Difference between revisions of "Team:ATOMS-Turkiye/Project/Ulcer2"

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<p>In isotropic chemical environments, E. coli swims in a random walk pattern produced by alternating episodes of counter-clockwise (CCW) and clockwise (CW) flagellar rotation (Fig. 3, left panel).  In an attractant or repellent gradient, the cells monitor chemoeffector concentration changes as they move about and use that information to modulate the probability of the next tumbling event (Fig. 3, right panel.  These locomotor responses extend runs that take the cells in favorable directions (toward attractants and away from repellents), resulting in net movement toward preferred environments.  Brownian motion and spontaneous tumbling episodes frequently knock the cells off course, so they must constantly assess their direction of travel with respect to the chemical gradient.</p>
 
<p>In isotropic chemical environments, E. coli swims in a random walk pattern produced by alternating episodes of counter-clockwise (CCW) and clockwise (CW) flagellar rotation (Fig. 3, left panel).  In an attractant or repellent gradient, the cells monitor chemoeffector concentration changes as they move about and use that information to modulate the probability of the next tumbling event (Fig. 3, right panel.  These locomotor responses extend runs that take the cells in favorable directions (toward attractants and away from repellents), resulting in net movement toward preferred environments.  Brownian motion and spontaneous tumbling episodes frequently knock the cells off course, so they must constantly assess their direction of travel with respect to the chemical gradient.</p>
  
<div class="img-text"><a href="https://static.igem.org/mediawiki/2015/e/ed/ATOMS-Turkiye_aRep_1.png" data-lightbox="image-1" data-title=""><img class="img-center-middle" src="https://static.igem.org/mediawiki/2015/e/ed/ATOMS-Turkiye_aRep_1.png"></a>
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<p><b>Figure 1: </b>Random and biased walks.  Left:  A random walk in isotropic environments.  When the cell's motors rotate CCW, the flagellar filaments form a trailing bundle that pushes the cell forward.  When one or more of the flagellar motors reverses to CW rotation, that filament undergoes a shape change (owing to the torque reversal) that disrupts the bundle.  Until all motors once again turn in the CCW direction, the filaments act independently to push and pull the cell in a chaotic tumbling motion.  Tumbling episodes enable the cell to try new, randomly-determined swimming directions.  Right  A biased walk In a chemoeffector gradient.  Sensory information suppresses tumbling whenever the cell happens to head in a favorable direction.  The cells cannot head directly up-gradient because they are frequently knocked off course by Brownian motion..</p>
 
<p><b>Figure 1: </b>Random and biased walks.  Left:  A random walk in isotropic environments.  When the cell's motors rotate CCW, the flagellar filaments form a trailing bundle that pushes the cell forward.  When one or more of the flagellar motors reverses to CW rotation, that filament undergoes a shape change (owing to the torque reversal) that disrupts the bundle.  Until all motors once again turn in the CCW direction, the filaments act independently to push and pull the cell in a chaotic tumbling motion.  Tumbling episodes enable the cell to try new, randomly-determined swimming directions.  Right  A biased walk In a chemoeffector gradient.  Sensory information suppresses tumbling whenever the cell happens to head in a favorable direction.  The cells cannot head directly up-gradient because they are frequently knocked off course by Brownian motion..</p>
 
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<div class="img-text"><a href="https://static.igem.org/mediawiki/2015/f/f1/ATOMS-Turkiye_aRep_1.2.png" data-lightbox="image-1" data-title=""><img class="img-center-middle" src="https://static.igem.org/mediawiki/2015/f/f1/ATOMS-Turkiye_aRep_1.2.png"></a>
 
<p><b>Figure 1: </b>Signaling components and circuit logic.  E. coli receptors employ a common set of cytoplasmic signaling proteins: CheW and CheA interact with receptor molecules to form stable ternary complexes that generate stimulus signals; CheY transmits those signals to the flagellar motors, CheZ controls their lifetime; CheR (methyltransferase) and CheB (methylesterase) regulate MCP methylation state.  Abbreviations: OM (outer membrane); PG (peptidoglycan layer of the cell wall); CM (cytoplasmic membrane)
 
<p><b>Figure 1: </b>Signaling components and circuit logic.  E. coli receptors employ a common set of cytoplasmic signaling proteins: CheW and CheA interact with receptor molecules to form stable ternary complexes that generate stimulus signals; CheY transmits those signals to the flagellar motors, CheZ controls their lifetime; CheR (methyltransferase) and CheB (methylesterase) regulate MCP methylation state.  Abbreviations: OM (outer membrane); PG (peptidoglycan layer of the cell wall); CM (cytoplasmic membrane)
 
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Revision as of 18:38, 18 September 2015


ULCER

Acid Resistance

The main goal of this part is; making the E. coli, which we used for eradicating H. Pylori, acid resistant for living in gastric juice’s low pH (pH: 2) microenvironment. Wild-type E. coli already has couple systems to show acid resistance until a certain pH level (pH: 5). Among those systems, the most stable-working and efficient one is known as Glutamate Dependent Acid Resistance(GDAR) system. The most important protein of Gad system is GadE, which controls the synthesis of all other proteins. By overexpressing this protein, we aim to have our bacteria resistant enough to live in gastric juice for a while.

Background

Escherchia coli Natural Acid Resistance System

E. coli possesses four phenotypically distinct systems of acid resistance. These systems:
1. Glutamate dependent acid resistance system (GDAR)
2. Arginine dependent acid resistance system (ADAR)
3. Lysine dependent acid resistance system (LDAR)
4. Ornithine dependent acid resistance system (ODAR)

The most effective one of these systems is the glutamate dependent system so we decided to focus on glutamate dependent system (GDAR).

The GDAR system has in the acid resistance complex pathways. We decided to do the certain pathways that how to do acid resistance with our results of research.

EvgA is the most effective positive regulator of GDAR. (Efficiency: evgA>ydeO>gadE) But evgA takes part in countless number different genes regulation and cellular processes (2,6,7) and also most of this cellular processes are unclear. We cannot predict the results of the overexpression of evgA so we chose gadE and using by overexpression of gadE we can induce glutamate depended acid resistance system. Briefly talk about the impact of the GadE on the mechanism.

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The central activator is the LuxR-family member GadE (formerly known as YhiE). GadE binds to a 20-bp sequence called the gad box, which is located 63-bp upstream of the transcriptional start sites of gadA and gadBC. (4)GadE and GadBox are an important point for GadA and GadBC. This means that GadE and GadBox are an important for acid resistance. The basis section of acid resistance is GadE’s regulation. At least 10 different regulatory take part in this regulation.

GadE have three main activation mechanisms. The first of these is performed by evgA and ydeO. About GadE activation phase: 1. EvgS (sensor kinase) activate EvgA (response regulator) 2. YdeO and evgA are independently from each other and GadE takes an active role in transcription activation. The second GadE activation circuit includes CRP,RpoS and two AraC-like regulators, GadXand GadW. These steps are as follows: 1. GadX and GadW, are located downstream of gadA also GadX and GadW directly activate transcription of gadE 2. GadX and GadW also bind to the gadA and gadBC gad box sequences and seem to repress the gadA and gadBC promoters. (4) GadW inhibits this GadX’s repression Also GadX and GadW regulate indirectly GadA/BC transcriptional functions. 3. The balance of power in this circuit is influenced by cAMP and CRP,which together inhibit the synthesis of RpoS. Growth under acidic conditions reduces the concentration of cAMP in the cell. RpoS increases GadX’s transcriptional function The increase in GadX then stimulates transcription of GadE and also down regulates GadW. The third activation of GadE contains TrmE and glucose. These steps are as follows: 1. The function of TrmE in the cell is not fully defined but it does have a clear effect on tRNA modification 2. TrmE and glucose increase independently GadE’s transcriptional function We discourse GadE’s regulation and then now we will discourse GadE’s effect mechanisms. GadA/BC’s effect mechanisms to acid resistance are as follows: 1. The external pH is normally neutral but if external pH turns to acidic pH, internal pH begins to become acidic pH with HCl diffusion. 2. If the external pH=2,5 and internal pH begins pH=4.2 ± 0.1. GDAR system will activate for acid resistance. 3. GadC is a transmembrane protein. The external pH begins to change from neutral pH to acidic pH, C-plug (is GadC’s subunit) will open. Then glutamate will take inside.

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4. Glutamate in cells convert to GABA by GadB/C that’s glutamate decarboxylase isozymes These steps are as follows: *This step contains pyridoxal phosphate-containing enzymes that replace the α-carboxyl groups of their amino acid substrates with a proton that is recruited from the cytoplasm. *HCl that diffusion from outside dissociates H+ and Cl-. This H+ is used and CO² is released by the agency of GadA/B isozymes than this is the last stage of glutamate changes to GABA. Besides this is the most important and the last step for acid resistance 5. If H+ leaves HCl it is staying back Cl and it will be export from the transport of chlorine channel. 6. The emitted CO² is taken out by diffusion. 7. Finally, the uncovered GABA is thrown out from the transmembrane protein GadC.

Design

In this section, we targeted to overexpress GadE protein. For this purpose, while we’re desinging the gene part, we chose to combine GadE sequence with T7 promoter, a promoter which has a high rate of transcription. In addition to this, to have a controllable system, LacI protein attachable Lac operator was added between T7 and GadE gene sequence. We searched to find a vector which can lay down all those conditions and found out that peT-45 expression vector is useful. When we ordered our genes, we put RFC10 prefix site on 3’ end of GadE and also BamHI restriction enzyme recognition site for cloning to peT-45. We added RFC10 suffix site on 5’ end of the same gene sequence and also XhoI restriction enzyme recognition site for cloning to peT-45 vector, again.

resim

As shown above,we planned to clone the ordered GadE gene into peT-45 vector by using BamHI and XhoI enzymes. Final construct after this cloning is, respectively T7 promoter-Lac operator(LacO)-HisTag-GadE. Besides, a constitutive promoter called LacI promoter and LacI protein sequence in front of that, found on peT45-b vector’s another part. It is obvious that this part is IPTG-dependent, so Western Blot can be performed easily with the help of His Tag.

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Results

GadE-PSB1C3 CLONNING

We cloned IDT G-Blocks GadE gene into PSB1C3 vector in order to make it ready to be submitted and have many copies of it. For this purpose we digested PSB1C3 vector and GadE G-Blocks with ECoRI and PstI restriction enzymes. Then we ligated these cut genes into the plasmid by using T4 DNA Ligase . Ocurring products were transformed into BL21 competent cell strain. To check if the cloning is correct, a colony PCR was perfomed with Verify Forward and Verify Reverse primers. If the cloning isn’t made properly t the band should be 314 bp long, but if colony PCR worked, then bands should be 858 bp long. As the result of colony PCR, the possible right cloned colonies were incubated in liquid culture for 16 hours. After this incubation, we isolated plasmid DNA from this bacteria culture by miniprep plasmid isolation method. We controlled obtained colonies with cut-check for a second cloning control. We used EcorI and PstI restriction enzymes for cut-check.

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GadE-pET45-b CLONNING

We cloned GadE into PSB1C3 vector successfully, then moved on cloning it into the expression vector pET45-b. For cloning into this plasmid, we removed our gene from PSB1C3-GadE plasmid with BamHI and XhoI enzymes. Then we ligated the cut gene with pET45-b which was cut with the same enzymes. We transformed ligated products into BL21 bacteria strain that we know it has T7 RNA polymerase.

To check if the cloning is correct, a colony PCR was performed with T7 Promoter Forward and T7 Terminator Reverse primers. If the cloning isn’t made properly the band should be 360 bp long, but if colony PCR worked, then bands should be 837 bp long. As the result of colony PCR, the possible right cloned colonies were incubated in liquid culture for 16 hours. After this incubation, we isolated plasmid DNA from this bacteria culture by miniprep plasmid isolation method. We controlled obtained colonies with cut-check for a second cloning control. We used BamHI and XhoI restriction enzymes for cut-check.

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WESTERN BLOTTING

After cloning GadE into pET45-b successfully, we did Western Blot experiment through N-terminal located His Tag in proteins, so we managed to show the production of required proteins.

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FUNCTIONAL ASSAY

To understand if the proteins we produced are functional, we designed and performed a functional assay. We incubated these two types of bacteria in liquid culture for 13 hours at 37 C; pET45-GadE plasmid containing BL21 bacteria and another BL21 bacteria which contains only pET45-b plasmid for negative control. At 13. our, we added 100 mM IPTG into these liquid cultures. By doing this, we removed the suppression on GadE protein expression. After adding IPTG, we incubated 3 hours more at 37 C. We prepared LB mediums with different pH values to show produced GadE proteins’ functionality. These LB mediums’ pH values are respectively 7, 5, 3,5; 2,5 and 2. We added thebacteria whichis incubated for 16 hours into LB mediums at the rate of 1:9. This means, for each pH value we added 0.5 ml liquid culture into 4.5 ml LB medium. We also added 1.5 mM Glutamat in each mix and incubated the final mix at 37 C. We made spectrophotometric measurement in 600 nm periodically for the samples that we incubated. Thus we observed how long the bacteria survives in different pH values. The measurement results are shown below.

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1.5 mMGlutamate / 600 nm OD / 3h 100 mM IPTG

grafik

When the given data checked, it is obvious that the produced GadE is functional and makes E. coli survive in the acidic microenvironment in comparison to negative control results. Based on the data given, the E. coli with overexpressed GadE can survive in pH 2 gastric juice for 5-9 hours.

Acid Repellency

The main objective of this part of our project is to direct resistant E. Coli into the internal mucus layer where Helicobacter Pylori are abundant for a length of time. We will direct our E. Coli using the hydrogen ion difference between the stomach fluid and mucus layer. The PH of gastric juice is 2.0 whereas the pH of gastric mucus layer is 7.0. The chemoreceptor tlpb naturally found in the inner membrane of helicobacter pylori enable these bacteria to move away from acidic condition to a more neutral and basic environment. Therefore, we decided to use the TIpB protein and designed a biobrick for our E. Coli in order to ensure that our Bacteria reach the region where the helicobacter pylori are.

Background

Chemotaxis, movement toward or away from chemicals, is a universal attribute of motile cells and organisms. E. coli cells swim toward amino acids (serine and aspartic acid), sugars (maltose, ribose, galactose, glucose), dipeptides, pyrimidines and electron acceptors (oxygen, nitrate, fumarate).

E. coli's optimal foraging strategy

In isotropic chemical environments, E. coli swims in a random walk pattern produced by alternating episodes of counter-clockwise (CCW) and clockwise (CW) flagellar rotation (Fig. 3, left panel).  In an attractant or repellent gradient, the cells monitor chemoeffector concentration changes as they move about and use that information to modulate the probability of the next tumbling event (Fig. 3, right panel.  These locomotor responses extend runs that take the cells in favorable directions (toward attractants and away from repellents), resulting in net movement toward preferred environments.  Brownian motion and spontaneous tumbling episodes frequently knock the cells off course, so they must constantly assess their direction of travel with respect to the chemical gradient.

Figure 1: Random and biased walks. Left: A random walk in isotropic environments. When the cell's motors rotate CCW, the flagellar filaments form a trailing bundle that pushes the cell forward. When one or more of the flagellar motors reverses to CW rotation, that filament undergoes a shape change (owing to the torque reversal) that disrupts the bundle. Until all motors once again turn in the CCW direction, the filaments act independently to push and pull the cell in a chaotic tumbling motion. Tumbling episodes enable the cell to try new, randomly-determined swimming directions. Right A biased walk In a chemoeffector gradient. Sensory information suppresses tumbling whenever the cell happens to head in a favorable direction. The cells cannot head directly up-gradient because they are frequently knocked off course by Brownian motion..

The chemotaxis signaling pathway of E.coli

E. coli senses chemoeffector gradients in temporal fashion by comparing current concentrations to those encountered over the past few seconds of travel.  E. coli has four transmembrane chemoreceptors, known as methyl-accepting chemotaxis proteins (MCPs), that have periplasmic ligand binding sites and conserved cytoplasmic signaling domains (Fig. 4).  MCPs record the cell's recent chemical past in the form of reversible methylation of specific glutamic acid residues in the cytoplasmic signaling domain (open and filled circles in Fig. 4).  Whenever current ligand occupancy state fails to coincide with the methylation record, the MCP initiates a motor control response and a feedback circuit that updates the methylation record to achieve sensory adaptation and cessation of the motor response. A fifth MCP-like protein, Aer, mediates aerotactic responses by monitoring redox changes in the electron transport chain.  Aer undergoes sensory adaptation through a poorly-understood, methylation-independent mechanism. The five MCP-family receptors in E. coli utilize a common set of cytoplasmic signaling proteins to control flagellar rotation and sensory adaptation (Fig. 4).  CheW and CheA generate receptor signals; CheY and CheZ control motor responses; CheR and CheB regulate MCP methylation state.

Figure 1: Signaling components and circuit logic. E. coli receptors employ a common set of cytoplasmic signaling proteins: CheW and CheA interact with receptor molecules to form stable ternary complexes that generate stimulus signals; CheY transmits those signals to the flagellar motors, CheZ controls their lifetime; CheR (methyltransferase) and CheB (methylesterase) regulate MCP methylation state. Abbreviations: OM (outer membrane); PG (peptidoglycan layer of the cell wall); CM (cytoplasmic membrane)

Design

Chemotaxis, movement toward or away from chemicals, is a universal attribute of motile cells and organisms. E. coli cells swim toward amino acids (serine and aspartic acid), sugars (maltose, ribose, galactose, glucose), dipeptides, pyrimidines and electron acceptors (oxygen, nitrate, fumarate).

E. coli's optimal foraging strategy

In isotropic chemical environments, E. coli swims in a random walk pattern produced by alternating episodes of counter-clockwise (CCW) and clockwise (CW) flagellar rotation (Fig. 3, left panel).  In an attractant or repellent gradient, the cells monitor chemoeffector concentration changes as they move about and use that information to modulate the probability of the next tumbling event (Fig. 3, right panel.  These locomotor responses extend runs that take the cells in favorable directions (toward attractants and away from repellents), resulting in net movement toward preferred environments.  Brownian motion and spontaneous tumbling episodes frequently knock the cells off course, so they must constantly assess their direction of travel with respect to the chemical gradient.

Figure 1: Random and biased walks. Left: A random walk in isotropic environments. When the cell's motors rotate CCW, the flagellar filaments form a trailing bundle that pushes the cell forward. When one or more of the flagellar motors reverses to CW rotation, that filament undergoes a shape change (owing to the torque reversal) that disrupts the bundle. Until all motors once again turn in the CCW direction, the filaments act independently to push and pull the cell in a chaotic tumbling motion. Tumbling episodes enable the cell to try new, randomly-determined swimming directions. Right A biased walk In a chemoeffector gradient. Sensory information suppresses tumbling whenever the cell happens to head in a favorable direction. The cells cannot head directly up-gradient because they are frequently knocked off course by Brownian motion.

Results
Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance..

Increased Motility

Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Some description.. Background
Background of acid resistance.. Background of acid resistance.. Background of acid resistance.. Background of acid resistance.. Background of acid resistance.. Background of acid resistance..
Design
Design of acid resistance.. Design of acid resistance.. Design of acid resistance.. Design of acid resistance.. Design of acid resistance.. Design of acid resistance.. Design of acid resistance..
Results
Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance..

Sensing h.p.

In this section, we aim to use our gene parts for making E. Coli, sensing H. Pylori’s existence and activating a pathogen-killer system, after it gets into the mucus layer. Targeting this pathogen will be provided by sensing Auto-inducer 2 (AI-2) and ammonia (NH3), both secreted from H. Pylori. AI-2 will be sensed by Lsr operon system and NH3 will be sensed by TnrA-pAlsT regulation system. Getting only one result of these two systems when they are sensed seperatley, is provided by Toehold-Triger RNA system. The output of this system, which works in the existence of these two molecules, is an endonuclease called TEV protease. Produced TEV protease will activate the antimicrobial peptide Pexiganan after this molecule synthesized in an inactive form and accumulated in cell. Activated Pexiganan molecules are expected to leave the cell, become free and kill H. Pylori.

Background

Helicobacter Pylori Sensing:

Helicobacter pylori lives in stomach, by connecting to epithelium cells under the mucus layer.This bacteria releases some molecules around which comes from its metabolic waste. Two of these molecules are Auto-inducer 2 and ammonia.

Ammonia (NH3)

H. pylori synthesizes urease to buffer the pH of its microenvironment within the stomach. H. pylori dedicates several genes to the biosynthesis of its cytosolic urease, a Ni2+-containing enzyme which hydrolyses urea into NH3 and CO2. Bacteria has urea channel which is regulated positively by protons, opening at acidic pH values to allow more urea in to buffer cytosolic and surface pH, and closing at neutral pH to avoid over-alkalinization [1].

Ammonia (NH3) buffers the cytosol and periplasm, and creates a neutral layer around the bacterial surface[1].With this surface created by bacteria, protects itself against low acid coditions of the stomach.

Figure 1: Helicobacter Pylori Environment.

Autoinducer 2 (AI-2)

Such as many gram-negative and gram positive bacteria has the quorum sensing (QS) molecule, H. Pylori has this molecule too. QS molecules are specific, low-molecular-weight signal molecules which used by bacteria to regulate expression of genes in response to changes in population density.[2]

H. pylori has Quorum Sensing molecule “Autoinducer-2 (AI-2)” which is produced depended on the activity of the LuxS enzyme [3].

Based on the information given above, we expect to find ammonia and Auto-inducer 2 molecules in the existence of H. pylori. Thus we aim to sense both of these molecules to find out if H. Pylori’s presence.

Figure 2:Our “AND GATE” system diagram: According to our system, TnrA transcription factor represses TnrA promoter which produce Toehold. In the presence of NH3 this press will be eliminated and Toehold will be produced. Lsr transcription factor represses pLsr promoter which produce Trigger mRNA. In the presence of AI-2 (Autoinducer-2) this press will be eliminated and Trigger mRNA will be produced. In conclusion Trigger mRNA opens the toehold system and TEV-Protease will be formed.

As a result, our “SENSING” system composed of three parties:

1.NH3 sensitive TnrA promoter


2. AI-2 sensitive Lsr promoter


3. Toehold system

1. NH3 Sensitive TnrA Promoter

Bacteria use nitrogen which is present in nearly all macromolecules such as proteins, carbonhydrates and peptidoglycan. Prokaryotes have developed transport and assimilation systems for a variety of nitrogen sources for living under optimal conditions and regulate their own systems. This regulatory network allows an adequate response to situations of nitrogen limitation.

In the Bacillus subtilis, ammonium assimilation occurs via the glutamine synthetase - glutamate synthase pathway. Bacillus subtilis faces nitrogen- limiting conditions when it consumes glutamate as a prior nitrogen source, while glutamine is the secondly preferred nitrogen source [3].

Two transcription factors, TnrA and GlnR, and one enzyme, the Glutamine Synthase, are the major players in the B. Subtilis nitrogen regulatory network [3]. We use TnrA transcription factor in our system.

Under nitrogen-limited conditions, TnrA works as an activator and a repressor both. TnrA represses expression of glnRA (Glutamine Synthase) [4], gltAB (Glutamate Synthase) [5] and other genes. Also the form of Glutamine Synthase which is feedback inhibited by excess glutamine, directly interacts with and unbinds from TnrA, thus blocks its DNA-binding activity [6]. Based on all this information, if the amount of NH3 is not sufficient, glutamine synthase will not work properly, glutamine will be produced in a low amount, TnrA will bind to promoter and Toehold production will be repressed. But if there is a sufficient amount of NH3, glutamine will be produced in a high level, TnrA will not repress the promoter as previous and Toehold – Tev Protease will be produced in a high amount.

Figure 3: If there is a sufficient amount of NH3, Toehold and TEV protease will be produced. If there isn’t a sufficient amount of NH3, Toehold and TEV Protease will not be produced.

Seventeen TnrA targets were detected by a combination of DNA microarray hybridization, a genome-wide search for TnrA boxes, and gel retardation assays [7]. The TnrA box consensus delimited in this study to a 17- bp interrupted, inverted repeat sequence, TGTNANAWWWTNTNACA.

2. AI-2 Sensitive Lsr Promoter

Figure 4:LsrR-binding site recognition and regulatory characteristics in Escherichia Coli AI-2 quorum sensing (Ting Xue, Liping Zhao, Haipeng Sun, Xianxuan Zhou and Baolin Sun).

In quorum sensing (QS) process, bacteria regulate gene expression by utilizing small signaling molecules called autoinducers in response to a variety of environmental cues. QS molecules secreted by bacteria are small, diffusible signaling molecules called autoinducers that accumulate in the external environment. When the concentration of the autoinducers reaches a threshold, an alteration of gene expression is induced, allowing the bacteria to adopt behaviors that are only productive when the bacteria are working together as a group [8].

Many quorum sensing molecules have been identified until now. In contrast to other autoinducers that are specific for a narrow range of organisms, the widely conserved AI-2 has been hypothesized to be a universal language for interspecies communication [9]. In every case, AI-2 is synthesized by LuxS, which functions in the pathway for metabolism of S-adenosylmethionine (SAM), a major cellular methyl donor. In a metabolic pathway known as the activated methyl cycle, SAM is metabolized to S-adenosylhomocysteine, which is subsequently converted to adenine, homocysteine, and 4,5-dihydroxy-2,3-pentanedione (DPD, the precursor of AI-2) by the sequential action of the enzymes Pfs and LuxS [10].

The regulatory network for AI-2 uptake is comprised of two other important components, lsrR and lsrK, which are located adjacent, but divergently transcribed from the lsr operon (Figure 1). LsrR is the repressor of the lsr operon and itself. LsrK is a kinase responsible for converting AI-2 to phospho-AI-2, which is required for relieving LsrR repression. It has also been postulated that phospho- AI-2 binds to LsrR and inactivates it to derepress the transcription of lsr [11].Since LsrR contains a helix-turn-helix (HTH) DNA-binding domain, it was hypothesized that LsrR represses the expression of lsr operon and itself by binding to their promoter regions [12].

Two independent groups demonstrated that H. pylori secretes AI-2 into its extracellular environment by a luxS-dependent mechanism.[13,14] Therefore we planned to use LsrR system to sense AI-2 molecules synthesized by H. Pylori.

In the absence of Autoinducer-2, LsrR repress the LsrR promoter to bind LsrR-Binding Site. In the presence of AI-2 extracellular AI-2 is imported into the cell (cytoplasmic AI-2) via LsrACDB transporter, where it is phosphorylated by LsrK. LsrK is a kinase responsible for converting AI-2 to phospho-AI-2, which is required for relieving LsrR repression. Phospho-AI-2 has been reported to bind to LsrR and relieve its repression effect on the lsrR promoter.

3. Toehold System

Toehold switches provide a high level of orthogonality and can be forward engineered to provide average dynamic range above 400. Toehold switches, with their wide dynamic range, orthogonality, and programmability, represent a versatile and powerful platform for regulation of translation, offering diverse applications in molecular biology, synthetic biology, and biotechnology.New classes of regulatory components that offer wide dynamic range, low system crosstalk, and design flexibility represent a much-needed, enabling step toward fully realizing the potential of synthetic biology in areas such as biotechnology and medicine. (Khalil and Collins, 2010).

Engineered riboregulators consist of cognate pairs of RNAs: a transducer strand that regulates translation or transcription and a trans-acting RNA that binds to the transducer to modulate its biological activity. Riboregulator designs can be classified according to the initial RNA-RNA interaction that drives hybridization between the transducer and trans-acting RNAs. Reactions initiated between loop sequences in both RNAs are termed loop-loop interactions, whereas those that occur between a loop sequence and an unstructured RNA are termed loop-linear(Takahashi and Lucks, 2013).

A common limitation for riboregulators has been their dynamic range (Liu et al., 2012). Previous prokaryotic translational riboregulators have typically modulated biological signals by up to a maximum of 55-fold for activators (Callura et al., 2012) and up to 10-fold for repressors (Mutalik et al., 2012). In contrast, protein-based transcriptional regulators have demonstrated dynamic ranges over an order of magnitude higher, with widely-used inducible promoters regulating protein expression over 350-fold (Lutz and Bujard, 1997) and sigma factor-promoter pairs providing up to 480-fold modulation (Rhodius et al., 2013).Despite the inherent programmability of RNA-based systems, efforts at constructing large sets of orthogonal riboregulators have been limited to libraries of at most seven parts with crosstalk levels of 20% (Takahashi and Lucks, 2013). Typical RNA-based regulators employ interaction domains consisting of30 nts, which corresponds to a sequence space of over 1018 potential regulatory elements. Thus, the sheer diversity of possible RNA-based parts suggests that previous devices have not come close to realizing the potential of highly orthogonal regulation.

Figure 5: (A and B) Design schematics of conventional riboregulators (A) and toehold switches (B). Variable sequences are shown in gray, whereas conserved or constrained sequences are represented by different colors.

Much of this discrepancy arises from the significant sequence constraints imposed on riboregulators engineered thus far (Figure1A). Like natural riboregulators, engineered riboregulators of translation have invariably used base pairing to the ribosome binding site (RBS) to prevent ribosome binding, thereby preventing translation (Callura et al., 2012; Isaacs et al., 2004; Mutaliket al., 2012; Rodrigo et al., 2012). Because repression is caused by RBS binding, trigger RNAs that activate translation are engineered to contain an RBS sequence to displace the repressing sequence, which in turn reduces the potential sequence space for the riboregulator.

Previous riboregulators have also relied on U-turn loop structures to drive loop-loop and loop-linear interactions between RNAs (Figure 1A) (Callura et al., 2012; Isaacs et al., 2004; Luckset al., 2011; Takahashi and Lucks, 2013). U-turn loops are common RNA structural motifs formed by tertiary interactions that have been identified in ribozymes, ribosomal RNAs, and transfer RNA anticodon loops (Gutell et al., 2000). Although recent work has begun to show that loops with canonical U-turn sequences are not essential for riboregulators (Mutalik et al., 2012; Rodrigoet al., 2012), the engineered systems reported to date have continued their reliance on the loop-mediated RNA interactions from natural systems. Although these loop interactions have been selected by evolution in nature, alternative approaches employing linear-linear RNA interactions are amenable to rational engineering and exhibit more favorable reaction kinetics and thermodynamics, factors that could be exploited to increase riboregulator dynamic range.

A riboregulator that activates gene expression must switch from a secondary structure that prevents translation to a configuration that promotes translation upon binding of a cognate trans-acting RNA. Although the Shine-Dalgarno sequence is an important factor in determining the efficiency of translation from a given mRNA, studies have found that secondary structure in regions near by the start codon also plays a critical role (Kudla et al., 2009).Furthermore, genome-wide analyses have revealed strong biases toward low secondary structures around the start codon of mRNAs from a panel of hundreds of bacterial genomes.

Toehold switch systems are composed of two RNA strands referred to as the switch and trigger (Figure 1B). The switch RNA contains the coding sequence of the gene being regulated. Upstream of this coding sequence is a hairpin-based processing module containing both a strong RBS and a start codon that is followed by a common 21 nt linker sequence coding for low-molecular-weight amino acids added to the N terminus of the gene of interest. A single-stranded toehold sequence at the 50 end of the hairpin module provides the initial binding site for the trigger RNA strand. This trigger molecule contains an extended single stranded region that completes a branch migration process with the hairpin to expose the RBS and start codon, thereby initiating translation of the gene of interest. The hairpin processing unit functions as a repressor of translation in the absence of the trigger strand. Unlike previous riboregulators, the RBS sequence is left completely unpaired within the 11 nt loop of the hairpin. Instead, the bases immediately before and after the start codon are sequestered within RNA duplexes that are 6 bp and 9 bp long, respectively. The start codon itself is left unpaired in the switches we tested, leaving a 3 nt bulge near the midpoint of the 18 nt hairpin stem. Because the repressing domain b (Figure 1B) does not possess complementary bases to the start codon, the cognate trigger strand in turn does not need to contain corresponding start codon bases, thereby increasing the number of potential trigger sequences. The sequence in the hairpin added after the start codon was also screened for the presence of stop codons, as they would prematurely terminate translation of the gene of interest when the riboregulator was activated. We employed a 12 nt Toehold domain at the 50 end of the hairpin to initiate its interaction with the cognate trigger strand. The trigger RNA contains a 30 nt single-stranded RNA sequence that is complementary to the toehold and stem of the switch RNA.

Figure 6: (C) Flow cytometry GFP fluorescence histograms for toehold switch number 2 compared to E. coli autofluorescence and a positive control. Autofluorescence level measured from induced cells not bearing a GFP-expressing plasmid.(D) GFP mode fluorescence levels measured for switches in their ON and OFF states in comparison to positive control constructs and autofluorescence. Error bars are the SD from at least three biological replicates.
Based on all information given above, we decided to use Toehold-Trigger RNA system fort he AND Gate part of our project.


Sources:

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Design

TnrA-pAlsT -RFP

Main goal of this part is to show TnrA protein’s repressor activity on pAlst promoter and derepression of this promoter in the presence of NH3. Thereby we combined TnrA protein’s and pAlst’s gene sequences on the same biobrick. As a reporter, we put RFP gene sequence in front of the pAlst sequence. To make sure the repressive protein TnrA is produced in a high amount, we combined TnrA-pAlst-RFP gene sequence with T7 promoter which has a high transcription rate. Also, we put a Lac operator which LacI protein can bind, between this sequence and T7 promoter, in order to create a controllable system. We searched to find an expression vector working in harmony with this system, peT45-b expression vector was serving this purpose. . When we ordered our genes, we put RFC10 prefix site on 3’ end of TnrA-pAlst-RFP gene sequence and also BamHI restriction enzyme recognition site for cloning to peT45-b. We added RFC10 suffix site on 5’ end of the same gene sequence and also XhoI restriction enzyme recognition site for cloning to peT-45 vector, again.

As shown above,we planned to clone the ordered TnrA-pAlst-RFP gene into peT45-b vector by using BamHI and XhoI enzymes. Final construct after this cloning is, T7 promoter-Lac operator(LacO)-HisTag-TnrA-pAlst-RFP, respectively. Besides, a constitutive promoter called LacI promoter and LacI protein sequence in front of that, found on peT45-b vector’s another part. It is obvious that this part is IPTG-dependent, so Western Blot can be performed easily with the help of His Tag.

According to this system, under the absence of IPTG; TnrA production will be repressed, pAlsT promoter will be derepressed and RFP won’t be produced. If IPTG is present, TnrA will be produced , pAlsT promoter becomes derepressed and red colored bacteria will be observed with production of RFP. After showing stability of TnrA-pAlst sytem by using the RFP fluorescence protein, Toehold-TEV protease will be replaced with RFP for binding to AND gate system.

QS dependent promoter pLsr

There are two promoters on LsrR’s operon Lsr . these promoters are called LsrA and LsrR, and they are repressed in the absence of AI-2. The location LsrR binds on these promoters(p-lsr-Box) are shown below. Dark ones indicate the common sequences in both promoters. We preferred to use lsR promoter as it is one of ATOMS Team’s parts in 2013.

FIGURE 5:LsrR-binding site recognition and regulatory characteristics in Escherichia Coli AI-2 quorum sensing (Ting Xue, Liping Zhao, Haipeng Sun, Xianxuan Zhou and Baolin Sun).

We aimed to show repression of LsrR protein on pLsr promoter and dereppession of it in the presence of AI-2. For this purpose, we gathered LsrR protein gene sequence and pLsr sequence on the same biobrick. We put RFP as a reporter in front of pLsr promoter. To produce th repressor protein Lsr in a high amount, we put LsrR-pLsr-RFP gene sequence in front of J23100 constutive promoter . We added RFC prefix on 3’end , RFC suffix on 5’ end of LsrR-pLsr-RFP gene sequence.

LsrABCD operon, which makes AI-2 getting into the cell, already present in E.coli; so it is expected to be enough when an AI-2 sensing promoter system placed into E. coli. Thereby under the absence of AI-2, Lsr promoter will be heavily repressed by LsrR protein. If Quorum Sensing molecule sensed successfully AI-2 will be phosphorylated and LsrR’s suppression on pLsr will disappear. Thus RFP expression will occur.

We chose to use the part J23100-LsrR-pLsR-RFP(BBa_K1202108) as 2013 ATOMS IGEM TEAM designed. After showing LsrR-pLsrR system’s stability by using RFP, Trigger RNA will be replaced with RFP to connect the inputs to the And gate system.

Trigger RNA-Toehold-GFP System

We aimed to show Toehold switch system’s incapability of protein expression when it is alone, which means the Trigger RNA and Toehold Switch must coexist for protein expression. To observe Toehold swtich’s and and Toehold Swtich-Trigger RNA’s coexisting results both, we designed Toehold switch and trigger RNA in different biobricks. Because of origin incompatibility process, we had to clone these two different gene sequences into different plasmids. Thus we cloned Toehold-GFP into ColA originated PColA plasmid, and Trigger RNA into ColE originated PSB1C3 plasmid.

The ordered form of Toehold G-blocks is shown above. We preferred to use T7 promoter, which is a very strong promoter in this gene’s design. Thus there won’t be any difficulty in Toehold-GFP RNA’s production. The RBS of GFP presented in Toehold structure. To clone Toehold-GFP sequence into PSB2C3 and pColA plasmids both, we added RFC 10 suffix region on 3’ end and RFC 10 prefix region on 5’ end of Toehold-GFP. We also put BamHI restriction sitebetween Toehold and GFP. After GFP expression, which shows that Toehold-trigger system works, any protein could be replaced with GFP. In our project, GFP will be replaced with TEV protease.

Trigger RNA, which turns on Toehold switch system, is shown above in its ordered form as G-Blocks. In the design of this biobrick, we used T7 promoter, which has a strong mRNA production rate. By doing these, an enough amount of Trigger RNA will be produced to open Toeholds. There is no RBS in this product, because Trigger RNA doesn’t codes a protein. Its only task is opening Toehold switch in order to produce protein. To clone Trigger RNA sequence into PSB1C3 plasmid, we added RFC10 prefix on 3’ end and RFC10 suffix on 5’ end.

Figure: Toehold switch and Trigger RNA deatiled design

Results

NH3 Sensitive Promoter and TnrA


PSB1C3-TnrA-pAlst-RFP CLONING

We cloned IDT G-Blocks GadE gene into PSB1C3 vector in order to make it ready to be submitted and have many copies of it. For this purpose we digested PSB1C3 vector and TnrA-pAlst-RFP G-Blocks with ECoRI and PstI restriction enzymes. Then we ligated these cut genes into the plasmid by using T4 DNA Ligase . Ocurring products were transformed into BL21 competent cell strain.

To check if the cloning is correct, a colony PCR was perfomed with Verify Forward and Verify Reverse primers. If the cloning isn’t made properly t the band should be 314 bp long, but if colony PCR worked, then bands should be 1800 bp long.

As the result of Colony PCR experiments, we observed bands are either negative or less molecule-weighted than we expected. We made liquid cultures of the not negative colonies, and isolated DNA from these colonies after incubating for 16 hours. we did cut-check with EcoRI and PstI enzymes in order to control occurring DNA’s.

After cut-check, we observed less molecule-weighted bands again. Therefore we decided to control our ordered G-Blocks and did a PCR experiment with CMV forward and SV40 reverse primers. The gel image of this PCR is shown below.

TnrA-pTnrA-RFP PCR

After that PCR, we observed less molecule-weighted bands than normal.

pET45 -TnrA-pTnrA-RFP CLONNING

We questioned if the plasmid is incorrect because the results of PSB1C3 cloning weren’t matching with our expected results. We cut the G-Block with BamHI and XhoI and ligated it with pET45-b which was cut with same enzymes. We transformed this ligated product into BL21 bacteria strain, which has T7 RNA polymerase.

In order to control if the cloning is made correctly, we did a colony PCR with T7 Promoter reverse and T7 promoter forward. If cloning isn’t made properly, the band should be at 360 bp line and if is made properly the band should be at 1779 bp line.

In colony PCR results, we observed lower molecule-weighted bands than expected, again. In this case we realized that this gene sequence was wrong.

We didn’t have enough time to order and clone this gene so we didn’t continue to do this part’s experiments.

AI-2Sensitive Promoter and LsrR

We got the results of Lsr promoter part from 2013 ATOMS iGEM team. Their results are shown below.

Inducible promoter experiment

To observe inducible promoters response, we co incubated two different bacteria. The first bacteria culture is expressing enzyme system and the second culture is including inducible promoter. At the experiment, we incubated them seperately for 16 hours and mixed them into one flask and 4 hour later, we add 0,1 mM SAH (with 10x PBS containing %1 BSA). Incubate with SAH for one day and, took 2 ml of liquid culture to santrifuge tube.Centrifuged it. We saw the red color at the pellet as you see below.

So, it means the enzyme system is working and inducible promoter is succesfully induced from AI-2.


Toehold-Trigger RNA-GFP

PSB1C3-Toehold-GFP/Trigger RNA CLONING

We cloned these two IDT G-Block genes into PSB1C3 vector in order to make it ready to be submitted and have many copies of it. For this purpose we digested PSB1C3 vector and TnrA-pAlst-RFP G-Blocks with ECoRI and PstI restriction enzymes. Then we ligated these cut genes into the plasmid by using T4 DNA Ligase . Ocurring products were transformed into BL21 competent cell strain.

To check if the cloning is correct, a colony PCR was perfomed with Verify Forward and Verify Reverse primers. If the cloning isn’t made properly t the band should be 314 bp long, but if colony PCR worked, Toehold-GFP’s band should be at 1294 bp line and Trigger RNA’s should be at 443.

As the result of colony PCR, the possible right cloned colonies were incubated in liquid culture for 16 hours. After this incubation, we isolated plasmid DNA from this bacteria culture by miniprep plasmid isolation method. We controlled obtained colonies with cut-check as a second control of cloning. We used EcorI and PstI restriction enzymes for cut-check.

RESULT FOR TOEHOLD-GFP


RESULT FOR TRIGGER RNA

In order to make And gate work, Toehold-GFP and Trigger RNA must be transformed into the same bacteria. Origin incompatibility prevents us to transform two different originated plasmids in the same bacteria. Therefore we decided to clone Toehold-GFP into a ColA originated plasmid and clone Trigger RNA into a ColE originated plasmid. PSB1C3 plasmid has a ColE origin so we cloned Trigger RNA into it. We designed this ColA originated plasmid for cloning Toehold-GFP sequence and named it ‘pColA’.

pColA-Toehold GFP CLONING

After cloning Toehold-GFP into PSB1C3 vector successfully, as we are planning to transform this gene into the same bacteria with Trigger RNA, we cloned it into pColA plasmid. In order to do cloning into this vector, we removed the gene from PSB1C3-Toehold GFP plasmid by cutting it with NotI enzyme. Then we ligated these cut genes into the plasmid by using T4 DNA Ligase . Ocurring products were transformed into BL21 competent cell strain.

To check if the cloning is correct, a colony PCR was perfomed with ColA Forward and ColA Reverse primers. If the cloning isn’t made properly t the band should be 192 bp long, but if colony PCR worked, Toehold-GFP’s band should be at 1196 bp line.

As the result of colony PCR, the possible right cloned colonies were incubated in liquid culture for 16 hours. After this incubation, we isolated plasmid DNA from this bacteria culture by miniprep plasmid isolation method. We controlled obtained colonies with cut-check as a second control of cloning. We used NotI restriction enzyme for cut-check.

PSB1C3-Trigger RNA/pColA-Toehold-GFP Cotransformation:

To show And Gate system works properly, these two plasmids with different origins should be transformed into the same bacteria. T7 is the promoter which produces Trigger RNA and Toehold-GFP mRNA’s , so we assured that they were cotransformed into a bacteria strain including T7 RNA polymerase. BL21 served this purpose, and after cotransformation, we observed grown colonies.

Functional Assay:

We designed a functional assay setup in order to figure out if Toehold-Trigger RNA system is functional. The main goal of this setup is to show that; Toehold-GFP doesn’t give fluorecence alone but if it comes together with Trigger RNA, GFP fluorescences. GFP production is also IPTG-dependent.

For the purposes given above, we made liquid culture of two different bacteria together; bacteria including only pColA-Toehold-GFP plasmid and bacteria including pCola-Toehold-GFP and PSB1C3-Trigger RNA. We incubated these bacteria in liquid culture for 13 hours at 37C and added IPTG into their mediums at 13. hour. After adding IPTG, we incubated them for more 3 hours at 37C. At the end of three hours, we firstly measured GFP fluorescence of the grown cultures by using VarioScan device. The results of measurements are given above. They were made twice.

When the results are analyzed, it is obvious that Toehold-Trigger RNA parts gave very high amounts of flourescence together while Toehold-GFP part gave flourescence in a very low amount. There is almost 15 times difference between these two fluoroscence amounts. This proves that Toehold-Trigger system works successfully. Also it is shown that systems work IPTG-dependently.

The graphs of measurement results are given below. The difference between two systems can be observed clearly.

Figure : GFP flourescent measurrement in LB mediums.

We also observed the liquid cultures under the fluorescence microscope.

Figure 2: Flourescence microscope image of GFP producing E. coli.

For better results, we isolated protein and we fluorimetrically measured them. Firstly we centrifuged the liquid cultures which were incubated for 16 hours. We took pictures of tubes after centrifugation, they are shown belown.

Figure : Pellets can be seen after 16 hours of liquid culter precipitated.

We applied Standard protein isolation protocol after this centrifuge and managed to isolate protein from the occured pellets. We made GFP fluorescence measurement with VarioScan from those isolated proteins. The results of measurements are shown below.


The measurement results of isolated proteins indicate that Toehold-Trigger system works very efficiently. GFP fluorescence amount of Toehold-trigger RNA including bacteria is about 175 times more than only Toehold including bacteria’s. also the leak of this system is almost negligible. In the absence of Trigger RNA, Toehold’s GFP fluorescence is almost zero. This indicates that our system works very efficient and in a very specific way.

Figure : Protein extract GFP florasans measurement

Killing h.p.

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Design
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Results
Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance.. Results of acid resistance..