Zengyi Shao

Fatty alcohols are important bio-based chemicals with applications in fuels, materials, and specialty products, yet their large-scale production from lignocellulosic biomass remains economically and environmentally challenging. This study presents an integrated framework combining experimental data, Aspen Plus process simulation, machine learning, and techno-economic and life-cycle assessment to evaluate fatty alcohol production from lignocellulosic feedstocks. A detailed process model was developed in Aspen Plus V14, incorporating pretreatment, fermentation in a novel modified Taylor Vortex Reactor (TVR), downstream separation, wastewater treatment, and combined heat and power generation. Experimentally informed relationships between fatty alcohol concentration and hydraulic retention time (HRT) were used to guide process modeling, while realistic biomass variability was represented using 3000 synthetic feedstock compositions generated by a generative adversarial network. Monte Carlo sampling enabled the execution of 3000 process simulations to train a machine-learning surrogate for rapid prediction of fatty alcohol production. Glucan availability and hydraulic retention time were the principal drivers of fatty alcohol production. Capital and operating cost were made responsive to both, which places the economic optimum between 60 and 66 h of retention time. Probability-based analysis indicates a minimum-selling price (MSP) of $30.6 ± 17.9 kg–1. A waterfall analysis indicates that simultaneous improvement in feedstock price, yield, capital cost, and operating hours would bring the MSP to approximately $3 kg–1. The corresponding global warming potential (GWP) is 2.78 ± 0.07 kg CO2-eq kg–1. Overall, this study demonstrates how data-driven process modeling can support large-scale uncertainty analysis, risk-informed decision making, and identification of economically and environmentally favorable operating regions for the sustainable production of fatty alcohols from lignocellulosic biomass.

Quantitative assessment of cellular oxidative stress requires simultaneous measurement of intracellular redox state and extracellular respiratory activity, yet integrated sensing approaches remain limited. Here, we present a dual-fluorescent sensing platform combining a genetically encoded redox biosensor (roGFP2□Tsa2ΔC _R ) with an optical oxygen sensor embedded in microwell plates for parallel, non-invasive quantification of intracellular reactive oxygen species (ROS) and oxygen consumption rates (OCR) in industrial yeast systems. The roGFP2-based sensor was stably expressed in Saccharomyces cerevisiae ( S. cerevisiae ) and Yarrowia lipolytica ( Y. lipolytica ), enabling dynamic monitoring of oxidative stress at population, single-cell, and subcellular levels, while oxygen-sensitive films provided real-time respiration measurements. Using this platform, we identified distinct redox–respiration phenotypes between the two yeasts. Crabtree-positive S. cerevisiae exhibited low OCR and mitochondrial ROS during glucose cultivation, whereas growth on glycerol increased OCR and mitochondrial ROS by ~2.5-fold and 12%, respectively. In contrast, the obligate respiratory yeast Y. lipolytica displayed 3-fold higher OCR and 16% lower mitochondrial ROS than respiring S. cerevisiae , indicating differences in respiratory oxidative burden. Antimycin A treatment reduced OCR by 60% in respiring S. cerevisiae while increasing mitochondrial ROS by 35%, whereas Y. lipolytica showed greater resistance to respiratory and oxidative perturbations. By integrating intracellular redox sensing with extracellular oxygen measurements, this platform enables quantitative coupling of redox state and respiration in living cells. The approach provides a scalable framework for evaluating cellular fitness, stress tolerance, and metabolic state in biomanufacturing and synthetic biology.

Robust strain stability is essential for industrial-scale fatty alcohol production, as metabolic burden and toxicity not only constrain productivity but also create selective pressure for low-producing or non-producing subpopulations. This genetic instability leads to genetic heterogeneity and compromises strain performance during large-scale fermentation. In this study, we investigated the production stability of fatty alcohol-producing Yarrowia lipolytica strains and developed systematic strategies to improve the genetic stability of engineered strains for scale-up production. In a mock fermentation scale-up, a fatty acyl-CoA reductase ( FAR )-expressing strain lost fatty alcohol production after five consecutive passages. To address this, we fused FAR to phosphoglycerate kinase I ( PGK1 ), a gene essential to cell growth, to promote the stability of FAR expression and prevent production loss. This strategy extended fatty alcohol production by one passage. Additionally, FAR was fused to GFP and extended production stability by four additional passages. In parallel, competitive co-culture experiments, in which producing strains were cultured alongside non-producing mutants, revealed that when non-producers emerged with a frequency of 10 ^{− 5} , they dominated the fermentation population within six passages; at 10%, they took only two passages. Furthermore, deep sequencing of strains that demonstrate different levels of stability and fatty alcohol productivity identified mutation patterns that contribute to strain instability. These findings provide insights into engineering Y. lipolytica with enhanced genetic stability for scale-up fatty alcohol production.

Plant-sourced aromatic amino acid (AAA) derivatives are a vast group of compounds with broad applications. Here, we present the development of a yeast consortium for efficient production of (S)-norcoclaurine, the key precursor for benzylisoquinoline alkaloid biosynthesis. A xylose transporter enables the concurrent mixed-sugar utilization in Scheffersomyces stipitis, which plays a crucial role in enhancing the flux entering the highly regulated shikimate pathway located upstream of AAA biosynthesis. Two quinate permeases isolated from Aspergillus niger facilitates shikimate translocation to the co-cultured Saccharomyces cerevisiae that converts shikimate to (S)-norcoclaurine, resulting in the maximal titer (11.5 mg/L), nearly 110-fold higher than the titer reported for an S. cerevisiae monoculture. Our findings magnify the potential of microbial consortium platforms for the economical de novo synthesis of complex compounds, where pathway modularization and compartmentalization in distinct specialty strains enable effective fine-tuning of long biosynthetic pathways and diminish intermediate buildup, thereby leading to increases in production.

Plant-sourced aromatic amino acid (AAA) derivatives are a vast group of compounds with broad applications. This study focuses on the development of a yeast consortium for efficient production of (S)-norcoclaurine, the key precursor for benzylisoquinoline alkaloid biosynthesis. A novel xylose-specific transporter insensitive to glucose inhibition enabled the concurrent mixed-sugar utilization in Scheffersomyces stipitis, which played a crucial role in enhancing the flux entering the highly regulated shikimate pathway located upstream of AAA biosynthesis. Two novel quinate permeases isolated from Aspergillus niger facilitated shikimate translocation to the co-cultured Saccharomyces cerevisiae that converted shikimate to (S)-norcoclaurine, resulting in the highest titer (4.2 mg/L) ever reported in literature, nearly 40-fold higher than the best titer from an S. cerevisiae monoculture. Our findings magnify the potential of microbial consortium platforms for the economical de novo synthesis of complex compounds, where pathway modularization and compartmentalization in distinct specialty strains enable effective fine-tuning of long biosynthetic pathways and diminish intermediate buildup, thereby leading to remarkable increases in production.

Inefficient homology-directed repair (HDR) constrains CRISPR–Cas9 genome editing in organisms that preferentially employ nonhomologous end joining (NHEJ) to fix DNA double-strand breaks (DSBs). Current strategies used to alleviate NHEJ proficiency involve NHEJ disruption. To confer precision editing without NHEJ disruption, we identified the shortcomings of the conventional CRISPR platforms and developed a CRISPR platform—lowered indel nuclease system enabling accurate repair (LINEAR)—which enhanced HDR rates (to 67–100%) compared to those in previous reports using conventional platforms in four NHEJ-proficient yeasts. With NHEJ preserved, we demonstrate its ability to survey genomic landscapes, identifying loci whose spatiotemporal genomic architectures yield favorable expression dynamics for heterologous pathways. We present a case study that deploys LINEAR precision editing and NHEJ-mediated random integration to rapidly engineer and optimize a microbial factory to produce (S)-norcoclaurine. Taken together, this work demonstrates how to leverage an antagonizing pair of DNA DSB repair pathways to expand the current collection of microbial factories.