Publication 3: A Lactose-Based Kluyveromyces lactis Cell-Free Protein Synthesis System
Tejasvi Shivakumar, Akashaditya Das, Maria Victoria Bussoletti Panizo, Marko Storch, Walter Thavarajah, Paul S. Freemont and Karen M. Polizzi | Chem Bio Eng., 2025, 2, 602–611
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Publication abstract
Yeasts have long been celebrated for their metabolic prowess, in particular, their ability to transform grain and fruit into valuable food products. In recent decades, humans have exploited them for pharmaceutical applications driven by advances in metabolic engineering and synthetic biology. Through convergence of these disciplines, this study highlights the development of a cell-free protein synthesis (CFPS) platform using Kluyveromyces lactis, a yeast prized for its role in the dairy industry. We present a workflow for preparing K. lactis extracts and incorporate lactose as a sustainable and cost-effective carbon source for biomass generation and as an energy source for CFPS. A semiautomated design-of-experiments (DoE) approach was undertaken, based on a Latin Hypercube experimental design, which tested 128 unique CFPS reaction mix compositions against a baseline optimized for Pichia pastoris. The optimized reaction mix was validated by the synthesis of two model proteins: green fluorescent protein (deGFP) and Erythropoietin (EPO), which is a clinically relevant therapeutic. We identified conditions with 4-fold improvement in yield with the optimized reaction producing 54 nM of EPO. By integrating lactose-based growth, protein synthesis, and rational optimization strategies, this study sets the scene for developing yeast-based CFPS platforms tailored for diverse applications, from biosensor development to industrially relevant biopharmaceutical production.
Publication 2: Energy Aware Technology Mapping of Genetic Logic Circuits
Erik Kubaczka, Maximilian Gehri, Jérémie J. M. Marlhens, Tobias Schwarz, Maik Molderings, Nicolai Engelmann, Hernan G. Garcia, Christian Hochberger and Heinz Koeppl | ACS Synth. Biol., 2024, 13, 3295–3311
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Publication abstract
Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers, as caused by the additional burden of artificial genetic circuits, shifts a cell’s priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation, which we link to the entropy production rate, and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit’s functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.
Publication 1: Mechanism-based and data-driven modeling in cell-free synthetic biology
Angelina Yurchenko, Gökçe Özkul, Natal A. W. van Riel, Jan C. M. van Hest and Tom F. A. de Greef | Chem. Commun., 2024,60, 6466-6475
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Publication abstract
Cell-free systems have emerged as a versatile platform in synthetic biology, finding applications in various areas such as prototyping synthetic circuits, biosensor development, and biomanufacturing. To streamline the prototyping process, cell-free systems often incorporate a modeling step that predicts the outcomes of various experimental scenarios, providing a deeper insight into the underlying mechanisms and functions. There are two recognized approaches for modeling these systems: mechanism-based modeling, which models the underlying reaction mechanisms; and data-driven modeling, which makes predictions based on data without preconceived interactions between system components. In this highlight, we focus on the latest advancements in both modeling approaches for cell-free systems, exploring their potential for the design and optimization of synthetic genetic circuits.