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<p >System based on CRISPR-Cas9</p><p>2016 EPFL iGEM team</p><p><br/></p><p >Summary</p><p><br/></p><p>CRISPR-Cas9 has already revolutionized synthetic biology. To build forward on this development we aim to implement digital-like circuits in yeast using a dCas9-based reprogrammable transcription factor. Recently, a study published the use of the modular CELLO software automating 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 pave the way for even more complex biological circuits in yeasts.</p><p><br/></p><p>Full description <span >1. Background</span></p><p>Coordination of vital functions in our body is dependent on intricate circuits of transcription factors (TFs) acting on gene regulation. In the early 2000’s, scientists took interest in reproducing those circuits in simple in vivo models, such as E. coli, to reprogram them and change functionality. Until recently, this was done by concatenating different TFs found naturally in the cells (Nissim et al., 2014).</p><p>Synthetic biological circuits allow gates - analogous to logic gates used in electronics - to be used in combination to create complex functions within the cell that can be receptive to external input. Each gate performs a simple calculation with given inputs and gives an output, which can be processed by other gates, acted upon by the cell, or observed by a researcher. A gate performs a logical function on one or more logical inputs. For example, with just one gate, a researcher can make a cell produce yellow fluorescent protein (YFP) if molecules A and B are both present within it. Another gate might give a positive signal in the presence of one or the other. With two gates, that cell can produce YFP if molecule B is present, but not A. With the emergence of the open-source software CELLO, recently published in Science, this process is significantly simplified and far less time consuming. CELLO is an extraordinarily powerful tool because it allows researchers to design circuits with up to sixteen gates in E. coli, allowing cells to investigate complex molecular pathways, or engineer cells that can be used in therapy for diseases. The process is entirely automated, taking only the desired circuit as input. CELLO assembles a plasmid containing this circuit using a library of sequences that code for TFs, promoters and other biological parts that together will be able to perform as a circuit. This plasmid, once constructed and transfected into a host organism, will recreate the desired circuit. Currently, CELLO only uses promoters that can be repressed using small metabolites to create its gates. Each one of these promoters and gates needs to be characterized, meaning that its output needs to be predictable given a certain level of input. Notably, gates for CELLO have only been characterized in E. coli thus far. This means that the most complex gates that can be created can use a maximum of sixteen</p><p>gates, but only in E. coli.</p><p><br/></p><p><br/></p><p>2. Research Description</p><p><br/></p><p>We aim to expand on this theme, and hopefully make this powerful tool even more so. The first modification we would like to introduce is a dCas9-based system, already partially designed and constructed by the previous iGEM team from the EPFL. In this system, a catalytically dead Cas9 protein is bound to a VP64 activating subunit and essentially acts as a reprogrammable TF. This dCas9 can be integrated into the host genome fairly easily. This could provide numerous benefits to the program. In our system, the small guide (sg)RNA would target a 23-nucleotide sequence that would be predicted by the program and placed before the gate, forming an artificial promoter. Although these artificial “promoters” could not be activated or repressed by environmental signals, such as metabolites, they could form the basis of communication between intermediate gates in the circuit. This would free up the limited number of inducible and repressible promoters to be used for the initial gates, therefore greatly increasing the potential complexity of the circuits that could be created.</p><p>Using dCas9-based gates also has other benefits. sgRNAs are much smaller than the genes coding the TFs they might replace, which would reduce the space that each gate occupies on a plasmid. Very little toxicity has been previously observed with the dCas9-sgRNA complex, while TFs may create toxicity in cells. The combination of reduced space and reduced complexity further suggests that implementing our system could lead to more complex circuits being created automatically.</p><p>A second goal of our project is to create this system in S. cerevisiae, which means that all gates and promoters will have to be characterized in this organism. This would increase the power of CELLO, since it would allow its method to be applied in eukaryotic systems. Although this would represent a first step in this direction, we predict that this yeast-oriented program could be modified to be used in other eukaryotic systems with relative ease, since many of the genetic components that are used are the same or similar (the polymerase II, for example).</p><p>Modifying the program to include new gates in a new organism is fairly straightforward, and already underway. Luckily, CELLO is a modular program. This means that new data can be provided to it in a separate file, called a User Constraint File, and CELLO will use the same algorithms to interpret this new data and create plasmids that are suitable for the new organism and use the gates specified by the user. Altogether, constructing and characterizing these new parts will require a great deal of lab work, making this largely a wet-lab project. Once the parts are characterized, the data obtained can be put in the user-constraint file, completing the foreseen project.</p><p>In the case that we have extra time, we plan to review whether all the functions of the program are necessary, given the new Cas9-based system, and remove pieces that are no longer necessary. In addition, we would like to add an extra library to the project, which will add a further level of abstraction to CELLO. What this means is that researchers who are not familiar with how transcriptional circuits might work in a certain</p><p>organism might still be able to create circuits in that organism. Instead of telling the program to create a certain circuit, the researcher might simply say, “create a circuit that will produce YFP when the cell is in an environment that contains high levels of glucose and iron, but low levels of zinc.” The program would then look in our open- source library for known sensors for glucose, iron, and zinc and create the circuit itself.</p><p>Potential applications and implications of the project</p><p><br/></p><p>Our project aims to increase the scope of genetic circuit automation to eukaryotes and enable this powerful technology to build more complex circuits. As a first proof-of-concept our team plans to construct a half-adder using the DNA sequence indicated by our modified CELLO. A half-adder permits the researcher to know when one molecule <i>but not </i>another one is present. The further applications of this project range from studying existing systems to creating novel ones. In yeasts, the complex interactions of metabolic processes could be studied by having different fluorescent proteins produced when certain proteins are abundant, and others produced when they are low. This could be used to give real-time data about the whole system at once. Once finished, this project could be easily redirected into other eukaryotes as well, and could have interesting therapeutic applications. For example, novel behaviors could be programmed into cells based on the environment they are in, which could be identified by the amount of secondary signals coming from receptors. In this example, researchers could reprogram cells to produce a therapeutic protein when in a certain niche, and this application would be straightforward using our project.</p>
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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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                                <img src="https://static.igem.org/mediawiki/2016/5/52/DCas9_CRISPRi.png" />
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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.