Lorenzi Marco, Gamache Mira T, Redman Holly J, Land Henrik, Senger Moritz, Berggren Gustav
Department of Chemistry - Ångström, Molecular Biomimetics, Uppsala University, Lägerhyddsvägen 1, 75120 Uppsala, Sweden.
Department of Chemistry - Ångström, Physical Chemistry, Uppsala University, Lägerhyddsvägen 1, 75120 Uppsala, Sweden.
ACS Sustain Chem Eng. 2022 Aug 22;10(33):10760-10767. doi: 10.1021/acssuschemeng.2c03657. Epub 2022 Aug 11.
Biohybrid technologies like semiartificial photosynthesis are attracting increased attention, as they enable the combination of highly efficient synthetic light-harvesters with the self-healing and outstanding performance of biocatalysis. However, such systems are intrinsically complex, with multiple interacting components. Herein, we explore a whole-cell photocatalytic system for hydrogen (H) gas production as a model system for semiartificial photosynthesis. The employed whole-cell photocatalytic system is based on cells heterologously expressing a highly efficient, but oxygen-sensitive, [FeFe] hydrogenase. The system is driven by the organic photosensitizer eosin Y under broad-spectrum white light illumination. The direct involvement of the [FeFe] hydrogenase in the catalytic reaction is verified spectroscopically. We also observe that provides protection against O damage, underscoring the suitability of this host organism for oxygen-sensitive enzymes in the development of (photo) catalytic biohybrid systems. Moreover, the study shows how factorial experimental design combined with analysis of variance (ANOVA) can be employed to identify relevant variables, as well as their interconnectivity, on both overall catalytic performance and O tolerance.
像半人工光合作用这样的生物杂交技术正吸引着越来越多的关注，因为它们能够将高效的合成光捕获器与生物催化的自我修复和出色性能相结合。然而，这类系统本质上很复杂，有多个相互作用的组件。在此，我们探索一种用于生产氢气（H₂）的全细胞光催化系统，作为半人工光合作用的模型系统。所采用的全细胞光催化系统基于异源表达高效但对氧敏感的[FeFe]氢化酶的细胞。该系统在广谱白光照射下由有机光敏剂曙红Y驱动。通过光谱学方法验证了[FeFe]氢化酶直接参与催化反应。我们还观察到[具体物质]能提供对氧损伤的保护，这突出了这种宿主生物体在（光）催化生物杂交系统开发中对于氧敏感酶的适用性。此外，该研究展示了如何将析因实验设计与方差分析（ANOVA）结合起来，以识别对整体催化性能和氧耐受性的相关变量及其相互关联性。
