Noise properties of adaptation-conferring biochemical control modules.

A key goal of synthetic biology is to develop functional biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently developed control module in which two control species perfectly annihilate each other's biological activity. The AIF module confers robust perfect adaptation to the steady-state average level of a controlled intracellular component when subjected to sustained perturbations. Recent work has suggested that such robustness comes at the unavoidable price of increased stochastic fluctuations around average levels. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the idealized limit with perfect annihilation. However, we also show that this trade-off is a singular limit of the control module: Even minute deviations from perfect adaptation allow systems to achieve effective noise suppression as long as cells can pay the corresponding energetic cost. We further show that a variant of the AIF control module can achieve significant noise suppression even in the idealized limit with perfect adaptation. This atypical configuration may thus be preferable in synthetic biology applications.

Quantifying metal-binding specificity of CcNikZ-II from Clostridium carboxidivorans in the presence of competing metal ions.

Many proteins bind transition metal ions as cofactors to carry out their biological functions. Despite binding affinities for divalent transition metal ions being predominantly dictated by the Irving-Williams series for wild-type proteins, in vivo metal ion binding specificity is ensured by intracellular mechanisms that regulate free metal ion concentrations. However, a growing area of biotechnology research considers the use of metal-binding proteins in vitro to purify specific metal ions from wastewater, where specificity is dictated by the protein's metal binding affinities. A goal of metalloprotein engineering is to modulate these affinities to improve a protein's specificity towards a particular metal; however, the quantitative relationship between the affinities and the equilibrium metal-bound protein fractions depends on the underlying binding mechanisms. Here we demonstrate a high-throughput intrinsic tryptophan fluorescence quenching method to validate binding models in multi-metal solutions for CcNikZ-II, a nickel-binding protein from Clostridium carboxidivorans. Using our validated models, we quantify the relationship between binding affinity and specificity in different classes of metal-binding models for CcNikZ-II. We further illustrate the potential relevance of data-informed models to predicting engineering targets for improved specificity.

Advancing undergraduate synthetic biology education: insights from a Canadian iGEM student perspective.

The last two decades have seen vigorous activity in synthetic biology research and the ever-increasing applications of these technologies. However, pedagogical research pertaining to teaching synthetic biology is scarce, especially when compared to other science and engineering disciplines. Within Canada, there are only three universities that offer synthetic biology programs, two of which are at the undergraduate level. Rather than taking place in formal academic settings, many Canadian undergraduate students are introduced to synthetic biology through participation in the annual International Genetically Engineered Machine (iGEM) competition. Although the iGEM competition has had a transformative impact on synthetic biology training in other nations, its impact in Canada has been relatively modest. Consequently, the iGEM competition remains a major setting for synthetic biology education in Canada. To promote further development of synthetic biology education, we surveyed undergraduate students from the Canadian iGEM design teams of 2019. We extracted insights from these data using qualitative analysis to provide recommendations for best teaching practices in synthetic biology undergraduate education, which we describe through our proposed Framework for Transdisciplinary Synthetic Biology Education (FTSBE).