Jin Shiyan, Farrand Isabella R, Chen Yan, Gin Jennifer W, Zhang Bo, Kirschke Elaine, Petzold Christopher J, Adams Paul D, O'Malley Michelle A
Department of Chemical Engineering, University of California, Santa Barbara, California, USA.
Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
mBio. 2025 Aug 5:e0100725. doi: 10.1128/mbio.01007-25.
The genomes of anaerobic gut fungi (AGF) encode a diverse array of carbohydrate-active enzymes (CAZymes), yet exceedingly few of these enzymes have been experimentally validated or expressed in heterologous systems. Here, we developed a predictive bioinformatic pipeline to annotate novel putative CAZymes from anaerobic fungi and validate their activity through large-scale heterologous expression in . A total of 173 fungal proteins from associated with biomass degradation were synthesized and expressed in , and 9.8% were soluble with expression levels exceeding 5% of the total proteome using high-throughput proteomic screening. Among these 17 heterologously expressed proteins, analysis with AlphaFold and FoldSeek predicted 13 multi-functional proteins containing catalytic domains fused with repetitive fungal dockerins, and half of the substrate predictions were experimentally validated. One promising enzyme, celsome_012, exhibited robust and specific activity against beechwood xylan at 37°C and pH 6.4, with titers that were also fivefold higher than those of other recombinant proteins screened here. Both Michaelis-Menten kinetics and the linearized Lineweaver-Burk equation yielded consistent values for , and its activation energy was estimated at 51.9 kJ/mol based on the Arrhenius model. This work supports the industrial translation of anaerobic fungal CAZymes due to their robust lignocellulolytic activity and provides a framework for prioritizing AGF proteins for efficient heterologous expression.IMPORTANCEEfficient breakdown of plant biomass is crucial for producing high-value bio-based products, but identifying enzymes that reduce deconstruction costs remains a challenge. In this study, we harnessed novel CAZymes encoded in the AGF genome through high-throughput proteomic screening for CAZyme expression to identify promising fungal enzymes suitable for large-scale production in . Additionally, we leveraged cutting-edge computational tools to predict enzyme structure and function, accelerating the screening process beyond traditional methods. Experimental validation confirmed the accuracy of these predictions and revealed a highly active novel xylanase, expanding the available enzyme toolbox for biomass conversion. Overall, this study represents a comprehensive large-scale screening campaign of putative AGF CAZymes, highlighting proteins amenable to overexpression, integrating advanced sequence and structural annotation, and identifying a robust, novel fungal xylanase for detailed biochemical characterization.
厌氧肠道真菌（AGF）的基因组编码了各种各样的碳水化合物活性酶（CAZymes），然而，这些酶中极少有经过实验验证或在异源系统中表达的。在此，我们开发了一种预测性生物信息学流程，用于注释来自厌氧真菌的新型假定CAZymes，并通过在……中的大规模异源表达来验证它们的活性。总共合成并表达了来自与生物质降解相关的……的173种真菌蛋白，通过高通量蛋白质组学筛选，9.8%的蛋白可溶，表达水平超过总蛋白质组的5%。在这17种异源表达的蛋白中，使用AlphaFold和FoldSeek分析预测有13种多功能蛋白，其催化结构域与重复性真菌dockerin融合，并且一半的底物预测得到了实验验证。一种有前景的酶celsome_012在37°C和pH 6.4条件下对山毛榉木聚糖表现出强大且特异的活性，其活性滴度也比在此筛选的其他重组蛋白高五倍。米氏动力学和线性化的Lineweaver - Burk方程得出的……值一致，基于阿伦尼乌斯模型估计其活化能为51.9 kJ/mol。这项工作支持了厌氧真菌CAZymes因其强大的木质纤维素分解活性而进行工业转化，并提供了一个框架，用于优先选择AGF蛋白以实现高效的异源表达。重要性植物生物质的高效分解对于生产高价值生物基产品至关重要，但识别能够降低解构成本的酶仍然是一项挑战。在本研究中，我们通过对CAZyme表达进行高通量蛋白质组学筛选，利用AGF基因组中编码的新型CAZymes来识别适合在……中大规模生产的有前景的真菌酶。此外，我们利用前沿的计算工具预测酶的结构和功能，加速了超越传统方法的筛选过程。实验验证证实了这些预测的准确性，并揭示了一种高活性的新型木聚糖酶，扩展了用于生物质转化的可用酶工具箱。总体而言，这项研究代表了对假定的AGF CAZymes进行的全面大规模筛选活动，突出了适合过表达的蛋白，整合了先进的序列和结构注释，并鉴定了一种强大的新型真菌木聚糖酶用于详细的生化表征。
