Team:Aalto-Helsinki/Research

From 2014.igem.org

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     <h3>Fluorescence measurements</h3>
     <h3>Fluorescence measurements</h3>
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         Fluorescence measurements were carried out in Thermo Scientific Varioskan. It is a microtiter plate reader capable of exitation and measuring the corresponding fluorsecense at user defined wavelengths. All measurements were made with over night cell cultures diluted to the same cell density. In the LEDrig there are 16 different LEDs but also many additional wells that can be used for control samples. That way, we can ensure identical conditions between our test and control samples. We always used two controls: blue chromoprotein BioBrick (<a href="http://parts.igem.org/Part:BBa_K592009">BBa_K592009</a>) without a promoter as the negative control and constitutive GFP generator from Measurement Interlabs study (<a href="http://parts.igem.org/Part:BBa_I20260">BBa_I20260</a>) as the positive control. All experiments were carried out in <em>E. coli</em> TOP10 strain.
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         Fluorescence measurements were carried out in Thermo Scientific Varioskan. It is a microtiter plate reader capable of exitation and measuring the corresponding fluorsecense at user defined wavelengths. All measurements were made with over night cell cultures diluted to the same cell density. In the LEDrig there are 16 different LEDs but also many additional wells that can be used for control samples. That way, we can ensure identical conditions between our test and control samples. We always used two controls: blue chromoprotein BioBrick (<a href="http://parts.igem.org/Part:BBa_K592009">BBa_K592009</a>) without a promoter as the negative control and constitutive GFP generator from Measurement Interlabs study (<a href="http://parts.igem.org/Part:BBa_I20260">BBa_I20260</a>) as the positive control. All experiments were carried out in <em>E. coli</em> Top10 strain.
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     </p>
     <p>
     <p>
         Our LED rig is controlled with programmable Arduino Nano computer. <strong>**Link the script file</strong>. The light intensity parameters vary between 0 and 4095 where 0 corresponds to the dark state and 4095 the maximal intensity. The observed light intensity, however, was logarithmically dependent on the intensity parameter. Thus, having equispaced intensity paramters for the LEDs led to biased distribution of light. Almost all the LEDs were very bright. To get equal difference in the LED intensities, we set the parameters linearly according to the log<sub>10</sub> of the intensity parameter value. In other words, the intesity of the LED lights was proportional to the log<sub>10</sub> of the intensity parameter.
         Our LED rig is controlled with programmable Arduino Nano computer. <strong>**Link the script file</strong>. The light intensity parameters vary between 0 and 4095 where 0 corresponds to the dark state and 4095 the maximal intensity. The observed light intensity, however, was logarithmically dependent on the intensity parameter. Thus, having equispaced intensity paramters for the LEDs led to biased distribution of light. Almost all the LEDs were very bright. To get equal difference in the LED intensities, we set the parameters linearly according to the log<sub>10</sub> of the intensity parameter value. In other words, the intesity of the LED lights was proportional to the log<sub>10</sub> of the intensity parameter.
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    <h4>Choosing the correct parameters</h4>
     <p>
     <p>
         Cormack <em>et al</em>., (1996) reported the wavelengths of green fluorescent protein mutant 3 to be the following
         Cormack <em>et al</em>., (1996) reported the wavelengths of green fluorescent protein mutant 3 to be the following
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             <img src="https://static.igem.org/mediawiki/2014/4/48/Aaltohelsinki_sample_vs_positive.png" class="img-responsive" ref="samplevspositive"></img>
             <img src="https://static.igem.org/mediawiki/2014/4/48/Aaltohelsinki_sample_vs_positive.png" class="img-responsive" ref="samplevspositive"></img>
             <p class="kuvateksti">
             <p class="kuvateksti">
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                 <b><span ref="samplevspositive">.</span></b>: GFP fluorescence of our light response element compared to the positive control. The 3D plot with respect to time, fluorescence and intensity shows the difference in fluorescence between our sample and the constant GFP producing strain (TOP10 transformed with Measurement Interlabs plasmid with <a href="http://parts.igem.org/Part:BBa_I20260">BBa_I20260</a>). The times indicated are times of the day, not incubation times.
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                 <b><span ref="samplevspositive">.</span></b>: GFP fluorescence of our light response element compared to the positive control. The 3D plot with respect to time, fluorescence and intensity shows the difference in fluorescence between our sample and the constant GFP producing strain (Top10 transformed with Measurement Interlabs plasmid with <a href="http://parts.igem.org/Part:BBa_I20260">BBa_I20260</a>). The times indicated are times of the day, not incubation times.
             </p>
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Revision as of 17:34, 11 October 2014

Research

We engineered a three-channel switch that allows you to choose which of its three genes is active. The switch is designed so that the user can define the expressed genes independently.

The Three-Channel Switch

Introduction

We engineered a three-channel switch that can be controlled with the intensity of blue light. By utilizing the mechanisms of lambda (λ) repressor and linking it to a blue light sensor protein, we would be able to swiftly switch between the expressions of three different genes. This mechanism could provide a nearly real-time control over the chosen genes, which could advance a variety of industrial bioprocesses, speed up research projects and benefit metabolic engineering. The switch has a modular structure, and thus, the users can decide the genes themselves without needing to modify the actual mechanism at all.

Previously gene regulation was controlled by chemical effectors, such as tetracycline and IPTG. In many cultures, a constat and uniform level of concentration is hard to maintain as the chemicals get absorbed, degraded and modified by the cells and environment. Moreover, export of these chemicals is hard and time consuming or even impossible and the response time is limited by the rate of chemical addition and diffusion. On top of all, the effector chemicals may even be toxic or bind unknown receptors leading to unwanted effects in the culture. (Schmidl et al., 2014)

Light signals, on the other hand, are non-toxic and we have full control over it: it is very easy to increase and decrease the light intensity. In many cases, light is orthogonal signal that is does not affect to the indigenous cell mechanisms and pathways. Such is the case in for ecample E. coli. We are also able to target light very specifically to single colonies or even single cells allowing unprecedented accuracy. This allows very precise spatial and temporal control over the light signal. And lastly, the light signals can be emitted using LEDs which are widely available, durable and very inexpensive even in a large scale.

Features

We chose YF1 fusion protein as the light receptor protein. The receptor autophosphorylates in darkness but in blue light, it is unphosphorylated. A phosphorylated YF1 protein acts as a kinase and activates FixJ transcription factor, which can then bind to a FixK2 binding site and activate the production of λ repressor protein CI. The kinase activity of YF1 is inversely proportional to blue light intensity and the effect is carried on to the acitve FixJ concentration. Thus, CI protein is not produced in bright blue light but the production increases when the blue light is dimmed down.

We used lambda repressor protein CI to regulate the genes in the switch. Only gene A is active when there is no repressor protein CI. At medium concentrations of CI, gene A becomes deactivated and gene B is activated. At high concentrations of CI, only gene C is active. The activity and deactivity of the gene C is based on tetracycline repressor protein that is produced with genes A and B. When neither of those genes are active, gene C is activated. The activities of genes A and B are controlled with an interesting mechanism of lambda repressor, which is explained thoroughly under the background title on this page.

So, to put it all together, in blue light the switch activates gene A, in dim blue light gene B, and in darkness gene C. The image illustrates this functionality.

In blue light the switch activates gene A, in dim blue light gene B, and in darkness gene C. The changes are based on differences in the concentration of the λ repressor protein CI.

Glossary

  • YF1 fusion protein = blue-light sensor that becomes unphosphorylated in blue light and phosphorylated (activated) in darkness
  • FixJ protein = after being phosphorylated by YF1, this activates promoter FixK2
  • FixK2 binding site = activates the production of CI when FixJ binds to it
  • lambda (λ) repressor protein CI = a protein that can repress and/or activate the transcription of two different genes
  • OR tripartite operator site = an operator site to which CI binds, downstream from OL in λ phage
  • OL tripartite operator site = and operator site to which CI binds, upstream from OR in λ phage
  • PRM promoter = a promoter that is active only when there’s no CI protein
  • PR promoter = a promoter that is active only when there’s little CI protein, too much or too little inhibit the production
  • genes A-C = the three genes that you could insert to our system and they would be expressed as explained here
  • Tetracycline repressor protein TetR = can bind to TetR repressible promoter sites and inhibit gene transcription

Background

Developing Our Idea

In the beginning of our project, from March 2013, we focused solely on coming up with new ideas for the project, building the public team website and applying for Summer of Startups 2014 and foundations with deadlines in spring. In our team meetings, we had different types of brainstorming sessions where all of us could present even the craziest ideas. We founded a shared folder where anybody could write down new ideas. We came up with disco bacteria that glow in sync with music, new kinds of bacterial drinks that change flavour with storing temperature, remote controllable bacteria, oil-eating bacteria, tooth paste bacteria that keeps up the mouth hygiene despite forgetting to brush the teeth, etc. On a Friday evening we had a vote and everybody gave a score from 1 to 5 for each idea. We made an idea gradient where the ideas were ranked according to the score from bottom left to top right.

This is the amazing post-it idea gradient that we made.

We chose the top 5 ideas and presented them to our advisors and researchers from Aalto University, VTT and University of Helsinki to get feedback and comment on the feasibility. After all, none of us had never done anything even close to this before. As a result of this feedback, further idea development and admission to Summer of Startups, we decided to work on the idea with a project name "nest box." It's a container resembling a traditional Finnish nest box but it includes bacteria producing different fragrances. These bacteria could be controlled using light concealed inside the box. The user can decide which fragrance to produce by a press of a button and this action would be translated into light signal to control the gene expression in the bacteria. Such a system is concrete and understandable for the public audience and it would help to build a positive image of synthetic biology in Finland. In theory, such system could be used in conference rooms, hotels, living rooms, saunas, movie theaters... The scent marketing is an expanding business and our idea had the potential to add something new to it. Furthermore, it was a concrete product which made our participation in Summer of Startups a lot easier.

We started our BioBrick learning practice project mid May and Summer of Startups early June. As we got forward, we realized that our idea is not very realistic. Implementation of such a separate unmaintained container would be very challenging and in addition, we cannot bring genetically modified bacteria outside laboratory conditions (it's defined in the gene technology legislation). We decided to solely focus on one element of our nest box idea. Constructing the interface between the bacteria and the user or a computer is not trivial. So, we redefined our direction which was maintained to the end. We wanted to develop a three channel switch that would allow us to activate one of the three genes at a time using only the intensity of single wavelength light. We could then connect this switch with fragrance producing genes, for example.

Earlier Research

Optical control over molecular interactions has been harnessed in metabolic signaling, dimerization systems and light activated adrenergic receptors and neuronal ion channels. Most importantly in terms of synthetic biology we can now regulate transcription with light. One of the foundational papers were written in 2005 by Levskaya et al. Synthetic biology: engineering Escherichia coli to see light. Since then, many different light sensors and light regulators have been built. This toolbox enables more precise spatial and temporal control over the synthetic biological systems. Hence, light regulation has been part of many iGEM projects. Light sensors are arguably one of the most important elements in controlling gene expression in synthetic biology. In contrast to chemicals, we have full control over light intensity.

The applications in previous iGEM teams include communication, kill switches and metabolic engineering, among many others. Previous teams have been very active in making BioBricks out of new light sensors published in research. Uppsala 2011 team designed a multichromatic light sensor system which regulates three independent genes. In their project the used blue, green and red light sensors and linked them to different chromoproteins. This way, different light signals produce different colors in bacteria. They added many useful BioBricks to the registry which has made also our project more feasible.

STJU BioX Shanghai 2013 team aimed to create a universal system to regulate genomic genes using blue, red and green light and CRISPR and dCas9 protein. Their fundamental idea is to regulate production of sgRNA with different wavelengths. This would enable regulation of three different genomic genes within the chromosome presumably independently of each other. Switching the regulatory targets would be done by changing the sgRNAs. The Shanghai team also built a box with computer controlled LEDs of all three different color. In addition, they shared the software as well as the instructions how to build such a light regulation box. This was very interesting project as we built a light regulation system for three genes using LEDs and a microcontroller. STJU BioX Shanghai gave some inspiration to our LED control system.

Interestingly, also Freiburg 2013 team made a universal regulatory system using CRISPR and dCas9 protein but they targeted mammalian cells. In their concept, dCas9 is guided to the site and the function to be carried out can be chosen remotely using different wavelengths of light. The effector either activates or represses the target gene or methylates a histone tail affecting the histone code at the site. The three effectors: repressor (KRAB), activator (VP16) and methyltransferase (G9a), can be controlled with red, blue and UV light. Such system would be able to regulate the target genes remotely in diverse ways.

Maybe the most interesting research group in this field is Jeffey Tabor's group. On their website they write: "We program living cells to sense, compute, and respond to information in their environments. Our programmable cells have applications in basic science, industry, and medicine." (http://www.taborlab.rice.edu/home, 5.20.2014). They have been involved in developing new light sensors, including CcaS/CcaR and Cph8. They also constructed a multichromatic gene regulation system combining both these receptors. In a very recent paper (Schmidl et al., 2014) they re-engineered Cph8 and CcaS/CcaR sensors to reduce cross-talk and leakiness and to increase the dynamic range.

Our setup was heavily inspired by Tabor lab. In their experiments they perform light exposure to bacterial cultures using a Light Tube Array, LTA. The LTA consists of 64 individually exposable slots for tubes and it can be placed inside an incubator in order to gather big amounts of data with precise control. Very little technical data was available of the rig hardware, so we designed our own. They still work using the same principles. Their rig is naturally much better calibrated than ours. They precondition the cultures with a "staggered start", which assures similar starting conditions for each tube (Olson et al., 2014, Supplementary Note 1). We did not perform this kind of starting procedure, but all our cultures were grown in the dark in similar conditions to minimize the different starting conditions.

Possible additional considerations that sould be taken into account when handling our data is that our rig runs of batteries. The depletion of the batteries results in lower power supply, although this should be covered to some extent by the on-board voltage regulator. Also tabor labs point out that newly produced fluorescence proteins do not exhibit a fluorescence signature until maturation has completed (Olson et al., 2014, Supplementary Note 2). This means that the actual fluorescence measured does not represent exactly the protein concentration. Their approach was to do a "post treatement" for the grown cultures to ensure protein maturation. We entirely ignored this procedure, mainly due to time concerns and the possible mis-exposure that could occur during such treatment.

In contrast to the previous research, our system attempts to regulate multiple targets with only one wavelenght of light. In the paper by Tabor et al. (2011) they say: "The development of multichromatic gene regulatory systems, where different light wavelengths regulate the expression of different genes, will allow more advanced control of synthetic and natural gene regulatory networks." Whereas we completely agree with that, we also claim if we're able to use single wavelengths more efficiently, we could achieve even greater level of control of the synthetic gene regulatory networks.

In Search of the Perfect Light Sensing System

First of all, to be able to control gene expression with light, we needed a light receptor protein. It would react to certain wavelength of light and mediate the signal to the DNA level and initiate the response. We found different alternatives in the iGEM registry but most of them were not properly characterized. We could not find reliable experiences of the use of such light receptors or, when we found them, the receptor protein was not available. Our requirements for the light receptor system were following: 1) it has worked for other iGEM teams 2) it should work in E. coli 3) it is available in the registry 4) it does not require any cofactors or special strains 5) short response time and sensitivity. In this section, we discuss about the different alternatives we found and what made us choose the YF1 protein. We also introduce the mechanism how the light signal is conveyed in our system.

Phytochrome interacting factors (PIF's) were used by some previous iGEM teams, including Freiburg 2013 and TU Munich 2012. The actual red light sensing protein is called Phytochrome B and in the active form it binds to the PIF (BBa_K1150005 or BBa_K365000). Thus, the cell also needs to express Phytochrome B. However, these PIFs were derived from Arabidopsis thaliana, which is an eukaryotic organism. Moreover, the response mechanism would require fusing the two proteins to the actual DNA binding domain and transcription factor. Unfortunately, Freiburg team only succeeded in 1.3 fold induction of gene expression after 48 hours of incubation in red light and TU Munich did not manage to implement the light sensing part in their kill switch.

The Peking 2012 team designed an ultra-sensitive light sensor for luminescence. They combined a LOV domain, a dimerizing domain and a DNA-binding LexA domain. Such protein becomes active when the cells are illuminated with 440 - 480 nm light. In active form, the dimerizing domains facilitate formation of LexA dimer which is able to bind DNA and repress transcription in only such form. Whereas their light sensing system seems to work very well there were three issues with it. Firstly, their light sensing system was not available and secondly, it might have been too sensitive; controlling the light at very low intensities could be rather challenging. Furthermore, LexA is a part of SOS system already part of E. coli so it might interfere with indigenous E. coli genes. However, according to Peking 2012, mutated version of LexA could solve this problem.

Cph8 (BBa_I15010) is a fusion of Cph1 red photoreceptor domain (660nm) and EnvZ histidine kinase domain. In absence of red light, EnvZ is active and it phosphorylates endogenous OmpR which in trun activates OmpC promoter (BBa_R0082). Red light activates Cph1 which inhbits EnvZ kinase domain function. However, as both EnvZ, OmpR and OmpC are endogenous in E. coli, reliable use would require EnvZ deficient strain. The activation Cph1 requires Phycocyanobilin which can be produced with heme oxygenase (BBa_I15008) and ferrodoxin oxidoreductase (BBa_I15009). The Cph8 was decribed by Levskaya et al. (2005) and they achieved nearly 10-fold induction. However, as EnvZ and OmpR are involved in indigenous osmolarity response, phosphorylated OmpR might also interfere with promoters encoding membrane porins.

CcaS (BBa_K592001) is a cyanobacteriochrome that gets activated by autophosphorylation. This is upregulated by green light (535nm). The activated CcaS phosphorylates its response regulator CCaR ( BBa_K592002) which then induces the promoter PcpcG2 (Hirose et al., 2008; Tabor et al., 2011). As Cph8 system, this light receptor also requires Phycocyanobilin to function. In addition, CcaS is inactivated in red light (672nm) allowing higher degree of control and fast response times. According to the experiments by Tabor et al. (2011), the promoter PcpcG2 showed only 2-fold induction in green light. The transcription response is somewhat linear to the light intensity of 0.01 W/m2 after which is rapidly saturates. Although CcaR and CcaS BioBricks are indeed available although the experiences of other iGEM teams were very few and poorly described.

YF1 Light Sensor

YF1 (BBa_K592004) is an engineered blue light (previous experiments in 430nm) sensor protein that consists of two initially separate domains, LOV domain (sensory domain) from YtvA and histidine kinase domain (effector domain) from FixL. This fusionprotein was designed and constructed by Möglich et al. (2009). YF1, nor it's precursors, do not exist naturally in E. coli nor reportedly interfere with indigenous E. coli genes but according to Möglich et al. (2009) the sensor works well in E. coli: it's capable of 70-fold supression of the target promoter when illuminated with blue light. The sensor does not require additional, foreign molecules in order to get activated by blue light. The gene is only 1132 bp long and it has been used by previous iGEM teams, including Uppsala 2011, STJU BioX Shanghai and Tokyo NoKoGen. Thus, we evaluated YF1 to be the most suitable for our three channel switch.

Based on the work of Möglich et al. (2009) we describe the mechanism of YF1 blue light sensor in greater detail. YF1 is a water soluble chimeric fusionprotein that contains two domains linked together with a Jα linker sequence. The N terminal domain is a flavin nucleotide binding LOV domain (light-oxygen-voltage, a sub group of PAS sensor domains) from Bacillus subtilis YtvA. This domain incorporates noncovalently flavin mononucleotide and blue light facilitates formation of a covalent bond with a cysteine residue of the LOV domain. This induces a conformational change in this light sensory domain.

The C terminal domain of YF1 is a histidine kinase, the FixL effector domain from Bradyrhizobium japonicum. The original protein, FixL, is involved in regulating the nitrate respiration and nitrate fixation. The histidine kinase functions only when it is phosphorylated. It has autophosphorylation activity that is regulated by the sensor domain. Autophosphorylated histidine kinase activates a FixJ (BBa_K592005) response regulator by transferring a phosphoryl group. However, when the histidine kinase domain is unphosphorylated, it has actually phosphatase activity for the response regulator. Phosphorylated FixJ binds to FixK2 promoter (BBa_K592006) initiating the expression of the corresponding genes. This system should be completely orthogonal in E. coli.

Möglich et al. (2009) proposed that the YF1 proteins form dimers. This would also bring the histdine kinase domains close to each other. It is proposed that the autophosphorylation actually work in trans within the dimer. They hypothesized the Jα helix linker to form a coiled coil with another YF1 protein. The linker would mediate the signal from the sensor domain to the effector domain inhibiting/enabling its kinase activity. The conformational change from the incorporated flavin domain is suggested to rotate the linker helix. The relative angle of the two domains greatly affect to the mechanism. If we add one amino acid to the Jα linker, the relative angle changes and the effect of the sensor domain is inverted: in presence of light the histidine kinase is active but in darkness, it is inactive. This presents interesting approaches and easy solution to invert the YF1 signal.

In our three channel switch, we fused a CI protein to the Bradyrhizobium japonicum FixK2 promoter. Thus, in the absence of blue light (470nm in our experiments), the angle between YF1 domains autophosphorylation of histidine kinase of YF1, which then transfers a phosphoryl group to FixJ activating it. The P-FixJ in binds to FixK2 promoter activating the CI transcription. The role of this CI protein in our switch is described in the next section.

Lambda (λ) Repressor

Lambda repressor plays a crucial role in our switch. The repressor is part of the lambda phage and it regulates the lysogenic an lytic states of the virus. The lambda phage genetic material can be integrated in the host genome as prophage. This phase is called lysogenic cycle and during that state, the host cell can proliferate and function normally. However, in lytic cycle the phage genetic material is separate from the host genome and it is hevily expressed to produce more viruses which eventually lyse the host cell (hence the name). Lambda repressor is the region in the lambda phage that is responsible for regulating the current state in infected host. This phage has some very interesting characteristics that are described in this subsection.

In the center of the lambda repressor there is a lambda repressor protein CI (BBa_K105004). This protein represses the genes in the lytic cycle and maintains the lysogenic state. Moreover, this protein is autoregulated in a very special manner. CI dimerizes and binds into its own promoter (PRM) upregulating its own production. However, in high concentrations, CI represses its production maintaining it on an appropriate level. Dimerized CI represses a lytic cycle transcription factor Cro by bindig to operator regions before PR. The lambda phage changes the state from lysogenic cycle to lytic cycle (i.e. lysogenic induction) when the host is exposed to DNA damaging factors, such as UV light. The damage activates the SOS reponse and production of RecA protein involved in repair and maintenance of DNA. RecA has protease activity and it cleaves CI resulting in drop of CI dimer concentration, derepression of Cro and lysogenic induction. Dodd et al (2001) showed that the concentration of CI affects the capability for lysogenic induction. Thus, it is important that lambda phage maintains the CI concentration in sepcific frame in order to be able to switch to lytic cycle when the opportunity arises. High concentration ledads to inability of lysogenic induction whereas low concentration results in too high induction sensitivity.

The interaction of CI protein and lambda repressor promoters is well illustrated in the figure (Dodd et al. 2001). The repressor region consists of two promoters, PRM and PR separated by common operator sites (OR 1, 2 and 3). The CI protein dimers bind DNA in these three operator sites. Johnson et al. (1979) showed that CI binds cooperatively on the three operator sites. The OR1 has the highest affinity for the CI dimer which recruits another dimer to OR2 site. This blocks the transcription of the PR promoter and activates PRM promoter blocking Cro production and activating CI production, respectively. Bell et al. (2000) suggested that these CI dimers at the two operator sites form a tetramer. Very similar interaction is observed between two of the three OL operator sites which are located 2,4kb away from OR operator. It was early that CI also binds to OR3 and OL3 sites, but in substantially higher CI concentrations (Johnson et al., 1979). This leads to repression of PRM promoter. Maurer et al. (1980) showed that 50% repression of PRM requires 15 times the normal lysogenic concentration. However, the mechanism of PRM repression is not result of only CI dimer binding in the OR3 site.

Dodd et al. (2001) showed that two tetramers at OL and OR sites form an octamer by looping the DNA. They proposed that this DNA looping juxtaposes OR3 and OL3 sites and allows them to be linked by a CI tetramer. This, in turn, would silence the PRM promoter. Thus, the lambda repressor has three different states regulated by CI concentration: lytic (low CI concentration, PR is active and PRM is inactive), lysogenic (moderate CI concentration, PR is inactive and PRM is active) and repressing lysogenic (high CI concentration, PR is inactive and PRM is inactive). This is the underlying principle of our three-channel switch. In our approach, we regulate the CI concentration with blue light intensity and replace the Cro and CI with other genes of interest. This way, we are able to use the characteristics of lambda repressor to construct the mechanism behind the three-channel switch.

Hypotheses

The very first and critical assumption is that the concentration of CI would be controlled by light when it is put behind FixK2 promoter. Moreover, we assume that this effect will be more or less linear on the relevant region so that double light intensity leads eventually to double concentration. It is also very crucial that FixK2 promoter does not show significant leaky expression in absence of phosphorylated FixJ. We need to be able to keep CI concentration low enough to keep PR promoter active in presence of strong blue light.

To better match the BioBrick standards and the idea about being able to ligate BioBricks together as is, we wanted to make our promoters unidirectional. The PRM and PR promoters, however, point to opposite directions. This would require flipping the BioBricks added to the preceding strand or using reverse complement BioBricks. This would not be very convenient. Hence, we make a duplication of the OR sites, one coupled with PRM and the other connected to PR promoter. We suggest we are able to repress PR promoter and activate PR promoter with CI dimers despite this duplication.

The third hypothesis is related to the DNA looping as a result of CI octamerization at the operator sites. Originally, DNA looping takes place between OR and OL sites by octamerization of CI dimers bound to operator sites 1 and 2 ab both locations. As OR and OL regions resemble each other in terms of CI affinity and as the interacting factor seems to be CI and not the DNA sequence, we hypothesize that OL could be replaced by OR region without losing the DNA looping capability. This would also underline the significance of the previous assumption: as we have duplicated the OR sites we already have the hypotetical factors required for DNA looping and PRM repression. Therefore, if we duplicate the OR region and separate them with correct number of bases, we might be able to form the DNA loop between these regions without having a OL region.

The lambda repressor functions in lambda profage when the virus is in the lysogenic state. This means the lambda repressor is integrated as a part of the genome. It has been shown that the DNA looping takes place in the infected E. coli cells. However, we have not found evidence that this would happen also in the plasmids containing the lambda repressor region. It is possible the supercoiled structure of the plasmid prevents the normal function of the lambda repressor. We have identified three possible scenarios. Firstly, the lambda repressor could function within the plasmid as is. Alternatively, the loop size formed by lambda repressor may be changed or it may be easier or more difficult to be formed but it may work with some modifications. The worst scenario is that the lambda repressor does not work at all in the plasmid context. In such case, our three channel switch could be integrater to the E. coli genome.

Lastly, we made some hypotheses regarding CI concentration. The wild type CI half life has been measured to be longer than 10 hours (Parsell et al., 1990). This would mean that it takes very long time to reduce the CI concentration that is, switch back from the channel C in our system. However, we can fuse an ssrA tag to the protein an target it for faster degradation within the cell. According to Keiler et al. (1996), such tagging can reduce the half life to 4 minutes. Hence, we used LVA tagged version of CI lambda repressor protein (BBa_K327018). This enables much shorter reaction time and nearly real-time control of CI concentration. However, it also lowers the highest possible concentration of CI. We hypothesize, that using strong enough promoter, we can reach sufficient CI concentrations for PRM repression.

Parts

/parts-lista-igem-template-säätö/

The final construct ended up being fairly large. The gene circuit consists of two different segments: the light sensor that produces CI according to the intensity of light and the actual switch that responds to the differences in the concentration of repressor protein CI.

We used fairly many already existing parts that were in the 2014 iGEM BioBrick Distribution. The parts we created ourselves are /mitä me nyt saadaan lähetettyä/. /selitystä kustakin partista ja että mitä se tekee/.

Here’s a list of all the parts we used in our gene switch. They are in the same order as in our gene circuit and each of them is color coded as follows: /hienot värikoodisysteemit/. /makee luettelo niistä brickeistä/.

This is the complete sequence that we put together. The color codes are the same as in the previous list. Gene A has 20 Xs as placeholders, gene B has 20 Xs and gene C has 20 Xs. As anyone could decide the genes themselves, the placeholders are just to show the correct place in the sequence.

In addition to these parts, we also used a GFP part for testing the response times of YF1. /ja mitä muuta nyt ollaankaan testailtu/

This is our gene circuit. The upper part is the light sensing segment that produces the CI protein and the lower part reacts to differences in the CI concentration and switches the gene channel. The turquoise arrows are promoters, the turquoise circles are operator sites, the light blue circles are ribosome binding sites, the gray squares are expressed genes. The promoter of YF1 gene can be any constitutive promoter.

Our Research Methods

LED Rig

To be able to expose our bacteria to light in a controlled manner, we designed a new kind of device from scratch. Inspired by the LTA developed by Tabor lab 1 we decided to build a simpler one, only with blue LED:s.

Luckily we had some electronic knowledge in our team, too. With Pietu designing the rig we built a foam-padded transportable rig that can be put in an incubator overnight.

Pietu presents the great LED rig.

Microcontroller

The core of the rig is an Arduino Nanomicrocontroller. The Arduino is responsible for the logic behind our illumination patterns.

The patterns in our experiments are fairly simple and could in theory be done without the Arduino, but we chose to use it due to its wide popularity and because we now could make advanced (and cool) animations on our rig. Also the Arduino acts as a 5v voltage regulator which provides the voltage for the second part of the rig: the Adafruit 16-channel 16-bit PWM controller.

LEDs

Light Emitting Diodes(LEDs) are current controlled components, and their intensity depends on the current passing trought them. In our project we used miniature leds because of their small power and small heat generation. It is important that the LED:s wont heat up the bacteria remarkably.

Controlling the intensity of these leds is trivial by varying the current, but this will cause the emission spectra to shift (Muthu et al., 2002). Hence we choose a different, and very popular, method for varying LED intensity: Pulse Width Modulation (PWM). The idea behind PWM is to turn the led on and off very in very short interval, up to frequencies of 1.6kHz. By varying the time the led is on and off we will be able to make a percieved difference in intensity. The bigger the ratio of on-time versus off-time the brighter the LED.

Due to the hurry of making this rig we chose to use a pre-made Arduino "shield" for this task. We chose the a 16-channel 16-bit PWM shield from Adafruit. The 16-bits provide us much more range than the standard 8-bits of the Arduino. Additionally the Nano does not support as many channels so having 16 LEDs provides more flexibility in our measurements.

Constructing

We wanted to be able to illuminante a bacterial culture with a single led at multiple different intensities. We choose to grow our bacteria on microtiter plates. This choice was also affected by the fact that we had an access to a fluorometer (Thermo Scientific Varioskan) that measures fluorescence out of such microtiter plates.

We designed our LED rig so that an unmodified 96 well microtiter plate with the test cultures can be easily inerted. Our LEDs are attached to a lid that can be placed on a standard microtiter plate. 16 LEDs will illuminate the wells on columns 11,9,7,5 and rows B, D, F, H.

Our LEDs' spectrum peak at the value of 470nm. This value is specified by the manufacturer but the spectra of individual leds can vary considerably. Therefore we will measure the spectra of our LED:s with a spectrophotometer to be sure of the excitation wavelength.

The Arduino source code used for the measurements is available on our github pages, and is discussed below.

Calibration of our device has not been done yet. We have yet to measure the LED intensity. TODO: calibration

Technical details

  • Arduino Nano microcontroller, http://arduino.cc/en/Main/arduinoBoardNano
  • Adafruit 16-channel PWM shield, https://learn.adafruit.com/adafruit-16-channel-pwm-slash-servo-shield?view=all
  • http://www.thermoscientific.com/content/tfs/en/product/varioskan-flash-multimode-reader.html

Fluorescence measurements

Fluorescence measurements were carried out in Thermo Scientific Varioskan. It is a microtiter plate reader capable of exitation and measuring the corresponding fluorsecense at user defined wavelengths. All measurements were made with over night cell cultures diluted to the same cell density. In the LEDrig there are 16 different LEDs but also many additional wells that can be used for control samples. That way, we can ensure identical conditions between our test and control samples. We always used two controls: blue chromoprotein BioBrick (BBa_K592009) without a promoter as the negative control and constitutive GFP generator from Measurement Interlabs study (BBa_I20260) as the positive control. All experiments were carried out in E. coli Top10 strain.

Our LED rig is controlled with programmable Arduino Nano computer. **Link the script file. The light intensity parameters vary between 0 and 4095 where 0 corresponds to the dark state and 4095 the maximal intensity. The observed light intensity, however, was logarithmically dependent on the intensity parameter. Thus, having equispaced intensity paramters for the LEDs led to biased distribution of light. Almost all the LEDs were very bright. To get equal difference in the LED intensities, we set the parameters linearly according to the log10 of the intensity parameter value. In other words, the intesity of the LED lights was proportional to the log10 of the intensity parameter.

Choosing the correct parameters

Cormack et al., (1996) reported the wavelengths of green fluorescent protein mutant 3 to be the following

  • Excitation wavelength: 501 nm
  • Emission wavelength: 511 nm

In addition Ashikawa et al., (2011) had used the following parameters in measuring GFP

  • Bandwidth: 12 nm
  • Measurement time: 500 ms

We tried measuring GFP using the parameters provided by Cormack et al., (1996) and Ashikawa et al., (2011), but we got strange results. We assumed that that this was because the excitation and emission wavelengths were so close to each other. Therefore we decided to change the excitation wavelength to 470 nm, as it seemed to be another peak of excitation for GFP mut 3 according to Cormack et al., (1996) (). For the same reason we also tried a narrower bandwidth of 5 nm, which is the other option available on Varioskan.

. Excitation and emission spectra for wild type and mutant GFPs. (A) Excitation spectra (emission 540 nm). Excitation maxima: wt GFP 395 nm, GFP mut 1 488 nm, GFP mut 2 481 nm and GFP mut 3 501 nm. (B) Emission spectra (excitation 395 nm for wild type and 450 nm for mutant types). Emission maxima: wt GFP 508 nm, GFP mut 1 507 nm, GFP mut 2 507 nm and GFP mut 3 511 nm.

In the end we settled for the following:

  • Excitation wavelength: 470 nm
  • Emission wavelength: 511 nm
  • Bandwidth: 5nm
  • Measurement time: 500 ms

With the chosen values we got sensible results and our blank samples gave practically zero emission.

Results

GFP fluorescence in high OD600 under different light intensities

In this experiment, we measured how cells will react to different intensities of blue light when grown in same conditions and very high cell density. In such conditions, the cells are not able to proliferate in a way that would affect to the measurements in short time period. This was the first experiment using different intensities of LED lights at 470 nm wavelength. Our purpose was to find out, how cells would respond to light in steady and high cell density and does the previous conditions affect to the fluorescence during a long time period. In addition, we were to observe the relative change between the highest and the lowest level of fluorescence. We had two kinds of samples: bacteria grown (overnight culture at 37C) in the darkness and in lit environment (usual lab lightning in addition to desk lamp directed to our sample). We also had a negative and a positive control for the fluorescence measurements.

We constructed a testing device in order to estimate the concentration and the dynamics of the CI concentration. In the desting device, we replaced CI encoding sequence with GFP encoding sequence. The GFP was fused with LVA degradation tag. We excluded the lambda repressor and gene C parts. As a result, our testing device consisted of a blue light sensing element (constitutive promoter (BBa_J23115), RBS-YF1-RBS-FixJ (BBa_K592016) and a double terminator (BBa_B0015)) and the testing element (FixK2 promoter (BBa_K592006), RBS (BBa_B0034), GFP-LVA (BBa_K082003) and double terminator (BBa_B0015).

At first, all the samples were diluted to OD600 2,4. They were inserted to different wells on microtiter plates, where control samples both were incubated in dark at two different wells each, and dark and light samples were incubated in 9 different intensities of blue 470 nm light (). The first measurements were taken after 4 hours of incubation and a second mesurement was taken after 23 hours of incubation. Both incubations had the temperature at 37 C and shaking 200 rpm.

Intensity parameter 4095 1582 650 290 120 40 10 1
log10 3.612 3.199 2.813 2.463 2.082 1.612 1.041 0.301 0.0

.: Different light intensity parameters and corresponding log10 values used in this experiment.

.: GFP fluorescence of light and dark sample after 4 hours of incubation in different blue light intensities. Control samples were measured only in darkness. Positive control value (101,5) was excluded from the picture to preserve resolution.

.: GFP fluorescence of light and dark sample after 23 hours of incubation in different blue light intensities. Control samples were measured only in darkness. Positive control value (176,9) was excluded from the picture to preserve resolution.

From both figures we can make speculation that bacteria grown in darkness are more fluoreschent compared to the light cultures. This may be because of many different reasons. One possible explanation is that the bacteria have simply accumulated GFP during the preceding over night incubation. Therefore, all measurement points for dark cultures would be shifted to higher level of fluorescent. However, we also know that the GFP-LVA fusion half life, around 40 minutes (Andersen et al., 1998), is rather short compared to the time period. Thus, such higher GFP concentrations should fade over time and settle close to the actual production rate. These figures suggest that long term elevation of GFP production might take place in our system. We would need further experiments to verify this.

When we observe the , we see a clear descending trend in the fluorescence towards higher intensities of light. This suggests that the bacteria indeed alter the rate of GFP production in response to the light even in very high cell densities. The brighter the light, the lower the GFP production and hence, the lower the fluorescence. The difference between bright light and darkness seems to be 1.5-2 fold. However, this effect could also be a result of the LED lights heating up the bacterial cultures and inhibiting proliferation and thus, leading to lower total GFP amount even if the per cell concentration would be constant. We also observe leaky production of GFP even in the bright light when we compare the fluorescence to the negative control strains without a GFP gene.

When compared to the 4 hour measurements, the does not have such a clear trend as in the . However, we also notice that the fluorescence values vary greatly and they are clearly lower compared to the values after 4 hours of incubation. This suggests that the response to the light stimuli is not as strong after long incubation and that the linear dependency on the light intensity seems to disappear. We must also take into account the length of the incubation with the original OD600 of the cell culture. After such a long time in high cell density without adding fresh media will inherently lead to low wellfare, low transcription and protein synthesis rate and poor response to the light stimuli. In other words, the 23 hour incubation is clearly too long and leads to bad sample quality.

GFP fluorescence of our light response element compared to constitutive GFP production strain and non-fluorescent strain

We designed new experiments based on the previous results. First of all, we need to address how positive and negative control respond to light. We need to address the possibility that some of the effects are due to warming effects of the LED lights. Moreover, we need to measure the light response in bacterial cultures in logarithmic growth state with lower cell density.

We prepared three different samples (light response element, positive control and negative control) and placed them under five different intensities of blue light (). The lowest intensity is actually a well without a led light, that is, darkness. However, we designate this intesity with parameter value of 1 instead of zero (which would translate to -infinity on the logarithmic scale). We had duplicate samples of our light response element and we measured the their average fluorescence in this experiment.

Intensity parameter 1 10 256 1024 4095
log10 0.0 1.0 2.41 3.01 3.61

.: Different light intensity parameters and corresponding log10 values used in this experiment.

We aimed to measure the GFP fluorescence regularly, every one hour throughout the experiment. The experiments lasted for approximately six hours yielding six different time points. This means 30 datapoints per sample. However, as the measurement device was reserved at times, the timepoints are not exactly regular. In addition, we noticed that between our 4th and 5th measurement, the batteries of our LEDrig had died and the LED intensities had all dimmed significantly. At this point, the batteries were immediately changed to fully charged ones.

.: GFP fluorescence of our light response element at different intensities in different times (upper figure). The intensity is a 10 base logarithm of the parameter values given in and the fluorescence is an average of two different samples. Negative control has calculated as the average of all the time points at the given intensity. The legend is in the figure below. The positive control is in the and the intensity values in the . The times indicated are times of the day, not incubation times.

The is very good example of the light response element capabilities. The first measurement is taken right after the dilutions before the incubation in blue light. We notice the fluorescence is constant for each sample (blue line, 10:43). However, already after one hour of incubation (green, 11:53), we can see a clear response effect to incubation in blue light. Bacteria grown in low intensity have a much higher fluorescence level compared to the those grown in high intensity blue light. The difference is over 4 fold. We also note the effect of light intensity to the fluorescence is nearly linear. We also need to take into account that the intensity level 0 is not comparable to the other values as the difference between darkness and very dimm light was hard to evaluate at the logarithmic scale.

When the incubation is continued (red and turqoise), the fluorescence also tend to increase at every point of measurement. The fluorescence at the highest blue light intensity increases but so does the fluorescence at the lowest intensity. In fact, they change at the same rate relative to each other so that the 4 fold difference is maintained. This suggests that this change in fluorescence is caused by the growth of bacteria in the sample leading to a GFP expression multiplied by scalar representing the cell density. In other words, the effect of blue light on the single cell level may be constant after the second measurement. Therefore, the full response to blue light intensity may take place already between the first and second measurement. This would imply very fast response times.

However, we observe a great difference at the 5th timepoint (violet, 15:43) when fluorescence rockets even at higher blue light intensities. This is due to batteries running low in our LEDrig. Interestingly, this incident reveals some very interesting dynamics in our light response element. Clearly, the effect of the batteries running low has emerged after the measurement at 14 o'clock. Our light response element has achieved the same fluorescence values as the samples incubated in dark since the beginning. This has happened in a time shorter than one and half hours which is the time difference between the measurements. As the main component of the fluorescence is GFP-LVA, the samples incubated in bright light have reached the full production capacity when compared to the most fluorescent samples. Moreover, this time has been enough to accumulate GFP long enough to reach seemingly steady state (degradation rate and production rate being equal). Therefore, the response is likely to be a lot shorter than the limiting one and half hours.

The last timepoint also reveals some very interesting features in our response element. As the light intensities were restored after the perturbation we incubated the samples in the original light intensities for 75 minutes prior to doing the last measurement. When we exmine these fluorescence values (orange, 16:49) we can see that the values were restored back to the same level as the measurements before the perturbation. Also the linear dependency and 4 fold fluorescence differences were retained. This means that our system seems to react very fast to increase in the blue light intensity.

Control!

.: GFP fluorescence of our light response element compared to the positive control. The 3D plot with respect to time, fluorescence and intensity shows the difference in fluorescence between our sample and the constant GFP producing strain (Top10 transformed with Measurement Interlabs plasmid with BBa_I20260). The times indicated are times of the day, not incubation times.

One question is still yet to be addressed: does the LEDs interact with heat or is light indeed the mechanism that affects do the fluorescence? Or maybe the blue light interferes straight with GFP inhibiting its fluorescence? To rule out these effects we compare our samples to a positive and neagtive control strains. We observe the effect of the blue light on strain producing GFP at a constant rate and on strain without GFP encoding sequence.

In the , we have plotted average value of negative control strain fluorescence as a function of blue light intensity. The values were averaged over all six timepoints. As we see, the fluorescence levels are clearly lower than any of the measurements with our light response element. Moreover, the value is nearly constant, only decreasing slightly towards higher intensities. This suggests that light intensity has some minor diminishing effects on fluorescence measured at 511 nm. However, these differences are negligible when compared to the differences in fluorescence observed with the light response element. Moreover, this also suggests that the fluorescence levels are clearly elevated even at the highest blue light intensities.

In we have compared our light response element with a strain producing GFP at a constant rate. First of all, we see that the fluorescence levels are on the different level of magnitude. This presumably is due to significantly longer half-life and presumably higher transription rate. This is supported by the fact that the fluorescence accumulates through the time (although the effect is largely contributed by the dividing cells). The main intrest is, however, to compare the effect of blue light to the fluorescence. First of all, we observe inclination to higher fluorescence levels at higher blue light intensities. This is opposing our previous observation with negative control. Moreover, this change is exactly opposite to what is observed in our light response element, which supports our hypothesis. The higher fluorescence may be, among many other possible reasons, result of LEDs heating up the sample a little bit and enabling the cells to proliferate a little bit faster during the measurements carried out in room temperature. We also need to take into account that as we only had on sample, the fluorescence values are subject to fluctuation and we cannot reliably conclude that there would be an increasing trend towards higher intensities in fluorescence of the positive control strain.

Induction dynamics and GFP fluorescence under varying light intensity

Discussion

Mutaatiot operaattorialueisiin Plasmidissa ei DNA:ssa Solutason kohina solusyklissä Results: Possible room for improvement? LED spectrum, power measurements and intensity measurements? Heat production measurements? Red light Phosphorylation transfer Leakiness Non-saturating intensity response

Conclusions

References

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