Molecular Basis for Converting (2S)-Methylsuccinyl-CoA Dehydrogenase into an Oxidase

Enzymatic Conversion of CO2: From Natural to Artificial Utilization

Enzymatic carbon dioxide fixation is one of the most important metabolic reactions as it allows the capture of inorganic carbon from the atmosphere and its conversion into organic biomass. However, due to the often unfavorable thermodynamics and the difficulties associated with the utilization of CO₂, a gaseous substrate that is found in comparatively low concentrations in the atmosphere, such reactions remain challenging for biotechnological applications. Nature has tackled these problems by evolution of dedicated CO₂-fixing enzymes, i.e., carboxylases, and embedding them in complex metabolic pathways. Biotechnology employs such carboxylating and decarboxylating enzymes for the carboxylation of aromatic and aliphatic substrates either by embedding them into more complex reaction cascades or by shifting the reaction equilibrium via reaction engineering. This review aims to provide an overview of natural CO₂-fixing enzymes and their mechanistic similarities. We also discuss biocatalytic applications of carboxylases and decarboxylases for the synthesis of valuable products and provide a separate summary of strategies to improve the efficiency of such processes. We briefly summarize natural CO₂ fixation pathways, provide a roadmap for the design and implementation of artificial carbon fixation pathways, and highlight examples of biocatalytic cascades involving carboxylases. Additionally, we suggest that biochemical utilization of reduced CO₂ derivates, such as formate or methanol, represents a suitable alternative to direct use of CO₂ and provide several examples. Our discussion closes with a techno-economic perspective on enzymatic CO₂ fixation and its potential to reduce CO₂ emissions.

A versatile active learning workflow for optimization of genetic and metabolic networks

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.

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, aimed at democratization and standardization, the authors describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets.

Alteration of Electron Acceptor Preferences in the Oxidative Half-Reaction of Flavin-Dependent Oxidases and Dehydrogenases

In this review, recent progress in the engineering of the oxidative half-reaction of flavin-dependent oxidases and dehydrogenases is discussed, considering their current and future applications in bioelectrochemical studies, such as for the development of biosensors and biofuel cells. There have been two approaches in the studies of oxidative half-reaction: engineering of the oxidative half-reaction with oxygen, and engineering of the preference for artificial electron acceptors. The challenges for engineering oxidative half-reactions with oxygen are further categorized into the following approaches: (1) mutation to the putative residues that compose the cavity where oxygen may be located, (2) investigation of the vicinities where the reaction with oxygen may take place, and (3) investigation of possible oxygen access routes to the isoalloxazine ring. Among these approaches, introducing a mutation at the oxygen access route to the isoalloxazine ring represents the most versatile and effective strategy. Studies to engineer the preference of artificial electron acceptors are categorized into three different approaches: (1) engineering of the charge at the residues around the substrate entrance, (2) engineering of a cavity in the vicinity of flavin, and (3) decreasing the glycosylation degree of enzymes. Among these approaches, altering the charge in the vicinity where the electron acceptor may be accessed will be most relevant.

Back to the future: Why we need enzymology to build a synthetic metabolism of the future

Biology is turning from an analytical into a synthetic discipline. This is especially apparent in the field of metabolic engineering, where the concept of synthetic metabolism has been recently developed. Compared to classical metabolic engineering efforts, synthetic metabolism aims at creating novel metabolic networks in a rational fashion from bottom-up. However, while the theoretical design of synthetic metabolic networks has made tremendous progress, the actual realization of such synthetic pathways is still lacking behind. This is mostly because of our limitations in enzyme discovery and engineering to provide the parts required to build synthetic metabolism. Here I discuss the current challenges and limitations in synthetic metabolic engineering and elucidate how modern day enzymology can help to build a synthetic metabolism of the future.

Special Issue: Flavoenzymes

The 19th International Symposium on Flavins and Flavoproteins was held from 2⁻6 July 2017 in Groningen, The Netherlands.[...].