Deconstructing synthetic biology across scales: a conceptual approach for training synthetic biologists.

Synthetic biology allows us to reuse, repurpose, and reconfigure biological systems to address society's most pressing challenges. Developing biotechnologies in this way requires integrating concepts across disciplines, posing challenges to educating students with diverse expertise. We created a framework for synthetic biology training that deconstructs biotechnologies across scales-molecular, circuit/network, cell/cell-free systems, biological communities, and societal-giving students a holistic toolkit to integrate cross-disciplinary concepts towards responsible innovation of successful biotechnologies. We present this framework, lessons learned, and inclusive teaching materials to allow its adaption to train the next generation of synthetic biologists.

Programming cell-free biosensors with DNA strand displacement circuits.

Cell-free biosensors are powerful platforms for monitoring human and environmental health. Here, we expand their capabilities by interfacing them with toehold-mediated strand displacement circuits, a dynamic DNA nanotechnology that enables molecular computation through programmable interactions between nucleic acid strands. We develop design rules for interfacing a small molecule sensing platform called ROSALIND with toehold-mediated strand displacement to construct hybrid RNA-DNA circuits that allow fine-tuning of reaction kinetics. We use these design rules to build 12 different circuits that implement a range of logic functions (NOT, OR, AND, IMPLY, NOR, NIMPLY, NAND). Finally, we demonstrate a circuit that acts like an analog-to-digital converter to create a series of binary outputs that encode the concentration range of the molecule being detected. We believe this work establishes a pathway to create 'smart' diagnostics that use molecular computations to enhance the speed and utility of biosensors.

RNA Engineering for Public Health: Innovations in RNA-Based Diagnostics and Therapeutics.

RNA is essential for cellular function: From sensing intra- and extracellular signals to controlling gene expression, RNA mediates a diverse and expansive list of molecular processes. A long-standing goal of synthetic biology has been to develop RNA engineering principles that can be used to harness and reprogram these RNA-mediated processes to engineer biological systems to solve pressing global challenges. Recent advances in the field of RNA engineering are bringing this to fruition, enabling the creation of RNA-based tools to combat some of the most urgent public health crises. Specifically, new diagnostics using engineered RNAs are able to detect both pathogens and chemicals while generating an easily detectable fluorescent signal as an indicator. New classes of vaccines and therapeutics are also using engineered RNAs to target a wide range of genetic and pathogenic diseases. Here, we discuss the recent breakthroughs in RNA engineering enabling these innovations and examine how advances in RNA design promise to accelerate the impact of engineered RNA systems.

Electronic effects due to organic linker-metal surface interactions: implications on screening of MOF-encapsulated catalysts.

MOF-encapsulated nanoparticles (NP@MOFs) are hybrid, heterogeneous catalysts, where the MOF could boost the activity and selectivity of the encapsulated NP for the reaction of choice by controlling reactant orientation. However, due to overwhelming combinatorics, methods to rapidly identify promising NP + MOF combinations for a given application are needed. Earlier work used a "surrogate" inert pore on top of NP-representative surfaces to generically capture MOF steric effects, hence enabling computational screening to focus on NP composition. However, the surrogate pore method neglects electronic effects of the MOF on the NP. Here, we use density functional theory to study how paradigmatic MOF linkers (imidazolate, carboxylate, and thiolate) impact the electronic structure of representative metal surfaces, and in turn the binding of small species, whose formation energies are commonly used in descriptor-based catalyst screening. We find that the coordinating moiety and functionalization of the linker modulates the shift in the metal d-band center and the electron transfer, which is correlated to experimentally measurable quantities such as C-O vibration frequencies. However, in the majority of cases, the effect of the linker on binding energies (for C*, O*, N*, H*, OH*, CH3* and CO*) was less than 10 kJ mol-1. Furthermore, scaling relationships between binding energies were only slightly affected by linker-originated electronic effects. Therefore, activity/selectivity "heat maps" derived from calculations under "generic" steric constrains could remain useful to screen the optimal NP composition of an NP@MOF catalyst. On the other hand, the placement of a given NP composition on the aforementioned heat maps is affected by the MOF. For an n-butane oxidation case study, we estimated that Ag3Pd-a promising NP composition for selective 1-butanol formation according to previous screenings using the surrogate pore method-has a ∼85% probability of retaining a selectivity for 1-butanol above 75% when encapsulated in a carboxylic MOF of suitable pore size.