Toward metabolic engineering in the context of system biology and synthetic biology: advances and prospects

Advances in Flavonoid and Derivative Biosynthesis: Systematic Strategies for the Construction of Yeast Cell Factories

Flavonoids, a significant group of natural polyphenolic compounds, possess a broad spectrum of pharmacological effects. Recent advances in the systematic metabolic engineering of yeast cell factories (YCFs) provide new opportunities for enhanced flavonoid production. Herein, we outline the latest research progress on typical flavonoid products in YCFs. Advanced engineering strategies involved in flavonoid biosynthesis are discussed in detail, including enhancing precursor supply, cofactor engineering, optimizing core pathways, eliminating competitive pathways, relieving transport limitations, and dynamic regulation. Additionally, we highlight the existing problems in the biosynthesis of flavonoid glucosides in yeast, such as endogenous degradation of flavonoid glycosides, substrate promiscuity of UDP-glycosyltransferases, and an insufficient supply of UDP-sugars, with summaries on the corresponding solutions. Discussions also cover other typical postmodifications like prenylation and methylation, and the recent biosynthesis of complex flavonoid compounds in yeast. Finally, a series of advanced technologies are envisioned, i.e., semirational enzyme engineering, ML/DL algorithn, and systems biology, with the aspiration of achieving large-scale industrial production of flavonoid compounds in the future.

Enhancing the biosynthesis of taxadien-5α-yl-acetate in Escherichia coli by combinatorial metabolic engineering approaches

Biosynthesis of paclitaxel (Taxol™) is a hot topic with extensive and durable interests for decades. However, it is severely hindered due to the very low titers of intermediates. In this study, Escherichia coli was employed to de novo synthesize a key intermediate of paclitaxel, taxadien-5α-yl-acetate (T5OAc). Plasmid-based pathway reconstruction and optimization were conducted for T5OAc production. The endogenous methylerythritol phosphate pathway was enhanced to increase the precursor supply. Three taxadien-5α-ol O-acetyltransferases were tested to obtain the best enzyme for the acetylation step. Metabolic burden was relieved to restore cell growth and promote production through optimizing the plasmid production system. In order to achieve metabolic balance, the biosynthesis pathway was regulated precisely by multivariate-modular metabolic engineering. Finally, in a 5-L bioreactor, the T5OAc titer was enhanced to reach 10.9 mg/L. This represents an approximately 272-fold increase in production compared to the original strain, marking the highest yield of T5OAc ever documented in E. coli, which is believed to be helpful for promoting the progress of paclitaxel biosynthesis.

Towards a hybrid model-driven platform based on flux balance analysis and a machine learning pipeline for biosystem design

Metabolic modeling and machine learning (ML) are crucial components of the evolving next-generation tools in systems and synthetic biology, aiming to unravel the intricate relationship between genotype, phenotype, and the environment. Nonetheless, the comprehensive exploration of integrating these two frameworks, and fully harnessing the potential of fluxomic data, remains an unexplored territory. In this study, we present, rigorously evaluate, and compare ML-based techniques for data integration. The hybrid model revealed that the overexpression of six target genes and the knockout of seven target genes contribute to enhanced ethanol production. Specifically, we investigated the influence of succinate dehydrogenase (SDH) on ethanol biosynthesis in Saccharomyces cerevisiae through shake flask experiments. The findings indicate a noticeable increase in ethanol yield, ranging from 6 % to 10 %, in SDH subunit gene knockout strains compared to the wild-type strain. Moreover, in pursuit of a high-yielding strain for ethanol production, dual-gene deletion experiments were conducted targeting glycerol-3-phosphate dehydrogenase (GPD) and SDH. The results unequivocally demonstrate significant enhancements in ethanol production for the engineered strains Δsdh4Δgpd1, Δsdh5Δgpd1, Δsdh6Δgpd1, Δsdh4Δgpd2, Δsdh5Δgpd2, and Δsdh6Δgpd2, with improvements of 21.6 %, 27.9 %, and 22.7 %, respectively. Overall, the results highlighted that integrating mechanistic flux features substantially improves the prediction of gene knockout strains not accounted for in metabolic reconstructions. In addition, the finding in this study delivers valuable tools for comprehending and manipulating intricate phenotypes, thereby enhancing prediction accuracy and facilitating deeper insights into mechanistic aspects within the field of synthetic biology.

Epistemology of synthetic biology: a new theoretical framework based on its potential objects and objectives

Synthetic biology is a new research field which attempts to understand, modify, and create new biological entities by adopting a modular and systemic conception of the living organisms. The development of synthetic biology has generated a pluralism of different approaches, bringing together a set of heterogeneous practices and conceptualizations from various disciplines, which can lead to confusion within the synthetic biology community as well as with other biological disciplines. I present in this manuscript an epistemological analysis of synthetic biology in order to better define this new discipline in terms of objects of study and specific objectives. First, I present and analyze the principal research projects developed at the foundation of synthetic biology, in order to establish an overview of the practices in this new emerging discipline. Then, I analyze an important scientometric study on synthetic biology to complete this overview. Afterwards, considering this analysis, I suggest a three-level classification of the object of study for synthetic biology (which are different kinds of living entities that can be built in the laboratory), based on three successive criteria: structural hierarchy, structural origin, functional origin. Finally, I propose three successively linked objectives in which synthetic biology can contribute (where the achievement of one objective led to the development of the other): interdisciplinarity collaboration (between natural, artificial, and theoretical sciences), knowledge of natural living entities (past, present, future, and alternative), pragmatic definition of the concept of "living" (that can be used by biologists in different contexts). Considering this new theoretical framework, based on its potential objects and objectives, I take the position that synthetic biology has not only the potential to develop its own new approach (which includes methods, objects, and objectives), distinct from other subdisciplines in biology, but also the ability to develop new knowledge on living entities.

Quorum sensing-mediated dynamic regulation of 4-hydroxyisoleucine biosynthesis in Corynebacterium glutamicum

With the development of synthetic biology, some quorum sensing (QS) systems have been studied and applied to coordinate growth and production. Recently, a novel ComQXPA-P_srfA system with different response strengths was constructed in Corynebacterium glutamicum. However, the plasmid-harbored ComQXPA-P_srfA system lacks genetic stability, which restricts the application of this QS system. In this study, the comQXPA expression cassette was integrated into the chromosome of C. glutamicum SN01, resulting in QSc chassis strain. The green fluorescence protein (GFP) was expressed by the natural and mutant P_srfA promoters (P_srfAM) with various strengths in QSc. All the expressions of gfp were activated to the related level in a cell density-dependent manner. Therefore, ComQXPA-P_srfAM circuit was applied for modulating the dynamic biosynthesis of 4-hydroxyisoleucine (4-HIL). First, the expression of ido encoding α-ketoglutarate (α-KG)-dependent isoleucine dioxygenase was dynamically regulated by P_srfAM promoters, resulting in QSc/_NI. The 4-HIL titer (125.18 ± 11.26 mM) increased by 45.1% compared to static ido expression strain. Then, to coordinate the α-KG supply between TCA cycle and 4-HIL synthesis, the activity of α-KG dehydrogenase complex (ODHC) was dynamically inhibited by regulating the expression of ODHC inhibitor gene odhI under QS-responsive P_srfAM promoters. The highest 4-HIL titer of QSc-₁₁O/₂₀I (145.20 ± 7.80 mM) increased by 23.2% compared to QSc/₂₀I. This study modulated two critical genes expression in both cell growth and 4-HIL de novo synthesis pathways by the stable ComQXPA-P_srfAM system, and 4-HIL was produced responsively with the cell density. This strategy enhanced the 4-HIL biosynthesis efficiently without additional genetic regulation.

Genetic and biochemical strategies for regulation of L-ascorbic acid biosynthesis in plants through the L-galactose pathway

Vitamin C (L-ascorbic acid, AsA) is an essential compound with pleiotropic functions in many organisms. Since its isolation in the last century, AsA has attracted the attention of the scientific community, allowing the discovery of the L-galactose pathway, which is the main pathway for AsA biosynthesis in plants. Thus, the aim of this review is to analyze the genetic and biochemical strategies employed by plant cells for regulating AsA biosynthesis through the L-galactose pathway. In this pathway, participates eight enzymes encoded by the genes PMI, PMM, GMP, GME, GGP, GPP, GDH, and GLDH. All these genes and their encoded enzymes have been well characterized, demonstrating their participation in AsA biosynthesis. Also, have described some genetic and biochemical strategies that allow its regulation. The genetic strategy includes regulation at transcriptional and post-transcriptional levels. In the first one, it was demonstrated that the expression levels of the genes correlate directly with AsA content in the tissues/organs of the plants. Also, it was proved that these genes are light-induced because they have light-responsive promoter motifs (e.g., ATC, I-box, GT1 motif, etc.). In addition, were identified some transcription factors that function as activators (e.g., SlICE1, AtERF98, SlHZ24, etc.) or inactivators (e.g., SlL1L4, ABI4, SlNYYA10) regulate the transcription of these genes. In the second one, it was proved that some genes have alternative splicing events and could be a mechanism to control AsA biosynthesis. Also, it was demonstrated that a conserved cis-acting upstream open reading frame (5'-uORF) located in the 5'-untranslated region of the GGP gene induces its post-transcriptional repression. Among the biochemical strategies discovered is the control of the enzyme levels (usually by decreasing their quantities), control of the enzyme catalytic activity (by increasing or decreasing its activity), feedback inhibition of some enzymes (GME and GGP), subcellular compartmentation of AsA, the metabolon assembly of the enzymes, and control of AsA biosynthesis by electron flow. Together, the construction of this basic knowledge has been establishing the foundations for generating genetically improved varieties of fruits and vegetables enriched with AsA, commonly used in animal and human feed.

An update on the review of microbial synthesis of glucosamine and N-acetylglucosamine

Glucosamine (GlcN) is a natural amino monosaccharide in which a hydroxyl group of glucose is substituted by an amino group. It belongs to functional amino sugar compounds. In the traditional preparation process, GlcN and GlcNAc are obtained by hydrolyzing the cell wall of shrimp and crab. There are many potential problems with this method, such as geographical and seasonal restrictions on the supply of raw materials, serious environmental pollution and potential allergic reactions. Microbial fermentation has the advantages of mild conditions, low environmental pollution, high production intensity, and product safety. It can effectively solve the problem of shrimp and crab hydrolysis process, attracting many researchers to participate in the research of microbial fermentation production of GlcN. This paper mainly summarizes the research on strain construction method, metabolic pathway design and fermentation condition optimization in microbial fermentation, which has certain guiding significance for the further production, research and production of glucosamine.

Bio-conversion of CO2 into biofuels and other value-added chemicals via metabolic engineering

Carbon dioxide (CO₂) occurs naturally in the atmosphere as a trace gas, which is produced naturally as well as by anthropogenic activities. CO₂ is a readily available source of carbon that in principle can be used as a raw material for the synthesis of valuable products. The autotrophic organisms are naturally equipped to convert CO₂ into biomass by obtaining energy from sunlight or inorganic electron donors. This autotrophic CO₂ fixation has been exploited in biotechnology, and microbial cell factories have been metabolically engineered to convert CO₂ into biofuels and other value-added bio-based chemicals. A variety of metabolic engineering efforts for CO₂ fixation ranging from basic copy, paste, and fine-tuning approaches to engineering and testing of novel synthetic CO₂ fixing pathways have been demonstrated. In this paper, we review the current advances and innovations in metabolic engineering for bio-conversion of CO₂ into bio biofuels and other value-added bio-based chemicals.

Model reduction of genome-scale metabolic models as a basis for targeted kinetic models

Constraint-based, genome-scale metabolic models are an essential tool to guide metabolic engineering. However, they lack the detail and time dimension that kinetic models with enzyme dynamics offer. Model reduction can be used to bridge the gap between the two methods and allow for the integration of kinetic models into the Design-Built-Test-Learn cycle. Here we show that these reduced size models can be representative of the dynamics of the original model and demonstrate the automated generation and parameterisation of such models. Using these minimal models of metabolism could allow for further exploration of dynamic responses in metabolic networks.

Towards a fully automated algorithm driven platform for biosystems design

Large-scale data acquisition and analysis are often required in the successful implementation of the design, build, test, and learn (DBTL) cycle in biosystems design. However, it has long been hindered by experimental cost, variability, biases, and missed insights from traditional analysis methods. Here, we report the application of an integrated robotic system coupled with machine learning algorithms to fully automate the DBTL process for biosystems design. As proof of concept, we have demonstrated its capacity by optimizing the lycopene biosynthetic pathway. This fully-automated robotic platform, BioAutomata, evaluates less than 1% of possible variants while outperforming random screening by 77%. A paired predictive model and Bayesian algorithm select experiments which are performed by Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB). BioAutomata excels with black-box optimization problems, where experiments are expensive and noisy and the success of the experiment is not dependent on extensive prior knowledge of biological mechanisms.

Existing efforts have been focused on one of the elements in the automation of the design, build, test, and learn (DBTL) cycle for biosystems design. Here, the authors integrate a robotic system with machine learning algorithms to fully automate the DBTL cycle and apply it in optimizing the lycopene biosynthetic pathway.

YeastFab: High-Throughput Genetic Parts Construction, Measurement, and Pathway Engineering in Yeast

For many years, researchers have devised elegant techniques to assemble genetic parts into larger constructs. Recently, increasing needs for complex DNA constructs has driven countless attempts to optimize DNA assembly methods for improved efficiency, fidelity, and modularity. These efforts have resulted in simple, robust, standardized, and fast protocols that enable the implementation of high-throughput DNA assembly projects for the fabrication of large synthetic genetic constructs. Recently our groups have developed the YeastFab assembly, a highly efficient method for the design and construction of DNA-building blocks based on the native elements from Saccharomyces cerevisiae. Furthermore, these standardized DNA parts can be readily characterized and assembled into transcriptional units and pathways. In this chapter, we describe the protocols to assemble pathways from characterized standardized yeast parts using YeastFab.

Experimental Protocols for Generating Focused Mutant Libraries and Screening for Thermostable Proteins

Many proteins are rapidly deactivated when exposed to high or even ambient temperatures. This cannot only impede the study of a particular protein, but also is one of the major reasons why enzyme catalysis is still widely unable to compete with established chemical processes. Furthermore, differences in protein stability are a challenge in synthetic biology, when individual modules prove to be incompatible. The targeted stabilization of proteins can overcome these hurdles, and protein engineering techniques are more and more reliably supported by computational chemistry tools. Accordingly, algorithms to predict the differences in folding energy of a mutant compared to the wild-type, ΔΔG^fold, are used in the highly successful FRESCO workflow. The resulting single mutant prediction library consists typically of a few hundred amino acid exchanges, and after combining the most successful hits we so far obtained stabilized mutants which exhibited increases in apparent melting temperature of 20-35°C and showed vastly increased half-lives, as well as resistance to cosolvents. Here, we report a detailed protocol to generate these mutant libraries experimentally, covering the entire workflow from primer design, through mutagenesis, protein production and screening, to mutation combination strategies. The individual parts of the method are furthermore applicable to many other scenarios besides protein stabilization, and these protocols are valuable for any project requiring individual or semi high-throughput site-directed mutagenesis, protein expression and purification, or generation of mutant combination libraries.

Pathway Design, Engineering, and Optimization

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Microbial Cell Factories for the Production of Terpenoid Flavor and Fragrance Compounds

Terpenoid flavor and fragrance compounds are of high interest to the aroma industry. Microbial production offers an alternative sustainable access to the desired terpenoids independent of natural sources. Genetically engineered microorganisms can be used to synthesize terpenoids from cheap and renewable resources. Due to its modular architecture, terpenoid biosynthesis is especially well suited for the microbial cell factory concept: a platform host engineered for a high flux toward the central C₅ prenyl diphosphate precursors enables the production of a broad range of target terpenoids just by varying the pathway modules converting the C₅ intermediates to the product of interest. In this review typical terpenoid flavor and fragrance compounds marketed or under development by biotech and aroma companies are given, and the specificities of the aroma market are discussed. The main part of this work focuses on key strategies and recent advances to engineer microbes to become efficient terpenoid producers.

Synbiological systems for complex natural products biosynthesis

Natural products (NPs) continue to play a pivotal role in drug discovery programs. The rapid development of synthetic biology has conferred the strategies of NPs production. Synthetic biology is a new engineering discipline that aims to produce desirable products by rationally programming the biological parts and manipulating the pathways. However, there is still a challenge for integrating a heterologous pathway in chassis cells for overproduction purpose due to the limited characterized parts, modules incompatibility, and cell tolerance towards product. Enormous endeavors have been taken for mentioned issues. Herein, in this review, the progresses in naturally discovering novel biological parts and rational design of synthetic biological parts are reviewed, combining with the advanced assembly technologies, pathway engineering, and pathway optimization in global network guidance. The future perspectives are also presented.

Mass spectrometry-guided refinement of chemical energy buffers

Biocatalytic reactions often require supplying chemical energy and phosphate groups in the form of adenosine triphosphate (ATP). Auxiliary enzymes can be used to convert a reaction by-product-adenosine diphosphate (ADP)-back to ATP. By employing real-time mass spectrometry (RTMS), one can gain an insight into inter-conversions of reactants in multi-enzyme reaction systems and optimize the reaction conditions. In this study, temporal traces of ions corresponding to adenosine monophosphate (AMP), ADP and ATP provided vital information that could be used to adjust activities of the 'buffering enzymes'. Using the RTMS results as a feedback, we also characterized a bienzymatic energy buffer that enables the recovery of ATP in the cases where it is directly hydrolysed to AMP in the main enzymatic reaction. The significance of careful selection of enzyme activities-guided by RTMS-is exemplified in the synthesis of glucose-6-phosphate by hexokinase in the presence of a buffering enzyme, pyruvate kinase. Relative activities of the two enzymes, present in the reaction mixture, influence biosynthetic reaction yields. This observation supports the conclusion that optimization of chemical energy recycling procedures is critical for the biosynthetic reaction economy.

The potential of the mevalonate pathway for enhanced isoprenoid production

The cytosol-localised mevalonic acid (MVA) pathway delivers the basic isoprene unit isopentenyl diphosphate (IPP). In higher plants, this central metabolic intermediate is also synthesised by the plastid-localised methylerythritol phosphate (MEP) pathway. Both MVA and MEP pathways conspire through exchange of intermediates and regulatory interactions. Products downstream of IPP such as phytosterols, carotenoids, vitamin E, artemisinin, tanshinone and paclitaxel demonstrate antioxidant, cholesterol-reducing, anti-ageing, anticancer, antimalarial, anti-inflammatory and antibacterial activities. Other isoprenoid precursors including isoprene, isoprenol, geraniol, farnesene and farnesol are economically valuable. An update on the MVA pathway and its interaction with the MEP pathway is presented, including the improvement in the production of phytosterols and other isoprenoid derivatives. Such attempts are for instance based on the bioengineering of microbes such as Escherichia coli and Saccharomyces cerevisiae, as well as plants. The function of relevant genes in the MVA pathway that can be utilised in metabolic engineering is reviewed and future perspectives are presented.

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

Motivation

Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented.

Results

In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models.

Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor

In silico model-driven analysis using genome-scale model of metabolism (GEM) has been recognized as a promising method for microbial strain improvement. However, most of the current GEM-based strain design algorithms based on flux balance analysis (FBA) heavily rely on the steady-state and optimality assumptions without considering any regulatory information. Thus, their practical usage is quite limited, especially in its application to secondary metabolites overproduction. In this study, we developed a transcriptomics-based strain optimization tool (tSOT) in order to overcome such limitations by integrating transcriptomic data into GEM. Initially, we evaluated existing algorithms for integrating transcriptomic data into GEM using Streptomyces coelicolor dataset, and identified iMAT algorithm as the only and the best algorithm for characterizing the secondary metabolism of S. coelicolor. Subsequently, we developed tSOT platform where iMAT is adopted to predict the reaction states, and successfully demonstrated its applicability to secondary metabolites overproduction by designing actinorhodin (ACT), a polyketide antibiotic, overproducing strain of S. coelicolor. Mutants overexpressing tSOT targets such as ribulose 5-phosphate 3-epimerase and NADP-dependent malic enzyme showed 2 and 1.8-fold increase in ACT production, thereby validating the tSOT prediction. It is expected that tSOT can be used for solving other metabolic engineering problems which could not be addressed by current strain design algorithms, especially for the secondary metabolite overproductions.

Designing cell lines for viral vaccine production: Where do we stand?

Established animal cells, such as Vero, Madin Darby canine kidney (MDCK) or chicken embryo fibroblasts (CEFs), are still the main cell lines used for viral vaccine production, although new "designer cells" have been available for some years. These designer cell lines were specifically developed as a cell substrate for one application and are well characterized. Later screening for other possible applications widened the product range. These cells grow in suspension in chemically defined media under controlled conditions and can be used for up to 100 passages. Scale-up is easier and current process options allow cultivation in disposable bioreactors at cell concentrations higher than 1 × 10(7) cells/mL. This review covers the limitations of established cell lines and discusses the requirements and screening options for new host cells. Currently available designer cells for viral vaccine production (PER.C6, CAP, AGE1.CR, EB66 cells), together with other new cell lines (PBS-1, QOR/2E11, SogE, MFF-8C1 cells) that were recently described as possible cell substrates are presented. Using current process knowledge and cell line development tools, future upstream processing could resemble today's Chinese hamster ovary (CHO) cell processes for monoclonal antibody production: small scale bioreactors (disposable) in perfusion or fed-batch mode with cell concentrations above 1 × 10(8) cells/mL.