Team:UT-Tokyo/Counter/Project/Project

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<p>Anti-sigma factors are proteins which is related to transcriptional control mechanism by sigma factors. An anti-sigma factor inhibits the binding between RNA polymerase and sigma factor. Consequently, anti-sigma factors repress the transcription from the promoters which sigma factors initiate. In the same way as sigma factor, anti-sigma factors have great variety and some anti-sigma factors prevent only a specific sigma factors from transcriptional control. Therefore a transcription control system (i.e. not only activating but also repressing) can be constructed by using specific sigma factors and anti-sigma factors which have one-to-one correspondence. [4]  
<p>Anti-sigma factors are proteins which is related to transcriptional control mechanism by sigma factors. An anti-sigma factor inhibits the binding between RNA polymerase and sigma factor. Consequently, anti-sigma factors repress the transcription from the promoters which sigma factors initiate. In the same way as sigma factor, anti-sigma factors have great variety and some anti-sigma factors prevent only a specific sigma factors from transcriptional control. Therefore a transcription control system (i.e. not only activating but also repressing) can be constructed by using specific sigma factors and anti-sigma factors which have one-to-one correspondence. [4]  
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                                 <legend><b>Fig. 6 anti-sigmas</b> An anti-sigmas physically blocks the binding between corresponding sigma factors and RNA polymerase. Consequently, transcription from corresponding promoter is inhibited.</legend>
                                 <legend><b>Fig. 6 anti-sigmas</b> An anti-sigmas physically blocks the binding between corresponding sigma factors and RNA polymerase. Consequently, transcription from corresponding promoter is inhibited.</legend>
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<h3>sigma-memory construction</h3>
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<h3>Sigma-Memory Construction</h3>
<img src = "https://static.igem.org/mediawiki/2014/f/f8/Nakashima_iroiro.png" class = "figure" />
<img src = "https://static.igem.org/mediawiki/2014/f/f8/Nakashima_iroiro.png" class = "figure" />
                                 <legend><b>Fig.7 construction of sigma memory</b></legend>
                                 <legend><b>Fig.7 construction of sigma memory</b></legend>

Revision as of 02:03, 18 October 2014

<img src = "Sub_introduction.png" class = "contTitle"/>

Contents

Project Overview

With a synthetic biological approach, Ari, et al. constructed a cellular counter termed the riboregulated transcriptional cascade (RTC) counter[1]. It counts the number of inputs by the state transition induced by an arabinose induction. The state tansition system is regulated by a riboregulator. The BioBrick part of this cellular counter has already been registered, which was constructed by Tokyo-Nokogen 2009 and was named BBa_K225002, BBa_K225003 [2].

In order to expand the function of this counter, we added a "reset system". The reset system enables the transition from any state to the initial state by a particular input, which gives applicability in various situations. One of the applications is the closed transition loop designed so that the reset system is exerted in the final state, which enables to regulate cellular behaviors periodically. For example, by constructing the state transition loop that have 7 states and assigning 7 states to the days of the week, it is possible to make cells produce drugs once a week by sensing hormone having a cycle of 24 hour-period and memorizing the number of times of the elevation of the hormone.

<img src = "Irie_induce.png" class = "figure" /> <legend>Fig. 1 The concept of RTC counter After first, second and third induction of arabinose, the state of cells moves from 0 to 1, 1 to 2 and 2 to 3, respectively.</legend>

                                       <img src = "Irie003.png" class = "figure" style="width:400px;margin-left:200px;"/>
                                       <legend>Fig. 2 7-state loop by reset system</legend>
                                

Riboregulated Transcriptional Cascade(RTC) counter

A riboregulator is a post-transcriptional regulation system composed of two kinds of RNAs, cis-repressed mRNA (crRNA) and trans-activating RNA (taRNA). crRNA forms a stem-loop and its ribosomal binding site (RBS) is covered (Fig. 1). Consequently the gene coded in cis-repressed mRNA isn't translated. However if trans-activating RNA exist, crRNA and taRNA are hybridized and RBS gets exposed and translation starts.[3]

<img src = "CrRNA-taRNA_introduction.png" class = "figure" /> <legend>Fig. 3 The system of a riboregulator When only cis-repressed RNA (crRNA) exists, the RBS is covered. In the presence of taRNA, stem-loop gets opened and translation is initiated. </legend>

Namely, the gene encoded in crRNA is expressed only when both crRNA and taRNA is transcribed. Therefore this system can be considered as the AND function. For example, consider the gene circuit, Plac-taRNA-d.term-Pbad-cr-RBS-GFP-d.term. (cr is the sequence in crRNA which binds to RBS) If and only if both IPTG and arabinose exists, GFP is expressed. Therefore, the riboregulator regulates the activities of both of the two promoters and produces AND functions.

The construct of the counter in Ari, et al. is as follows.

<img src = "Construction%28Ari%29.png" class = "figure" /> <legend>Fig. 4 The construction of RTC counter “crRBS” means cis-repressed RBS.</legend>

In the initial state, T7RNAP is transcribed but not translated because of translational inhibition by crRBS. taRNA induced by the first arabinose induction promotes translation of T7RNAP and it initiates transcription of T3RNAP. Translation of T3RNAP is induced by the second induction and it promotes transcription of GFP. GFP is translated by the third induction. This system can be expanded by adding pairs of transcriptional activators and corresponding promoters.

<img src = "Sub_memory.png" class = "contTitle" />

Sigma factors and anti-sigma factors are used for constructing the sigma-memory. Sigma memory is a genetic device which have two states and can memorize the state. Sigma-memory is applied for constructing resettable counter.

Sigma Factor

The sigma factors is promoter recognition subunits of RNA polymerase. A sigma factor is associated with a part of promoters. A sigma factor recruits RNA polymerase to its corresponding promoter and initiates transcription. Sigma factors have great variety. Some of sigma factor-promoter pairs have one-to-one correspondence. Thus, if only sigma factors which have one-to-one correspondence are used, a transcription activating system in which a sigma factor activate the transcription only from corresponding promoter can be made.

<img src = "Nakashima_image%281-0%29.png" class = "figure-height" style="margin-left:200px;"/> <legend>Fig. 5 sigma factor A sigma factor recruits RNA polymerase to its corresponding promoter. Then transcription starts.</legend>

Anti-sigma factors are proteins which is related to transcriptional control mechanism by sigma factors. An anti-sigma factor inhibits the binding between RNA polymerase and sigma factor. Consequently, anti-sigma factors repress the transcription from the promoters which sigma factors initiate. In the same way as sigma factor, anti-sigma factors have great variety and some anti-sigma factors prevent only a specific sigma factors from transcriptional control. Therefore a transcription control system (i.e. not only activating but also repressing) can be constructed by using specific sigma factors and anti-sigma factors which have one-to-one correspondence. [4]

<img src = "Nakashima_image%281-1%29.png" class = "figure-height" style="margin-left:200px;"/>

                               <legend>Fig. 6 anti-sigmas An anti-sigmas physically blocks the binding between corresponding sigma factors and RNA polymerase. Consequently, transcription from corresponding promoter is inhibited.</legend>

Sigma-Memory Construction

<img src = "Nakashima_iroiro.png" class = "figure" />

                               <legend>Fig.7 construction of sigma memory</legend>

This is the construction of our sigma-memory. This genetic circuit is composed of three parts. The gene of a sigma factor is placed at the downstream of the promoter that is induced by a substance A and at the downstream of Psigma, which is the promoter induced by the sigma factor. The latter one forms a positive feedback circuit. The gene of the corresponding anti-sigma factor is placed at the downstream of the promoter which is induced by a substance B.

At first, sigma factors and anti-sigma factors do not exist. Input A induces the sigma factor expression and the concentration of the sigma factor rises. Though sigma factors are subjects to degradation [3], the state where sigma factors exist remains after the induction of A finished since the positive feedback circuit produces more sigma factor when sigma factor exist. After the induction of input B, anti-sigma factor is expressed and transcriptions from the corresponding promoters, including positive feedback circuit, is inhibited. Both sigma factors and anti-sigma factors are subjects to degradation[3], so all of them are decomposed after some time and sigma-memory returns to its original state (i.e. sigma factors and anti-sigma factors do not exist.) This states remains since no substance that affect transcription exist.

<img src = "Nakashima_induced.png" class = "figure" />

                               <legend>Fig. 8 sigma-memory Sigma-memory is a genetic device which have two states and can memorize the state. Induction of A or B changes the state.</legend>

The existence/absence of sigma factor can be regard as a binary 1/0 of memory, and this value of memory can be switched upon input A or input B. Using the promoter which is corresponding to the sigma factor, the information whether the value of memory is 1 or 0 can be observed as reporter expression. For example, consider the circuits below. The reporter is expressed when the value of the sigma-memory is 1 (i.e. sigma factor exists).

<img src = "Nakashima_sigma.png" class = "figure" />

                               <legend>Fig. 9 construction of sigma memory with reporter The value of sigma-memory can be observed as reporter expression. </b></legend>

<img src = "Nakashima_reset_func01.png" class = "figure" style="width:400px;float:left;"/> <img src = "Nakashima_reset_func02.png" class = "figure" style="width:400px;float:left;" /> <legend style="clear:both">Fig. 10 mechanism of sigma memory</legend>

In addition, sigma factors, promoters, and anti-sigma factors which have one-to-one correspondence enable us to make multi-sigma-memory genetic circuits. To make the explanation easier, consider the case in which E. coli has two sigma memories, sigmaA-memory and sigmaB-memory. The value of sigmaA-memory changes from 0 to 1 after the induction of A1 exists and change from 1 to 0 after the induction of B1 exists. Also the value of sigmaB-memory changes from 0 to 1 if input A2 exists and changes from 1 to 0 if input B2 exists. For example, after the induction of A1, only the value of sigmaA-memory change from 0 to 1 since sigmaA promotes only transcription from PsigmaA (the promoter that is corresponding to sigmaA). Since the transcription from PsigmaB is not activated, sigmaB is not expressed and the value of sigmaB does not change. The same is true of input A2. After the induction of B1, anti-sigmaA is expressed and the value of sigmaA-memory changes from 1 to 0. However, anti-sigmaA has no effect on the transcription of PsigmaB and the value of sigmaB does not change. The same is also true of the input B2. Hence it can be confidently said that E. coli has two sigma memories.

<img src = "Nakashima_sigma_memory.png" class = "figure" /> <legend>Fig. 11 Multi sigma-memory and information processing A example of information processing by a sigma-memory. Only after induction of A1 and A2 in this order, the value of sigmaB-memory changes from 0 to 1.</legend>

<img src = "Sub_construction_of_counter.png" class = "contTitle" />

Resettable counter is a genetic device which count the number of the induction event of arabinose. In addition the count can be reset to 0 by IPTG induction. In this section, the application of sigma-factor for constructing resettable counter is explained.

resettable counter construction

<img src = "Nakashima_const.png" class = "figure" /> <legend>Fig. 12 construction of resettable 2-counter The construction of resettable 2-counter, which can count the number of induction event of arabinose. The count can be reset by IPTG induction. The maximum number that this counter can count is 2.</legend>

The construction of our resettable counter is explained here.

The construction of our resettable counter is explained here. The maximum number this counter can count is 2. Sigma factors used in this construction are Ecf20_992 (Sigma1, BBa_K1461004) and Ecf11_3726 (Sigma2, BBa_K1461005). The promoter that correspond to sigma1 and sigma2 are Pecf20_992 (Psigma1, BBa_K1461001) and Pecf11_3726 (Psigma2, BBa_K1461002), respectively. The corresponding anti-sigma factors are AS20_992 (anti-1, BBa_K1461006) and AS11_3726 (anti-2, BBa_K1461007) respectively. These two sigma factors were chosen because they most strongly activate transcription from the corresponding promoter within sigma factors which satisfy following conditions. (1)Promoter-sigma factor pair and anti-sigma factor-sigma factor pair have one-to-one correspondence. (2)The anti-sigma factors strongly repress the transcription from their corresponding promoter. (3)They and their corresponding anti-sigmas have negligible impact on growth of E. coli. (4) The sequence of their corresponding promoter conform to the standard of BioBrick. [4]

The cis-repressor sequence is crR12 (BBa_K1461000) and trans-activating RNA is taR12 (BBa_K1461003). This pair is selected because the leakage is minimum. [5]The reporter in this construction is GFP(BBa_E0040) with AAV degradation tag (BBa_I11012).

mechanism and extension

At first, both the values of sigma1-memory and sigma2-memory are 0. Only the crRNA coding sigma1, which is at downstream of the constitutive promoter is transcribed. After the first induction of arabinose, taRNA at the downstream of PBAD is transcribed and the crRNA coding sigma1 is translated, and the value of sigma1-memory changes from 0 to 1. Since sigma1 exists, crRNA coding sigma2 at the downstream of Psigma1 is transcribed. After the second induction of arabinose, taRNA is transcribed and sigma2 is expressed, and the value of sigma2-memory changes from 0 to 1. At this time, GFP at the downstream of Psigma2 is expressed and the number of count being 2 is observed.

After induction of IPTG, anti-sigma1 and anti-sigma2 are expressed, and the value of sigma1-memory and sigma2-memory changes to 0 (if the value of sigma memories are already 0, they remains 0). GFP is decomposed since AAV degradation tag is added. Therefore the count is reset.

<img src="Nakashima_const002.png" class="figure" /> <legend>Fig. 13 mechanism of resettable counter</legend>

Since there are many kinds of pairs of sigma factors and corresponding promoters which have one-to-one correspondence, an n-counter, which is a resettable counter which can count up to the number n, can be made by the same way. Furthermore, the construction of 2-counter can be simplified.

<img src = "Nakashima_sigmaconst.png" class = "figure" /> <legend>Fig. 14 construction of simplified resettable counter The construction of resettable counter can be simplified. However, the simplified counter cannot reset from their final count.

</legend>

This simplified counter is made by only one sigma factor. In this construction, GFP without degradation tags is used. It works as the same way as original 2-counter until the first count. After the first count, crRNA coding GFP is transcribed at the downstream of Psigma. Then when the next arabinose induction occurs, GFP is translated. This expression can be considered a report of the second count. If GFP with degradation tag is used in this construction, GFP is decomposed after some time since GFP is translated only when taRNA exist. Thus GFP without degradation tag is used. This simplified counter can be also extended to the nth count. The simplified counter can count up to larger numbers compared to the original counter even when the same number of sigma factors are used, but cannot be reset from their final count. since half-life of GFP without degradation tag is too long. We performed our experiments on this simplified counter.

comparison with previous counter

Our σ-Re Counter is the improved version of the previous counter constructed by Ari.[1]In the previous counter, T7 RNA polymerase and T3 RNA polymerase was used as the counterpart of sigma factor in our counter Using sigma factors has two merits. One is the ability to make it easy to extend 2-counter for n-counters. The number of RNA polymerase derived from virus is limited, but there are many kinds of sigma factors. Consequently it is easier to construct n-counter by using sigma factor. Another advantage is the existence of inhibitors. Anti-sigma factors are inhibitors of sigma factors which has one-to-one correspondence. Inhibitors are necessary to realize reset functions.

Another difference is the positive feedback circuits whereas the previous counter design had no feedback circuits. Since sigma factors are more subject to degradation than RNA polymerase, the positive feedback circuits are necessary to keep "memory" (i.e. enable sigma factor to remain) in our counter.

<img src = "Sub_application.png" class = "contTitle" />

In a previous study[3], many sigma factors and anti-sigma factors that can regulate 1-to-1 transcription have been reported. Thus, a counter that has many states (count number) can be constructed. Even though in this project the reset function is simply a transition from other states to state 0, more general system that is capable of changing one state to any other states can be realized. Such system is clearly beyond a counter because it can have an input corresponding to any arbitrary transition between states. This system can be applied to algorithmic system, for example, biocomputer etc. Furthermore, a more general circuit that responds to more various inputs is possible to be considered by integrating additional circuits.

For example, the change of balance between 2 substances itself can be considered as a input. Considering substances A and B, following additional circuit is possible:

pA-repressorB-GFP-activatorX-pX-repressorA

pB-repressorA-RFP-activatorY-pY-repressorB

<img src ="Sumi_AB.png" class = "figure" />

                               <legend>Fig. 15 The construction of converter</legend>

Here, substances A/B activate promoter A/B. This additional circuit notably contains a toggle switch structure with delay negative feedback loops. For example, when substance A becomes dominant against substance B, the toggle switch amplifies the dominance of promoter A and the following negative feedback suppresses the dominance. Consequently, this additional circuit is expected to convert the change of the dominance to a pulse-like expression of a reporter protein. Therefore, this additional circuit can expand the range of input.

Our concept is easily applied, for instance, to drug delivery system or health care by using a counter circuit for a transition loop. Regarding certain circadian rhythms or hormones in a human as inputs and some drugs as outputs, this theme producing drugs at particular time can be good for drug delivery system or health care to tune the medicine administration with the proper timing.

Reference

[1] Friedland, Ari E., et al. "Synthetic gene networks that count." science 324.5931 (2009): 1199-1202.
[2] iGEM Tokyo-NokoGen 2009<https://2009.igem.org/Team:Tokyo-Nokogen/Parts>(We finally accessed on 014/10/12)
[3]Zhou, Yanning, and Susan Gottesman. "Regulation of proteolysis of the stationary-phase sigma factor RpoS." Journal of bacteriology 180.5 (1998): 1154-1158.
[4]Rhodius, Virgil A., et al. "Design of orthogonal genetic switches based on a crosstalk map of σs, anti‐σs, and promoters." Molecular systems biology 9.1 (2013).
[5]Isaacs, Farren J., et al. "Engineered riboregulators enable post-transcriptional control of gene expression." Nature biotechnology 22.7 (2004): 841-847.