Nature integrates complex biosynthetic and energy-converting tasks within compartments such as chloroplasts and mitochondria. Chloroplasts convert light into chemical energy, driving carbon dioxide fixation. We used microfluidics to develop a chloroplast mimic by encapsulating and operating photosynthetic membranes in cell-sized droplets. These droplets can be energized by light to power enzymes or enzyme cascades and analyzed for their catalytic properties in multiplex and real time. We demonstrate how these microdroplets can be programmed and controlled by adjusting internal compositions and by using light as an external trigger. We showcase the capability of our platform by integrating the crotonyl–coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA (CETCH) cycle, a synthetic network for carbon dioxide conversion, to create an artificial photosynthetic system that interfaces the natural and the synthetic biological worlds.
The capture of CO2 by carboxylases is key to sustainable biocatalysis and a carbon-neutral bio-economy, yet currently limited to few naturally existing enzymes. Here, we developed glycolyl-CoA carboxylase (GCC), a new-to-nature enzyme, by combining rational design, high-throughput microfluidics and microplate screens. During this process, GCC’s catalytic efficiency improved by three orders of magnitude to match the properties of natural CO2-fixing enzymes. We verified our active-site redesign with an atomic-resolution, 1.96-Å cryo-electron microscopy structure and engineered two more enzymes that, together with GCC, form a carboxylation module for the conversion of glycolate (C2) to glycerate (C3). We demonstrate how this module can be interfaced with natural photorespiration, ethylene glycol conversion and synthetic CO2 fixation. Based on stoichiometrical calculations, GCC is predicted to increase the carbon efficiency of all of these processes by up to 150% while reducing their theoretical energy demand, showcasing how expanding the solution space of natural metabolism provides new opportunities for biotechnology and agriculture.
Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, we describe METIS, a versatile active machine learning workflow with a simple online interface for the data-driven optimization of biological targets with minimal experiments. We demonstrate our workflow for various applications, including cell-free transcription and translation, genetic circuits, and a 27-variable synthetic CO2-fixation cycle (CETCH cycle), improving these systems between one and two orders of magnitude. For the CETCH cycle, we explore 1025 conditions with only 1,000 experiments to yield the most efficient CO2-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system identifying unknown interactions and bottlenecks. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.
SummaryMicrobes must ensure robust amino acid metabolism in the face of external and internal perturbations. This robustness is thought to emerge from regulatory interactions in metabolic and genetic networks. Here, we explored the consequences of removing allosteric feedback inhibition in seven amino acid biosynthesis pathways in Escherichia coli (arginine, histidine, tryptophan, leucine, isoleucine, threonine, and proline). Proteome data revealed that enzyme levels decreased in five of the seven dysregulated pathways. Despite that, flux through the dysregulated pathways was not limited, indicating that enzyme levels are higher than absolutely needed in wild-type cells. We showed that such enzyme overabundance renders the arginine, histidine, and tryptophan pathways robust against perturbations of gene expression, using a metabolic model and CRISPR interference experiments. The results suggested a sensitive interaction between allosteric feedback inhibition and enzyme-level regulation that ensures robust yet efficient biosynthesis of histidine, arginine, and tryptophan in E. coli.
A long-term goal in realizing a sustainable biocatalysis and organic synthesis is the direct use of the greenhouse gas CO 2 as feedstock for the production of bulk and fine chemicals, such as pharmaceuticals, fragrances and food additives. Here we developed a modular in vitro platform for the continuous conversion of CO 2 into complex multi-carbon compounds, such as monoterpenes (C 10 ), sesquiterpenes (C 15 ) and polyketides. Combining natural and synthetic metabolic pathway modules, we established a route from CO 2 into the key intermediates acetyl-and malonyl-CoA, which can be subsequently diversified through the action of different terpene and polyketide synthases. Our proof-of-principle study demonstrates the simultaneous operation of different metabolic modules comprising of up to 29 enzymes in one pot, which paves the way for developing and optimizing synthesis routes for the generation of complex CO 2 -based chemicals in the future.Cell-free synthetic biology involves the in vitro assembly of multiple purified and semi-purified enzymes into metabolic cascades to generate natural and new-to-nature high-value chemicals. The in vitro reconstitution of metabolic pathways allows the convenient manipulation and optimization of reaction conditions, enzyme concentrations, cofactor supply, energy flux and yield, which are difficult to control in living microorganisms. [1] Glucose is frequently used as an inexpensive feedstock for these complex systems. Over the recent
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