Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points

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.

Autotrophic growth of Escherichia coli is achieved by a small number of genetic changes

Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for Escherichia coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzyme's activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycle's electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.

Characterization of the enzyme kinetics of EMP and HMP pathway in Corynebacterium glutamicum: reference for modeling metabolic networks

The model of intracellular metabolic network based on enzyme kinetics parameters plays an important role in understanding the intracellular metabolic process of Corynebacterium glutamicum, and constructing such a model requires a large number of enzymological parameters. In this work, the genes encoding the relevant enzymes of the EMP and HMP metabolic pathways from Corynebacterium glutamicum ATCC 13032 were cloned, and engineered strains for protein expression with E.coli BL21 and P.pastoris X33 as hosts were constructed. The twelve enzymes (GLK, GPI, TPI, GAPDH, PGK, PMGA, ENO, ZWF, RPI, RPE, TKT, and TAL) were successfully expressed and purified by Ni2+ chelate affinity chromatography in their active forms. In addition, the kinetic parameters (V max, K m, and K cat) of these enzymes were measured and calculated at the same pH and temperature. The kinetic parameters of enzymes associated with EMP and the HMP pathway were determined systematically and completely for the first time in C.glutamicum. These kinetic parameters enable the prediction of key enzymes and rate-limiting steps within the metabolic pathway, and support the construction of a metabolic network model for important metabolic pathways in C.glutamicum. Such analyses and models aid in understanding the metabolic behavior of the organism and can guide the efficient production of high-value chemicals using C.glutamicum as a host.

Design and Construction of Artificial Biological Systems for One-Carbon Utilization

The third-generation (3G) biorefinery aims to use microbial cell factories or enzymatic systems to synthesize value-added chemicals from one-carbon (C1) sources, such as CO2, formate, and methanol, fueled by renewable energies like light and electricity. This promising technology represents an important step toward sustainable development, which can help address some of the most pressing environmental challenges faced by modern society. However, to establish processes competitive with the petroleum industry, it is crucial to determine the most viable pathways for C1 utilization and productivity and yield of the target products. In this review, we discuss the progresses that have been made in constructing artificial biological systems for 3G biorefineries in the last 10 years. Specifically, we highlight the representative works on the engineering of artificial autotrophic microorganisms, tandem enzymatic systems, and chemo-bio hybrid systems for C1 utilization. We also prospect the revolutionary impact of these developments on biotechnology. By harnessing the power of 3G biorefinery, scientists are establishing a new frontier that could potentially revolutionize our approach to industrial production and pave the way for a more sustainable future.

Synergistic investigation of natural and synthetic C1-trophic microorganisms to foster a circular carbon economy

A true circular carbon economy must upgrade waste greenhouse gases. C1-based biomanufacturing is an attractive solution, in which one carbon (C1) molecules (e.g. CO2, formate, methanol, etc.) are converted by microbial cell factories into value-added goods (i.e. food, feed, and chemicals). To render C1-based biomanufacturing cost-competitive, we must adapt microbial metabolism to perform chemical conversions at high rates and yields. To this end, the biotechnology community has undertaken two (seemingly opposing) paths: optimizing natural C1-trophic microorganisms versus engineering synthetic C1-assimilation de novo in model microorganisms. Here, we pose how these approaches can instead create synergies for strengthening the competitiveness of C1-based biomanufacturing as a whole.

Metabolite interactions in the bacterial Calvin cycle and implications for flux regulation

Metabolite-level regulation of enzyme activity is important for microbes to cope with environmental shifts. Knowledge of such regulations can also guide strain engineering for biotechnology. Here we apply limited proteolysis-small molecule mapping (LiP-SMap) to identify and compare metabolite-protein interactions in the proteomes of two cyanobacteria and two lithoautotrophic bacteria that fix CO2 using the Calvin cycle. Clustering analysis of the hundreds of detected interactions shows that some metabolites interact in a species-specific manner. We estimate that approximately 35% of interacting metabolites affect enzyme activity in vitro, and the effect is often minor. Using LiP-SMap data as a guide, we find that the Calvin cycle intermediate glyceraldehyde-3-phosphate enhances activity of fructose-1,6/sedoheptulose-1,7-bisphosphatase (F/SBPase) from Synechocystis sp. PCC 6803 and Cupriavidus necator in reducing conditions, suggesting a convergent feed-forward activation of the cycle. In oxidizing conditions, glyceraldehyde-3-phosphate inhibits Synechocystis F/SBPase by promoting enzyme aggregation. In contrast, the glycolytic intermediate glucose-6-phosphate activates F/SBPase from Cupriavidus necator but not F/SBPase from Synechocystis. Thus, metabolite-level regulation of the Calvin cycle is more prevalent than previously appreciated.

Paving the way for synthetic C1 - Metabolism in Pseudomonas putida through the reductive glycine pathway

One-carbon (C1) compounds such as methanol, formate, and CO₂ are alternative, sustainable microbial feedstocks for the biobased production of chemicals and fuels. In this study, we engineered the carbon metabolism of the industrially important bacterium Pseudomonas putida to modularly assimilate these three substrates through the reductive glycine pathway. First, we demonstrated the functionality of the C1-assimilation module by coupling the growth of auxotrophic strains to formate assimilation. Next, we extended the module in the auxotrophic strains from formate to methanol-dependent growth using both NAD and PQQ-dependent methanol dehydrogenases. Finally, we demonstrated, for the first time, engineered CO₂-dependent formation of part of the biomass through CO₂ reduction to formate by the native formate dehydrogenase, which required short-term evolution to rebalance the cellular NADH/NAD ⁺ ratio. This research paves the way to further engineer P. putida towards full growth on formate, methanol, and CO₂ as sole feedstocks, thereby substantially expanding its potential as a sustainable and versatile cell factory.

Dynamics of co-substrate pools can constrain and regulate metabolic fluxes

Cycling of co-substrates, whereby a metabolite is converted among alternate forms via different reactions, is ubiquitous in metabolism. Several cycled co-substrates are well known as energy and electron carriers (e.g. ATP and NAD(P)H), but there are also other metabolites that act as cycled co-substrates in different parts of central metabolism. Here, we develop a mathematical framework to analyse the effect of co-substrate cycling on metabolic flux. In the cases of a single reaction and linear pathways, we find that co-substrate cycling imposes an additional flux limit on a reaction, distinct to the limit imposed by the kinetics of the primary enzyme catalysing that reaction. Using analytical methods, we show that this additional limit is a function of the total pool size and turnover rate of the cycled co-substrate. Expanding from this insight and using simulations, we show that regulation of these two parameters can allow regulation of flux dynamics in branched and coupled pathways. To support these theoretical insights, we analysed existing flux measurements and enzyme levels from the central carbon metabolism and identified several reactions that could be limited by the dynamics of co-substrate cycling. We discuss how the limitations imposed by co-substrate cycling provide experimentally testable hypotheses on specific metabolic phenotypes. We conclude that measuring and controlling co-substrate dynamics is crucial for understanding and engineering metabolic fluxes in cells.

Growth and depletion in linear stochastic reaction networks

This paper is about a class of stochastic reaction networks. Of interest are the dynamics of interconversion among a finite number of substances through reactions that consume some of the substances and produce others. The models we consider are continuous-time Markov jump processes, intended as idealizations of a broad class of biological networks. Reaction rates depend linearly on "enzymes," which are among the substances produced, and a reaction can occur only in the presence of sufficient upstream material. We present rigorous results for this class of stochastic dynamical systems, the mean-field behaviors of which are described by ordinary differential equations (ODEs). Under the assumption of exponential network growth, we identify certain ODE solutions as being potentially traceable and give conditions on network trajectories which, when rescaled, can with high probability be approximated by these ODE solutions. This leads to a complete characterization of the ω-limit sets of such network solutions (as points or random tori). Dimension reduction is noted depending on the number of enzymes. The second half of this paper is focused on depletion dynamics, i.e., dynamics subsequent to the "phase transition" that occurs when one of the substances becomes unavailable. The picture can be complex, for the depleted substance can be produced intermittently through other network reactions. Treating the model as a slow-fast system, we offer a mean-field description, a first step to understanding what we believe is one of the most natural bifurcations for reaction networks.

Generation of an Escherichia coli strain growing on methanol via the ribulose monophosphate cycle

Methanol is a liquid with high energy storage capacity that holds promise as an alternative substrate to replace sugars in the biotechnology industry. It can be produced from CO₂ or methane and its use does not compete with food and animal feed production. However, there are currently only limited biotechnological options for the valorization of methanol, which hinders its widespread adoption. Here, we report the conversion of the industrial platform organism Escherichia coli into a synthetic methylotroph that assimilates methanol via the energy efficient ribulose monophosphate cycle. Methylotrophy is achieved after evolution of a methanol-dependent E. coli strain over 250 generations in continuous chemostat culture. We demonstrate growth on methanol and biomass formation exclusively from the one-carbon source by ¹³C isotopic tracer analysis. In line with computational modeling, the methylotrophic E. coli strain optimizes methanol oxidation by upregulation of an improved methanol dehydrogenase, increasing ribulose monophosphate cycle activity, channeling carbon flux through the Entner-Doudoroff pathway and downregulating tricarboxylic acid cycle enzymes. En route towards sustainable bioproduction processes, our work lays the foundation for the efficient utilization of methanol as the dominant carbon and energy resource.

Using one carbon compounds as feedstock is a promising approach in abating climate change. Here, the authors report the conversion of E. coli into a synthetic methylotroph that assimilates methanol via the ribulose monophosphate cycle and a set of distinctive mutations.

Two major metabolic factors for an efficient NADP-malic enzyme type C4 photosynthesis

Compared to the large number of studies focused on the factors controlling C3 photosynthesis efficiency, there are relatively fewer studies of the factors controlling photosynthetic efficiency in C4 leaves. Here, we used a dynamic systems model of C4 photosynthesis based on maize (Zea mays) to identify features associated with high photosynthetic efficiency in NADP-malic enzyme (NADP-ME) type C4 photosynthesis. We found that two additional factors related to coordination between C4 shuttle metabolism and C3 metabolism are required for efficient C4 photosynthesis: (1) accumulating a high concentration of phosphoenolpyruvate through maintaining a large PGA concentration in the mesophyll cell chloroplast and (2) maintaining a suitable oxidized status in bundle sheath cell chloroplasts. These identified mechanisms are in line with the current cellular location of enzymes/proteins involved in the starch synthesis, the Calvin-Benson cycle and photosystem II of NADP-ME type C4 photosynthesis. These findings suggested potential strategies for improving C4 photosynthesis and engineering C4 rice.

A cell-free self-replenishing CO2-fixing system

Biological CO2 fixation is so far the most effective means for CO2 reduction at scale and accounts for most of the CO2 fixed on Earth. Through this process, carbon is fixed in cellular components and biomass during organismal growth. To uncouple CO2 fixation from growth and cellular regulation, cell-free CO2 fixation systems represent an alternative approach since the rate can be independently manipulated. Here we designed an oxygen-insensitive, self-replenishing CO2 fixation system with opto-sensing. The system comprises a synthetic reductive glyoxylate and pyruvate synthesis (rGPS) cycle and the malyl-CoA-glycerate (MCG) pathway to produce acetyl-coenzyme A (CoA), pyruvate and malate from CO2, which are also intermediates in the cycle. We solved various problems associated with the in vitro system, and implemented opto-sensing modules to control the regeneration of cofactors. We accomplished sustained operation for 6 hours with a CO2-fixing rate comparable to or greater than typical CO2 fixation rates of photosynthetic or lithoautotrophic organisms.

Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth

Traditional (genome-scale) metabolic models of cellular growth involve an approximate biomass “reaction”, which specifies biomass composition in terms of precursor metabolites (such as amino acids and nucleotides). On the one hand, biomass composition is often not known exactly and may vary drastically between conditions and strains. On the other hand, the predictions of computational models crucially depend on biomass. Also elementary flux modes (EFMs), which generate the flux cone, depend on the biomass reaction. To better understand cellular phenotypes across growth conditions, we introduce and analyze new classes of elementary vectors for comprehensive (next-generation) metabolic models, involving explicit synthesis reactions for all macromolecules. Elementary growth modes (EGMs) are given by stoichiometry and generate the growth cone. Unlike EFMs, they are not support-minimal, in general, but cannot be decomposed “without cancellations”. In models with additional (capacity) constraints, elementary growth vectors (EGVs) generate a growth polyhedron and depend also on growth rate. However, EGMs/EGVs do not depend on the biomass composition. In fact, they cover all possible biomass compositions and can be seen as unbiased versions of elementary flux modes/vectors (EFMs/EFVs) used in traditional models. To relate the new concepts to other branches of theory, we consider autocatalytic sets of reactions. Further, we illustrate our results in a small model of a self-fabricating cell, involving glucose and ammonium uptake, amino acid and lipid synthesis, and the expression of all enzymes and the ribosome itself. In particular, we study the variation of biomass composition as a function of growth rate. In agreement with experimental data, low nitrogen uptake correlates with high carbon (lipid) storage.

Next-generation, genome-scale metabolic models allow to study the reallocation of cellular resources upon changing environmental conditions, by not only modeling flux distributions, but also expression profiles of the catalyzing proteome. In particular, they do no longer assume a fixed biomass composition. Methods to identify optimal solutions in such comprehensive models exist, however, an unbiased understanding of all feasible allocations is missing so far. Here we develop new concepts, called elementary growth modes and vectors, that provide a generalized definition of minimal pathways, thereby extending classical elementary flux modes (used in traditional models with a fixed biomass composition). The new concepts provide an understanding of all possible flux distributions and of all possible biomass compositions. In other words, elementary growth modes and vectors are the unique functional units in any comprehensive model of cellular growth. As an example, we show that lipid accumulation upon nitrogen starvation is a consequence of resource allocation and does not require active regulation. Our work puts current approaches on a theoretical basis and allows to seamlessly transfer existing workflows (e.g. for the design of cell factories) to next-generation metabolic models.

Adaptive laboratory evolution and reverse engineering enhances autotrophic growth in Pichia pastoris

Synthetic biology offers several routes for CO₂ conversion into biomass or bio-chemicals, helping to avoid unsustainable use of organic feedstocks, which negatively contribute to climate change. The use of well-known industrial organisms, such as the methylotrophic yeast Pichia pastoris (Komagataella phaffii), for the establishment of novel C1-based bioproduction platforms could wean biotechnology from feedstocks with alternative use in food production. Recently, the central carbon metabolism of P. pastoris was re-wired following a rational engineering approach, allowing the resulting strains to grow autotrophically with a μ_max of 0.008 h^-1, which was further improved to 0.018 h^-1 by adaptive laboratory evolution. Using reverse genetic engineering of single-nucleotide (SNPs) polymorphisms occurring in the genes encoding for phosphoribulokinase and nicotinic acid mononucleotide adenylyltransferase after evolution, we verified their influence on the improved autotrophic phenotypes. The reverse engineered SNPs lead to lower enzyme activities in putative branching point reactions and in reactions involved in energy balancing. Beyond this, we show how further evolution facilitates peroxisomal import and increases growth under autotrophic conditions. The engineered P. pastoris strains are a basis for the development of a platform technology, which uses CO₂ for production of value-added products, such as cellular biomass, technical enzymes and chemicals and which further avoids consumption of organic feedstocks with alternative use in food production. Further, the identification and verification of three pivotal steps may facilitate the integration of heterologous CBB cycles or similar pathways into heterotrophic organisms.

Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2

Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO2 concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C3 cereal crops. This decreased protein content in crops constrains the benefits of elevated CO2 on crop yield and affects their nutritional value for humans. To support studies of photosynthetic nitrogen assimilation and its complex interaction with photosynthetic carbon metabolism for crop improvement, we developed a dynamic systems model of plant primary metabolism, which includes the Calvin-Benson cycle, the photorespiration pathway, starch synthesis, glycolysis-gluconeogenesis, the tricarboxylic acid cycle, and chloroplastic nitrogen assimilation. This model successfully captures responses of net photosynthetic CO2 uptake rate (A), respiration rate, and nitrogen assimilation rate to different irradiance and CO2 levels. We then used this model to predict inhibition of nitrogen assimilation under elevated CO2. The potential mechanisms underlying inhibited nitrogen assimilation under elevated CO2 were further explored with this model. Simulations suggest that enhancing the supply of α-ketoglutarate is a potential strategy to maintain high rates of nitrogen assimilation under elevated CO2. This model can be used as a heuristic tool to support research on interactions between photosynthesis, respiration, and nitrogen assimilation. It also provides a basic framework to support the design and engineering of C3 plant primary metabolism for enhanced photosynthetic efficiency and nitrogen assimilation in the coming high-CO2 world.

Protein allocation and utilization in the versatile chemolithoautotroph Cupriavidus necator

Bacteria must balance the different needs for substrate assimilation, growth functions, and resilience in order to thrive in their environment. Of all cellular macromolecules, the bacterial proteome is by far the most important resource and its size is limited. Here, we investigated how the highly versatile 'knallgas' bacterium Cupriavidus necator reallocates protein resources when grown on different limiting substrates and with different growth rates. We determined protein quantity by mass spectrometry and estimated enzyme utilization by resource balance analysis modeling. We found that C. necator invests a large fraction of its proteome in functions that are hardly utilized. Of the enzymes that are utilized, many are present in excess abundance. One prominent example is the strong expression of CBB cycle genes such as Rubisco during growth on fructose. Modeling and mutant competition experiments suggest that CO₂-reassimilation through Rubisco does not provide a fitness benefit for heterotrophic growth, but is rather an investment in readiness for autotrophy.

Growth-coupled selection of synthetic modules to accelerate cell factory development

Synthetic biology has brought about a conceptual shift in our ability to redesign microbial metabolic networks. Combining metabolic pathway-modularization with growth-coupled selection schemes is a powerful tool that enables deep rewiring of the cell factories’ biochemistry for rational bioproduction.

Kinetic Selection in the Out-of-Equilibrium Autocatalytic Reaction Networks that Produce Macrocyclic Peptides

Autocatalytic reaction networks are instrumental for validating scenarios for the emergence of life on Earth and for synthesizing life de novo. Here, we demonstrate that dimeric thioesters of tripeptides with the general structure (Cys-Xxx-Gly-SEt)₂ form strongly interconnected autocatalytic reaction networks that predominantly generate macrocyclic peptides up to 69 amino acids long. Some macrocycles of 6-12 amino acids were isolated from the product pool and were characterized by NMR spectroscopy and single-crystal X-ray analysis. We studied the autocatalytic formation of macrocycles in a flow reactor in the presence of acrylamide, whose conjugate addition to thiols served as a model "removal" reaction. These results indicate that even not template-assisted autocatalytic production combined with competing removal of molecular species in an open compartment could be a feasible route for selecting functional molecules during the pre-Darwinian stages of molecular evolution.

Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as "a self-sustaining chemical system capable of Darwinian evolution". It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

Wide range of metabolic adaptations to the acquisition of the Calvin cycle revealed by comparison of microbial genomes

Knowledge of the genetic basis for autotrophic metabolism is valuable since it relates to both the emergence of life and to the metabolic engineering challenge of incorporating CO2 as a potential substrate for biorefining. The most common CO2 fixation pathway is the Calvin cycle, which utilizes Rubisco and phosphoribulokinase enzymes. We searched thousands of microbial genomes and found that 6.0% contained the Calvin cycle. We then contrasted the genomes of Calvin cycle-positive, non-cyanobacterial microbes and their closest relatives by enrichment analysis, ancestral character estimation, and random forest machine learning, to explore genetic adaptations associated with acquisition of the Calvin cycle. The Calvin cycle overlaps with the pentose phosphate pathway and glycolysis, and we could confirm positive associations with fructose-1,6-bisphosphatase, aldolase, and transketolase, constituting a conserved operon, as well as ribulose-phosphate 3-epimerase, ribose-5-phosphate isomerase, and phosphoglycerate kinase. Additionally, carbohydrate storage enzymes, carboxysome proteins (that raise CO2 concentration around Rubisco), and Rubisco activases CbbQ and CbbX accompanied the Calvin cycle. Photorespiration did not appear to be adapted specifically for the Calvin cycle in the non-cyanobacterial microbes under study. Our results suggest that chemoautotrophy in Calvin cycle-positive organisms was commonly enabled by hydrogenase, and less commonly ammonia monooxygenase (nitrification). The enrichment of specific DNA-binding domains indicated Calvin-cycle associated genetic regulation. Metabolic regulatory adaptations were illustrated by negative correlation to AraC and the enzyme arabinose-5-phosphate isomerase, which suggests a downregulation of the metabolite arabinose-5-phosphate, which may interfere with the Calvin cycle through enzyme inhibition and substrate competition. Certain domains of unknown function that were found to be important in the analysis may indicate yet unknown regulatory mechanisms in Calvin cycle-utilizing microbes. Our gene ranking provides targets for experiments seeking to improve CO2 fixation, or engineer novel CO2-fixing organisms.

Investigating the Evolution and Development of Biological Systems from the Perspective of Thermo-Kinetics and Systems Theory

Life itself is grander than the sum of its constituent molecules. Any living organism may be regarded as a part of a dissipative process that connects irreversible energy consumption with growth, reproduction, and evolution. Under energy-fuelled, far-from-equilibrium conditions, chemical systems capable of exponential growth can manifest a specific form of stability- dynamic kinetic stability (DKS) - indicating the persistence of self-reproducible entities. This kinetic behavior is associated with thermodynamic conditions far from equilibrium leading to an evolutionary view of the origin of life in which increasing entities have to be associated with the dissipation of free energy. This review aims to reformulate Darwinian theory in physicochemical terms so that it can handle both animate and inanimate systems, thus helping to overcome this theoretical divide. The expanded formulation is based on the principle of dynamic kinetic stability and evidence from the emerging field of systems chemistry. Although the classic Darwinian theory is useful for understanding the origins and evolution of species, it is not meant to primarily build an explicit framework for predicting potential evolution routes. Throughout the last century, the inherently systemic and dynamic nature of the biological systems has been brought to the attention of researchers. During the last decades, "systems" approaches to biology and genome evolution are gaining ever greater significance providing the possibility of a deeper interpretation of the basic concepts of life. Further progress of this approach depends on crossing disciplinary boundaries and complex simulations of biological systems. Evolutionary systems biology (ESB) through the integration of methods from evolutionary biology and systems biology aims to the understanding of the fundamental principles of life as well as the prediction of biological systems evolution.

Awakening a latent carbon fixation cycle in Escherichia coli

Carbon fixation is one of the most important biochemical processes. Most natural carbon fixation pathways are thought to have emerged from enzymes that originally performed other metabolic tasks. Can we recreate the emergence of a carbon fixation pathway in a heterotrophic host by recruiting only endogenous enzymes? In this study, we address this question by systematically analyzing possible carbon fixation pathways composed only of Escherichia coli native enzymes. We identify the GED (Gnd-Entner-Doudoroff) cycle as the simplest pathway that can operate with high thermodynamic driving force. This autocatalytic route is based on reductive carboxylation of ribulose 5-phosphate (Ru5P) by 6-phosphogluconate dehydrogenase (Gnd), followed by reactions of the Entner-Doudoroff pathway, gluconeogenesis, and the pentose phosphate pathway. We demonstrate the in vivo feasibility of this new-to-nature pathway by constructing E. coli gene deletion strains whose growth on pentose sugars depends on the GED shunt, a linear variant of the GED cycle which does not require the regeneration of Ru5P. Several metabolic adaptations, most importantly the increased production of NADPH, assist in establishing sufficiently high flux to sustain this growth. Our study exemplifies a trajectory for the emergence of carbon fixation in a heterotrophic organism and demonstrates a synthetic pathway of biotechnological interest.

Origin of exponential growth in nonlinear reaction networks

Exponentially growing systems are prevalent in nature, spanning all scales from biochemical reaction networks in single cells to food webs of ecosystems. How exponential growth emerges in nonlinear systems is mathematically unclear. Here, we describe a general theoretical framework that reveals underlying principles of long-term growth: scalability of flux functions and ergodicity of the rescaled systems. Our theory shows that nonlinear fluxes can generate not only balanced growth but also oscillatory or chaotic growth modalities, explaining nonequilibrium dynamics observed in cell cycles and ecosystems. Our mathematical framework is broadly useful in predicting long-term growth rates from natural and synthetic networks, analyzing the effects of system noise and perturbations, validating empirical and phenomenological laws on growth rate, and studying autocatalysis and network evolution.

Recent Advances in Developing Artificial Autotrophic Microorganism for Reinforcing CO2 Fixation

With the goal of achieving carbon sequestration, emission reduction and cleaner production, biological methods have been employed to convert carbon dioxide (CO₂) into fuels and chemicals. However, natural autotrophic organisms are not suitable cell factories due to their poor carbon fixation efficiency and poor growth rate. Heterotrophic microorganisms are promising candidates, since they have been proven to be efficient biofuel and chemical production chassis. This review first briefly summarizes six naturally occurring CO₂ fixation pathways, and then focuses on recent advances in artificially designing efficient CO₂ fixation pathways. Moreover, this review discusses the transformation of heterotrophic microorganisms into hemiautotrophic microorganisms and delves further into fully autotrophic microorganisms (artificial autotrophy) by use of synthetic biological tools and strategies. Rapid developments in artificial autotrophy have laid a solid foundation for the development of efficient carbon fixation cell factories. Finally, this review highlights future directions toward large-scale applications. Artificial autotrophic microbial cell factories need further improvements in terms of CO₂ fixation pathways, reducing power supply, compartmentalization and host selection.

Methanol-dependent Escherichia coli strains with a complete ribulose monophosphate cycle

Methanol is a biotechnologically promising substitute for food and feed substrates since it can be produced renewably from electricity, water and CO2. Although progress has been made towards establishing Escherichia coli as a platform organism for methanol conversion via the energy efficient ribulose monophosphate (RuMP) cycle, engineering strains that rely solely on methanol as a carbon source remains challenging. Here, we apply flux balance analysis to comprehensively identify methanol-dependent strains with high potential for adaptive laboratory evolution. We further investigate two out of 1200 candidate strains, one with a deletion of fructose-1,6-bisphosphatase (fbp) and another with triosephosphate isomerase (tpiA) deleted. In contrast to previous reported methanol-dependent strains, both feature a complete RuMP cycle and incorporate methanol to a high degree, with up to 31 and 99% fractional incorporation into RuMP cycle metabolites. These strains represent ideal starting points for evolution towards a fully methylotrophic lifestyle.

Universal motifs and the diversity of autocatalytic systems

Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks. This allows for a classification of minimal autocatalytic motifs called cores. While all known autocatalytic systems indeed contain minimal motifs, the classification also reveals hitherto unidentified motifs. We further examine conditions for kinetic viability of such networks, which depends on the autocatalytic motifs they contain and is notably increased by internal catalytic cycles. Finally, we show how this framework extends the range of conceivable autocatalytic systems, by applying our stoichiometric and kinetic analysis to autocatalysis emerging from coupled compartments. The unified approach to autocatalysis presented in this work lays a foundation toward the building of a systems-level theory of chemical evolution.

Escherichia coli in Auto(trophic) Mode

It is challenging to convert a heterotrophic organism that loves sugars and other multicarbon compounds as energy and carbon sources into an autotroph that builds all biomass from carbon dioxide. In this issue, Gleizer et al. demonstrate how this can be achieved.

Conversion of Escherichia coli to Generate All Biomass Carbon from CO2

The living world is largely divided into autotrophs that convert CO₂ into biomass and heterotrophs that consume organic compounds. In spite of widespread interest in renewable energy storage and more sustainable food production, the engineering of industrially relevant heterotrophic model organisms to use CO₂ as their sole carbon source has so far remained an outstanding challenge. Here, we report the achievement of this transformation on laboratory timescales. We constructed and evolved Escherichia coli to produce all its biomass carbon from CO₂. Reducing power and energy, but not carbon, are supplied via the one-carbon molecule formate, which can be produced electrochemically. Rubisco and phosphoribulokinase were co-expressed with formate dehydrogenase to enable CO₂ fixation and reduction via the Calvin-Benson-Bassham cycle. Autotrophic growth was achieved following several months of continuous laboratory evolution in a chemostat under intensifying organic carbon limitation and confirmed via isotopic labeling.

Glycolytic Shunts Replenish the Calvin-Benson-Bassham Cycle as Anaplerotic Reactions in Cyanobacteria

The recent discovery of the Entner-Doudoroff (ED) pathway as a third glycolytic route beside Embden-Meyerhof-Parnas (EMP) and oxidative pentose phosphate (OPP) pathway in oxygenic photoautotrophs requires a revision of their central carbohydrate metabolism. In this study, unexpectedly, we observed that deletion of the ED pathway alone, and even more pronounced in combination with other glycolytic routes, diminished photoautotrophic growth in continuous light in the cyanobacterium Synechocystis sp. PCC 6803. Furthermore, we found that the ED pathway is required for optimal glycogen catabolism in parallel to an operating Calvin-Benson-Bassham (CBB) cycle. It is counter-intuitive that glycolytic routes, which are a reverse to the CBB cycle and do not provide any additional biosynthetic intermediates, are important under photoautotrophic conditions. However, observations on the ability to reactivate an arrested CBB cycle revealed that they form glycolytic shunts that tap the cellular carbohydrate reservoir to replenish the cycle. Taken together, our results suggest that the classical view of the CBB cycle as an autocatalytic, completely autonomous cycle that exclusively relies on its own enzymes and CO2 fixation to regenerate ribulose-1,5-bisphosphate for Rubisco is an oversimplification. We propose that in common with other known autocatalytic cycles, the CBB cycle likewise relies on anaplerotic reactions to compensate for the depletion of intermediates, particularly in transition states and under fluctuating light conditions that are common in nature.

Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.

The industrial yeast Pichia pastoris is converted from a heterotroph into an autotroph capable of growth on CO2

The methylotrophic yeast Pichia pastoris is widely used in the manufacture of industrial enzymes and pharmaceuticals. Like most biotechnological production hosts, P. pastoris is heterotrophic and grows on organic feedstocks that have competing uses in the production of food and animal feed. In a step toward more sustainable industrial processes, we describe the conversion of P. pastoris into an autotroph that grows on CO2. By addition of eight heterologous genes and deletion of three native genes, we engineer the peroxisomal methanol-assimilation pathway of P. pastoris into a CO2-fixation pathway resembling the Calvin-Benson-Bassham cycle, the predominant natural CO2-fixation pathway. The resulting strain can grow continuously with CO2 as a sole carbon source at a µmax of 0.008 h-1. The specific growth rate was further improved to 0.018 h-1 by adaptive laboratory evolution. This engineered P. pastoris strain may promote sustainability by sequestering the greenhouse gas CO2, and by avoiding consumption of an organic feedstock with alternative uses in food production.

Renewable methanol and formate as microbial feedstocks

Methanol and formate are attractive microbial feedstocks as they can be sustainably produced from CO₂ and renewable energy, are completely miscible, and are easy to store and transport. Here, we provide a biochemical perspective on microbial growth and bioproduction using these compounds. We show that anaerobic growth of acetogens on methanol and formate is more efficient than on H₂/CO₂ or CO. We analyze the aerobic C₁ assimilation pathways and suggest that new-to-nature routes could outperform their natural counterparts. We further discuss practical bioprocessing aspects related to growth on methanol and formate, including feedstock toxicity. While challenges in realizing sustainable production from methanol and formate still exist, the utilization of these feedstocks paves the way towards a truly circular carbon economy.

Design of conditions for self-replication

A "self-replicator" is usually understood to be an object of definite form that promotes the conversion of materials in its environment into a nearly identical copy of itself. The challenge of engineering novel, micro- or nanoscale self-replicators has attracted keen interest in recent years, both because exponential amplification is an attractive method for generating high yields of specific products and, also, because self-reproducing entities have the potential to be optimized or adapted through rounds of iterative selection. Substantial steps forward have been achieved both in the engineering of particular self-replicating molecules and in the characterization of the physical basis for possible mechanisms of self-replication. At present, however, there is a need for a theoretical treatment of what physical conditions are most conducive to the emergence of novel self-replicating structures from a reservoir of building blocks on a desired time scale. Here we report progress in addressing this need. By analyzing the kinetics of a toy chemical model, we demonstrate that the emergence of self-replication can be controlled by coarse, tunable features of the chemical system, such as the fraction of fast reactions and the width of the rate constant distribution. We also find that the typical mechanism is dominated by the cooperation of multiple interconnected reaction cycles as opposed to a single isolated cycle. The quantitative treatment presented here may prove useful for designing novel self-replicating chemical systems.

Detailed profiling of carbon fixation of in silico synthetic autotrophy with reductive tricarboxylic acid cycle and Calvin-Benson-Bassham cycle in Esherichia coli using hydrogen as an energy source

Carbon fixation is the main route of inorganic carbon in the form of CO₂ into the biosphere. In nature, RuBisCO is the most abundant protein that photosynthetic organisms use to fix CO₂ from the atmosphere through the Calvin-Benson-Bassham (CBB) cycle. However, the CBB cycle is limited by its low catalytic rate and low energy efficiency. In this work, we attempt to integrate the reductive tricarboxylic acid and CBB cycles in silico to further improve carbon fixation capacity. Key heterologous enzymes, mostly carboxylating enzymes, are inserted into the Esherichia coli core metabolic network to assimilate CO₂ into biomass using hydrogen as energy source. Overall, such a strain shows enhanced growth yield with simultaneous running of dual carbon fixation cycles. Our key results include the following. (i) We identified two main growth states: carbon-limited and hydrogen-limited; (ii) we identified a hierarchy of carbon fixation usage when hydrogen supply is limited; and (iii) we identified the alternative sub-optimal growth mode while performing genetic perturbation. The results and modeling approach can guide bioengineering projects toward optimal production using such a strain as a microbial cell factory.

Kinetic modeling of the Calvin cycle identifies flux control and stable metabolomes in Synechocystis carbon fixation

Biological fixation of atmospheric CO2 via the Calvin-Benson-Bassham cycle has massive ecological impact and offers potential for industrial exploitation, either by improving carbon fixation in plants and autotrophic bacteria, or by installation into new hosts. A kinetic model of the Calvin-Benson-Bassham cycle embedded in the central carbon metabolism of the cyanobacterium Synechocystis sp. PCC 6803 was developed to investigate its stability and underlying control mechanisms. To reduce the uncertainty associated with a single parameter set, random sampling of the steady-state metabolite concentrations and the enzyme kinetic parameters was employed, resulting in millions of parameterized models which were analyzed for flux control and stability against perturbation. Our results show that the Calvin cycle had an overall high intrinsic stability, but a high concentration of ribulose 1,5-bisphosphate was associated with unstable states. Low substrate saturation and high product saturation of enzymes involved in highly interconnected reactions correlated with increased network stability. Flux control, that is the effect that a change in one reaction rate has on the other reactions in the network, was distributed and mostly exerted by energy supply (ATP), but also by cofactor supply (NADPH). Sedoheptulose 1,7-bisphosphatase/fructose 1,6-bisphosphatase, fructose-bisphosphate aldolase, and transketolase had a weak but positive effect on overall network flux, in agreement with published observations. The identified flux control and relationships between metabolite concentrations and system stability can guide metabolic engineering. The kinetic model structure and parameterizing framework can be expanded for analysis of metabolic systems beyond the Calvin cycle.

Daring metabolic designs for enhanced plant carbon fixation

Increasing agricultural productivity is one of the major challenges our society faces. While multiple strategies to enhance plant carbon fixation have been suggested, and partially implemented, most of them are restricted to relatively simple modifications of endogenous metabolism, i.e., "low hanging fruit". Here, I portray the next generation of metabolic solutions to increase carbon fixation rate and yield. These strategies involve major rewiring of central metabolism, including dividing Rubisco's catalysis between several enzymes, replacing Rubisco with a different carboxylation reaction, substituting the Calvin Cycle with alternative carbon fixation pathways, and engineering photorespiration bypass routes that do not release carbon. While the barriers for implementing these elaborated metabolic architectures are quite significant, if we truly want to revolutionize carbon fixation, only daring engineering efforts will lead the way.

Exploiting limited valence patchy particles to understand autocatalytic kinetics

Autocatalysis, i.e., the speeding up of a reaction through the very same molecule which is produced, is common in chemistry, biophysics, and material science. Rate-equation-based approaches are often used to model the time dependence of products, but the key physical mechanisms behind the reaction cannot be properly recognized. Here, we develop a patchy particle model inspired by a bicomponent reactive mixture and endowed with adjustable autocatalytic ability. Such a coarse-grained model captures all general features of an autocatalytic aggregation process that takes place under controlled and realistic conditions, including crowded environments. Simulation reveals that a full understanding of the kinetics involves an unexpected effect that eludes the chemistry of the reaction, and which is crucially related to the presence of an activation barrier. The resulting analytical description can be exported to real systems, as confirmed by experimental data on epoxy-amine polymerizations, solving a long-standing issue in their mechanistic description.

Improving formaldehyde consumption drives methanol assimilation in engineered E. coli

Due to volatile sugar prices, the food vs fuel debate, and recent increases in the supply of natural gas, methanol has emerged as a promising feedstock for the bio-based economy. However, attempts to engineer Escherichia coli to metabolize methanol have achieved limited success. Here, we provide a rigorous systematic analysis of several potential pathway bottlenecks. We show that regeneration of ribulose 5-phosphate in E. coli is insufficient to sustain methanol assimilation, and overcome this by activating the sedoheptulose bisphosphatase variant of the ribulose monophosphate pathway. By leveraging the kinetic isotope effect associated with deuterated methanol as a chemical probe, we further demonstrate that under these conditions overall pathway flux is kinetically limited by methanol dehydrogenase. Finally, we identify NADH as a potent kinetic inhibitor of this enzyme. These results provide direction for future engineering strategies to improve methanol utilization, and underscore the value of chemical biology methodologies in metabolic engineering.

Ribulose Monophosphate Shunt Provides Nearly All Biomass and Energy Required for Growth of E. coli

The ribulose monophosphate (RuMP) cycle is a highly efficient route for the assimilation of reduced one-carbon compounds. Despite considerable research, the RuMP cycle has not been fully implemented in model biotechnological organisms such as Escherichia coli, mainly since the heterologous establishment of the pathway requires addressing multiple challenges: sufficient formaldehyde production, efficient formaldehyde assimilation, and sufficient regeneration of the formaldehyde acceptor, ribulose 5-phosphate. Here, by efficiently producing formaldehyde from sarcosine oxidation and ribulose 5-phosphate from exogenous xylose, we set aside two of these concerns, allowing us to focus on the particular challenge of establishing efficient formaldehyde assimilation via the RuMP shunt, the linear variant of the RuMP cycle. We have generated deletion strains whose growth depends, to different extents, on the activity of the RuMP shunt, thus incrementally increasing the selection pressure for the activity of the synthetic pathway. Our final strain depends on the activity of the RuMP shunt for providing the cell with almost all biomass and energy needs, presenting an absolute coupling between growth and activity of key RuMP cycle components. This study shows the value of a stepwise problem solving approach when establishing a difficult but promising pathway, and is a strong basis for future engineering, selection, and evolution of model organisms for growth via the RuMP cycle.

The genetic basis for the adaptation of E. coli to sugar synthesis from CO2

Understanding the evolution of a new metabolic capability in full mechanistic detail is challenging, as causative mutations may be masked by non-essential "hitchhiking" mutations accumulated during the evolutionary trajectory. We have previously used adaptive laboratory evolution of a rationally engineered ancestor to generate an Escherichia coli strain able to utilize CO₂ fixation for sugar synthesis. Here, we reveal the genetic basis underlying this metabolic transition. Five mutations are sufficient to enable robust growth when a non-native Calvin-Benson-Bassham cycle provides all the sugar-derived metabolic building blocks. These mutations are found either in enzymes that affect the efflux of intermediates from the autocatalytic CO₂ fixation cycle toward biomass (prs, serA, and pgi), or in key regulators of carbon metabolism (crp and ppsR). Using suppressor analysis, we show that a decrease in catalytic capacity is a common feature of all mutations found in enzymes. These findings highlight the enzymatic constraints that are essential to the metabolic stability of autocatalytic cycles and are relevant to future efforts in constructing non-native carbon fixation pathways.