A generalized computational framework to streamline thermodynamics and kinetics analysis of metabolic pathways

The Calvin Benson cycle in bacteria: New insights from systems biology

The Calvin Benson cycle in phototrophic and chemolithoautotrophic bacteria has ecological and biotechnological importance, which has motivated study of its regulation. I review recent advances in our understanding of how the Calvin Benson cycle is regulated in bacteria and the technologies used to elucidate regulation and modify it, and highlight differences between and photoautotrophic and chemolithoautotrophic models. Systems biology studies have shown that in oxygenic phototrophic bacteria, Calvin Benson cycle enzymes are extensively regulated at post-transcriptional and post-translational levels, with multiple enzyme activities connected to cellular redox status through thioredoxin. In chemolithoautotrophic bacteria, regulation is primarily at the transcriptional level, with effector metabolites transducing cell status, though new methods should now allow facile, proteome-wide exploration of biochemical regulation in these models. A biotechnological objective is to enhance CO2 fixation in the cycle and partition that carbon to a product of interest. Flux control of CO2 fixation is distributed over multiple enzymes, and attempts to modulate gene Calvin cycle gene expression show a robust homeostatic regulation of growth rate, though the synthesis rates of products can be significantly increased. Therefore, de-regulation of cycle enzymes through protein engineering may be necessary to increase fluxes. Non-canonical Calvin Benson cycles, if implemented with synthetic biology, could have reduced energy demand and enzyme loading, thus increasing the attractiveness of these bacteria for industrial applications.

The potential of CO2-based production cycles in biotechnology to fight the climate crisis

Rising CO2 emissions have pushed scientists to develop new technologies for a more sustainable bio-based economy. Microbial conversion of CO2 and CO2-derived carbon substrates into valuable compounds can contribute to carbon neutrality and sustainability. Here, we discuss the potential of C1 carbon sources as raw materials to produce energy, materials, and food and feed using microbial cell factories. We provide an overview of potential microbes, natural and synthetic C1 utilization pathways, and compare their metabolic driving forces. Finally, we sketch a future in which C1 substrates replace traditional feedstocks and we evaluate the costs associated with such an endeavor.

Regulation on Pathway Metabolic Fluxes to Enhance Colanic Acid Production in Escherichia coli

Colanic acid (CA) is a natural polysaccharide macromolecule with rich and unique biological properties and is a promising candidate for use in food and cosmetics. To date, the efficient biosynthesis of CA and the influence of product accumulation on the strains used have yet to be precisely investigated. Herein, bottlenecks in the CA metabolic pathway were untangled by finely regulating the expression of manA, cpsG, fcl, and rcsA. Engineered strains produced CA at >1 g/L in shake flasks without dependence on cold temperatures, and it was verified in a 1 L bioreactor with a titer up to 18.64 g/L within 24 h. The accumulation of CA caused a decrease in the saturated fatty acid content (represented by C16:0 and C18:0) in the cell membrane. This study demonstrated pathway engineering for efficient CA production in cell factories and provided insights into the barriers and solutions faced in the biosynthesis of natural products.

Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants

This work presents a methodology to evaluate the bioenergetic feasibility of alternative metabolic pathways for a given microbial conversion, optimising their energy yield and driving forces as a function of the concentration of metabolic intermediates. The tool, based on thermodynamic principles and multi-objective optimisation, accounts for pathway variants in terms of different electron carriers, as well as energy conservation (proton translocating) reactions within the pathway. The method also accommodates other constraints, some of them non-linear, such as the balance of conserved moieties. The approach involves the transformation of the maximum energy yield problem into a multi-objective mixed-integer linear optimisation problem which is then subsequently solved using the epsilon-constraint method, highlighting the trade-off between yield and rate in metabolic reactions. The methodology is applied to analyse several pathway alternatives occurring during propionate oxidation in anaerobic fermentation processes, as well as to the reverse TCA cycle pathway occurring during autotrophic microbial CO2 fixation. The results obtained using the developed methodology match previously reported literature and bring about insights into the studied pathways.

Deep Proteogenomics of a Photosynthetic Cyanobacterium

Cyanobacteria, the evolutionary ancestors of plant chloroplasts, contribute substantially to the Earth's biogeochemical cycles and are of great interest for a sustainable economy. Knowledge of protein expression is the key to understanding cyanobacterial metabolism; however, proteome studies in cyanobacteria are limited and cover only a fraction of the theoretical proteome. Here, we performed a comprehensive proteogenomic analysis of the model cyanobacterium Synechocystis sp. PCC 6803 to characterize the expressed (phospho)proteome, re-annotate known and discover novel open reading frames (ORFs). By mapping extensive shotgun mass spectrometry proteomics data onto a six-frame translation of the Synechocystis genome, we refined the genomic annotation of 64 ORFs, including eight completely novel ORFs. Our study presents the largest reported (phospho)proteome dataset for a unicellular cyanobacterium, covering the expression of about 80% of the theoretical proteome under various cultivation conditions, such as nitrogen or carbon limitation. We report 568 phosphorylated S/T/Y sites that are present on numerous regulatory proteins, including the transcriptional regulators cyAbrB1 and cyAbrB2. We also catalogue the proteins that have never been detected under laboratory conditions and found that a large portion of them is plasmid-encoded. This dataset will serve as a resource, providing dedicated information on growth condition-dependent protein expression and phosphorylation.

Thermodynamic and Kinetic Modeling Directs Pathway Optimization for Isopropanol Production in a Gas-Fermenting Bacterium

Highly efficient bioproduction from gaseous substrates (e.g., hydrogen and carbon oxides) will require systematic optimization of the host microbes. To date, the rational redesign of gas-fermenting bacteria is still in its infancy, due in part to the lack of quantitative and precise metabolic knowledge that can direct strain engineering.

Metabolic Engineering Interventions for Sustainable 2,3-Butanediol Production in Gas-Fermenting Clostridium autoethanogenum

Gas fermentation provides a promising platform to turn low-cost and readily available single-carbon waste gases into commodity chemicals, such as 2,3-butanediol. Clostridium autoethanogenum is usually used as a robust and flexible chassis for gas fermentation. Here, we leveraged constraint-based stoichiometric modeling and kinetic ensemble modeling of the C. autoethanogenum metabolic network to provide a systematic in silico analysis of metabolic engineering interventions for 2,3-butanediol overproduction and low carbon substrate loss in dissipated CO₂. Our analysis allowed us to identify and to assess comparatively the expected performances for a wide range of single, double, and triple interventions. Our analysis managed to individuate bottleneck reactions in relevant metabolic pathways when suggesting intervening strategies. Besides recapitulating intuitive and/or previously attempted genetic modifications, our analysis neatly outlined that interventions-at least partially-impinging on by-products branching from acetyl coenzyme A (acetyl-CoA) and pyruvate (acetate, ethanol, amino acids) offer valuable alternatives to the interventions focusing directly on the specific branch from pyruvate to 2,3-butanediol. IMPORTANCE Envisioning value chains inspired by environmental sustainability and circularity in economic models is essential to counteract the alterations in the global natural carbon cycle induced by humans. Recycling carbon-based waste gas streams into chemicals by devising gas fermentation bioprocesses mediated by acetogens of the genus Clostridium is one component of the solution. Carbon monoxide originates from multiple biogenic and abiogenic sources and bears a significant environmental impact. This study aims at identifying metabolic engineering interventions for increasing 2,3-butanediol production and avoiding carbon loss in CO₂ dissipation via C. autoethanogenum fermenting a substrate comprising CO and H₂. 2,3-Butanediol is a valuable biochemical by-product since, due to its versatility, can be transformed quite easily into chemical compounds such as butadiene, diacetyl, acetoin, and methyl ethyl ketone. These compounds are usable as building blocks to manufacture a vast range of industrially produced chemicals.

Thermodynamics contributes to high limonene productivity in cyanobacteria

Terpenoids are a large group of secondary metabolites with broad industrial applications. Engineering cyanobacteria is an attractive route for the sustainable production of commodity terpenoids. Currently, a major obstacle lies in the low productivity attained in engineered cyanobacterial strains. Traditional metabolic engineering to improve pathway kinetics has led to limited success in enhancing terpenoid productivity. In this study, we reveal thermodynamics as the main determinant for high limonene productivity in cyanobacteria. Through overexpressing the primary sigma factor, a higher photosynthetic rate was achieved in an engineered strain of Synechococcus elongatus PCC 7942. Computational modeling and wet lab analyses showed an increased flux toward both native carbon sink glycogen synthesis and the non-native limonene synthesis from photosynthate output. On the other hand, comparative proteomics showed decreased expression of terpene pathway enzymes, revealing their limited role in determining terpene flux. Lastly, growth optimization by enhancing photosynthesis has led to a limonene titer of 19 mg/L in 7 days with a maximum productivity of 4.3 mg/L/day. This study highlights the importance of enhancing photosynthesis and substrate input for the high productivity of secondary metabolic pathways, providing a new strategy for future terpenoid engineering in phototrophs.

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Pathway enzyme engineering marginally increases cyanobacterial terpene production.

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Sigma factor overexpression improves photosynthetic efficiency in cyanobacteria.

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Enhanced photosynthesis results in high limonene production in cyanobacteria.

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Enhanced photosynthesis provides high thermodynamic driving force for terpenes.

Efficient Terpene Production by Marine Thraustochytrids: Shedding Light on the Thermodynamic Driving Force

Terpenoids, such as squalene, are valuable compounds for cosmetic and drug industries, the supply of which is often limited by natural sources. Alternative production strategies have been investigated for decades but remain challenging due to low yields. In a recent study, Zhang and coworkers (A. Zhang, K. Mernitz, C. Wu, W. Xiong, et al., mBio 12:e0088121, 2021, https://doi.org/10.1128/mBio.00881-21) report the potential use of marine thraustochytrid metabolic thermodynamics in effective terpene engineering. Through comparative proteomics and metabolomics, as well as thermodynamic modeling, the authors demonstrated sodium-induced changes in thraustochytrid metabolism leading to a twofold increase in squalene accumulation. The differential abundances of the metabolic enzymes and metabolites, as well as higher respiration, indicated the metabolic shift from carbohydrate to lipid oxidation and increased ATP input to the mevalonate pathway and squalene synthesis. This breakthrough provides new important insights into microbial terpene metabolic engineering but above all displays thermodynamics as a valuable tool in metabolic engineering.

Probing Light-Dependent Regulation of the Calvin Cycle Using a Multi-Omics Approach

Photoautotrophic microorganisms are increasingly explored for the conversion of atmospheric carbon dioxide into biomass and valuable products. The Calvin-Benson-Bassham (CBB) cycle is the primary metabolic pathway for net CO₂ fixation within oxygenic photosynthetic organisms. The cyanobacteria, Synechocystis sp. PCC 6803, is a model organism for the study of photosynthesis and a platform for many metabolic engineering efforts. The CBB cycle is regulated by complex mechanisms including enzymatic abundance, intracellular metabolite concentrations, energetic cofactors and post-translational enzymatic modifications that depend on the external conditions such as the intensity and quality of light. However, the extent to which each of these mechanisms play a role under different light intensities remains unclear. In this work, we conducted non-targeted proteomics in tandem with isotopically non-stationary metabolic flux analysis (INST-MFA) at four different light intensities to determine the extent to which fluxes within the CBB cycle are controlled by enzymatic abundance. The correlation between specific enzyme abundances and their corresponding reaction fluxes is examined, revealing several enzymes with uncorrelated enzyme abundance and their corresponding flux, suggesting flux regulation by mechanisms other than enzyme abundance. Additionally, the kinetics of ¹³C labeling of CBB cycle intermediates and estimated inactive pool sizes varied significantly as a function of light intensity suggesting the presence of metabolite channeling, an additional method of flux regulation. These results highlight the importance of the diverse methods of regulation of CBB enzyme activity as a function of light intensity, and highlights the importance of considering these effects in future kinetic models.

Thermodynamic and Kinetic Modeling of Co-utilization of Glucose and Xylose for 2,3-BDO Production by Zymomonas mobilis

Prior engineering of the ethanologen Zymomonas mobilis has enabled it to metabolize xylose and to produce 2,3-butanediol (2,3-BDO) as a dominant fermentation product. When co-fermenting with xylose, glucose is preferentially utilized, even though xylose metabolism generates ATP more efficiently during 2,3-BDO production on a BDO-mol basis. To gain a deeper understanding of Z. mobilis metabolism, we first estimated the kinetic parameters of the glucose facilitator protein of Z. mobilis by fitting a kinetic uptake model, which shows that the maximum transport capacity of glucose is seven times higher than that of xylose, and glucose is six times more affinitive to the transporter than xylose. With these estimated kinetic parameters, we further compared the thermodynamic driving force and enzyme protein cost of glucose and xylose metabolism. It is found that, although 20% more ATP can be yielded stoichiometrically during xylose utilization, glucose metabolism is thermodynamically more favorable with 6% greater cumulative Gibbs free energy change, more economical with 37% less enzyme cost required at the initial stage and sustains the advantage of the thermodynamic driving force and protein cost through the fermentation process until glucose is exhausted. Glucose-6-phosphate dehydrogenase (g6pdh), glyceraldehyde-3-phosphate dehydrogenase (gapdh) and phosphoglycerate mutase (pgm) are identified as thermodynamic bottlenecks in glucose utilization pathway, as well as two more enzymes of xylose isomerase and ribulose-5-phosphate epimerase in xylose metabolism. Acetolactate synthase is found as potential engineering target for optimized protein cost supporting unit metabolic flux. Pathway analysis was then extended to the core stoichiometric matrix of Z. mobilis metabolism. Growth was simulated by dynamic flux balance analysis and the model was validated showing good agreement with experimental data. Dynamic FBA simulations suggest that a high agitation is preferable to increase 2,3-BDO productivity while a moderate agitation will benefit the 2,3-BDO titer. Taken together, this work provides thermodynamic and kinetic insights of Z. mobilis metabolism on dual substrates, and guidance of bioengineering efforts to increase hydrocarbon fuel production.

ATP Drives Efficient Terpene Biosynthesis in Marine Thraustochytrids

Understanding carbon flux controlling mechanisms in a tangled metabolic network is an essential question of cell metabolism. Secondary metabolism, such as terpene biosynthesis, has evolved with low carbon flux due to inherent pathway constraints. Thraustochytrids are a group of heterotrophic marine unicellular protists and can accumulate terpenoids under the high-salt conditions in their natural environment. However, the mechanism behind terpene accumulation is not well understood. Here, we show that terpene biosynthesis in Thraustochytrium sp. ATCC 26185 is constrained by local thermodynamics in the mevalonate pathway. Thermodynamic analysis reveals metabolite limitation in the nondecarboxylative Claisen condensation of acetyl-coenzyme A (CoA) to the acetoacetyl-CoA step, catalyzed by the acetyl-CoA acetyltransferase (ACAT). Through a sodium-elicited mechanism, higher respiration leads to increased ATP investment into the mevalonate pathway, providing a strong thermodynamic driving force for enhanced terpene biosynthesis. Proteomic and metabolomic analyses further show that the increased ATP demands are fulfilled by shifting energy generation from carbohydrate to lipid oxidation. This study demonstrates a unique strategy in nature that uses ATP to drive a low-flux metabolic pathway, providing an alternative solution for efficient terpene metabolic engineering. IMPORTANCE Terpenoids are a large class of lipid molecules with important biological functions and diverse industrial and medicinal applications. Metabolic engineering for terpene production has been hindered by the low-flux distribution to its biosynthesis pathway. In practice, a high substrate load is generally required to reach high product titers. Here, we show that mevalonate-derived terpene biosynthesis is constrained by local pathway thermodynamics, which can only be partially relieved by increasing substrate levels. Through comparative omics and biochemical analyses, we discovered a unique mechanism for high terpene accumulation in marine protist thraustochytrids. Through a sodium-induced mechanism, thraustochytrids shift their energy metabolism from carbohydrate to lipid oxidation for enhanced ATP production, providing a strong thermodynamic driving force for efficient terpene biosynthesis. This study reveals an important mechanism in eukaryotes to overcome the thermodynamic constraint in low-flux pathways by increased ATP consumption. Engineering energy metabolism thus provides an important alternative to relieve flux constraints in low-flux and energy-consuming pathways.

Biotechnology for secure biocontainment designs in an emerging bioeconomy

Genetically modified organisms (GMOs) have emerged as an integral component of a sustainable bioeconomy, with an array of applications in agriculture, bioenergy, and biomedicine. However, the rapid development of GMOs and associated synthetic biology approaches raises a number of biosecurity concerns related to environmental escape of GMOs, detection thereof, and impact upon native ecosystems. A myriad of genetic safeguards have been deployed in diverse microbial hosts, ranging from classical auxotrophies to global genome recoding. However, to realize the full potential of microbes as biocatalytic platforms in the bioeconomy, a deeper understanding of the fundamental principles governing microbial responsiveness to biocontainment constraints, and interactivity of GMOs with the environment, is required. Herein, we review recent analytical biotechnological advances and strategies to assess biocontainment and microbial bioproductivity, as well as opportunities for predictive systems biodesigns towards securing a viable bioeconomy.

Genetic, Genomics, and Responses to Stresses in Cyanobacteria: Biotechnological Implications

Cyanobacteria are widely-diverse, environmentally crucial photosynthetic prokaryotes of great interests for basic and applied science. Work to date has focused mostly on the three non-nitrogen fixing unicellular species Synechocystis PCC 6803, Synechococcus PCC 7942, and Synechococcus PCC 7002, which have been selected for their genetic and physiological interests summarized in this review. Extensive "omics" data sets have been generated, and genome-scale models (GSM) have been developed for the rational engineering of these cyanobacteria for biotechnological purposes. We presently discuss what should be done to improve our understanding of the genotype-phenotype relationships of these models and generate robust and predictive models of their metabolism. Furthermore, we also emphasize that because Synechocystis PCC 6803, Synechococcus PCC 7942, and Synechococcus PCC 7002 represent only a limited part of the wide biodiversity of cyanobacteria, other species distantly related to these three models, should be studied. Finally, we highlight the need to strengthen the communication between academic researchers, who know well cyanobacteria and can engineer them for biotechnological purposes, but have a limited access to large photobioreactors, and industrial partners who attempt to use natural or engineered cyanobacteria to produce interesting chemicals at reasonable costs, but may lack knowledge on cyanobacterial physiology and metabolism.

Building kinetic models for metabolic engineering

Kinetic formalisms of metabolism link metabolic fluxes to enzyme levels, metabolite concentrations and their allosteric regulatory interactions. Though they require the identification of physiologically relevant values for numerous parameters, kinetic formalisms uniquely establish a mechanistic link across heterogeneous omics datasets and provide an overarching vantage point to effectively inform metabolic engineering strategies. Advances in computational power, gene annotation coverage, and formalism standardization have led to significant progress over the past few years. However, careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges. In this review we highlight fundamental considerations which influence model quality and prediction, advances in methodologies, and success stories of deploying kinetic models to guide metabolic engineering.

Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms

Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both external environmental factors and internal genotypic perturbations. The fundamental concepts of reaction stoichiometry, thermodynamics, and mass action kinetics have emerged as the foundational principles of many modeling frameworks designed to describe how and why organisms allocate resources towards both growth and bioproduction. This review focuses on the latest algorithmic advancements that have integrated these foundational principles into increasingly sophisticated quantitative frameworks.

Computational approaches to understanding nutrient metabolism and metabolic disorders

Computational methods are becoming more and more essential to elucidate biological systems. Many different approaches exist with pros and cons. This paper reviews the most useful technologies focusing on nutrient metabolism and metabolic disorders. Space limitation prevents from exploring the examples in details, but pointers to the relevant papers are reported.