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<title>Synthopedia | iGEM | IITM</title>
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<p class="first-para">Synthetic biology envisions a bioengineering<br>domain for designing new genetic parts and <br>systems, or redesigning of existing ones. <br><br> Until now, the most versatile workhorse of <br>synthetic biology has been <i><b>Escherichia coli.</b></i><br>However, there is a need for exploring new <br>chassis which can be naturally adapted to <br>unique traits or metabolic pathways.</p>
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<p class="second-para"><span class="enlarge">Lactococcus lactis (L. lactis)</span><br> is a ‘Generally Regarded As Safe’ (GRAS)<br>organism. It is naturally found in milk products<br> and is also known to colonize the human gut.<br> Unlike E. coli, it does not have an endotoxin<br> layer, which requires extra measures for<br> purification.<br><br>Due to its ability to use a wide range of<br> substrates and tolerance for a wide range of<br> conditions (pH, temperature, solvent<br> concentration), L. lactis serves as an alternate<br> bacterial model for metabolic and bioprocess<br> engineering.</p>
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<p class="third-para">The range of products it can be engineered to<br>produce include bioplastics, biofuels,<br>biopolymers, polyols, and food flavors.<br><br>However, the absence of genetic and regulatory<br>libraries for this organism make genetic<br>circuits design and assembly challenging in<br>this chassis.<br><br>The ability to fine-tune gene expression forms<br>a cornerstone for the design and operation of<br>genetic circuits. This optimization has not<br>been fully carried out in non-traditional<br>chassis like L. lactis.</p>
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<p class="fourth-para">Our project is aimed at the <b>construction and testing of a<br> library of synthetic 5’ untranslated regions (UTR) <br>containing ribosome binding sites (RBS) in <i>L. lactis.</i></b></p>
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<p class="fifth-para">In addition to our lab work, we also plan to study these drawbacks and come up with <br>potential improvements to the existing model. This would include studying the effect <br>of temperature on mRNA folding, the interaction between the mRNA and the ribosomal S1<br>protein, the difference in optimal RBS-AUG spacing in Gram-positive and Gram-negative<br>bacteria, and the effect of RNAse-mediated degradation of the transcript.<br><br>Combining the model with an optimisation algorithm, we aim to rationally design the <br>‘best’ RBS for a given gene, in a given organism.</p>
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