Metabolic Engineering: Methodologies and Applications

Re-vitalizing wastewater: Nutrient recovery and carbon capture through microbe-algae synergy using omics-biology

Increasing amounts of wastewater is the most pervasive and challenging environmental problem globally. Conventional treatment methods are costly and entail huge energy, carbon consumption and greenhouse gas emissions. Owing to their unique ability of carbon capturing and resource recovery, microalgae-microbiome based treatment is a potential approach and is widely used for carbon-neutral wastewater treatment. Microalgae-bacteria synergy (i.e., the functionally beneficial microbial synthetic communities) performs better and enhances carbon-sequestration and nutrient recovery from wastewater treatment plants. This review presents a comprehensive information regarding the potential of microalgae-microbiome as a sustainable agent for wastewater and discusses synergistic approaches for effective nutrient removal. Moreover, this review discusses, the role of omics-biology and Insilco approaches in unravelling and understanding the algae-microbe synergism and their response toward wastewater treatment. Finally, it discusses various microbiome engineering approaches for developing the effective microalgae-bacteria partners for carbon sequestration and nutrient recovery from wastewater, and summarizes future research perspectives on microalgae-microbiome based bioremediation.

Cell factory design with advanced metabolic modelling empowered by artificial intelligence

Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a bio-based product succeeds or fails in the fierce competition with petroleum-based products. To date, one of the greatest challenges in synthetic biology is the creation of high-performance cell factories in a consistent and efficient manner. As so-called white-box models, numerous metabolic network models have been developed and used in computational strain design. Moreover, great progress has been made in AI-powered strain engineering in recent years. Both approaches have advantages and disadvantages. Therefore, the deep integration of AI with metabolic models is crucial for the construction of superior cell factories with higher titres, yields and production rates. The detailed applications of the latest advanced metabolic models and AI in computational strain design are summarized in this review. Additionally, approaches for the deep integration of AI and metabolic models are discussed. It is anticipated that advanced mechanistic metabolic models powered by AI will pave the way for the efficient construction of powerful industrial chassis strains in the coming years.

Multiplex Expression Cassette Assembly: A flexible and versatile method for building complex genetic circuits in conventional vectors

The manipulation of multiple transcription units for simultaneous and coordinated expression is not only key to building complex genetic circuits to accomplish diverse functions in synthetic biology, but is also important in crop breeding for significantly improved productivity and overall performance. However, building constructs with multiple independent transcription units for fine-tuned and coordinated regulation is complicated and time-consuming. Here, we introduce the Multiplex Expression Cassette Assembly (MECA) method, which modifies canonical vectors compatible with Golden Gate Assembly, and then uses them to produce multi-cassette constructs. By embedding the junction syntax in primers that are used to amplify functional elements, MECA is able to make complex constructs using only one intermediate vector and one destination vector via two rounds of one-pot Golden Gate assembly reactions, without the need for dedicated vectors and a coherent library of standardized modules. As a proof-of-concept, we modified eukaryotic and prokaryotic expression vectors to generate constructs for transient expression of green fluorescent protein and β-glucuronidase in Nicotiana benthamiana, genome editing to block monoterpene metabolism in tomato glandular trichomes, production of betanin in tobacco and synthesis of β-carotene in Escherichia coli. Additionally, we engineered the stable production of thymol and carvacrol, bioactive compounds from Lamiaceae family plants, in glandular trichomes of tobacco. These results demonstrate that MECA is a flexible, efficient and versatile method for building complex genetic circuits, which will not only play a critical role in plant synthetic biology, but also facilitate improving agronomic traits and pyramiding traits for the development of next-generation elite crops.

Harnessing and Mimicking Bacterial Features to Combat Cancer: From Living Entities to Artificial Mimicking Systems

Bacterial-derived micro-/nanomedicine has garnered considerable attention in anticancer therapy, owing to the unique natural features of bacteria, including specific targeting ability, immunogenic benefits, physicochemical modifiability, and biotechnological editability. Besides, bacterial components have also been explored as promising drug delivery vehicles. Harnessing these bacterial features, cutting-edge physicochemical and biotechnologies have been applied to attenuated tumor-targeting bacteria with unique properties or functions for potent and effective cancer treatment, including strategies of gene-editing and genetic circuits. Further, the advent of bacteria-inspired micro-/nanorobots and mimicking artificial systems has furnished fresh perspectives for formulating strategies for developing highly efficient drug delivery systems. Focusing on the unique natural features and advantages of bacteria, this review delves into advances in bacteria-derived drug delivery systems for anticancer treatment in recent years, which has experienced a process from living entities to artificial mimicking systems. Meanwhile, a summary of relative clinical trials is provided and primary challenges impeding their clinical application are discussed. Furthermore, future directions are suggested for bacteria-derived systems to combat cancer.

Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling

Engineering metabolism to efficiently produce chemicals from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important tools for programming multi-gene expression, but poor predictability of guide RNA folding can disrupt expression control. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) in E. coli with a computational kinetic parameter describing scRNA folding rate into the active structure (rS = 0.8). This parameter also enables forward design of scRNAs, allowing us to design a system of three synthetic CRISPRa promoters that can orthogonally activate (>35-fold) expression of chosen outputs. Through combinatorial activation tuning, we profile a three-dimensional design space expressing two different biosynthetic pathways, demonstrating variable production of pteridine and human milk oligosaccharide products. This RNA design approach aids combinatorial optimization of metabolic pathways and may accelerate routine design of effective multi-gene regulation programs in bacterial hosts.

AutoBioTech─A Versatile Biofoundry for Automated Strain Engineering

The inevitable transition from petrochemical production processes to renewable alternatives has sparked the emergence of biofoundries in recent years. Manual engineering of microbes will not be sufficient to meet the ever-increasing demand for novel producer strains. Here we describe the AutoBioTech platform, a fully automated laboratory system with 14 devices to perform operations for strain construction without human interaction. Using modular workflows, this platform enables automated transformations of Escherichia coli with plasmids assembled via modular cloning. A CRISPR/Cas9 toolbox compatible with existing modular cloning frameworks allows automated and flexible genome editing of E. coli. In addition, novel workflows have been established for the fully automated transformation of the Gram-positive model organism Corynebacterium glutamicum by conjugation and electroporation, with the latter proving to be the more robust technique. Overall, the AutoBioTech platform excels at versatility due to the modularity of workflows and seamless transitions between modules. This will accelerate strain engineering of Gram-negative and Gram-positive bacteria.

High-Throughput Metabolite Analysis of Unicellular Microalgae by Orthogonal Hybrid Ionization Label-Free Mass Cytometry

Microalgae metabolite analysis is fundamental for the rational design of metabolic engineering strategies for the biosynthesis of high-value products. Mass spectrometry (MS) has been utilized for single-cell microalgae analysis. However, limitations in the detection throughput and polarities of detectable substances make it difficult to realize high-throughput screening of high-performance microalgae. Herein, a plasma-assisted label-free mass cytometry, named as PACyESI-MS, was proposed combining the advantages of orthogonal hybrid ionization and high-throughput MS analysis, which realized rapid metabolite detection of single microalgae. The cell detection throughput of PACyESI-MS was up to 52 cells/min. Dozens of the critical primary and secondary metabolites within single microalgae were detected simultaneously, including pigments, lipids, and energy metabolites. Furthermore, metabolite changes of Chlamydomonas reinhardtii and Haematococcus pluvialis under nitrogen deficiency stress were studied. Discrimination of Chlamydomonas under different nutrient conditions was realized using single-cell metabolite profiles obtained by PACyESI-MS. The relationships between the accumulation of bioactive astaxanthin and changes in functional primary metabolites of Haematococcus were investigated. It was demonstrated that PACyESI-MS can detect the flexible change of metabolites in single microalgae cells under different nutritional conditions and during the synthesis of high-value products, which is expected to become an important tool for the design of metabolic engineering-based high-performance microalgae factories.

Engineering microbial metabolic homeostasis for chemicals production

Microbial-based bio-refining promotes the development of a biotechnology revolution to encounter and tackle the enormous challenges in petroleum-based chemical production by biomanufacturing, biocomputing, and biosensing. Nevertheless, microbial metabolic homeostasis is often incompatible with the efficient synthesis of bioproducts mainly due to: inefficient metabolic flow, robust central metabolism, sophisticated metabolic network, and inevitable environmental perturbation. Therefore, this review systematically summarizes how to optimize microbial metabolic homeostasis by strengthening metabolic flux for improving biotransformation turnover, redirecting metabolic direction for rewiring bypass pathway, and reprogramming metabolic network for boosting substrate utilization. Future directions are also proposed for providing constructive guidance on the development of industrial biotechnology.

Research progress on biosynthesis of erythritol and multi-dimensional optimization of production strategies

Erythritol, as a new type of natural sweetener, has been widely used in food, medical, cosmetics, pharmaceutical and other fields due to its unique physical and chemical properties and physiological functions. In recent years, with the continuous development of strategies such as synthetic biology, metabolic engineering, omics-based systems biology and high-throughput screening technology, people's understanding of the erythritol biosynthesis pathway has gradually deepened, and microbial cell factories with independent modification capabilities have been successfully constructed. In this review, the cheap feedstocks for erythritol synthesis are introduced in detail, the environmental factors affecting the synthesis of erythritol and its regulatory mechanism are described, and the tools and strategies of metabolic engineering involved in erythritol synthesis are summarized. In addition, the study of erythritol derivatives is helpful in expanding its application field. Finally, the challenges that hinder the effective production of erythritol are discussed, which lay a foundation for the green, efficient and sustainable production of erythritol in the future and breaking through the bottleneck of production.

TRYing to evaluate production costs in microbial biotechnology

Microbial fermentations offer the opportunity to produce a wide range of chemicals in a sustainable fashion, but it is important to carefully evaluate the production costs. This can be done on the basis of evaluation of the titer, rate, and yield (TRY) of the fermentation process. Here we describe how the three TRY metrics impact the technoeconomics of a microbial fermentation process, and we illustrate the use of these for evaluation of different processes in the production of two commodity chemicals, 1,3-propanediol (PDO) and ethanol, as well as for the fine chemical penicillin. On the basis of our discussions, we provide some recommendations on how the TRY metrics should be reported when new processes are described.

Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides

BACKGROUND

The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers.

RESULTS

We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides. One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation.

CONCLUSIONS

Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

Self-Buffering system for Cost-Effective production of lactic acid from glucose and xylose using Acid-Tolerant Issatchenkia orientalis

This study presents a cost-effective strategy for producing organic acids from glucose and xylose using the acid-tolerant yeast, Issatchenkia orientalis. I. orientalis was engineered to produce lactic acid from xylose, and the resulting strain, SD108XL, successfully converted sorghum hydrolysates into lactic acid. In order to enable low-pH fermentation, a self-buffering strategy, where the lactic acid generated by the SD108XL strain during fermentation served as a buffer, was developed. As a result, the SD108 strain produced 67 g/L of lactic acid from 73 g/L of glucose and 40 g/L of xylose, simulating a sugar composition of sorghum biomass hydrolysates. Moreover, techno-economic analysis underscored the efficiency of the self-buffering strategy in streamlining the downstream process, thereby reducing production costs. These results demonstrate the potential of I. orientalis as a platform strain for the cost-effective production of organic acids from cellulosic hydrolysates.

A pilot oral history of plant synthetic biology

The whole field of synthetic biology (SynBio) is only about 20 years old, and plant SynBio is younger still. Nevertheless, within that short time, SynBio in general has drawn more scientific, philosophical, government, and private-sector interest than anything in biology since the recombinant DNA revolution. Plant SynBio, in particular, is now drawing more and more interest in relation to plants' potential to help solve planetary problems such as carbon capture and storage and replacing fossil fuels and feedstocks. As plant SynBio is so young and so fast-developing, we felt it was too soon to try to analyze its history. Instead, we set out to capture the essence of plant SynBio's origins and early development through interviews with 8 of the field's founders, representing 5 countries and 3 continents. We then distilled these founders' personal recollections and reflections into this review, centering the narrative on timelines for pivotal events, articles, funding programs, and quoting from interviews. We have archived the interview recordings and documented timeline entries. This work provides a resource for future historical scholarship.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

CRISPR-COPIES: an in silico platform for discovery of neutral integration sites for CRISPR/Cas-facilitated gene integration

The CRISPR/Cas system has emerged as a powerful tool for genome editing in metabolic engineering and human gene therapy. However, locating the optimal site on the chromosome to integrate heterologous genes using the CRISPR/Cas system remains an open question. Selecting a suitable site for gene integration involves considering multiple complex criteria, including factors related to CRISPR/Cas-mediated integration, genetic stability, and gene expression. Consequently, identifying such sites on specific or different chromosomal locations typically requires extensive characterization efforts. To address these challenges, we have developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. This tool leverages ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search, and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. As a proof of concept, we utilized CRISPR-COPIES to characterize neutral integration sites in three diverse species: Saccharomyces cerevisiae, Cupriavidus necator, and HEK293T cells. In addition, we developed a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate that CRISPR-COPIES will serve as a valuable tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, enable rapid strain construction to produce valuable biochemicals, and support human gene and cell therapy applications.

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

A major challenge in the fields of biological imaging and synthetic biology is noninvasively visualizing the functions of natural and engineered cells inside opaque samples such as living animals. One promising technology that addresses this limitation is ultrasound (US), with its penetration depth of several cm and spatial resolution on the order of 100 µm. 1 Within the past decade, reporter genes for US have been introduced 2,3 and engineered 4,5 to link cellular functions to US signals via heterologous expression in commensal bacteria and mammalian cells. These acoustic reporter genes (ARGs) represent a novel class of genetically encoded US contrast agent, and are based on air-filled protein nanostructures called gas vesicles (GVs). 6 Just as the discovery of fluorescent proteins was followed by the improvement and diversification of their optical properties through directed evolution, here we describe the evolution of GVs as acoustic reporters. To accomplish this task, we establish high-throughput, semi-automated acoustic screening of ARGs in bacterial cultures and use it to screen mutant libraries for variants with increased nonlinear US scattering. Starting with scanning site saturation libraries for two homologs of the primary GV structural protein, GvpA/B, two rounds of evolution resulted in GV variants with 5- and 14-fold stronger acoustic signals than the parent proteins. We anticipate that this and similar approaches will help high-throughput protein engineering play as large a role in the development of acoustic biomolecules as it has for their fluorescent counterparts.

Synthetically-primed adaptation of Pseudomonas putida to a non-native substrate D-xylose

To broaden the substrate scope of microbial cell factories towards renewable substrates, rational genetic interventions are often combined with adaptive laboratory evolution (ALE). However, comprehensive studies enabling a holistic understanding of adaptation processes primed by rational metabolic engineering remain scarce. The industrial workhorse Pseudomonas putida was engineered to utilize the non-native sugar D-xylose, but its assimilation into the bacterial biochemical network via the exogenous xylose isomerase pathway remained unresolved. Here, we elucidate the xylose metabolism and establish a foundation for further engineering followed by ALE. First, native glycolysis is derepressed by deleting the local transcriptional regulator gene hexR. We then enhance the pentose phosphate pathway by implanting exogenous transketolase and transaldolase into two lag-shortened strains and allow ALE to finetune the rewired metabolism. Subsequent multilevel analysis and reverse engineering provide detailed insights into the parallel paths of bacterial adaptation to the non-native carbon source, highlighting the enhanced expression of transaldolase and xylose isomerase along with derepressed glycolysis as key events during the process.

Recent progress in the reprogramming of nonribosomal peptide synthetases

Nonribosomal peptide synthetases (NRPSs) biosynthesize nonribosomal peptide (NRP) natural products, which belong to the most promising resources for drug discovery and development because of their wide range of therapeutic applications. The results of genetic, biochemical, and bioinformatics analyses have enhanced our understanding of the mechanisms of the NRPS machinery. A major goal in NRP biosynthesis is to reprogram the NRPS machinery to enable the biosynthetic production of designed peptides. Reprogramming strategies for the NRPS machinery have progressed considerably in recent years, thereby increasing the yields and generating modified peptides. Here, the recent progress in NRPS reprogramming and its application in peptide synthesis are described.

Metabolic engineering of Saccharomyces cerevisiae for de novo production of odd-numbered medium-chain fatty acids

Odd-numbered fatty acids (FAs) have been widely used in nutrition, agriculture, and chemical industries. Recently, some studies showed that they could be produced from bacteria or yeast, but the products are almost exclusively odd-numbered long-chain FAs. Here we report the design and construction of two biosynthetic pathways in Saccharomyces cerevisiae for de novo production of odd-numbered medium-chain fatty acids (OMFAs) via ricinoleic acid and 10-hydroxystearic acid, respectively. The production of OMFAs was enabled by introducing a hydroxy fatty acid cleavage pathway, including an alcohol dehydrogenase from Micrococcus luteus, a Baeyer-Villiger monooxygenase from Pseudomonas putida, and a lipase from Pseudomonas fluorescens. These OMFA biosynthetic pathways were optimized by eliminating the rate-limiting step, generating heptanoic acid, 11-hydroxyundec-9-enoic acid, nonanoic acid, and 9-hydroxynonanoic acid at 7.83 mg/L, 9.68 mg/L, 9.43 mg/L and 13.48 mg/L, respectively. This work demonstrates the biological production of OMFAs in a sustainable manner in S. cerevisiae.

Reprogramming Metabolic Flux in Escherichia Coli to Enhance Chondroitin Production

Reprogramming metabolic flux is a promising approach for constructing efficient microbial cell factories (MCFs) to produce chemicals. However, how to boost the transmission efficiency of metabolic flux is still challenging in complex metabolic pathways. In this study, metabolic flux is systematically reprogrammed by regulating flux size, flux direction, and flux rate to build an efficient MCF for chondroitin production. The ammoniation pool for UDP-GalNAc synthesis and the carbonization pool for UDP-GlcA synthesis are first enlarged to increase flux size for providing enough precursors for chondroitin biosynthesis. Then, the ammoniation pool and the carbonization pool are rematched using molecular valves to shift flux direction from cell growth to chondroitin biosynthesis. Next, the adaptability of polymerization pool with the ammoniation and carbonization pools is fine-tuned by dynamic and static valve-based adapters to accelerate flux rate for polymerizing UDP-GalNAc and UDP-GlcA to produce chondroitin. Finally, the engineered strain E. coli F51 is able to produce 9.2 g L-1 chondroitin in a 5-L bioreactor. This strategy shown here provides a systematical approach for regulating metabolic flux in complex metabolic pathways for efficient biosynthesis of chemicals.

Design of a dual-responding genetic circuit for high-throughput identification of L-threonine-overproducing Escherichia coli

L-threonine is a crucial amino acid that is extensively employed in the realms of food, animal feed and pharmaceuticals. Unfortunately, the lack of an appropriate biosensor has hindered the establishment of a robust high-throughput screening (HTS) system for the identification of the desired strains from random mutants. In this study, a dual-responding genetic circuit that capitalizes on the L-threonine inducer-like effect, the L-threonine riboswitch, and a signal amplification system was designed for the purpose of screening L-threonine overproducers. This platform effectively enhanced the performance of the enzyme and facilitated the identification of high L-threonine-producing strains from a random mutant library. Consequently, pathway optimization and directed evolution of the key enzyme enhanced L-threonine production by 4 and 7-fold, respectively. These results demonstrate the potential of biosensor design for dynamic metabolite detection and offer a promising tool for HTS and metabolic regulation for the development of L-threonine-hyperproducing strains.

Sustainable B12-Dependent Dehalogenation of Organohalides in E. coli

Microbial bioremediation can provide an environmentally friendly and scalable solution to treat contaminated soil and water. However, microbes have yet to optimize pathways for degrading persistent anthropogenic pollutants, in particular organohalides. In this work, we first expand our repertoire of enzymes useful for bioremediation. By screening a panel of cobalamin (B12)-dependent reductive dehalogenases, we identified previously unreported enzymes that dechlorinate perchloroethene and regioselectively deiodinate the thyroidal disruptor 2,4,6-triiodophenol. One deiodinase, encoded by the animal-associated anaerobe Clostridioides difficile, was demonstrated to dehalogenate the naturally occurring metabolites L-halotyrosines. In cells, several combinations of ferredoxin oxidoreductase and flavodoxin extract and transfer low-potential electrons from pyruvate to drive reductive dehalogenation without artificial reductants and mediators. This work provides new insights into a relatively understudied family of B12-dependent enzymes and sets the stage for engineering synthetic pathways for degrading unnatural small molecule pollutants.

Engineering bacteria for cancer immunotherapy

Bacterial therapeutics have emerged as promising delivery systems to target tumors. These engineered live therapeutics can be harnessed to modulate the tumor microenvironment or to deliver and selectively release therapeutic payloads to tumors. A major challenge is to deliver bacteria systemically without causing widespread inflammation, which is critical for the many tumors that are not accessible to direct intratumoral injection. We describe potential strategies to address this challenge, along with approaches for specific payload delivery and biocontainment to ensure safety. These strategies will pave the way for the development of cost-effective, widely applicable next-generation cancer therapeutics.

Dual cytoplasmic-peroxisomal compartmentalization engineering and multiple metabolic engineering strategies for high yield non-psychoactive cannabinoid in Saccharomyces cerevisiae

CBG (Cannabigerol), a nonpsychoactive cannabinoid, has garnered attention due to its extensive antimicrobial and anti-inflammatory properties. However, the natural content of CBG in Cannabis sativa L. is minimal. In this study, we developed an engineered cell factory for CBG production using Saccharomyces cerevisiae. We introduced the CBGA biosynthetic pathway into S. cerevisiae and employed several strategies to enhance CBGA production. These strategies included dynamically inhibiting the competitive bypass of key metabolic pathways regulated by Erg20p. Additionally, we implemented a dual cytoplasmic-peroxisomal compartmentalization approach to further increase CBGA production. Furthermore, we ensured efficient CBGA production by optimizing NADPH and acetyl-CoA pools. Ultimately, our engineered strain achieved a CBG titer of 138 mg L-1 through fed-batch fermentation in a 5 L bioreactor, facilitated by microwave decarboxylation extraction. These findings underscore the significant potential of yeast cell factories for achieving higher yields in cannabinoid production.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

Advances in the Discovery and Engineering of Gene Targets for Carotenoid Biosynthesis in Recombinant Strains

Carotenoids are naturally occurring pigments that are abundant in the natural world. Due to their excellent antioxidant attributes, carotenoids are widely utilized in various industries, including the food, pharmaceutical, cosmetic industries, and others. Plants, algae, and microorganisms are presently the main sources for acquiring natural carotenoids. However, due to the swift progress in metabolic engineering and synthetic biology, along with the continuous and thorough investigation of carotenoid biosynthetic pathways, recombinant strains have emerged as promising candidates to produce carotenoids. The identification and manipulation of gene targets that influence the accumulation of the desired products is a crucial challenge in the construction and metabolic regulation of recombinant strains. In this review, we provide an overview of the carotenoid biosynthetic pathway, followed by a summary of the methodologies employed in the discovery of gene targets associated with carotenoid production. Furthermore, we focus on discussing the gene targets that have shown potential to enhance carotenoid production. To facilitate future research, we categorize these gene targets based on their capacity to attain elevated levels of carotenoid production.

Computational redesign of taxane-10β-hydroxylase for de novo biosynthesis of a key paclitaxel intermediate

Paclitaxel (Taxol®) is the most popular anticancer diterpenoid predominantly present in Taxus. The core skeleton of paclitaxel is highly modified, but researches on the cytochrome P450s involved in post-modification process remain exceedingly limited. Herein, the taxane-10β-hydroxylase (T10βH) from Taxus cuspidata, which is the third post-modification enzyme that catalyzes the conversion of taxadiene-5α-yl-acetate (T5OAc) to taxadiene-5α-yl-acetoxy-10β-ol (T10OH), was investigated in Escherichia coli by combining computation-assisted protein engineering and metabolic engineering. The variant of T10βH, M3 (I75F/L226K/S345V), exhibited a remarkable 9.5-fold increase in protein expression, accompanied by respective 1.3-fold and 2.1-fold improvements in turnover frequency (TOF) and total turnover number (TTN). Upon integration into the engineered strain, the variant M3 resulted in a substantial enhancement in T10OH production from 0.97 to 2.23 mg/L. Ultimately, the titer of T10OH reached 3.89 mg/L by fed-batch culture in a 5-L bioreactor, representing the highest level reported so far for the microbial de novo synthesis of this key paclitaxel intermediate. This study can serve as a valuable reference for further investigation of other P450s associated with the artificial biosynthesis of paclitaxel and other terpenoids. KEY POINTS: • The T10βH from T. cuspidata was expressed and engineered in E. coli unprecedentedly. • The expression and activity of T10βH were improved through protein engineering. • De novo biosynthesis of T10OH was achieved in E. coli with a titer of 3.89 mg/L.

Design and engineering of artificial biosynthetic pathways-where do we stand and where do we go?

The production of commodity and specialty chemicals relies heavily on fossil fuels. The negative impact of this dependency on our environment and climate has spurred a rising demand for more sustainable methods to obtain such chemicals from renewable resources. Herein, biotransformations of these renewable resources facilitated by enzymes or (micro)organisms have gained significant attention, since they can occur under mild conditions and reduce waste. These biotransformations typically leverage natural metabolic processes, which limits the scope and production capacity of such processes. In this mini-review, we provide an overview of advancements made in the past 5 years to expand the repertoire of biotransformations in engineered microorganisms. This ranges from redesign of existing pathways driven by retrobiosynthesis and computational design to directed evolution of enzymes and de novo pathway design to unlock novel routes for the synthesis of desired chemicals. We highlight notable examples of pathway designs for the production of commodity and specialty chemicals, showcasing the potential of these approaches. Lastly, we provide an outlook on future pathway design approaches.

Modular bioengineering of whole-cell catalysis for sialo-oligosaccharide production: coordinated co-expression of CMP-sialic acid synthetase and sialyltransferase

BACKGROUND

In whole-cell bio-catalysis, the biosystems engineering paradigm shifts from the global reconfiguration of cellular metabolism as in fermentation to a more focused, and more easily modularized, optimization of comparably short cascade reactions. Human milk oligosaccharides (HMO) constitute an important field for the synthetic application of cascade bio-catalysis in resting or non-living cells. Here, we analyzed the central catalytic module for synthesis of HMO-type sialo-oligosaccharides, comprised of CMP-sialic acid synthetase (CSS) and sialyltransferase (SiaT), with the specific aim of coordinated enzyme co-expression in E. coli for reaction flux optimization in whole cell conversions producing 3'-sialyllactose (3SL).

RESULTS

Difference in enzyme specific activity (CSS from Neisseria meningitidis: 36 U/mg; α2,3-SiaT from Pasteurella dagmatis: 5.7 U/mg) was compensated by differential protein co-expression from tailored plasmid constructs, giving balance between the individual activities at a high level of both (α2,3-SiaT: 9.4 × 102 U/g cell dry mass; CSS: 3.4 × 102 U/g cell dry mass). Finally, plasmid selection was guided by kinetic modeling of the coupled CSS-SiaT reactions in combination with comprehensive analytical tracking of the multistep conversion (lactose, N-acetyl neuraminic acid (Neu5Ac), cytidine 5'-triphosphate; each up to 100 mM). The half-life of SiaT in permeabilized cells (≤ 4 h) determined the efficiency of 3SL production at 37 °C. Reaction at 25 °C gave 3SL (40 ± 4 g/L) in ∼ 70% yield within 3 h, reaching a cell dry mass-specific productivity of ∼ 3 g/(g h) and avoiding intermediary CMP-Neu5Ac accumulation.

CONCLUSIONS

Collectively, balanced co-expression of CSS and SiaT yields an efficient (high-flux) sialylation module to support flexible development of E. coli whole-cell catalysts for sialo-oligosaccharide production.

An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis

Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34-90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

Synthetic Biology─High Time to Deliver?

Synthetic biology (SynBio) has attracted like no other recent development the attention not only of Life Science researchers and engineers but also of intellectuals, technology think-tanks, and private and public investors. This is largely due to its promise to propel biotechnology beyond its traditional realms in medicine, agriculture, and environment toward new territories historically dominated by the chemical and manufacturing industries─but now claimed to be amenable to complete biologization. For this to happen, it is crucial for the field to remain true to its foundational engineering drive, which relies on mathematics and quantitative tools to construct practical solutions to real-world problems. This article highlights several SynBio themes that, in our view, come with somewhat precarious promises that need to be tackled. First, SynBio must critically examine whether enough basic information is available to enable the design or redesign of life processes and turn biology from a descriptive science into a prescriptive one. Second, unlike circuit boards, cells are built with soft matter and possess inherent abilities to mutate and evolve, even without external cues. Third, the field cannot be presented as the one technical solution to many grave world problems and so must avoid exaggerated claims and hype. Finally, SynBio should pay heed to public sensitivities and involve social science in its development and growth, and thus change the technology narrative from sheer domination of the living world to conversation and win-win partnership.