Difference between revisions of "Team:EPFL/Description"

 
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                        <h2 class="lead animate-box text-center">intelligene</h2>
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                            A new way to design biological circuits
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                          In the world of synthetic biology, it is difficult to not be surrounded by examples of the applications of genetic engineering. After all, anything a cell
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                          does can be traced back to its DNA. Many teams are genetically modifying cells to do amazing things, but rather than work on biosensors or cancer, we decided
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                          we wanted to make a tool that could help everybody modify their cells faster, more predictably, and more powerfully than ever. As a community, we have become
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                          pretty good at modifying cells to incorporate new genes precisely into their genomes, but what if we don’t want to make our cells just produce new proteins or
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                          RNAs? What if we want to make cells that are capable of making new decisions, ones they have never made before? The idea is not so outlandish. After all cells
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                            make decisions based on their surroundings, their health, and their metabolism all the time as signaling cascades modify the expression of their genes. By inserting plasmids with interconnected genetic elements, we can already make these “decision-making” circuits! Currently, these circuits are built using transcription factors, but finding transcription factors appropriate for this application can prove to be quite a challenge. This is because they must work in the host to target promoters in the new circuit, but also be completely orthogonal to the host genome, to not interfere with the cell’s survival.
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                          dCas9 has already been used by a variety of authors to act as a sort of “programmable” transcription factor (“Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system”, Nucl. Acids Res. 2013). Since dCas9 uses a guide RNA to find sequences on the DNA, it can be used to guide transcriptional activators or repressors to their targets. As you will see, this can be used to intuitively make complex transcriptional networks. This summer, we harnessed the power of dCas9 and worked to create a suite of tools to make the creation of synthetic genetic networks easier than ever, saving scientists valuable time and reducing the cost of project development.
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                          To increase the ease of development of new synthetic genetic circuits we also worked on computational tools that aid in their design. Notably, we modified Cello – a program published earlier this year in Science, which automates synthetic genetic network design – to help make it compatible with emerging dCas9-based technologies.
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                          Intelligene is best thought of as a suite of tools, combining aspects of computational biology and synthetic biology to help scientists with new dCas9-based genetic circuits, from their design all the way through to their implementation.
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                        <h2>General idea of the project</h2>
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                          We based our project on CRISPR/Cas9, a system largely used for genome engineering. Taking the catalytically dead dCas9 from this system allows the targeted binding of almost any DNA sequence. dCas9 is a mutant of the original Cas9 protein that lost its ability to cut DNA, but can still bind to DNA sequences using a specific guide RNA (gRNA). The only limitation for the target is that it has to lie next to a 3-base-pairs “PAM” sequence, NGG, N being any nucleotide. At the molecular level, the gRNA encodes the target sequence which is then ‘loaded’ into the dCas9, which, in turn then, ‘opens up’ the two DNA strands at the target sequence. Changing the sequence of the gRNA means changing which DNA sequence is targeted. In this way, it is possible to target different regions of a promoter. Moreover, dCas9 can be fused with activating transcriptional effectors to increase the expression of the promoter it binds to. This allows for the activation of the downstream gene that is associated to the promoter region.
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                            The main disadvantage of this system was that it only relied on allosteric repression to turn genes off by not allowing the polymerase to bind to the targeted promoter. This type of repression is not entirely reliable and is not performed by a “real” repressor, making it less efficient
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<p><strong>Description summary:</strong></p>
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<p>CRISPR-Cas9 has already revolutionized synthetic biology. To build upon this development we aim to implement digital-like circuits in yeast using a CRISPR-associated RNA scaffold system (Zalatan et al, 2015). Recently, a study published the use of the modular software CELLO which automates the design of DNA circuits using transcription factors in E. coli. As a proof of concept we will modify CELLO to use our dCas9 transistors in yeast for a so-called half-adder system, using AND and XOR gates, that we can then experimentally assess. With this approach we hope to pave the way for even more complex biological circuits in yeasts.</p>
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<p><strong>What have we done?</strong></p>
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<p>We started brainstorming in December and quickly decided to work on the creation of a biological circuit.<br />We were inspired by the EPFL&rsquo;s 2015 iGEM team, who worked on bioLOGIC. This system uses a catalytically dead version of Cas9 fused with an RNA Polymerase recruiting element (VP64) to create transistors, and depending on the identity of the promoter that dCas9-VP64 binds, it will either be repressed or activated.</p>
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<p>At first, we created brainstorming groups to find applications of the project. The idea of creating a half-adder stood out from the rest for its possible applications as well as its suitability as a proof of concept. Later, we discovered a program called CELLO that automates the design of DNA based logic circuits.</p>
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<p>At this point, we split into two groups. The first group worked on the design of the system, the second on the understanding of Cello&rsquo;s software in order to implement it with our system.</p>
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The project was defined as to create simple gates using biological parts. We wanted to use d-Cas9 to target specific sequences of promoters and therefore be able to activate or repress the expression of the genes controlled by them. In order to build biosensors, we imagined a system that allows our gates to respond differently to various environments, such as presence of galactose. <br />We also want to implement our system in yeast as they are well representation of mammalian cells and easy to handle. With this system we aim to create an half-adder which correspond to a XOR and an AND gate linked together.</p>
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<p>As mentioned before, we also plan to modify CELLO to be able to design genetic circuits in yeast using it. Fortunately, CELLO has a modular nature, allowing us to do this easily. CELLO has a User Constraint File that enables users to pass the program information about this system it is designing the circuit for. This file includes information pertaining to the species, the reactivity of gates to inputs, and the plasmids used. In order to obtain this new information, we plan on characterizing our system and gates using photometric experiments.</p>
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<p>During the process of designing our system, we stumbled upon a paper outlining a more intuitive way to activate and inhibit genes with dCas9, and we decided to improve our project using its results.</p>
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<p>This paper describes synthetic dcas9-based transcriptional programs in yeast. Instead of having the dcas9 unit fused to an activator or repressor protein, the guide RNA is extended to include an effector protein recruitment site, so that scaffold RNAs that encode both target locus and regulatory action.</p>
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<p>Using a dCas9 based system with scaffold guide RNAs offers numerous advantages with regards to previous biological circuit designing systems. Firstly, using gRNAs as parts of gates, instead of transcription factors reduces toxicity related to transcription factor density in the nucleus. In addition, our system can be even more complex than systems based on transcription factors since the amount of connections between gates are not limited by the amount of transcription factors available. Finally, the use of scaffolding RNAs simplifies design, since we can have just one dCas9, and it will also hopefully lead to more predictable repression and activation in the system. </p>
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                            Figure 1: Two ways to act on the expression of a promoter through CRISPR/dCas9 classical system. Figure adapted from Zalatan et al. 2015.
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                            With these limitations in mind, we set out to develop a system that was more intuitive, precise, and dynamic.
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                          This is exactly what we found in the study of Zalatan et al. (Engineering Complex Synthetic Transcriptional Programs with CRISPR RNA Scaffolds, Cell 2015) as it described a system in which a small hairpin is added to the end of the gRNA which is able to recruit either activators or repressors. RNA binding molecules can then bind to the RNA hairpin and depending on which molecule is recruited, activate or repress the expression of a downstream gene. In this way, a ‘repressing’ gRNA will assure the repression of a gene, and an ‘activating’ gRNA will activate gene expression. This makes the system more intuitive than previous studies that use an ‘activating’ system to repress gene expression.
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                                <!--<figcaption class="text-center">Figure 2: CRISPR/dCas9 new scaffold system. The gRNA is supplemented with an additional hairpin to be able to recruit transcriptional effectors and becomes a scRNA. In this way, the scRNA does not only determine the sequence of the promoter targeted, but also the effect imposed on the promoter.</figcaption>
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                            Figure 2: CRISPR/dCas9 new scaffold system. The gRNA is supplemented with an additional hairpin to be able to recruit transcriptional effectors and becomes a scRNA. In this way, the scRNA does not only determine the sequence of the promoter targeted, but also the effect imposed on the promoter.
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                        <h2>How to obtain a <b>modular</b> system?</h2>
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                          Modularity is the ability of a system to be composed of simple pieces that can then be recombined to form another one. It is also the key to obtaining an easy-to-use and understandable tool. Something that was unavailable until recently, was a truly modular way to achieve complex biological circuits composed of many different gates. The choice of the promoter was pivotal as the ability to use only one promoter in entire circuits would significantly simplify the system many times over. We had to find a promoter with distinct regions that could be targeted by different gRNAs: some for gene activation and other for repression. The sequences of those regions would also have to be modifiable to avoid cross-talk between all the gRNAs composing a given biological circuit.
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                        <!-- TODO: immagine modularità -->
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                            Making it work when you want to,
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                            means making it <b>inducible</b>
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                          As we now solved the issue of modularity of our system, it would be a lost opportunity to only end up with a tool that is not able to adapt to its surrounding. Adapting to its surrounding means requiring inducible promoters that do not interfere with the vital functions of the cell but still detect the molecule of interest. These promoters would allow researchers to achieve functional biosensors for many applications by triggering distinct responses in the cell according to the signals they detect.
  
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                        <!-- TODO: immagine modularità -->
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                        <h2 class="">Finding the right organism to work with</h2>
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                          We choose to work in yeasts for two main reasons: firstly, the promising results regarding transcription activation of genes using the new CRISPR/dCas9 system from Zalatan et al. 2015 were obtained in yeast, so we knew that our activation experiments on our modular promoter should function accordingly.
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                          Second, yeast is a eukaryotic system which means that the results can be predictably extrapolated to mammalian cells, without their high cost and long replication time. This makes it appealing for many other researchers as they may take advantage of our system to develop new ways to detect and cure diseases in humans for example.
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                        <h2 class="">How to <b>automate</b> the process? </h2>
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                          In order to help with the intelligent and intuitive design of these circuits, we decided to modify a recently-published program called Cello (Nielsen et al., Science 2016). Cello works by combining information about the circuit the user wants to create, and biological information about the system the user is building the circuit for. After putting this information through a series of algorithms, it produces plasmids which contain an optimized biological form of that circuit. While we loved the concept and its powerful design, we thought that certain aspects could be built upon to increase user-friendliness and embellish its open-source nature. To this end, we created a new, simple, graphical user interface, and connected Cello with databases of dCas9-based parts we created, which make the information it uses public and easily transferrable between users. These databases help to expand Cello’s capabilities by allowing it to handle emerging dCas9-based technologies. <a href="https://2016.igem.org/Team:EPFL/Software_CELLO">Click here to learn more about our tools!</a>
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                        <!-- TODO: immagine cello -->
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                        <h2 class="">Going further with activation and repression: <br/><b>proof of concept</b></h2>
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                          As a proof of concept, we chose to bring together all the preceding steps to build a simple logic gate: the NOT gate. This NOT gate will be inducible by galactose. The final step of our project should prove that all the foregoing work done functions accordingly and can simply be integrated in the automatically biological circuits design. The NOT gate is also interesting because in electrical circuits, one can build any possible gate with a NOT and a XOR gate.  From all of this, reaching the final goal of creating even more complex biological circuits in living cells is only a few steps away.
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                        <!-- TODO: immagine gate logico + biologico -->
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                        <h2 class="">Cool! But is it useful?</h2>
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                          Sure it is! Designing and constructing gates is one of the trickiest steps in the synthetic biology. And with this project, it just became easier! Once your gates are designed and ready, you can make a lot of things such as strong biosensors, or even detection methods for diseases or substances. And these are only few examples of the large applications of biological circuits.
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Latest revision as of 02:08, 20 October 2016

iGEM EPFL 2016

intelligene

A new way to design biological circuits

In the world of synthetic biology, it is difficult to not be surrounded by examples of the applications of genetic engineering. After all, anything a cell does can be traced back to its DNA. Many teams are genetically modifying cells to do amazing things, but rather than work on biosensors or cancer, we decided we wanted to make a tool that could help everybody modify their cells faster, more predictably, and more powerfully than ever. As a community, we have become pretty good at modifying cells to incorporate new genes precisely into their genomes, but what if we don’t want to make our cells just produce new proteins or RNAs? What if we want to make cells that are capable of making new decisions, ones they have never made before? The idea is not so outlandish. After all cells make decisions based on their surroundings, their health, and their metabolism all the time as signaling cascades modify the expression of their genes. By inserting plasmids with interconnected genetic elements, we can already make these “decision-making” circuits! Currently, these circuits are built using transcription factors, but finding transcription factors appropriate for this application can prove to be quite a challenge. This is because they must work in the host to target promoters in the new circuit, but also be completely orthogonal to the host genome, to not interfere with the cell’s survival.

dCas9 has already been used by a variety of authors to act as a sort of “programmable” transcription factor (“Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system”, Nucl. Acids Res. 2013). Since dCas9 uses a guide RNA to find sequences on the DNA, it can be used to guide transcriptional activators or repressors to their targets. As you will see, this can be used to intuitively make complex transcriptional networks. This summer, we harnessed the power of dCas9 and worked to create a suite of tools to make the creation of synthetic genetic networks easier than ever, saving scientists valuable time and reducing the cost of project development.

To increase the ease of development of new synthetic genetic circuits we also worked on computational tools that aid in their design. Notably, we modified Cello – a program published earlier this year in Science, which automates synthetic genetic network design – to help make it compatible with emerging dCas9-based technologies.

Intelligene is best thought of as a suite of tools, combining aspects of computational biology and synthetic biology to help scientists with new dCas9-based genetic circuits, from their design all the way through to their implementation.

General idea of the project

We based our project on CRISPR/Cas9, a system largely used for genome engineering. Taking the catalytically dead dCas9 from this system allows the targeted binding of almost any DNA sequence. dCas9 is a mutant of the original Cas9 protein that lost its ability to cut DNA, but can still bind to DNA sequences using a specific guide RNA (gRNA). The only limitation for the target is that it has to lie next to a 3-base-pairs “PAM” sequence, NGG, N being any nucleotide. At the molecular level, the gRNA encodes the target sequence which is then ‘loaded’ into the dCas9, which, in turn then, ‘opens up’ the two DNA strands at the target sequence. Changing the sequence of the gRNA means changing which DNA sequence is targeted. In this way, it is possible to target different regions of a promoter. Moreover, dCas9 can be fused with activating transcriptional effectors to increase the expression of the promoter it binds to. This allows for the activation of the downstream gene that is associated to the promoter region.

The main disadvantage of this system was that it only relied on allosteric repression to turn genes off by not allowing the polymerase to bind to the targeted promoter. This type of repression is not entirely reliable and is not performed by a “real” repressor, making it less efficient

Figure 1: Two ways to act on the expression of a promoter through CRISPR/dCas9 classical system. Figure adapted from Zalatan et al. 2015.

With these limitations in mind, we set out to develop a system that was more intuitive, precise, and dynamic.

This is exactly what we found in the study of Zalatan et al. (Engineering Complex Synthetic Transcriptional Programs with CRISPR RNA Scaffolds, Cell 2015) as it described a system in which a small hairpin is added to the end of the gRNA which is able to recruit either activators or repressors. RNA binding molecules can then bind to the RNA hairpin and depending on which molecule is recruited, activate or repress the expression of a downstream gene. In this way, a ‘repressing’ gRNA will assure the repression of a gene, and an ‘activating’ gRNA will activate gene expression. This makes the system more intuitive than previous studies that use an ‘activating’ system to repress gene expression.

Figure 2: CRISPR/dCas9 new scaffold system. The gRNA is supplemented with an additional hairpin to be able to recruit transcriptional effectors and becomes a scRNA. In this way, the scRNA does not only determine the sequence of the promoter targeted, but also the effect imposed on the promoter.

How to obtain a modular system?

Modularity is the ability of a system to be composed of simple pieces that can then be recombined to form another one. It is also the key to obtaining an easy-to-use and understandable tool. Something that was unavailable until recently, was a truly modular way to achieve complex biological circuits composed of many different gates. The choice of the promoter was pivotal as the ability to use only one promoter in entire circuits would significantly simplify the system many times over. We had to find a promoter with distinct regions that could be targeted by different gRNAs: some for gene activation and other for repression. The sequences of those regions would also have to be modifiable to avoid cross-talk between all the gRNAs composing a given biological circuit.

Making it work when you want to, means making it inducible

As we now solved the issue of modularity of our system, it would be a lost opportunity to only end up with a tool that is not able to adapt to its surrounding. Adapting to its surrounding means requiring inducible promoters that do not interfere with the vital functions of the cell but still detect the molecule of interest. These promoters would allow researchers to achieve functional biosensors for many applications by triggering distinct responses in the cell according to the signals they detect.

Finding the right organism to work with

We choose to work in yeasts for two main reasons: firstly, the promising results regarding transcription activation of genes using the new CRISPR/dCas9 system from Zalatan et al. 2015 were obtained in yeast, so we knew that our activation experiments on our modular promoter should function accordingly.

Second, yeast is a eukaryotic system which means that the results can be predictably extrapolated to mammalian cells, without their high cost and long replication time. This makes it appealing for many other researchers as they may take advantage of our system to develop new ways to detect and cure diseases in humans for example.

How to automate the process?

In order to help with the intelligent and intuitive design of these circuits, we decided to modify a recently-published program called Cello (Nielsen et al., Science 2016). Cello works by combining information about the circuit the user wants to create, and biological information about the system the user is building the circuit for. After putting this information through a series of algorithms, it produces plasmids which contain an optimized biological form of that circuit. While we loved the concept and its powerful design, we thought that certain aspects could be built upon to increase user-friendliness and embellish its open-source nature. To this end, we created a new, simple, graphical user interface, and connected Cello with databases of dCas9-based parts we created, which make the information it uses public and easily transferrable between users. These databases help to expand Cello’s capabilities by allowing it to handle emerging dCas9-based technologies. Click here to learn more about our tools!

Going further with activation and repression:
proof of concept

As a proof of concept, we chose to bring together all the preceding steps to build a simple logic gate: the NOT gate. This NOT gate will be inducible by galactose. The final step of our project should prove that all the foregoing work done functions accordingly and can simply be integrated in the automatically biological circuits design. The NOT gate is also interesting because in electrical circuits, one can build any possible gate with a NOT and a XOR gate. From all of this, reaching the final goal of creating even more complex biological circuits in living cells is only a few steps away.

Cool! But is it useful?

Sure it is! Designing and constructing gates is one of the trickiest steps in the synthetic biology. And with this project, it just became easier! Once your gates are designed and ready, you can make a lot of things such as strong biosensors, or even detection methods for diseases or substances. And these are only few examples of the large applications of biological circuits.