ETHZ/Biology

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<a href="https://2007.igem.org/wiki/index.php?title=ETHZ/Biology#Introduction">Introduction</a>
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<a href="https://2007.igem.org/wiki/index.php?title=ETHZ/Biology#The_Complete_System">The Complete System</a>
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<center><font size = '+1'><b> .:: EducatETH <i>E. coli</i> - Biology Perspective ::. </b></font></center><br>
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= Introduction =
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=====.:: Introduction ::.=====
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On this page, you can find an analysis of the function of our system, its biological design, and a list of the parts that make up the system. Under [https://2007.igem.org/ETHZ/Biology/Lab Lab Notes], you can find the ingredients and equipment we used, the electronic version of our lab notebook and a presentation of all the difficulties that we encountered.
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<p>Our aim is to engineer a biological model system which exhibits [http://en.wikipedia.org/wiki/Learning learning ability] and can also work according to [http://en.wikipedia.org/wiki/Divergent_evolution the mechanism of divergent evolution], i.e. a system which can alter its behavior according to external stimuli. We are interested in such a system, since learning and adaptation are playing major roles in living organisms and machine learning has numerous applications in engineering - it is therefore a fantastic interface between engineering and biology. Possible applications are as exciting as biological memories or self-adaptative systems.</p><br>
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educatETH <i>E.coli</i> is a system which can distinguish between [http://openwetware.org/wiki/ATc anhydrotetracycline (aTc)] and [http://openwetware.org/wiki/IPTG Isopropyl-beta-D-thiogalactopyranoside (IPTG)] based on a previous learning phase conducted with the same chemicals and the help of [http://partsregistry.org/Acyl-HSLs acylhomoserine lactone (AHL)]. It is composed of three subsystems: the subsystem of constitutively produced proteins, the learning subsystem and the reporting subsystem. The constitutively produced proteins (LacI, TetR and LuxR) control the learning subsystem. At the core of the latter there exists an extended version of the original toggle switch found in [1]. That is, a multi-inducible toggle switch. The main difference is reflected in the use of double promoters, so that the toggle switch only changes its state when both, one of the two chemicals (aTc/IPTG), and AHL are present. As AHL is only present during the learning phase, the toggle maintains its state during testing/recognition, and thus can “memorize”. AHL can therefore be seen as a training- or learning substance. In the reporting subsystem, four reporters ([http://partsregistry.org/Featured_Parts:Fluorescent_proteins fluorescent proteins]) allow supervision of (1.) the chemical the system was trained with and (2.) if the system recognizes the chemical it is being exposed to in the recognition phase as one it has been previously trained with or not.
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=====.:: A Biological Multiple State Automaton ::.=====
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== The Complete System ==
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<p>[[Image:LearningSystemOverview.jpg|thumb|right|200px| Abstraction of our learning system (Fig. 1)]]
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A straightforward approach on how to describe learning behavior and adaptive evolution, can be see in Figure 1. We can separate the process in two phases: a <i>training</i> or <i>learning phase</i> (shown in blue), and an <i>application</i> or <i>"real world" phase</i> (shown in pink), and describe our system as a multiple state automaton. The examined system can alter its state according to a certain input/stimuli that it was exposed to in the first phase. In this binary example, the system changes its state from <i>a</i> to <i>b</i> when it is exposed to a first training-phase-input (<i>IT1</i>). Similarly, the system changes its state from <i>a</i> to <i>c</i> when the other training-phase-input (<i>IT2</i>) is applied.
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<p>[[Image:Biol_system_stand24.10.png|thumb|left|350px|'''Fig. 1:''' Gene interaction network of educatETH ''E.coli'' ]] The biological design of educatETH <i>E.coli</i> is presented in Fig. 1 and below, we clarify the function of all depicted components. (Are you interested in how the complex system of Fig. 1 was modeled? Then visit the [[ETHZ/Model|  System Modeling]]!)</p>
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The principle described above is also valid in the <i>application phase</i>. In the application phase, we have two possibilities for initial system state. Thus, the automaton expands with four more states. Depending on which state the system is at the start of the <i>application phase</i>, and which chemical it is exposed to, it reaches a different final state. State <i>d</i> is reached if the first out of two possible application-phase-inputs (<i>IA1</i>) is applied while the system is at state <i>b</i>.  In the end, we can differentiate between the possibilities of the system being trained with one chemical, and being exposed to a different chemical in the application phase. Since we have two different <i>training</i> chemicals, and two different <i>application</i> chemicals, we reach the final number of four states.
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==== Constitutive Subsystem ====
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In the following, we elaborate on the two phases of our system:
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<p>The constitutively produced proteins of the system are LacI, TetR and LuxR. The LuxR part has a special function: when AHL is present, it forms a LuxR-AHL complex which acts on the learning subsystem (more on this later). For now, we will consider that AHL is absent and therefore LuxR cannot activate transcription. The TetR and LacI parts behave similarly: more specifically, the TetR protein in the absence of aTc inhibits the production of p22cII and LacI in the absence of IPTG inhibits the production of cI. When aTc is present, however, the p22cII production is no longer inhibited (and thus p22cII is produced). Correspondingly, cI is produced when IPTG is present.</p>
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<ul>
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<li>How can we describe learning ability with this approach?<br>Define the training-phase-inputs themselves as the information entities to be learned. This implies that after the training phase, the information is permanently stored in the system - ''a memory has been created''. According to its memory, the system will behave differently when it is exposed to a certain stimuli in a later stage.
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==== Learning Subsystem ====
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<p>The learning subsystem is a toggle switch with two operator sites. The upper part of the toggle (cI production) has operator sites for the LuxR-AHL complex and p22cII (whose production has in turn been induced by aTc). The LuxR-AHL complex induces cI production, whereas p22cII inhibits it. The lower part of the toggle (p22cII production) has operator sites for the LuxR-AHL complex and cI (which has been induced by IPTG). In analogy to the upper part, the LuxR-AHL complex induces production of p22cII and cI inhibits it. Therefore, the switch always requires the presence of the LuxR-AHL complex in order for it to operate. Its state depends on the presence of p22cII and cI in the system, which in turn was caused through the exposure of the system to aTc and IPTG.</p>
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==== Reporting Subsystem ====
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<p>There are four reporters in the system. CFP (more precisely: enhanced CFP, that is ECFP) and YFP (more precisely: enhanced YFP, that is EYFP) are active during the learning phase of the system and show which chemical the system is exposed to during learning, whereas all four reporters (the latter and GFP and RFP) are active during the recognition phase and show if the system is exposed to the same chemical as in learning or not.
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More specifically, the YFP production is regulated with help of two operator sites controlled by cI and aTc (TetR inhibitor). cI inhibits the YFP production and aTc induces it. Therefore, YFP is synthesized when the system is exposed to only aTc and cI is not produced within the system (i.e. the system has not been previously exposed to IPTG). The production of the other fluorescent proteins is regulated in a similar manner. Overall, the production of the fluorescent proteins is regulated as follows:
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*YFP gets produced when the system is exposed to only aTc and no cI is produced (i.e. the system has ''not'' been previously exposed to IPTG).
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*CFP gets produced when the system is exposed to only IPTG and no p22cII is produced (i.e. the system has ''not'' been previously exposed to aTc).
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*GFP gets produced when the system is exposed to only IPTG and no cI is produced (i.e. the system has ''not'' been previously exposed to IPTG).
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*RFP gets produced when the system is exposed to only aTc and no p22cII is produced (i.e. the system has ''not'' been previously exposed to aTc).</p>
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<li>If one have a look at ''Figure 1'' once more, one can easily spot similarity to family trees or [http://en.wikipedia.org/wiki/Phylogenetic_tree phylogenetic trees]. This raises the concept of divergent evolution (adaptation). There are several differences to the learning model: First of all, the states don't describe a single living entity with changing characteristics but different populations or species. Secondly, the training-phase-inputs and application-phase-inputs are not related to information inputs but rather to events acting on those populations/species. Thirdly, there is no specific training- and application phase but just two phases with different events/stimuli acting on the populations/species.<br>The following example might show this concept more clearly: Let's say the population of precursor (= ancestor) species ''a'' is splitted into two subpopulations (''a1'' and ''a2'') due to emigration of subpopulation ''a1'' to another geographic region. Application-phase-input 1 (''AI1'') would then equal "emigration" (''a'' -> ''a2'') and application-phase-input 2 (''AI2'') would be "no emigration" (''a'' -> ''a1''). The isolated populations then undergo changes as they (1.) become subjected to dissimilar selective pressures or (2.) they independently undergo genetic drift. When the populations come back into contact, they have evolved such that they are reproductively isolated and are no longer capable of exchanging genes [1]. Therefore, subpopulation ''a1'' has evolved into species ''b'', whereas subpopulation ''a2'' has evolved into species ''c''.<br>This example explains the principle of [http://en.wikipedia.org/wiki/Allopatric_speciation allopatric speciation]. However, our model is not limited to this: Peripatric speciation, parapatric speciation, sympatric speciation or artificial speciation can also be expressed through this model system. Another highly exciting aspect of our model system is, that it can describe '''Evolution without changing the DNA content over time!''' How this can be achieved is explained in more detail in the following sections.
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This behaviour is visualized in Fig. 2.
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<li>(The automaton of Fig. 1 presents similarities to family trees, or [http://en.wikipedia.org/wiki/Phylogenetic_tree phylogenetic trees]. According to different external stimuli, the initial population divides, and evolves into different species. The proposed automaton model can be used to explain the concepts of peripatric speciation, parapatric speciation, sympatric speciation or artificial speciation e.t.c. However, the most imporant fact, and what has stimulated our research in the area, is, to <i>create a biological system that can evolve without changing its DNA content over time</i>).
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[[Image:ETHzFlowdiagram2.png|center|thumb|350px|<b>Fig. 2</b>: Flow diagram. This figure shows the protocol with which the final system should be tested, as well as the test results in the form of the reported colors. There are three phases the system has to go through: (1) a training or learning phase in which the system learns an input and stores it in its memory, (2) a memory phase in which the system has to keep the content of its memory and, (3) a recognition phase where the output of the system depends on the content of its memory as well as on the current input. |500px]]
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</ul></p><br>
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=====.:: Detailed System ::.=====
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== System Phases ==
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<p>[[Image:new_learning_system3.png|thumb|left|300px|EducatETH System (Fig. 2)]]  In our project we are constructing an E. coli strain which with the help of an external chemical signal (AHL) is able to remember which of the two chemical substances (aTc and IPTG) it has previously been exposed to. The system architecture is based on a toggle switch consisting of different repressor and activator proteins synthesized from promoters which subject to two different regulations. The full system can be seen in Fig. 2.
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<p>The system operation is divided into three main phases: a learning phase, a memory phase and a recognition phase. During the learning phase, the system is first exposed to one of the two chemicals it is designed to detect (aTc or IPTG). During the memory phase, the specific chemical (aTc or  IPTG) is removed and AHL is added to activate the systems internal toggle switch. This maintains the toggle switch to its acquired steady state, which is reported with YFP (if aTc was detected) or CFP (if IPTG was detected). During the recognition phase, the system is exposed to any of the two chemicals (aTc or IPTG), with AHL present. Lets compare the systems toggle switch state with the effect of the newly introduced chemical: the system shows a different response if it has previously been exposed to this certain chemical and reports with the same XFP as in the learning phase (YFP for aTc, CFP for IPTG) or if it recognizes a different chemical and reports with a different XFP (GFP for trained with aTc and recognizing IPTG, RFP for trained with IPTG and recognizing aTc). The following table represents all possible paths that may be taken by the system during all phases of operation according to external stimuli: </p>
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In the first operation phase (learning), the system is exposed to one of the two chemicals (aTC and IPTG) and AHL is added, causing a steady system behavior. In the second phase (remembering), the chemicals are removed, but AHL allows the system to still maintain its state. [[Image:All_parts.png|EducatETH E. Coli Parts (Fig. 3)|thumb|300px]]Finally, in the final phase (recognition), the system is exposed to any of the two chemicals again. Its response, reported with four fluorescent proteins, differs according not only to which chemical the system is exposed to now, but also to if this chemical is the same that the system has already experienced (learning effect). Therefore, four possible system responses are possible:
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{| class="wikitable" border="1" cellspacing="0" cellpadding="2" style="text-align:center; margin: 1em 1em 1em 0; background: #f9f9f9; border: 1px #aaa solid; border-collapse: collapse;"       
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#now exposed and initially trained with aTc
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|+ '''System phases'''         
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#now exposed but initially not trained with aTc
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!
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#now exposed and initially trained with IPTG
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!width="44" style="background:#446084; color:white"| aTc
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#now exposed and initially not trained with IPTG
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!width="44" style="background:#446084; color:white"| IPTG
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!width="44" style="background:#446084; color:white"| AHL
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!width="44" style="background:#446084; color:white"| p22cII
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!width="44" style="background:#446084; color:white"| cI
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! style="background:#446084; color:white"| Reporting 
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|- 
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|colspan="7"  style="background:#96c9cf;" align="center"|'''Start''' 
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|-   
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| no input
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| no
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| no
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| no
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| no
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| no
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| non
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|-     
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| colspan="7" style="background:#96c9cf;" align="center"| '''Learning'''
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|-
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| Trained with aTc
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| yes
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| no
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| no
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| yes
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| no
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| YFP
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|-   
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| Trained with IPTG
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| no
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| yes
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| no
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| no
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| yes
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| CFP
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|- 
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|  colspan="7" style="background:#96c9cf;" align="center"| '''Memorizing'''
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|-   
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| Trained with aTc
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| yes
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| no
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| yes
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| yes
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| no
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| YFP (fading)<br>finally no color
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|-   
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| Trained with IPTG
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| no
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| yes
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| yes
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| no
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| yes
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| CFP (fading)<br>finally no color
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|- 
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| colspan="7" style="background:#96c9cf;" align="center"|  '''Recognition'''
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|-
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| Trained with aTc<br>Tested with aTc
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| yes
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| no
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| yes
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| yes
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| no
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| YFP
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|-       
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| Trained with aTc<br>Tested with IPTG
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| no
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| yes
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| yes
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| yes
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| no
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| GFP
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|-   
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| Trained with IPTG<br>Tested with IPTG
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| no
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| yes
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| yes
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| no
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| yes
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| CFP
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|- 
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| Trained with IPTG<br>Tested with aTc
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| yes
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| no
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| yes
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| no
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| yes
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| RFP
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|-       
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|}
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The system consists of 11 parts that can be synthesized independently (Fig. 3): [[Image:Assembly _process.png|thumb|300px|DNA assembly process ([1]) (Fig. 4)]]
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== System Parts ==
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{| class="wikitable" border = "0" style="text-align:left"
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|+ '''System parts'''
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|-
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|-
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! 1
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| [http://partsregistry.org/Part:BBa_I739001 TetR production] (constitutive part of system)
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|-
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! 2
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| [http://partsregistry.org/Part:BBa_I739002 LacI production] (constitutive part of system)
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|-
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! 3
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| [http://partsregistry.org/Part:BBa_I739003 LuxR production] (constitutive part of system)
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|-
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! 4
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| 1st half of p22/YFP production (outer part of system, reporting)
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|-
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! 5
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| 2nd half of p22/YFP production (outer part of system, reporting)
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|-
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!6
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| CI production (inner part of system)
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|-
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! 7
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| p22 production (inner part of system)
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|-
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! 8
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| 1st half of CI/CFP production (outer part of system, reporting)
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|-
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! 9
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| 2nd half of CI/CFP production (outer part of system, reporting)
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|-
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! 10
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| RFP production (reporting)
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! 11
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| GFP production (reporting)
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|}
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Three plasmids are used to house the above DNA parts, as can be seen from the following table:
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<p>educatETH <i>E.coli</i> was implemented with 11 basic parts designed by the ETH Zurich team. [https://2007.igem.org/wiki/index.php?title=ETHZ/Biology/parts The list of all the parts, plasmids and strains used] is available. Because the part information is retrieved from the Registry, the page needs some time to load. <br>(Are you interested in this information because you want to implement educatETH <i>E.coli</i> in your lab? Then visit our [https://2007.igem.org/ETHZ/Biology/Lab In the Lab] page!)</p>
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{| class="wikitable" border = "1" style="text-align:left"
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|+'''Plasmids and contents'''
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|-
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! plasmid !! resistance !! copy type!! contents !! comments
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|-
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| [[ETHZ/pbr322| pbr322]] || ampicillin || medium || 1,2,3 || constitutive part
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|-
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| [[ETHZ/pck01| pck01]] || chloramphenicol|| low || 4,5,8,9 || outer part
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|-
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| [[ETHZ/pacyc177| pacyc177]] || kanamycin|| low || 6,7,10,11 || inner part, reporting
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The standard BioBrick assembly will be used to put the parts in the plasmids. Detailed information on how the BioBrick part fabrication works can be found  [http://openwetware.org/wiki/Synthetic_Biology:BioBricks/Part_fabrication here]. For a shorter explanation of how to assemble two parts together check [http://partsregistry.org/Assembly:Standard_assembly here] (Fig. 4). Note that the composite part is constructed from the end to the beginning, i.e. each new part is inserted ''before'' the existing one. In the following, the plasmid containing the new part to be inserted will be referred to as the ''donor'' and the plasmid accepting the new part will be referred to as the ''acceptor''. Composite pars made of parts '''a''' and '''b''' are denoted '''a.b'''.</p><br>
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== Current Cloning Status (26.10.07) ==
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=====.:: Experiments ::.=====
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We have sent 9 new parts and 3 new plasmids to the registry. As soon as the missing parts are available in their destined plasmids, we will forward them to the parts registry as well. Additionally, we will be able to test parts of our system next week, using the FACS machine provided by [http://www.facs.ethz.ch Alfredo Franco-Obregón's lab].
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<p></p><br>
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=====.:: References ::.=====
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== References ==
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<p>[1] <i>Standard Assembly Process</i>, http://partsregistry.org/Assembly:Standard_assembly</p><br>
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=====.:: To Do ::.=====
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[http://www.nature.com/nature/journal/v403/n6767/abs/403339a0.html &#91;1&#93; Gardner TS, Cantor CR and Collins JJ] <i>"Construction of a genetic toggle switch in Escherichia coli"</i>, Nature 403:339–342, 2000<br />
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<p><ul>
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<li>''Katerina'': 1. Number system parts on both figures for easier reference.
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<li>''Katerina'': 2. Add more info on all system parts and link to the ones existing in the registry. Write info on the ones that didn't exist in the registry (with detailed info such as addition of bp's as Christian and Sven had done).
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<li>''Katerina'': 3. Add cloning plan. (Christos: Maybe the details will be at the team note's?)<br>Martin: I wouldn't put it here, I mean the cloning plan is really nothing special, it's like an auxiliary calculation for a polynom division... Not exciting and everyone could do it... Please correct me if I'm wrong.
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<li>''Christos'': 1. The picture with the abstraction - maybe we can put better names on the arrows.
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<li>''Christos'': 2. We can make figure 1 more specific. Instead of having IT and IA, we can have Chemical 1, Chemical 2, and then again. I think it will be more obvious like that.
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<li>''Christos'': 3. Nice descriptions Stefan. However, I made the text less, and kept the original idea, since I felt like it was moving away from the purpose, which is a simple introduction and clarification of concepts. I also removed the pictures. I have backups of everything, so, we can put it back if the others disagree.
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<li>''Christos'': 4. Figure 3 needs to be replaced with the new parts.
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<li>''Christos'': 5. Are we sure the plasmids that we say are the correct ones? Sven said they were changed, but I didn't really get it.<br>Martin: Yes, they are the right ones... If not, the shit is hitting the fan - albeit in my opinion it has already hit the fan, but not due to the plasmids more due to Genefart...I can really assure you, that they are right. ;-)
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</ul></p><br>
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Latest revision as of 23:14, 26 October 2007

ETHZ banner.png

 


Introduction

On this page, you can find an analysis of the function of our system, its biological design, and a list of the parts that make up the system. Under Lab Notes, you can find the ingredients and equipment we used, the electronic version of our lab notebook and a presentation of all the difficulties that we encountered.

educatETH E.coli is a system which can distinguish between [http://openwetware.org/wiki/ATc anhydrotetracycline (aTc)] and [http://openwetware.org/wiki/IPTG Isopropyl-beta-D-thiogalactopyranoside (IPTG)] based on a previous learning phase conducted with the same chemicals and the help of [http://partsregistry.org/Acyl-HSLs acylhomoserine lactone (AHL)]. It is composed of three subsystems: the subsystem of constitutively produced proteins, the learning subsystem and the reporting subsystem. The constitutively produced proteins (LacI, TetR and LuxR) control the learning subsystem. At the core of the latter there exists an extended version of the original toggle switch found in [1]. That is, a multi-inducible toggle switch. The main difference is reflected in the use of double promoters, so that the toggle switch only changes its state when both, one of the two chemicals (aTc/IPTG), and AHL are present. As AHL is only present during the learning phase, the toggle maintains its state during testing/recognition, and thus can “memorize”. AHL can therefore be seen as a training- or learning substance. In the reporting subsystem, four reporters ([http://partsregistry.org/Featured_Parts:Fluorescent_proteins fluorescent proteins]) allow supervision of (1.) the chemical the system was trained with and (2.) if the system recognizes the chemical it is being exposed to in the recognition phase as one it has been previously trained with or not.

The Complete System

Fig. 1: Gene interaction network of educatETH E.coli
The biological design of educatETH E.coli is presented in Fig. 1 and below, we clarify the function of all depicted components. (Are you interested in how the complex system of Fig. 1 was modeled? Then visit the System Modeling!)

Constitutive Subsystem

The constitutively produced proteins of the system are LacI, TetR and LuxR. The LuxR part has a special function: when AHL is present, it forms a LuxR-AHL complex which acts on the learning subsystem (more on this later). For now, we will consider that AHL is absent and therefore LuxR cannot activate transcription. The TetR and LacI parts behave similarly: more specifically, the TetR protein in the absence of aTc inhibits the production of p22cII and LacI in the absence of IPTG inhibits the production of cI. When aTc is present, however, the p22cII production is no longer inhibited (and thus p22cII is produced). Correspondingly, cI is produced when IPTG is present.

Learning Subsystem

The learning subsystem is a toggle switch with two operator sites. The upper part of the toggle (cI production) has operator sites for the LuxR-AHL complex and p22cII (whose production has in turn been induced by aTc). The LuxR-AHL complex induces cI production, whereas p22cII inhibits it. The lower part of the toggle (p22cII production) has operator sites for the LuxR-AHL complex and cI (which has been induced by IPTG). In analogy to the upper part, the LuxR-AHL complex induces production of p22cII and cI inhibits it. Therefore, the switch always requires the presence of the LuxR-AHL complex in order for it to operate. Its state depends on the presence of p22cII and cI in the system, which in turn was caused through the exposure of the system to aTc and IPTG.

Reporting Subsystem

There are four reporters in the system. CFP (more precisely: enhanced CFP, that is ECFP) and YFP (more precisely: enhanced YFP, that is EYFP) are active during the learning phase of the system and show which chemical the system is exposed to during learning, whereas all four reporters (the latter and GFP and RFP) are active during the recognition phase and show if the system is exposed to the same chemical as in learning or not. More specifically, the YFP production is regulated with help of two operator sites controlled by cI and aTc (TetR inhibitor). cI inhibits the YFP production and aTc induces it. Therefore, YFP is synthesized when the system is exposed to only aTc and cI is not produced within the system (i.e. the system has not been previously exposed to IPTG). The production of the other fluorescent proteins is regulated in a similar manner. Overall, the production of the fluorescent proteins is regulated as follows:

  • YFP gets produced when the system is exposed to only aTc and no cI is produced (i.e. the system has not been previously exposed to IPTG).
  • CFP gets produced when the system is exposed to only IPTG and no p22cII is produced (i.e. the system has not been previously exposed to aTc).
  • GFP gets produced when the system is exposed to only IPTG and no cI is produced (i.e. the system has not been previously exposed to IPTG).
  • RFP gets produced when the system is exposed to only aTc and no p22cII is produced (i.e. the system has not been previously exposed to aTc).

This behaviour is visualized in Fig. 2.
Fig. 2: Flow diagram. This figure shows the protocol with which the final system should be tested, as well as the test results in the form of the reported colors. There are three phases the system has to go through: (1) a training or learning phase in which the system learns an input and stores it in its memory, (2) a memory phase in which the system has to keep the content of its memory and, (3) a recognition phase where the output of the system depends on the content of its memory as well as on the current input.

System Phases

The system operation is divided into three main phases: a learning phase, a memory phase and a recognition phase. During the learning phase, the system is first exposed to one of the two chemicals it is designed to detect (aTc or IPTG). During the memory phase, the specific chemical (aTc or IPTG) is removed and AHL is added to activate the systems internal toggle switch. This maintains the toggle switch to its acquired steady state, which is reported with YFP (if aTc was detected) or CFP (if IPTG was detected). During the recognition phase, the system is exposed to any of the two chemicals (aTc or IPTG), with AHL present. Lets compare the systems toggle switch state with the effect of the newly introduced chemical: the system shows a different response if it has previously been exposed to this certain chemical and reports with the same XFP as in the learning phase (YFP for aTc, CFP for IPTG) or if it recognizes a different chemical and reports with a different XFP (GFP for trained with aTc and recognizing IPTG, RFP for trained with IPTG and recognizing aTc). The following table represents all possible paths that may be taken by the system during all phases of operation according to external stimuli:

System phases
aTc IPTG AHL p22cII cI Reporting
Start
no input no no no no no non
Learning
Trained with aTc yes no no yes no YFP
Trained with IPTG no yes no no yes CFP
Memorizing
Trained with aTc yes no yes yes no YFP (fading)
finally no color
Trained with IPTG no yes yes no yes CFP (fading)
finally no color
Recognition
Trained with aTc
Tested with aTc
yes no yes yes no YFP
Trained with aTc
Tested with IPTG
no yes yes yes no GFP
Trained with IPTG
Tested with IPTG
no yes yes no yes CFP
Trained with IPTG
Tested with aTc
yes no yes no yes RFP

System Parts

educatETH E.coli was implemented with 11 basic parts designed by the ETH Zurich team. The list of all the parts, plasmids and strains used is available. Because the part information is retrieved from the Registry, the page needs some time to load.
(Are you interested in this information because you want to implement educatETH E.coli in your lab? Then visit our In the Lab page!)

Current Cloning Status (26.10.07)

We have sent 9 new parts and 3 new plasmids to the registry. As soon as the missing parts are available in their destined plasmids, we will forward them to the parts registry as well. Additionally, we will be able to test parts of our system next week, using the FACS machine provided by [http://www.facs.ethz.ch Alfredo Franco-Obregón's lab].

References

[http://www.nature.com/nature/journal/v403/n6767/abs/403339a0.html [1] Gardner TS, Cantor CR and Collins JJ] "Construction of a genetic toggle switch in Escherichia coli", Nature 403:339–342, 2000