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The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L-1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

Jasmonates are a class of plant hormones with many agricultural applications and potential medicinal properties. However, the low content of jasmonates in plants and environmental issues with their production make their supply challenging. In the present study, we report the de novo microbial biosynthesis of jasmonic acid and its derivatives, methyl jasmonate and jasmonoyl isoleucine, from glucose using an engineered baker’s yeast. The study uses enzymes located in the endoplasmic reticulum and cytosol to generate the intermediates α-linolenic acid and cis-12-oxophytodienoic acid. Our final engineered stain, which integrates 15 heterologous genes from diverse plants and fungi and had 3 of its native genes deleted, produces jasmonic acid at titres of 19.0 mg l−1 in flask cultures through in vitro supplementation of α-linolenic acid. In addition to the well-known natural structures (−)-jasmonic acid and (+)-epi-jasmonic acid, the engineered yeast also synthesized the previously unobserved unnatural structures (+)-jasmonic acid and (−)-epi-jasmonic acid. These results demonstrate that yeast is a scalable and sustainable platform to produce both naturally occurring jasmonates and those structures not found naturally in plants. (Figure presented.)

The increase in population-related and environmental issues has emphasized the need for more efficient and sustainable production strategies for foods and chemicals. Carbohydrates are macronutrients sourced from crops and undergone transformation into various products ranging from foods to chemicals. Continuous efforts have led to the identification of a promising hybrid system that couples the electrochemical reduction of CO2 to intermediates containing one to three carbons (C1–3) with the transformation of the intermediates using engineered microorganisms into valuable products. Here we use yeast to transform C1–3 substrates into glucose and structurally tailored glucose derivatives, such as the sugar alcohol myo-inositol, the amino monosaccharide glucosamine, the disaccharide sucrose and the polysaccharide starch. By metabolic rewiring and mitigation of glucose repression, the titre of glucose and sucrose reached dozens of grams per litre. These results provide directions for microbial sugar-derived foods and chemicals production from renewable reduced CO2-based feedstocks. [Figure not available: see fulltext.].

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number (kcat), Michaelis constant (Km), and catalytic efficiency (kcat / Km), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust kcat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

Activating inert substrates is a challenge in nature and synthetic chemistry, but essential for creating functionally active molecules. In this work, we used a combinatorial optimization approach to assemble cytochrome P450 monooxygenases (CYPs) and reductases (CPRs) to achieve a target product profile. By creating 110 CYP-CPR pairs and iteratively screening different pairing libraries, we demonstrated a framework for establishing a CYP network that catalyzes six oxidation reactions at three different positions of a chemical scaffold. Target product titer was improved by remodeling endoplasmic reticulum (ER) size and spatially controlling the CYPs configuration on the ER. Out of 47 potential products that could be synthesized, 86% of the products synthesized by the optimized network was our target compound quillaic acid (QA), the aglycone backbone of many pharmaceutically important saponins, and fermentation achieved QA titer 2.23 g/L.

Valerolactam is a monomer used to manufacture high-value nylon-5 and nylon-6,5. However, the biological production of valerolactam has been limited by the inadequate efficiency of enzymes to cyclize 5-aminovaleric acid to produce valerolactam. In this study, we engineered Corynebacterium glutamicum with a valerolactam biosynthetic pathway consisting of DavAB from Pseudomonas putida to convert L-lysine to 5-aminovaleric acid and β-alanine CoA transferase (Act) from Clostridium propionicum to produce valerolactam from 5-aminovaleric acid. Most of the L-lysine was converted into 5-aminovaleric acid, but promoter optimization and increasing the copy number of Act were insufficient to significantly improve the titer of valerolactam. To eliminate the bottleneck at Act, we designed a dynamic upregulation system (a positive feedback loop based on the valerolactam biosensor ChnR/Pb). We used laboratory evolution to engineer ChnR/Pb to have higher sensitivity and a higher dynamic output range, and the engineered ChnR-B1/Pb-E1 system was used to overexpress the rate-limiting enzymes (Act/ORF26/CaiC) that cyclize 5-aminovaleric acid into valerolactam. In glucose fed-batch culture, we obtained 12.33 g/L valerolactam from the dynamic upregulation of Act, 11.88 g/L using ORF26, and 12.15 g/L using CaiC. Our engineered biosensor (ChnR-B1/Pb-E1 system) was also sensitive to 0.01-100 mM caprolactam, which suggests that this dynamic upregulation system can be used to enhance caprolactam biosynthesis in the future.

BackgroundSaccharomyces cerevisiae is an important synthetic biology chassis for microbial production of valuable molecules. Promoter engineering has been frequently applied to generate more synthetic promoters with a variety of defined characteristics in order to achieve a well-regulated genetic network for high production efficiency. Galactose-inducible (GAL) expression systems, composed of GAL promoters and multiple GAL regulators, have been widely used for protein overexpression and pathway construction in S. cerevisiae. However, the function of each element in synthetic promoters and how they interact with GAL regulators are not well known.ResultsHere, a library of synthetic GAL promoters demonstrate that upstream activating sequences (UASs) and core promoters have a synergistic relationship that determines the performance of each promoter under different carbon sources. We found that the strengths of synthetic GAL promoters could be fine-tuned by manipulating the sequence, number, and substitution of UASs. Core promoter replacement generated synthetic promoters with a twofold strength improvement compared with the GAL1 promoter under multiple different carbon sources in a strain with GAL1 and GAL80 engineering. These results represent an expansion of the classic GAL expression system with an increased dynamic range and a good tolerance of different carbon sources.ConclusionsIn this study, the effect of each element on synthetic GAL promoters has been evaluated and a series of well-controlled synthetic promoters are constructed. By studying the interaction of synthetic promoters and GAL regulators, synthetic promoters with an increased dynamic range under different carbon sources are created.

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.

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Cannabis sativa L. has been cultivated and used around the globe for its medicinal properties for millennia1. Some cannabinoids, the hallmark constituents of Cannabis, and their analogues have been investigated extensively for their potential medical applications2. Certain cannabinoid formulations have been approved as prescription drugs in several countries for the treatment of a range of human ailments3. However, the study and medicinal use of cannabinoids has been hampered by the legal scheduling of Cannabis, the low in planta abundances of nearly all of the dozens of known cannabinoids4, and their structural complexity, which limits bulk chemical synthesis. Here we report the complete biosynthesis of the major cannabinoids cannabigerolic acid, Δ9-tetrahydrocannabinolic acid, cannabidiolic acid, Δ9-tetrahydrocannabivarinic acid and cannabidivarinic acid in Saccharomyces cerevisiae, from the simple sugar galactose. To accomplish this, we engineered the native mevalonate pathway to provide a high flux of geranyl pyrophosphate and introduced a heterologous, multi-organism-derived hexanoyl-CoA biosynthetic pathway5. We also introduced the Cannabis genes that encode the enzymes involved in the biosynthesis of olivetolic acid6, as well as the gene for a previously undiscovered enzyme with geranylpyrophosphate:olivetolate geranyltransferase activity and the genes for corresponding cannabinoid synthases7,8. Furthermore, we established a biosynthetic approach that harnessed the promiscuity of several pathway genes to produce cannabinoid analogues. Feeding different fatty acids to our engineered strains yielded cannabinoid analogues with modifications in the part of the molecule that is known to alter receptor binding affinity and potency9. We also demonstrated that our biological system could be complemented by simple synthetic chemistry to further expand the accessible chemical space. Our work presents a platform for the production of natural and unnatural cannabinoids that will allow for more rigorous study of these compounds and could be used in the development of treatments for a variety of human health problems.

We have developed a novel antibody-drug conjugate (ADC) that can selectively deliver the Lck inhibitor dasatinib to human T lymphocytes. This ADC is based on a humanized antibody that selectively binds with high affinity to CXCR4, an antigen that is selectively expressed on hematopoietic cells. The resulting dasatinib-antibody conjugate suppresses T-cell-receptor (TCR)-mediated T-cell activation and cytokine expression with low nM EC50 and has minimal effects on cell viability. This ADC may lead to a new class of selective immunosuppressive drugs with improved safety and extend the ADC strategy to the targeted delivery of kinase inhibitors for indications beyond oncology.

SUMMARY: Chromoplasts act as a metabolic sink for carotenoids, in which plastoglobules serve as versatile lipoprotein particles. PGs in chloroplasts have been characterized. However, the features of PGs from non‐photosynthetic plastids are poorly understood. We found that the development of chromoplast plastoglobules (CPGs) in globular and crystalloid chromoplasts of citrus is associated with alterations in carotenoid storage. Using Nycodenz density gradient ultracentrifugation, an efficient protocol for isolating highly purified CPGs from sweet orange (Citrus sinensis) pulp was established. Forty‐four proteins were defined as likely comprise the core proteome of CPGs using comparative proteomics analysis. Lipidome analysis of different chromoplast microcompartments revealed that the nonpolar microenvironment within CPGs was modified by 35 triacylglycerides, two sitosterol esters, and one stigmasterol ester. Manipulation of the CPG‐localized gene CsELT1 (esterase/lipase/thioesterase) in citrus calli resulted in increased lipids and carotenoids, which is further evidence that the nonpolar microenvironment of CPGs contributes to carotenoid accumulation and storage in the chromoplasts. This multi‐feature analysis of CPGs sheds new light on the role of chromoplasts in carotenoid metabolism, paving the way for manipulating carotenoid content in citrus fruit and other crops. [ABSTRACT FROM AUTHOR]