Alter Tobias B, Pieters Pascal A, Lloyd Colton J, Feist Adam M, Özdemir Emre, Palsson Bernhard O, Zielinski Daniel C
The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800, Kgs. Lyngby, Denmark.
Department of Bioengineering, University of California, 9500 Gilman Dr. #0412, La Jolla, San Diego, CA, 92093-0412, USA.
Metab Eng Commun. 2025 Feb 12;20:e00257. doi: 10.1016/j.mec.2025.e00257. eCollection 2025 Jun.
Whole-cell biocatalysis facilitates the production of a wide range of industrially and pharmaceutically relevant molecules from sustainable feedstocks such as plastic wastes, carbon dioxide, lignocellulose, or plant-based sugar sources. The identification and use of efficient enzymes in the applied biocatalyst is key to establishing economically feasible production processes. The generation and selection of favorable enzyme variants in adaptive laboratory evolution experiments using growth as a selection criterion is facilitated by tightly coupling enzyme catalytic activity to microbial metabolic activity. Here, we present a computational workflow to design strains that have a severe, growth-limiting metabolic chokepoint through a shared class of enzymes. The resulting chassis cell, termed enzyme selection system (ESS), is a platform for growth-coupling any enzyme from the respective enzyme class, thus offering cross-pathway application for enzyme engineering purposes. By applying the constraint-based modeling workflow, a publicly accessible database of 25,505 potential and experimentally tractable ESS designs was built for and a broad range of production pathways with biotechnological relevance. A model-based analysis of the generated design database reveals a general design principle that the target enzyme activity is linked to overall microbial metabolic activity, not just the synthesis of one biomass precursor. It can be observed that the stronger the predicted coupling between target enzyme and metabolic activity, the lower the maximum growth rate and therefore the viability of an ESS. Consequently, growth-coupling strategies with only suboptimal coupling strengths, as are included in the ESS design database, may be of interest for practical applications of ESSs in order to circumvent overly restrictive growth defects. In summary, the computed design database, which is accessible via https://biosustain.github.io/ESS-Designs/, and its analysis provide a foundation for the generation of valuable ESSs for enzyme optimization purposes and a range of biotechnological applications in general.
全细胞生物催化有助于从可持续原料（如塑料废料、二氧化碳、木质纤维素或植物基糖源）生产多种具有工业和药学相关性的分子。在所应用的生物催化剂中鉴定和使用高效酶是建立经济可行的生产工艺的关键。在以生长为选择标准的适应性实验室进化实验中，通过将酶催化活性与微生物代谢活性紧密耦合，有助于生成和选择有利的酶变体。在此，我们提出一种计算工作流程，以设计通过一类共享酶具有严重的、限制生长的代谢瓶颈的菌株。所得的底盘细胞，称为酶选择系统（ESS），是一个用于将来自相应酶类的任何酶与生长耦合的平台，从而为酶工程目的提供跨途径应用。通过应用基于约束的建模工作流程，为广泛的具有生物技术相关性的生产途径建立了一个可公开访问的包含25505个潜在且实验上易于处理的ESS设计的数据库。对生成的设计数据库进行基于模型的分析揭示了一个通用的设计原则，即目标酶活性与整体微生物代谢活性相关联，而不仅仅是一种生物质前体的合成。可以观察到，目标酶与代谢活性之间预测的耦合越强，最大生长速率越低，因此ESS的生存能力越低。因此，ESS设计数据库中包含的仅具有次优耦合强度的生长耦合策略可能对于ESS在实际应用中的应用很有意义，以规避过度限制性的生长缺陷。总之，通过https://biosustain.github.io/ESS-Designs/可访问的计算设计数据库及其分析为生成用于酶优化目的的有价值的ESS以及一般的一系列生物技术应用提供了基础。
