Team:BostonU/Project Overview

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BostonU iGEM Team: Welcome


Project Overview


    Overall goals: Our major goal is to generate a standard protocol for the characterization of genetic circuits containing fluorescent proteins and share this protocol with the synthetic biology community. Our secondary goal is to introduce MoClo as an alternative assembly method for iGEM teams to use.

    In order to achieve this goal, there are many steps that must be taken:

    • Convert BioBrick Parts into MoClo Parts
    • Build Genetic Circuits with MoClo Parts
    • Characterize Circuits using Flow Cytometry
    • Generate Data Sheet for MoClo Parts

Abstract


Title

    Abandon All Hope, Ye Who PCR: MoClo and the Quest for Genetic Circuit Characterization


Authors

    Monique De Freitas¹, Shawn Jin¹, Evan Appleton², Swati Carr², Sonya Iverson², Traci Haddock³, and Douglas Densmore§


Affiliations

    ¹iGEM Team Member, ²iGEM Team Mentor, ³iGEM Team Advisor, §Faculty Sponsor, Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA


Abstract

    Our project aims to introduce a standardized protocol for the characterization of genetic circuits using flow cytometry. We built a vast number of both simple and complex genetic circuits that were characterized using flow cytometry. These genetic circuits were built using an assembly technique called MoClo (developed by Weber et al, 2011), which involves a multi-way, one-pot digestion-ligation reaction, enabling faster and more efficient construction of genetic circuits. We converted a large subset of BioBrick Parts from the Registry into MoClo Parts using PCR and cloning strategies. We built and characterized various genetic circuits using MoClo Parts and compared them against their pre-existing BioBrick counterparts in order to compare the characterization results from the two assembly techniques. We also created a standardized data sheet to be included in the Registry of Standard Biological Parts for each Part we characterized to easily share our data with the synthetic biology community.