Difference between revisions of "Team:Vilnius-Lithuania/Description"
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| − | <p class="text-content"> | + | <p class="text-content">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.</p> |
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Revision as of 12:37, 16 October 2018
Description
Lorem ipsum, dolor sit amet consectetur adipisicing
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.
Description
What is SynORI?
SynORI stands for synthetic origin of replication. It is a framework designed to make working with single and multi-plasmid systems precise, easy and on top of that - more functional.
The SynORI framework enables scientists to build a multi-plasmid system in a standardized manner by:
- Selecting the number of plasmid groups
- Choosing the copy number of each group
- Picking the type of copy number control (specific to one group or regulating all of them at once).
The framework also includes a possibility of adding a selection system that reduces the usage of antibiotics (only 1 antibiotic for up to 5 different plasmids!) and an active partitioning system to make sure that low copy number plasmid groups are not lost during the division.
Applications
Everyday lab work
A multi-plasmid system that is easy to assemble and control. With our framework the need to limit your research to a particular plasmid copy number just because there are not enough right replicons to choose from, is eliminated. With SynORI you can easily create a vector with a desired copy number that suits your needs.
Biological computing
The ability to choose a wide range of copy number options and their control types will make the synthetic biology engineering much more flexible and predictable. Introduction of plasmid copy number regulation is equivalent to adding a global parameter to a computer system. It enables the coordination of multiple gene group expression.
Smart assembly of large protein complexes
The co-expression of multi-subunit complexes using different replicons brings incoherency to an already chaotic cell system. This can be avoided by using SynORI, as in this framework every plasmid group uses the same type of control, and in addition can act in a group-specific manner.
Metabolic engineering
A big challenge for heterologous expression of multiple gene pathways is to accurately adjust the levels of each enzyme to achieve optimal production efficiency. Precise promoter tuning in transcriptional control and synthetic ribosome binding sites in translational control are already widely used to maintain expression levels. In addition to current approaches, our framework allows a simultaneous multiple gene control. Furthermore, an inducible regulation that we offer, can make the search for perfect conditions a lot easier.
| Species sign in ODE system | Species | Initial concentration (M) |
| A | pDNA+RNA I+RNAII early | 0 |
| B | pDNA+RNA II short | 0 |
| RNAI | RNA I | 1E-6 |
| D | pDNA+RNA II long | 0 |
| E | pDNA+RNAII primer | 0 |
| F | RNA II long | 0 |
| G | pDNA | 4E-8* |
| H | pDNA+RNA II+RNA I late | 0 |
| RNA II | RNA II | 0 |
| J | RNAI+RNAII | 0 |
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