Evaluation of a Microreactor for Flow Biocatalysis by Combined Theory and Experiment

A Magnetosome-Based Platform for Flow Biocatalysis

Biocatalysis in flow reactor systems is of increasing importance for the transformation of the chemical industry. However, the necessary immobilization of biocatalysts remains a challenge. We here demonstrate that biogenic magnetic nanoparticles, so-called magnetosomes, represent an attractive alternative for the development of nanoscale particle formulations to enable high and stable conversion rates in biocatalytic flow processes. In addition to their intriguing material characteristics, such as high crystallinity, stable magnetic moments, and narrow particle size distribution, magnetosomes offer the unbeatable advantage over chemically synthesized nanoparticles that foreign protein "cargo" can be immobilized on the enveloping membrane via genetic engineering and thus, stably presented on the particle surface. To exploit these advantages, we develop a modular connector system in which abundant magnetosome membrane anchors are genetically fused with SpyCatcher coupling groups, allowing efficient covalent coupling with complementary SpyTag-functionalized proteins. The versatility of this approach is demonstrated by immobilizing a dimeric phenolic acid decarboxylase to SpyCatcher magnetosomes. The functionalized magnetosomes outperform similarly functionalized commercial particles by exhibiting stable substrate conversion during a 60 h period, with an average space-time yield of 49.2 mmol L^-1 h^-1. Overall, our results demonstrate that SpyCatcher magnetosomes significantly expand the genetic toolbox for particle surface functionalization and increase their application potential as nano-biocatalysts.

Modeling-Assisted Design of Thermostable Benzaldehyde Lyases from Rhodococcus erythropolis for Continuous Production of α-Hydroxy Ketones

Enantiopure α-hydroxy ketones are important building blocks of active pharmaceutical ingredients (APIs), which can be produced by thiamine-diphosphate-dependent lyases, such as benzaldehyde lyase. Here we report the discovery of a novel thermostable benzaldehyde lyase from Rhodococcus erythropolis R138 (ReBAL). While the overall sequence identity to the only experimentally confirmed benzaldehyde lyase from Pseudomonas fluorescens Biovar I (PfBAL) was only 65 %, comparison of a structural model of ReBAL with the crystal structure of PfBAL revealed only four divergent amino acids in the substrate binding cavity. Based on rational design, we generated two ReBAL variants, which were characterized along with the wild-type enzyme in terms of their substrate spectrum, thermostability and biocatalytic performance in the presence of different co-solvents. We found that the new enzyme variants have a significantly higher thermostability (up to 22 °C increase in T50 ) and a different co-solvent-dependent activity. Using the most stable variant immobilized in packed-bed reactors via the SpyCatcher/SpyTag system, (R)-benzoin was synthesized from benzaldehyde over a period of seven days with a stable space-time-yield of 9.3 mmol ⋅ L-1  ⋅ d-1 . Our work expands the important class of benzaldehyde lyases and therefore contributes to the development of continuous biocatalytic processes for the production of α-hydroxy ketones and APIs.

On the reproducibility of enzyme reactions and kinetic modelling

Enzyme reactions are highly dependent on reaction conditions. To ensure reproducibility of enzyme reaction parameters, experiments need to be carefully designed and kinetic modeling meticulously executed. Furthermore, to enable quality control of enzyme reaction parameters, the experimental conditions, the modeling process as well as the raw data need to be reported comprehensively. By taking these steps, enzyme reaction parameters can be open and FAIR (findable, accessible, interoperable, re-usable) as well as repeatable, replicable and reproducible. This review discusses these requirements and provides a practical guide to designing initial rate experiments for the determination of enzyme reaction parameters and gives an open, FAIR and re-editable example of the kinetic modeling of an enzyme reaction. Both the guide and example are scripted with Python in Jupyter Notebooks and are publicly available (https://fairdomhub.org/investigations/483/snapshots/1). Finally, the prerequisites of automated data analysis and machine learning algorithms are briefly discussed to provide further motivation for the comprehensive, open and FAIR reporting of enzyme reaction parameters.

Two-Phase Biocatalysis in Microfluidic Droplets

This Perspective discusses the literature related to two-phase biocatalysis in microfluidic droplets. Enzymes used as catalysts in biocatalysis are generally less stable in organic media than in their native aqueous environments; however, chemical and pharmaceutical compounds are often insoluble in water. The use of aqueous/organic two-phase media provides a solution to this problem and has therefore become standard practice for multiple biotransformations. In batch, two-phase biocatalysis is limited by mass transport, a limitation that can be overcome with the use of microfluidic systems. Although, two-phase biocatalysis in laminar flow systems has been extensively studied, microfluidic droplets have been primarily used for enzyme screening. In this Perspective, we summarize the limited published work on two-phase biocatalysis in microfluidic droplets and discuss the limitations, challenges, and future perspectives of this technology.

Towards a Novel Computer-Aided Optimization of Microreactors: Techno-Economic Evaluation of an Immobilized Enzyme System

Immobilized multi-enzyme cascades are increasingly used in microfluidic devices. In particular, their application in continuous flow reactors shows great potential, utilizing the benefits of reusability and control of the reaction conditions. However, capitalizing on this potential is challenging and requires detailed knowledge of the investigated system. Here, we show the application of computational methods for optimization with multi-level reactor design (MLRD) methodology based on the underlying physical and chemical processes. We optimize a stereoselective reduction of a diketone catalyzed by ketoreductase (Gre2) and Nicotinamidadenindinukleotidphosphat (NADPH) cofactor regeneration with glucose dehydrogenase (GDH). Both enzymes are separately immobilized on magnetic beads forming a packed bed within the microreactor. We derive optimal reactor feed concentrations and enzyme ratios for enhanced performance and a basic economic model in order to maximize the techno-economic performance (TEP) for the first reduction of 5-nitrononane-2,8-dione.