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<h1>Background</h1> | <h1>Background</h1> | ||
<p></p> | <p></p> | ||
+ | <p> | ||
+ | Synthetic biologists have come a long way since 1912 Stéphane Leduc’s <var>La Biologie Synthétique</var>. Throughout the course of synthetic biology, there were many stepping stones that lead to greater things, such as the discovery of restriction enzymes which lead to the simplified construction of recombinant DNA molecules and arrangements of new genes, or the creation of synthetic biological circuit devices by combining different genes within E. coli. Through these canonical inventions we acquired not only better tools, but also greater ambitions. From understanding how genes work and that they can be modified or replaced, to programming cellular behavior with external impulses, we have reached a point, where no longer the singular modal elements like switches, cascades, pulse generators or oscillators matter. We have reached a point where scientists are ready to face the biggest challenge of synthetic biology - creating an artificial cell. | ||
+ | </p> | ||
+ | <p> | ||
+ | However designing complex, several layered circuitries resembling the behavior of a natural cell is still an overwhelming challenge due to many limitations like crosstalk, mutations, ambiguous intracellular and extracellular conditions, and biological noise. Therefore we propose to start from something simpler and more minimal.. Although the journey of creating a synthetic minimal cell has already begun, we hoped to contribute to this ultimate goal as well by investing our time and effort. This year we are engineering liposomes, lipid-coated vesicles, that are perfect models to study the initial steps for creating synthetic cells. Liposomes can offer a system with fully controllable experimental parameters and only the exact elements for our custom circuit design without the need to ever worry about the crosstalk and noise. We believe that most of the future synthetic biology applications will rely on bottom-up engineering solutions. Having mastered some hard-core bottom-up liposome engineering, we won’t take long to create the first synthetic cell. | ||
+ | </p> | ||
+ | <p> | ||
+ | Keeping that in mind we raised a question - what is the trivial difference between completely artificial systems like liposomes and living cells? The answer has pushed us to develop the SynDrop system the way it is being presented today. That major difference between synthetic and natural systems is the capacity to develop an active interface between outside and inside, which is vital for communication, transport, signaling, growth, and proliferation. Most of this communication is mediated by integral membrane proteins. Surprisingly, though membrane proteins are key players in many cellular functions and even human health and disease, they are greatly understudied when compared to e.g. globular proteins. Membrane protein integration into the membranes <var>in vitro</var> is still a particularly delicate issue that halts more rapid scientific development in this field. Having realized this, we knew that our goal this year was going to be the creation of an <var>in vitro</var> membrane protein synthesis system in liposomes in order to not only broaden the research possibilities of integral proteins but also to move one step further in building a minimal cell, which with what SynDrop offers - now will be capable of executing at least minimal .communication between its inside (genotype) and surrounding environment (display phenotype). | ||
+ | </p> | ||
+ | <p></p> | ||
+ | <h1><var>SynDrop - Synthetic Droplets for Membrane Protein Research</var> </h1> | ||
+ | <p></p> | ||
+ | <P> | ||
+ | Current methods for studying MPs are mostly based on cellular systems, which are really not the best environment to study membrane proteins. Large intrinsic and extrinsic cellular noise makes it awfully difficult to characterize discrete MPs as well as other limitations like toxicity and limited yields. Only a few self-integrating membrane proteins have been utilized for research as the majority of them aggregate or are toxic to the host. The capacity to vary parameters is too restrictive for an in-depth investigation of a complete spatiotemporal arrangement of a particular protein or mechanism. | ||
+ | </P> | ||
+ | <p> | ||
+ | As mentioned above, to untangle these problems we decided not to try to decipher and modulate natural cells. We chose something much more simple - a <var>cell-free</var> synthetic system with well defined, easily controlled parameters, that could be engineered from scratch. We called it SynDrop - Synthetic Droplets for Membrane Protein Research. SynDrop edges not only cellular systems, but also other current cell-free systems in terms of membrane protein research and studying their behavior, including folding and membrane insertion. | ||
+ | </p> | ||
+ | <p> | ||
+ | Thus SynDrop is a novel bottom-up liposome-based platform created to empower the manipulation of membrane proteins. It is carefully though and bares the exact minimum components to successfully perform its function and not become too unpredictable or metabolically unstable. Transcriptional and translational machineries together with the plasmid DNA, chaperones, energy regeneration systems, and cellular MP insertion facilitators are encapsulated within the liposomes, enabling synthesis, integration, and display of target membrane proteins. It is also equipped with synthetic tools that regulate, attenuate and modulate the whole system. | ||
+ | </p> | ||
+ | <p></p> | ||
+ | <h1>Applications</h1> | ||
+ | <p></p> | ||
+ | <p>As our project focuses on a novel platform for membrane protein research it offers various future applications. | ||
+ | </p> | ||
+ | <p></p> | ||
+ | <h2>1. Membrane protein characterization</h2> | ||
+ | <p>Since liposome systems contain no unknown variables, SynDrop could be used to characterize membrane proteins and their biogenesis. This could possibly unlock new and innovative breakthrough in proteomics.</p> | ||
+ | <p></p> | ||
+ | <h2>2. Membrane protein-lipid interactions</h2> | ||
+ | <p>Microfluidics allow to synthetize liposomes with modifying their lipid composition rather simply. By using SynDrop we can quickly get huge quantities of liposomes with various lipid compositions. Further, membrane proteins translated in these liposomes will interact accordingly with these lipids. This characterization of membrane protein interactions with custom lipids can be modelled and then implemented in <var>in vivo</var> systems.</p> | ||
+ | <p></p> | ||
+ | <h2>3. Membrane protein-membrane protein interactions</h2> | ||
+ | <p> Expanding even further of the membrane protein interactions. The amount of genetic material that gets encapsulated in the liposome can be regulated. Therefore multiple genes coding for different membrane proteins can be translated inside liposomes. It yields multiple membrane protein-protein interactions that can be measured and modelled accordingly.</p> | ||
+ | <p></p> | ||
+ | <h2>4. Molecular evolution of the exposed particle</h2> | ||
+ | <p> Liposomes could be effectively used in molecular evolution. We constructed a few membrane proteins that proved to display a protein particle on the surface of bacteria. By incorporating a few membrane protein integration helpers, we believe that liposome exposition could serve as a better alternative to current molecular evolution methods.</p> | ||
+ | <p></p> | ||
+ | <h2>5. Molecular evolution of the membrane protein</h2> | ||
+ | <p>Molecular evolution could be also applied not only for the exposed protein particle, but also for the membrane protein itself. Since liposomes have no additional noise and contains a changeable lipid bilayer, it could be one of the most feasible methods of membrane protein evolution.</p> | ||
+ | <p></p> | ||
+ | <h2>6. Membrane protein biogenesis regulation</h2> | ||
+ | <p>DNA or RNA that gets encapsulated inside liposomes can be altered. Therefore we can insert modifications that change the rate and volume of membrane protein biogenesis. For example, modifications might include thermoswitches that we used in our project to regulate the rate of translation inside the liposomes, so that one membrane protein has the priority to get translated over the other. These or similar modifications might lead to a fully functional one or more genetic circuit incorporation into liposomes that regulate the biogenesis of membrane proteins.</p> | ||
+ | <p></p> | ||
+ | <h2>7. Liposome communication</h2> | ||
+ | <p>Microfluidic field enables the production of similar or different composition liposomes. Theoretically, these liposomes could cross-react with each other or even share signals. This could create an autonomous artificial ecosystem and could lead towards the creation of artificial life.</p> | ||
+ | <p></p> | ||
+ | <p></p> | ||
+ | <h1>Background of other display systems</h1> | ||
+ | <p></p> | ||
+ | <p> | ||
+ | An extensive literature search was performed to analyze every display system type that currently exists in order to be sure about the necessity and applicability of our project. | ||
+ | </p> | ||
+ | <p></p> | ||
+ | <h2>Phage display</h2> | ||
+ | <p></p> | ||
+ | <table class="c65"> | ||
+ | <tbody> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Library size </span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c17">10</span><span class="c17 c31">7</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c1"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Transformation required</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Yes</span></p> | ||
+ | <p class="c7 c28"><span class="c2"></span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c55"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Mechanism </span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c12"><span class="c2">Phage display systems can be grouped into two classes: true phage vectors and phagemid vectors. In both cases, the protein to be displayed is fused to the capsid protein. </span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Evolution</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c12"><span class="c2">Typically the phage library screening entails several (usually three) consecutive rounds of panning and phage amplification before the selected phage and the polypeptide that they present are individually analyzed.</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c54"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Protein displayed </span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Fv, scFv or Fab fragments</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Proteins to be displayed </span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Soluble, non-toxic, compatible with crossing membranes</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Surface anchorage </span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Capsid proteins</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Properties of protein enhanced</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c12"><span class="c2">Affinity, enzymatic activity, stability, folding, selection from cDNA libraries</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c92"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Stability</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Stable</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c80"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Applications</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <ul class="c20 lst-kix_8x5880tr1n6b-0 start"> | ||
+ | <li class="c11"><span class="c2">To enhance catalytic activity, proteolytic stability, or attach conjugation site and photoaffinity labels </span></li> | ||
+ | <li class="c11"><span class="c2">Affinity selection of protein fragments expressed from cDNA fragments</span></li> | ||
+ | <li class="c11"><span class="c2">Immunotherapy</span></li> | ||
+ | <li class="c11"><span class="c2">Developing diagnostic or therapeutic reagents in medicine</span></li> | ||
+ | <li class="c11"><span class="c2">Developing nanomaterials in material science</span></li> | ||
+ | <li class="c45 c67"><span class="c2">Identifying receptor agonists or antagonists in cell biology</span></li> | ||
+ | </ul> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c19"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Advantages</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <ul class="c20 lst-kix_r1elq1tnko7i-0 start"> | ||
+ | <li class="c7 c67"><span class="c2">Biopanning of phage libraries on whole cells</span></li> | ||
+ | <li class="c7 c67"><span class="c2">Wide range of pH could be used for selection</span></li> | ||
+ | </ul> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Disadvantages</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <ul class="c20 lst-kix_vaxyq0tqgdpb-0 start"> | ||
+ | <li class="c34"><span class="c2">The low display rate can be a drawback. In the first round of panning where very few binders are to be enriched from a huge excess of unwanted phages, phages that are mostly “bald” can reduce the accessible molecular diversity of the library and the efficiency of the system</span></li> | ||
+ | <li class="c34"><span class="c2">If selection is done on cells, non specific phage binding is observed, due to phage protein interaction with cell membrane proteins </span></li> | ||
+ | <li class="c62"><span class="c17">In phage display, libraries must be transformed into bacteria, limiting the number of possible independent sequences to 10</span><span class="c17 c31">9</span><span class="c17">–10</span><span class="c17 c31">10</span></li> | ||
+ | </ul> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c105"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">Membrane protein research</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c12"><span class="c2">Compatible</span></p> | ||
+ | <p class="c12"><span class="c2">Nogo-66 - monotopic membrane protein (7,5 kDa)<br>ShuA - beta barrel forming protein, which pass through membrane 22 times (72.5 kDa)<br>MOMP - beta barrel forming protein, which pass through membrane 16 times (40 kDa)<br>Nef - peripheral protein (23 kDa)<br>Neuromodulin - peripheral protein (25 kDa)<br>Caveolin-1 - monotopic membrane protein (22 kDa)</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | <tr class="c25"> | ||
+ | <td class="c18" colspan="1" rowspan="1"> | ||
+ | <p class="c7"><span class="c2">References</span></p> | ||
+ | </td> | ||
+ | <td class="c43" colspan="1" rowspan="1"> | ||
+ | <p class="c12"><span class="c17">1. </span><span class="c17 c29">Imai, S. et al. Development of an antibody proteomics system using a phage antibody library for efficient screening of biomarker proteins. </span><span class="c5 c29">Biomaterials</span><span class="c17 c29"> 32, 162-169 (2011).</span><span class="c17"> <br>2. </span><span class="c17 c29">Petrenko, V. Evolution of phage display: from bioactive peptides to bioselective nanomaterials. </span><span class="c5 c29">Expert Opinion on Drug Delivery</span><span class="c17 c29"> 5, 825-836 (2008).</span></p> | ||
+ | <p class="c12"><span class="c17 c29">3. Paschke, M. Phage display systems and their applications. </span><span class="c5 c29">Applied Microbiology and Biotechnology</span><span class="c17 c29"> 70, 2-11 (2005).</span><span class="c17"><br></span><span class="c17 c29">4. Reiersen, H. Covalent antibody display--an in vitro antibody-DNA library selection system. </span><span class="c5 c29">Nucleic Acids Research</span><span class="c17 c29"> 33, 10 (2005).</span><span class="c17"><br></span><span class="c17 c29">5. Vithayathil, R., Hooy, R., Cocco, M. & Weiss, G. The Scope of Phage Display for Membrane Proteins. </span><span class="c5 c29">Journal of Molecular Biology</span><span class="c17 c29"> 414, 499-510 (2011).</span><span class="c17"><br></span><span class="c17 c29">6. Morrison, K. & Weiss, G. Combinatorial alanine-scanning. </span><span class="c5 c29">Current Opinion in Chemical Biology</span><span class="c17 c29"> 5, 302-307 (2001).</span><span class="c17"><br></span><span class="c17 c29">7. Clackson, T. & Wells, J. In vitro selection from protein and peptide libraries. </span><span class="c5 c29">Trends in Biotechnology</span><span class="c17 c29"> 12, 173-184 (1994).</span><span class="c17"><br></span><span class="c17 c29">8. Galán, A. et al. Library-based display technologies: where do we stand?. </span><span class="c5 c29">Molecular BioSystems</span><span class="c17 c29"> 12, 2342-2358 (2016).</span></p> | ||
+ | </td> | ||
+ | </tr> | ||
+ | </tbody> | ||
+ | </table> | ||
</div> | </div> | ||
</div> | </div> |
Revision as of 02:38, 18 October 2018
Description
Describe the Impossible
Cell-free systems are becoming an increasingly popular in vitro tool to study biological processes as it is accompanied by less intrinsic and extrinsic noise. Relying on fundamental concepts of synthetic biology, we apply a bottom-up forward engineering approach to create a novel cell-free system for unorthodox protein-evolution. The core of this system is cell-sized liposomes that serve as excellent artificial membrane models. By encapsulating genetic material and full in vitro protein transcription and translation systems within the liposomes, we create reliable and incredibly efficient nanofactories for the production of target proteins. Even though there are many alternative proteins that can be synthesized, our main focus is directed towards membrane proteins, which occupy approximately one third of living-cells’ genomes. Considering their significance, membrane proteins are spectacularly understudied since synthesis and thus characterization of them remain prevailing obstacles to this day. We aim to utilize liposomes as nanofactories for directed evolution of membrane proteins. Furthermore, by means of directed membrane protein-evolution, a universal exposition system will be designed in order to display any protein of interest on the surface of the liposome. This way, a system is built where a phenotype of a particular protein is expressed on the outside while containing its genotype within the liposome. To prove the concept, small antibody fragments will be displayed to create a single-chain variable fragment (scFv) library for rapid screening of any designated target.