Stoichiometric Constraints Research Articles

Elemental composition and potential toxicity of the riverine macrophyte Podostemum ceratophyllum Michx. reflects land use in eastern North America

Land use influences surface water quality, often alleviating stoichiometric constraints on primary production and altering biogeochemical cycling. However, land use effects on nutrient content and potential trace metal accumulation in aquatic plants remain unclear, and high concentrations of metals and altered nutrient ratios could impact the health of herbivores and detritivores. We tested for land use effects on nutrient and trace metal accumulation in a widespread riverine macrophyte, Podostemum ceratophyllum, collected from 91 locations from Georgia to Maine, USA in 2014–2016. We quantified carbon (C), nitrogen (N), phosphorus (P), their molar and mass ratios, N and C stable isotopes, and 17 additional elements in dried plants collected from each location to estimate relationships between plant tissue content and watershed land use, which we quantified as agriculture, forest, and development. Decreasing forest cover was correlated with increasing δ15N, Mg, Mn, and P in Podostemum tissue. Increasing urban development was correlated with increasing δ15N, Mg and P, while increasing agriculture was correlated with a decrease in C: P and the concentrations of multiple metals, along with increases in P, Mg and δ15N. Decreases in ratios of N: P and C:P with increasing agriculture and urban development in the watershed indicate more rapid P storage relative to C and N in plant tissue, and increased resource quality of the plant to consumers in these watersheds. We also observed potentially toxic dietary concentrations of some trace metals (B, Cd, Tl, Zn) in plant tissue which could be related to the plant's natural herbivory defense system or to land use. We conclude that land use influences the elemental composition of P. ceratophyllum, and potentially the quality and toxicity of the plant to herbivores and detritivores in eastern North American rivers.

MInsc coordinates Par3 and NuMA condensates for assembly of the spindle orientation machinery in asymmetric cell division

As a fundamental process governing the self-renewal and differentiation of stem cells, asymmetric cell division is controlled by several conserved regulators, including the polarity protein Par3 and the microtubule-associated protein NuMA, which orchestrate the assembly and interplay of the Par3/Par6/mInsc/LGN complex at the apical cortex and the LGN/Gαi/NuMA/Dynein complex at the mitotic spindle to ensure asymmetric segregation of cell fate determinants. However, this model, which is well-supported by genetic studies, has been challenged by evidence of competitive interaction between NuMA and mInsc for LGN. Here, the solved crystal structure of the Par3/mInsc complex reveals that mInsc competes with Par6β for Par3, raising questions about how proteins assemble overlapping targets into functional macromolecular complexes. Unanticipatedly, we discover that Par3 can recruit both Par6β and mInsc by forming a dynamic condensate through phase separation. Similarly, the phase-separated NuMA condensate enables the coexistence of competitive NuMA and mInsc with LGN in the same compartment. Bridge by mInsc, Par3/Par6β and LGN/NuMA condensates coacervate, robustly enriching all five proteins both in vitro and within cells. These findings highlight the pivotal role of protein condensates in assembling multi-component signalosomes that incorporate competitive protein-protein interaction pairs, effectively overcoming stoichiometric constraints encountered in conventional protein complexes.

Gas-Solid flow and mass transfer characteristics in activated carbon adsorption equipment: The impact of structural outline

The efficacy of adsorption of volatile organic compounds (VOCs) in industrial emissions by activated carbon (AC) is influenced by adsorption kinetics and hydrodynamics. To simulate the performance of continuous flow AC adsorption process, a computational fluid dynamics (CFD) model that includes both multiphase flow and adsorption kinetics was developed. Because of its well-understood adsorption mechanism, N-butane was chosen as the target contaminant in this investigation. Simulation results revealed that velocity distribution uniformity is deeply affected by structural outline. According to simulations of the heat and mass transfer process, the adsorption reaction stoichiometric constraints between n-butane and AC were achieved; however, full utilization of AC was difficult to reach because of the hindered heat accumulation and mass transfer diffusion. Different structural outline leads to a 2.15 % improvement of adsorption efficiency due to an enhancement in the velocity distribution uniformity. The CFD model adequately describes the breakage curve occurring in the gas-solid multiphase flow system and confirms that heat and mass transfer is the rate limiting step in contaminant adsorption. This article investigates the effects of velocity distribution, heat and mass transfer on adsorption efficiency in equipment with different structural outline, and provide valuable insights into the design and application of equipment for eliminating VOCs.

Microbial utilisation of maize rhizodeposits applied to agricultural soil at a range of concentrations

AbstractRhizodeposition fuels carbon (C) and nutrient cycling in soil. However, changes in the dynamics of microbial growth on rhizodeposits with increasing distance from the root is not well studied. This study investigates microbial growth on individual organic components of rhizodeposits and maize root‐derived exudates and mucilage from agricultural soil. By creating a gradient of substrate concentrations, we simulated reduced microbial access to rhizosphere C with increasing distance to the root surface. We identified distinct C‐thresholds for the activation of microbial growth, and these were significantly higher for rhizodeposits than singular, simple sugars. In addition, testing for stoichiometric constraints of microbial growth by supplementing nitrogen (N) and phosphorus (P) showed accelerated and increased microbial growth by activating a larger proportion of the microbial biomass. Early and late season exudates triggered significantly different microbial growth responses. The mineralization of early‐season exudates was induced at a high C‐threshold. In contrast, the mineralization of late‐season exudates showed ‘sugar‐like’ properties, with a low C‐threshold, high substrate affinity, and a reduced maximum respiration rate of microorganisms growing on the added substrate. Mucilage exhibited the highest C‐threshold for the activation of microbial growth, although with a short lag‐period and with an efficient mucilage degradation comparable to that of sugars. By determining kinetic parameters and turnover times for different root‐derived substrates, our data enable the upscaling of micro‐scale processes to the whole root system, allowing more accurate predictions of how rhizodeposition drives microbial C and nutrient dynamics in the soil.

Thermodynamic and stoichiometric laws ruling the fates of growing systems

We delve into growing open chemical reaction systems (CRSs) characterized by autocatalytic reactions within a variable volume, which changes in response to these reactions. Understanding the thermodynamics of such systems is crucial for comprehending biological cells and constructing protocells because it sheds light on the physical conditions necessary for their self-replication. Building on our recent work, where we developed a thermodynamic theory for growing CRSs featuring basic autocatalytic motifs with regular stoichiometric matrices, we now expand this theory to include scenarios where the stoichiometric matrix has a nontrivial left kernel space. This extension introduces conservation laws, which limit the variations in chemical species due to reactions, thereby confining the system's possible states to those compatible with its initial conditions. By considering both thermodynamic and stoichiometric constraints, we clarify the environmental and initial conditions that dictate the CRSs' fate—whether they grow, shrink, or reach equilibrium. We also find that the conserved quantities significantly influence the equilibrium state achieved by a growing CRS. These results are derived independently of specific thermodynamic potentials or reaction kinetics, therefore underscoring the fundamental impact of conservation laws on the growth of the system. Published by the American Physical Society 2024

WinClbclas, a Windows program for columbite-supergroup minerals

AbstractA Microsoft® Visual Basic software, WinClbclas, has been developed to calculate the chemical formulae of columbite-supergroup minerals based on data obtained from wet-chemical and electron-microprobe analyses and using the current nomenclature scheme adopted by the Commission on New Minerals, Nomenclature and Classification (CNMNC) of the International Mineralogical Association (IMA) for columbite-supergroup minerals. The program evaluates 36 IMA-approved species, three questionable in terms of their unit-cell parameters, four insufficiently studied questionable species and one ungrouped species, all according to the dominant valance and constituent status in five mineral groups including ixiolite (MO2), wolframite (M1M2O4), samarskite (ABM2O8), columbite (M1M2O6) and wodginite (M1M2M32O8). Mineral compositions of the columbite supergroup are calculated on the basis of 24 oxygen atoms per formula unit. However, the formulae of the five ixiolite to wodginite groups can be estimated by the program on the basis of their cation and anion values in their typical mineral formulae (e.g. 4 cations and 8 oxygens for the wodginite group) with normalisation procedures. The Fe3+ and Fe2+ contents from microprobe-derived total FeO (wt.%) amounts are estimated by stoichiometric constraints. WinClbclas allows users to: (1) enter up to 47 input variables for mineral compositions; (2) type and load multiple columbite-supergroup mineral compositions in the data entry section; (3) edit and load the Microsoft® Excel files used in calculating, classifying, and naming the columbite-supergroup minerals, together with the total monovalent to hexavalent ion; and (4) store all the calculated parameters in the output of a Microsoft® Excel file for further data evaluation. The program is distributed as a self-extracting setup file, including the necessary support files used by the program, a help file and representative sample data files.

Does nutrient enrichment alleviate stoichiometric constraint on plankton trophic structure?

AbstractStoichiometric mismatch between phytoplankton and zooplankton has implication for trophic transfer efficiency. Phosphorus (P) enrichment is expected to lower phytoplankton carbon (C) to P ratio (C : P) and thereby either alleviate P deficiency or induce excess P for zooplankton. However, the generality of zooplankton facing excess P and its effect on plankton trophic structure in natural systems are poorly understood. We analyzed the stoichiometry of seston and zooplankton, and plankton trophic structure in 32 (sub)tropical Chinese reservoirs. Our results showed that (1) stoichiometric mismatch between seston and zooplankton involved P or/and nitrogen (N) deficits in low‐nutrient reservoirs and P excess in high‐nutrient reservoirs; (2) at given seston C and phytoplankton compositional food quality levels, zooplankton to phytoplankton biomass ratio (Zoo : Phyto) showed a two‐segment piecewise relationship to seston N : P with a maximum at a breakpoint of 12.6 and strong reductions toward the extremes of seston N : P gradient; (3) increasing stoichiometric mismatch between seston and consumers reduced the contribution of cladocerans to zooplankton biomass and increased the trophic position of copepods; and (4) chlorophyll a (Chl a) to total phosphorus (TP) ratio (Chl a : TP) increased with decreasing Zoo : Phyto, and at a given Zoo : Phyto, it was higher in reservoirs with zooplankton dominated by copepods than in reservoirs with zooplankton dominated by cladocerans. These findings suggest that nutrient enrichment might improve stoichiometric constraint on plankton trophic structure in low‐nutrient reservoirs, but enhance negative effect of excess P in high‐nutrient reservoirs. Thus, negative impact of excess P on zooplankton may be a mechanism partly contributing to low Zoo : Phyto and high Chl a : TP in eutrophic reservoirs.

Understanding stoichiometric constraints on growth using resource use efficiency imbalances

Growth is a function of the net accrual of resources by an organism. Energy and elemental contents of organisms are dynamically linked through their uptake and allocation to biomass production, yet we lack a full understanding of how these dynamics regulate growth rate. Here, we develop a multivariate imbalance framework, the growth efficiency hypothesis, linking organismal resource contents to growth and metabolic use efficiencies, and demonstrate its effectiveness in predicting consumer growth rates under elemental and food quantity limitation. The relative proportions of carbon (%C), nitrogen (%N), phosphorus (%P), and adenosine triphosphate (%ATP) in consumers differed markedly across resource limitation treatments. Differences in their resource composition were linked to systematic changes in stoichiometric use efficiencies, which served to maintain relatively consistent relationships between elemental and ATP content in consumer tissues and optimize biomass production. Overall, these adjustments were quantitatively linked to growth, enabling highly accurate predictions of consumer growth rates.

Convex Representation of Metabolic Networks with Michaelis–Menten Kinetics

Polyhedral models of metabolic networks are computationally tractable and can predict some cellular functions. A longstanding challenge is incorporating metabolites without losing tractability. In this paper, we do so using a new second-order cone representation of the Michaelis–Menten kinetics. The resulting model consists of linear stoichiometric constraints alongside second-order cone constraints that couple the reaction fluxes to metabolite concentrations. We formulate several new problems around this model: conic flux balance analysis, which augments flux balance analysis with metabolite concentrations; dynamic conic flux balance analysis; and finding minimal cut sets of networks with both reactions and metabolites. Solving these problems yields information about both fluxes and metabolite concentrations. They are second-order cone or mixed-integer second-order cone programs, which, while not as tractable as their linear counterparts, can nonetheless be solved at practical scales using existing software.

ECMpy 2.0: A Python package for automated construction and analysis of enzyme-constrained models

Genome-scale metabolic models (GEMs) have been widely employed to predict microorganism behaviors. However, GEMs only consider stoichiometric constraints, leading to a linear increase in simulated growth and product yields as substrate uptake rates rise. This divergence from experimental measurements prompted the creation of enzyme-constrained models (ecModels) for various species, successfully enhancing chemical production. Building upon studies that allocate macromolecule resources, we developed a Python-based workflow (ECMpy) that constructs an enzyme-constrained model. This involves directly imposing an enzyme amount constraint in GEM and accounting for protein subunit composition in reactions. However, this procedure demands manual collection of enzyme kinetic parameter information and subunit composition details, making it rather user-unfriendly. In this work, we've enhanced the ECMpy toolbox to version 2.0, broadening its scope to automatically generate ecGEMs for a wider array of organisms. ECMpy 2.0 automates the retrieval of enzyme kinetic parameters and employs machine learning for predicting these parameters, which significantly enhances parameter coverage. Additionally, ECMpy 2.0 introduces common analytical and visualization features for ecModels, rendering computational results more user accessible. Furthermore, ECMpy 2.0 seamlessly integrates three published algorithms that exploit ecModels to uncover potential targets for metabolic engineering. ECMpy 2.0 is available at https://github.com/tibbdc/ECMpy or as a pip package (https://pypi.org/project/ECMpy/).

Diatom-mediated food web functioning under ocean artificial upwelling

Enhancing ocean productivity by artificial upwelling is evaluated as a nature-based solution for food security and climate change mitigation. Fish production is intended through diatom-based plankton food webs as these are assumed to be short and efficient. However, our findings from mesocosm experiments on artificial upwelling in the oligotrophic ocean disagree with this classical food web model. Here, diatoms did not reduce trophic length and instead impaired the transfer of primary production to crustacean grazers and small pelagic fish. The diatom-driven decrease in trophic efficiency was likely mediated by changes in nutritional value for the copepod grazers. Whilst diatoms benefitted the availability of essential fatty acids, they also caused unfavorable elemental compositions via high carbon-to-nitrogen ratios (i.e. low protein content) to which the grazers were unable to adapt. This nutritional imbalance for grazers was most pronounced in systems optimized for CO2 uptake through carbon-to-nitrogen ratios well beyond Redfield. A simultaneous enhancement of fisheries production and carbon sequestration via artificial upwelling may thus be difficult to achieve given their opposing stoichiometric constraints. Our study suggest that food quality can be more critical than quantity to maximize food web productivity during shorter-term fertilization of the oligotrophic ocean.

WinPclclas, a Windows Program for Pyrochlore Supergroup Minerals

Abstract A Microsoft® Visual Basic program, WinPclclas, has been developed to calculate the chemical formulae of pyrochlore supergroup minerals (PSM) based on data obtained from wet-chemical and electron-microprobe analyses. These are also classified following the nomenclature scheme adopted by the Commission on New Minerals, Nomenclature and Classification (CNMNC) of the International Mineralogical Association for PSM (IMA-10) and including both subsequent group and species updates. The program considers classification among the 33 IMA-approved PSM, as well as ten species that have not been approved, adhering to the general formula A2B2X6Y and considering the dominant ions at the A, B, and Y sites. It considers PSM represented by the pyrochlore, microlite, roméite, elsmoreite, and betafite groups, along with unassigned members of the ralstonite and coulsellite groups. Mineral formulae of the PSM are calculated based on the ideal number of B cations being two apfu, owing to the potential for vacancies at the A, X, and Y sites. WinPclclas operates in four stages: (1) it estimates cation and anion contents provided by input chemical data; (2) it determines the dominant cation and anion at the A, B, and Y sites; (3) it assigns the PSM to one of the seven groups, based on the dominant cation at the B site (i.e., W6+, Nb5+, Ta5+, Sb5+, Ti4+, Al3+, and Mg2+); and (4) it classifies the pyrochlore species into an appropriate group, based on the dominant cation at the A site and the dominant anion at the Y site. The H2O (wt.%) content for the PSM is estimated by stoichiometric constraints. WinPclclas allows users to: (1) enter up to 51 input variables for mineral-chemical analyses; (2) type and load multiple PSM compositions in the data entry section; (3) edit and load the Microsoft® Excel files used in calculating, classifying, and naming the PSM, together with the total monovalent to hexavalent cation, and (4) store all the calculated parameters in the output of a Microsoft® Excel file for further data evaluations. The program is distributed as a self-extracting setup file, including the necessary support files used by the program, a help file, and representative sample data files.

Carbon and nutrient colimitations control the microbial response to fresh organic carbon inputs in soil at different depths

Despite the potential of subsoil carbon (C) to buffer or amplify climate change impacts, how fresh C and nutrients interact to control microorganismal effects on the C balance in deep soil horizons has yet to be determined. In this study, we aimed to estimate the impact of fresh C input at different soil depths on soil microbial activity. To conduct this study, Mediterranean soils from 3 layers (0–20, 20–50 and 50–100 cm of depth) were incubated over 28 days. Carbon and nutrient fluxes were measured after the addition of an amount of C equivalent to the postharvest root litter derived-C of a barley crop (4.3 atom% 13C), with and without nitrogen and phosphorus supply. We found that the microbial mineralization was C limited in the topsoil, while C and N colimited in the subsoil. These variations in stoichiometric constraints along the soil profile induced different microbial responses to C and/or nutrient addition. A stronger priming effect was observed in the topsoil than in the subsoil, and the sole C addition induced a negative C balance. Conversely, subsoil showed a positive C balance following fresh C addition, changing to critical soil C losses when nutrients were supplied with C. Our results show that fresh C input to subsoil (e.g., through deep-rooting crops) might foster soil C sequestration, but this positive effect can be reversed if such C inputs are combined with high nutrient availability (e.g., through fertilization), alleviating microbial limitation at depth.

Improving pathway prediction accuracy of constraints-based metabolic network models by treating enzymes as microcompartments

Metabolic network models have become increasingly precise and accurate as the most widespread and practical digital representations of living cells. The prediction functions were significantly expanded by integrating cellular resources and abiotic constraints in recent years. However, if unreasonable modeling methods were adopted due to a lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of l-serine and l-tryptophan. A specific analysis explains the application method of the EcoETM-like model and demonstrates its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Our work is of great value for the structural improvement of constraints-based models.

Agricultural biomethane production in France: A spatially-explicit estimate

Biomethane production by anaerobic digestion can significantly contribute to the decarbonation and defossilization of the European energy mix. Although previous estimates have been provided about biomethane potential production in several European countries, they suffer from a coarse evaluation of substrate availability and a lack of spatial resolution. This paper provides a spatially-explicit assessment of the potential for biomethane production in France at a fine spatial resolution (NUTS 4 region) from agricultural biomass (livestock manure, crop residues and cover crops) and sewage sludge. This assessment is based on (i) a fine estimation of substrate availability, particularly for cover crop production, by combining a crop model with spatially-explicit soil and climate databases; (ii) the use of an anaerobic digestion model that predicts biomethane production from agricultural biomass; and (iii) a procedure for optimizing biomethane production while respecting the stoichiometric constraints of the substrate mixture. We found a significant potential for annual biomethane production of 64.1 TWh, mainly from cattle manure, a value that could reach 108.7 TWh through the generalization of cover crops within arable cropping systems. Our results also highlighted the importance of detailed substrate availability data to account for their large spatial variations. Accordingly, we showed that biomethane production was highly variable across the French regions and that crop residues could only partly be used for anaerobic digestion – especially in arable regions – because they lead to excessively dry substrate mixtures. This study helped to identify the most suitable regions for biomethane production and to provide accurate estimates for biomethane development in France.

Rate-independent Computation in Continuous Chemical Reaction Networks

Understanding the algorithmic behaviors that are in principle realizable in a chemical system is necessary for a rigorous understanding of the design principles of biological regulatory networks. Further, advances in synthetic biology herald the time when we will be able to rationally engineer complex chemical systems and when idealized formal models will become blueprints for engineering. Coupled chemical interactions in a well-mixed solution are commonly formalized as chemical reaction networks (CRNs). However, despite the widespread use of CRNs in the natural sciences, the range of computational behaviors exhibited by CRNs is not well understood. Here, we study the following problem: What functions f : ℝ k → ℝ can be computed by a CRN, in which the CRN eventually produces the correct amount of the “output” molecule, no matter the rate at which reactions proceed? This captures a previously unexplored but very natural class of computations: For example, the reaction X 1 + X 2 → Y can be thought to compute the function y = min ( x 1 , x 2 ). Such a CRN is robust in the sense that it is correct whether its evolution is governed by the standard model of mass-action kinetics, alternatives such as Hill-function or Michaelis-Menten kinetics, or other arbitrary models of chemistry that respect the (fundamentally digital) stoichiometric constraints (what are the reactants and products?). We develop a reachability relation based on a broad notion of “what could happen” if reaction rates can vary arbitrarily over time. Using reachability, we define stable computation analogously to probability 1 computation in distributed computing and connect it with a seemingly stronger notion of rate-independent computation based on convergence in the limit t → ∞ under a wide class of generalized rate laws. Besides the direct mapping of a concentration to a nonnegative analog value, we also consider the “dual-rail representation” that can represent negative values as the difference of two concentrations and allows the composition of CRN modules. We prove that a function is rate-independently computable if and only if it is piecewise linear (with rational coefficients) and continuous (dual-rail representation), or non-negative with discontinuities occurring only when some inputs switch from zero to positive (direct representation). The many contexts where continuous piecewise linear functions are powerful targets for implementation, combined with the systematic construction we develop for computing these functions, demonstrate the potential of rate-independent chemical computation.

Stoichiometric constraints in plankton communities of Patagonian lakes. Implications for Parabroteas sarsi distribution and conservation

The Patagonian region, from the Andes to the steppe, includes a profuse hydrographic network with deep and shallow lakes. Here, we analyze the stoichiometric constraints for the large predaceous copepod Parabroteas sarsi in fish and fishless lakes. For this purpose, we examined previous literature data on the composition of the zooplankton community in different Patagonian lakes with and without fish (mainly introduced in the XX century) and own laboratory and field experiments. The ecological stoichiometry theory predicts that consumers need to attain specific elemental ratios to achieve maximum growth, and the geometric framework of nutrition proposes that consumers may need to combine food items to fulfill nutrient requirements. We show that the predaceous copepod does not necessarily encounter prey that fulfills their stoichiometric requirements, thus growth is impaired. However, through the combination of different prey, this predator can fulfill its requirements. In the presence of fishes, food webs change towards smaller-sized zooplankton species with the loss of low C:nutrient ratio species. In this sense, we demonstrate the direct and indirect impact of fish introduction on the stoichiometric balances and the disappearance of this invertebrate predator in lacustrine food webs.

Existence, uniqueness and asymptotic behavior of solutions for a nonsmooth producer-grazer system with stoichiometric constraints

A reaction-diffusion-ODE system of stoichiometric producer-grazer type is considered in this paper. Since the system has nonsmooth nonlinearity, it is shown that the system has new dynamics different from the smooth case. We construct various types of discontinuous steady states and investigate their asymptotic behavior. In addition, the steady-state bifurcation near a constant solution is studied by treating the diffusion coefficient as a bifurcation parameter and the existence of Hopf bifurcation is derived. Our results cover the case where the number of positive equilibria of the kinetic system (i.e. without diffusion) changes from one to three in the spatial interval. Finally, some numerical simulations are given to illustrate the theoretical results.

Dynamics of a Stoichiometric Regrowth-Consumer Model

The relationship between the producer and the consumer is important in grassland ecosystems. Most producer-consumer models only consider food quantity and focus on the above ground part of producers in producer-consumer interactions, while food quality and the below ground part of the producer can be an important factor in these models. We developed a stoichiometric producer-consumer model, where the producer represents a primary production in terrestrial plant with above ground and below ground parts subject to stoichiometric constraints of carbon and phosphorus. The analysis shows that the dynamic behavior of the model is richer than that of the traditional producer-consumer models. The solution curves of the model can be used to explain the paradox of enrichment and reflect the rapid growth of the vegetation. Our findings help understand and interpret the relationship between the producer and the consumer in grassland ecosystems and provide guidance for ecosystem management on maintaining ecological equilibrium.

Construction and Analysis of an Enzyme-Constrained Metabolic Model of Corynebacterium glutamicum.

The genome-scale metabolic model (GEM) is a powerful tool for interpreting and predicting cellular phenotypes under various environmental and genetic perturbations. However, GEM only considers stoichiometric constraints, and the simulated growth and product yield values will show a monotonic linear increase with increasing substrate uptake rate, which deviates from the experimentally measured values. Recently, the integration of enzymatic constraints into stoichiometry-based GEMs was proven to be effective in making novel discoveries and predicting new engineering targets. Here, we present the first genome-scale enzyme-constrained model (ecCGL1) for Corynebacterium glutamicum reconstructed by integrating enzyme kinetic data from various sources using a ECMpy workflow based on the high-quality GEM of C. glutamicum (obtained by modifying the iCW773 model). The enzyme-constrained model improved the prediction of phenotypes and simulated overflow metabolism, while also recapitulating the trade-off between biomass yield and enzyme usage efficiency. Finally, we used the ecCGL1 to identify several gene modification targets for l-lysine production, most of which agree with previously reported genes. This study shows that incorporating enzyme kinetic information into the GEM enhances the cellular phenotypes prediction of C. glutamicum, which can help identify key enzymes and thus provide reliable guidance for metabolic engineering.