Predicting the dynamics of mutation spread in engineered cell populations is a sought-after goal in synthetic biology. Until now, models that capture these processes have been lacking, either by failing to account for the diversity of mutation types, or by failing to link the growth rate of a cell to the consumption of shared cellular resources by synthetic constructs. In this study we address these shortcomings by building a novel mutation-aware modelling framework of cell growth in a

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... at. Our framework allows users to input essential design elements of their synthetic constructs so as to predict the time evolution of different mutation phenotypes and protein production dynamics. Its structure allows quick mutation-based analysis of any construct design, from single-gene constructs to multi-gene devices with regulatory elements. We show how our framework can generate new insights into industrial applications, such as how the design of synthetic constructs impacts long-term protein yield and genetic shelf-life. Our framework also uncovers new mutation-driven design paradigms for synthetic gene regulatory networks, such as how mutations can temporarily increase the bistability of toggle switches, or how repressilators can be resistant to single points of failure.