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NPTEL – Biotechnology- Systems Biology Transcription Networks Dr. M. Vijayalakshmi School of Chemical and Biotechnology SASTRA University Joint Initiative of IITs and IISc – Funded by MHRD Page 1 of 9 NPTEL – Biotechnology- Systems Biology Table of Contents 1 INTRODUCTION ............................................................................................... 3 1.1 TRANSCRIPTION NETWORK-ELEMENTS ............................................................ 3 1.2 TIMESCALES OF TRANSCRIPTION NETWORKS ................................................... 6 1.3 MODULARITY OF TRANSCRIPTION NETWORKS ................................................... 6 1.2 SIGNS ON THE EDGES .................................................................................... 7 1.2.1 Activation or Positive Control ................................................................ 7 1.2.2 Repression or Negative Control ........................................................... 8 2 REFERENCES .................................................................................................. 9 2.1 TEXT BOOK ................................................................................................... 9 2.2 LITERATURE REFERENCES .............................................................................. 9 Joint Initiative of IITs and IISc – Funded by MHRD Page 2 of 9 NPTEL – Biotechnology- Systems Biology 1 Introduction The living cell is a complex machinery involving thousands of interacting proteins and other biological molecules. These cells utilise proteins based on the situations they encounter. During sugar sensing, the cells begin to secrete proteins that transport sugar into the cells. Cells respond to damage by producing damage repair proteins. Every cell thus senses its environment continuously, regulates protein production and maintains cellular homeostasis. Live cells as we know are kept dynamic through gene expression programs that involve the transcription of thousands of genes in a coordinated manner. As we all know, the expression of a gene is facilitated by transcription regulatory proteins which recognize specific promoter sequences. The association of regulatory proteins with genes across a genome and the continuous cascade of information processing which senses the rate of production of a particular protein inside a cell constitute a transcription regulatory network. These are in general called transcription networks. Metabolic networks describe the possible pathways that a cell may use to accomplish metabolic processes. In a similar way the map of the transcriptional regulatory network of an organism describes potential pathways the cells of the organisms utilise to regulate global gene expression programs. This network map establishes a high connectivity between gene expression programs and cellular functions through networks of transcriptional regulatory molecules which in turn regulate other molecular players in transcription. 1.1 Transcription Network-Elements We know that transcription networks depict the interaction between transcription factors and genes. The process of transcription ensures that RNA polymerase produces mRNA (messenger RNA) corresponding to the coding sequence of a gene. The mRNA is translated to form a protein which is also referred to as the gene product. Each gene is preceded by a small stretch of regulatory DNA called promoter. The promoter is a specific DNA sequence that can bind RNA polymerase, which is a complex of several proteins. The rate at which the gene is transcribed is determined by the quality of the binding site and the promoter Joint Initiative of IITs and IISc – Funded by MHRD Page 3 of 9 NPTEL – Biotechnology- Systems Biology which controls the number of mRNA produced per unit time. The RNA polymerase complex acts on a number of genes while the transcription factors regulate changes in expression profiles of specific genes. The transcription factors when bound change the probability per unit time of RNA polymerase binding to the promoter to produce the mRNA. Transcription factors can also function as activators which increase the transcription rate of a gene or as repressors which reduce the transcription rate. The transcription factor proteins themselves are encoded by genes which are regulated by other transcription factors. These transcription factors might have been regulated by other set of transcription factors in the genome. Such a complexity leads to a set of interactions which may be visualised to form a transcription network. Thus a transcription network depicts all interactions of the transcription regulatory proteins inside the cell. In such a network the genes are represented by nodes and the edges represents the transcription regulation of one gene by the protein product of the other. Therefore in a transcription network the directed edge XY means that the product of a gene X is a transcription factor protein which controls the rate of transcription of gene Y (by binding to the promoter of gene Y) , which is explained in the following Fig 1. Fig 1 A schematic of transcription and translation of a gene Y Joint Initiative of IITs and IISc – Funded by MHRD Page 4 of 9 NPTEL – Biotechnology- Systems Biology As shown in the Fig 2, the network has inputs called signals which represent information from the environment. A signal could be a protein modification, environmental signal, biochemical stimuli, small molecule or a molecular partner that influences one of the transcription factors in the network. The signals initiate a physical change in the transcription factor protein and switch it to an active molecular state. The signal SX therefore shifts the gene X to its active state X*, binds to the promoter of the gene Y, increasing the rate of transcription and hence increasing the production of protein Y. The gene network is thus a dynamic system. With the arrival of the input signal S X gene activation profiles change, activities of transcription factors change resulting in changes in protein production rate. Fig 2. A typical Transcription Network depicting the interaction between the Signals, Transcription Factors and Genes Joint Initiative of IITs and IISc – Funded by MHRD Page 5 of 9 NPTEL – Biotechnology- Systems Biology 1.2 Timescales of Transcription Networks The timescales at which reactions happen in transcription network are quite interesting to note. Table 1 explain timescales of reactions taking place in E. coli. We can observe that the input signals such as biochemical stimuli or temperature change the activity of transcription factors on sub second (milliseconds) timescale. The binding of the active transcription factor to its DNA site attains equilibrium in seconds. The transcription and translation of the target gene happens in minutes while the accumulation if protein products and change in the concentration of the stable protein takes hours. Table 1 Timescales of reactions in the Transcription Network of the Bacterium E. coli Binding of a small molecule (a signal) to a transcription factor, causing a change in transcription factor activity ~1 ms Binding of active transcription factor to its DNA site ~1 sec Transcription + Translation of the gene ~5 min Timescale for 50% change in concentration of the translated protein (stable proteins) ~1 h (one cell generation) 1.3 Modularity of Transcription Networks A remarkable property of transcription networks is the modularity of the components of the network. This allows taking off the DNA of a gene from one organism and expressing it on the other. The best example is the isolation of the green fluorescent protein (GFP) from the genome of a jelly fish and to introduce this gene into bacteria causing the bacteria to express green fluorescence. This modularity confers plasticity to transcription networks during evolution, facilitating introduction of newer genes and newer regulatory pathways. The Joint Initiative of IITs and IISc – Funded by MHRD Page 6 of 9 NPTEL – Biotechnology- Systems Biology edges in transcription networks appear to evolve on a faster timescale than the coding regions of the genes. For example, mice and humans are closely related and have similar genes. But their transcription regulation mechanisms and timescale of protein production are quite different. 1.2 Signs on the Edges Each edge in a transcription network corresponds to an interaction in which a transcription factor directly controls the transcription rate of a gene. Such interactions can be classified into two types. 1. Activation or positive control 2. Repression or negative control 1.2.1 Activation or Positive Control When a transcription factor binds to the promoter and increases the rate of transcription it is referred to as activation or positive control. Fig 3 clearly explains the concept further. X Y Fig 3. Binding of an activator protein (X*) iIncreases the rate of Transcription of gene Y Joint Initiative of IITs and IISc – Funded by MHRD Page 7 of 9 NPTEL – Biotechnology- Systems Biology 1.2.2 Repression or Negative Control When a transcription factor binds to the promoter and decreases the rate of transcription it is referred to as repression or negative control. Fig 4 further explains in detail. X Y Fig 4. Bound and unbound repressor protein (X*) regulate the rate of transcription of gene Y. Hence each edge in the network is represented by a plus sign for activation and a minus sign for repression. Generally transcription networks show more positive interactions than negative interactions. For example organisms such as E. coli and yeast show 60-80% activation interactions Joint Initiative of IITs and IISc – Funded by MHRD Page 8 of 9 NPTEL – Biotechnology- Systems Biology 2 References 2.1 Text Book 1. Uri Alon, An Introduction to Systems Biology: Design Principles of Biological Circuits, 2/e, CRC Press, (2006). 2. Madan Babu M, Bacterial Gene Regulation and Transcriptional Networks, 1/e, Caister Academic Press, (2013). 2.2 Literature References 1. Blais A et al., Constructing Transcptional regulatory networks, Genes & Dev. ,(2005), 19, 1499-1511. 2. Lee et al., Transcriptional regulatory networks in Saccharomyces cerevisiae, Science, (2002), 298, 799-804. 3. Potapov et al.,Topology of mammalian transcription networks, Genome. Inform., (2005), 16, 270-278. Joint Initiative of IITs and IISc – Funded by MHRD Page 9 of 9