshangi, Abigail Kalmbach, David Karig, Rishabh Mehreja and Ilka Netravali Additional References: 1. Lecture slides by Ravi Tiruvury 2. http://cnx.org/content/m12383/latest/ 3. http://en.wikipedia.com Outline 1. Background 1.1 Revisiting Logic Gates 1.2 Defining Signal Processing 2. Gene Networks 2.1 Definition 2.2 Need for Gene Networks 3. Generic Circuit 3.1 Electrical Circuit vs. Genetic Circuit 3.2 Building Genetic Circuits 3.3 Genetic Circuit Building Block 4. Circuit Design 4.1 Rational Design 4.2 Direct Evolution 5. Cell-Cell Communication 6. Signal Processing 7. ConclusionsCS374 Fall 2006 October 17, 2006 Transforming Cells into Automata - Scribed by Rashmi Raj 1 Background Genetic engineering with recombinant DNA is a powerful and widespread technology that enables biologists to redesign life forms by modifying or extending their DNA. Advances in this domain allow us to gain insight into the operating principles that govern living organisms, and can also be applied to a variety of fields including human therapeutics, synthesis of pharmaceutical products, and molecular fabrication of biomaterials, crops and livestock engineering. Constructing DNA fragments that consist of almost any gene sequence is not a difficult task. However the behavior of the resulting genetic constructs is not easy to predict. To address this issue, it is important to develop an engineering methodology for creating synthetic gene networks that will allow us to engineer cells with the same ease and capability with which we currently program computers and robots. The first step in making programmed cell behavior a practical and useful engineering discipline is to assemble a component library of genetic circuit building blocks. These building blocks perform computation and communications using DNA-binding proteins, small inducer molecules that interact with these proteins. A component library of cellular gates can be defined that implement several digital logic functions. 1.1 Revisiting Logic Gates Basic Logic Gates: Type Distinctive shape Truth Table AND A B out 1 1 1 1 0 0 0 1 0 0 0 0 OR A B out 1 1 1 1 0 1 0 1 1 0 0 0 NOT A out 1 0 0 1CS374 Fall 2006 October 17, 2006 Transforming Cells into Automata - Scribed by Rashmi Raj Universal Logic Gates: Type Distinctive shape Truth Table NAND A B out 1 1 0 1 0 1 0 1 1 0 0 1 NOR A B out 1 1 0 1 0 0 0 1 0 0 0 1 1.2 Defining Signal Processing Signal processing is the processing, amplification and interpretation of signals (either analog or digital), and deals with the analysis and manipulation of signals. Signals of interest include sound, images, and biological signals such as ECG, radar signals, and many others. Processing of such signals includes storage and reconstruction, separation of information from noise (e.g., aircraft identification by radar), compression (e.g., image compression), and feature extraction (e.g., speech-to-text conversion). 2 Gene Networks 2.1 Definition A gene network (also called a Gene Regulatory Network (GRN) or genetic regulatory network,) is a collection of DNA segments in a cell which interact with each other and with other substances in the cell, thereby governing the rates at which genes are transcribed into mRNA. Genes can be viewed as nodes in such a network, with input being proteins such as transcription factors, and outputs being the level of gene expression. The node itself can also be viewed as a function which can be obtained by combining basic functions upon the inputs (in the Boolean network these are Boolean functions or gates computed using the basic AND OR and NOT gates in electronics). These functions have been interpreted as performing kind information processing within cell which determines cellular behavior. The basic drivers within cells are levels of some proteins, which determine both spatial (tissue related) and temporal (developmental stage) co-ordinates of the cell, as a kind of "cellular memory". The gene networks areCS374 Fall 2006 October 17, 2006 Transforming Cells into Automata - Scribed by Rashmi Raj only beginning to be understood, and it is a next step for biology to attempt to deduce the functions for each gene "node", to assist in modeling behavior of a cell. Gene networks act as analog biochemical computers to specify the identity and level of expression of groups of target genes. Central to this computation are DNA recognition sequences with which transcription factors associate. When active transcription factors associate with the promontory region of target genes, they can function to specifically repress (down-regulate) or induce (up-regulate) synthesis of the corresponding RNA. The immediate molecular output of a gene regulatory network is the constellation of RNAs and proteins encoded by network target genes. The resulting cellular outputs are changes in the structure, metabolic capacity, or behavior of the cell mediated by new expression of up-regulated proteins and elimination of down-regulated proteins. 2.2 Need for Gene Networks A central focus of genomic research concerns understanding the manner in which cells execute and control the enormous number of operations required for their function. Biological systems behave in an exceedingly parallel and extraordinarily integrated fashion. Feedback and damping are routine even for the most common activities. Thus, in this area of genomic biology, single gene perspectives are becoming increasingly limited for gaining insight into biological processes. Network models (Gene network) are becoming increasingly important for making progress in our understanding of the manner in which genes and molecules collectively form a biological system and harnessing this understanding in educated intervention for correcting human diseases. 3 Genetic Circuit 3.1 Definition Genetic circuit is an approach to model genetic networks using boolean constructs such as AND, OR, NOT, NAND.
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