Predictable activity is what synthetic biologists seek as they combine DNA parts they have designed in order to re-create a biological process. Two methods published online this week in Nature Methods propose how to first assess the quality of current biological parts and then how to design an element that performs reliably.
One of the ongoing challenges in synthetic biology is that parts that work well in one local DNA neighborhood or genomic context fail to perform in another. Drew Endy, Adam Arkin, and colleagues tackled this problem of reliability with two studies. First they introduce a statistical framework to assess the quality of bacterial transcription and translation control elements. They assign to each part a quality score that predicts its performance across different contexts. Then they design a control element to drive the expression of a gene of interest that performed reliably over a 1,000-fold dynamic range.
These methods will take most of the guess work out of synthetic circuit design. Once a large number of elements are characterized, researchers can more confidently select the part they need to achieve the desired level of expression, without having to worry that neighboring DNA will interfere with or even silence the part.
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