Beyond Biobricks: Synthesizing Synergistic Biochemical Systems from the Bottom-up

Engineers who attempt to discover and optimize the behavior of complex biochemical systems face a dauntingly difficult task. This is especially true if the systems are governed by multiple qualitative and quantitative variables that have non-linear response functions and that interact synergistically. The synthetic biology community has responded to this difficulty by promoting the use of standard biological parts called BioBricks , which are supposed to make biology into traditional engineering and enable engineers to program living organisms in the same way a computer scientists can program a computer . But the BioBricks research program faces daunting hurdles, because the nonlinearity and synergy found throughout biochemical systems generates lots of unpredictable emergent properties. This talk describes an alternative vision of how to engineer complex biochemical systems, according to which we would refashion engineering to fit biology (rather than the other way around). The resulting method (termed Predictive Design Technology or PDT) is a robot- and computer-driven automatic and autonomous implementation of traditional Edisonian science. The PDT method is described and illustrated in application to a number of practical biochemical design tasks, including (2) optimizing combination drug therapies, (2) optimizing cargo capacity of liposomes that self-assemble from complex amphiphile mixtures, (3) optimizing the liposomal formulation of insoluble drugs, and (4) optimizing in vitro protein expression.https://pdxscholar.library.pdx.edu/systems_science_seminar_series/1040/thumbnail.jp