Detoxification as metabolic rewiring: carbon and redox recovery from lignocellulosic inhibitors in biorefinery hosts

The pretreatment process of lignocellulosic biomass results in the formation of inhibitory by-products such as furan aldehydes, phenolics, and weak acids that hinder the process of microbial fermentation. Historically, the detoxification process has been regarded as an exercise in waste management, resulting in carbon loss and reduced strength. The current review illustrates how detoxification can be viewed from a new perspective, making it possible to recover carbon and balance redox simultaneously. The results of our analysis indicate that oxidation-based detoxification pathways, and particularly the conversion of furfural into 2-furoic acid by aldehyde hydrogenases followed by entry into the TCA cycle, allow for the recovery of five carbon atoms from each molecule of inhibitor. Our findings revealed the importance of cofactor specificity in the detoxification process: NADPH-dependent reductases negatively affect biosynthesis while their NADH-dependent or bifunctional counterparts allow for the retention of the biosynthetic potential. The modification of aldo-keto reductases to favor NADH along with the combination of detoxification reactions with transhydrogenases and fusion proteins facilitate the process of detoxification without harming product yields. The integration of processes into host organisms is of critical significance acetyl-CoA pathway serves well for lipid synthesis by Yarrowia lipolytica while TCA pathway is beneficial for Pseudomonas spp. The co-utilization of inhibitors with sugars in conditions representative of real hydrolysates offers a win-win situation for carbon recovery when detoxification routes are implemented prior to key metabolic pathways. This approach allows us to regard the inhibitors as auxiliary substrates and develop biorefineries that benefit from the detoxication step in terms of increased product yield. It appears that industrial implementation will require systemic modeling and rational enzyme redesign.