Streptomyces clavuligerus is a filamentous Gram-positive bacterial producer of the β-lactamase inhibitor clavulanic acid. Antibiotics biosynthesis in the Streptomyces genus is usually triggered by nutritional and environmental perturbations. In this work, a new genome scale metabolic network of Streptomyces clavuligerus was reconstructed and used to study the experimentally observed effect of oxygen and phosphate concentrations on clavulanic acid biosynthesis under high and low shear stress. A flux balance analysis based on experimental evidence revealed that clavulanic acid biosynthetic reaction fluxes are favored in conditions of phosphate limitation, and this is correlated with enhanced activity of central and amino acid metabolism, as well as with enhanced oxygen uptake. In silico and experimental results show a possible slowing down of tricarboxylic acid (TCA) due to reduced oxygen availability in low shear stress conditions. In contrast, high shear stress conditions are connected with high intracellular oxygen availability favoring TCA activity, precursors availability and clavulanic acid (CA) production. Streptomyces clavuligerus (S. clavuligerus) is a biotechnologically important Gram-positive filamentous bacterium for the production of β-lactam antibiotic compounds such as clavulanic acid (CA) and cephamycin C. In the current emergence of extended multidrug and antibiotic resistance phenomena, the β-lactam inhibitors remain as one of the main drugs used against bacterial resistant infections [S. clavuligerus [S. clavuligerus to different environmental and nutritional factors and its relationship with CA biosynthesis is not completely understood. In this regard, a strong correlation between macromorphology and CA production under low and high shear stress conditions in submerged cultures of S. clavuligerus was recently reported [S. clavuligerus cells, as comparably high specific growth and CA production rates were achieved. Additionally, it was assumed that CA production might be affected by a lower surface-to-volume ratio at thicker mycelia evolving under low-shear cultivation conditions, which would impact negatively upon the diffusion capacity and, therefore, the transport of nutrients, oxygen and product secretion.fections . CA has fections ,3. Severfections . It is luligerus ,6. Neverreported . The stuN2-(2-carboxy-ethyl) L-arginine to -clavaminic acid, and the late steps, comprising the reactions up to CA and the clavam 5S compounds [2-(2-carboxy-ethyl) L-arginine in a reaction catalyzed by the N2-(2-carboxyethyl) arginine synthase (CEAS). Glycerol is the preferred substrate for production of CA because of its rather direct conversion into glyceraldehyde 3-phosphate (GAP). GAP can be metabolized through three different pathways: (i) the gluconeogenesis and pentose phosphate pathway, (ii) the glycolysis and tricarboxylic acid (TCA) cycle and (iii) the clavam and CA biosynthesis pathway [CA is a product of the so-called clavam pathway. The clavam pathway is usually divided into the early steps, including the reactions from ompounds ,9. The f pathway .N2-(2-carboxy-ethyl) L-arginine by action of β-lactam synthetase (BLS) [Subsequently, deoxyguanidinoproclavaminic acid, a β-lactam compound, is formed by intramolecular reaction of se (BLS) ,12. Enzyse (BLS) . The amise (BLS) ,15. Procse (BLS) . At thisse (BLS) . Clavulase (BLS) . The thrse (BLS) ,20. CA bS. clavuligerus, metabolic network models have been reconstructed and/or updated for this purpose [A common approach for studying the effect of nutritional, genetic and environmental perturbations on metabolism is the genome-scale metabolic modeling using flux balance analysis (FBA) . In the  purpose ,22,23,24S. clavuligerus metabolism has been developed in this work. A novel top-down automated reconstruction tool proposed by Machado et al. [S. clavuligerus by Cao et al. [S. clavuligerus metabolism. This model was used in a combined approach of experimental and modeling work for investigating the connection between the different nutritional conditions observed in S. clavuligerus cultivations and CA biosynthesis. Defined media was used to study the influence of nutrients on carbon flux distribution during CA biosynthesis [S. clavuligerus given their connections with amino acid biosynthesis and degradation pathways [S. clavuligerus in a stirred tank and single-use 2-D rocking-motion bioreactors. A medium rich in glycerol but limited in phosphate and glutamate was used as feed in order to explore the effects of their depletion on the CA biosynthesis rate. Subsequently, the experimentally observed metabolic scenarios were simulated using the constructed and validated genome-scale model of S. clavuligerus in order to identify putative connections between the central carbon and amino acid metabolism, nutrient limiting conditions and CA production.Starting from recent advances in genome-scale model reconstruction and available genetic information, a new and improved genome-scale model of the o et al.  was usedo et al. . The iniynthesis ,27. Prevpathways . In thisS. clavuligerus representative genomes range between 7.6 and 8.5 Mb with a GC content of 72.6% and a median protein count of 6654. An initial Genome-Scale Metabolic Model (GEM) was generated from the representative genome of S. clavuligerus, sequenced by Cao et al. [S. clavuligerus, the script of CarveMe was executed in the Anaconda Python distribution for Linux; externally, the Diamond sequence aligner [o et al.  and curro et al. . The reco et al. . For the aligner  and IBM The initial GEM was manually curated by following a systematic procedure in order to improve the in silico representation of the physiology of the organism. The missing reactions and metabolites in the secondary metabolism, which correspond to penicillin–cephalosporin biosynthesis, clavulanic acid biosynthesis and 5S-clavams bifurcation were manually added and associated to the corresponding genes, while maintaining the connectivity of the model, and the mass and charge balances, respectively.® implementation of the Flux Variability Analysis (FVA) methodology proposed by Schellenberger et al. [−1.The flux distribution, obtained by solving a standard FBA optimization, frequently include thermodynamic infeasible cycles (TICs) that represent slopes of reactions like a perpetual motion machine that violates the Second Law of Thermodynamics. This heavily distorts the reaction flux predictions. It has been demonstrated that the number of infeasible loops grows rapidly with the network size . Therefor et al.  for TICsThe set of unbounded reactions which are part of the TICs were used to define a stoichiometric matrix. Its null space was used for the individual identification of TICs composed by two or more reactions. The manual curation of the TICs was performed by (i) elimination of linearly dependent reversible reactions resulting in redundancy due to erroneous identification of GPR during the automated reconstruction, and (ii) restriction of the reaction directionality by calculation of the correspondent Standard Gibbs free energy of reaction (∆Gr) using the NExT  algorithm . The scrS. clavuligerus is available in SBML (xml) and MS Excel (xlsx) file formats in the The final GEM, denoted as iDG1237, was reviewed with the MC3 Consistency Checker algorithm, which implements stoichiometric-based identification and FVA analysis to determine single connected and dead end metabolites in the network, as well as the consistent coupled and inconsistent coupled/zero-flux reactions . The iDGS. clavuligerus cultivations at high and low shear stress conditions. FBA solves a linear programming problem for calculating the steady-state reaction flux distributions along the metabolic network that maximizes (or minimizes) a pre-defined objective function, under specific constraints. The objective function shall reflect the achievement of a meaningful physiological state of the organism like a maximal ATP production, growth rate, or specific metabolite production [S is the stoichiometric matrix of coefficients for m metabolites and n reactions, v is the flux vector of dimension n, maxZ represents the biomass maximization, f is a vector of weights, and bl and bu are the lower and upper bounds, respectively. Thus, in the first stage the FBA standard problem for biomass maximization is solved, whereas the second stage deals with the minimization of the vector of fluxes. It is important to notice that the assumption underlying the objective function minimization, postulates that living organisms gain functional fitness by fulfilling their functions with maximal efficiency, and thus assuring a minimal energy requirement to accomplish a specific pattern of cellular functions [In the FBA studies the external/internal exchange reactions were constrained to represent, in silico, the environmental conditions observed in oduction . Some vaunctions . All FBAS. clavuligerus DSM 41826, cryo-preserved at −80 °C in glycerol solution (16.7% v/v), was inoculated for activation in seed medium as described by Roubos et al. [®  both operating at 5 L initial filling volume. Chemically defined media were used in all cultivations, prepared as follows (in g.L−1 deionized and distilled water): glycerol (9.3), K2HPO4 (0.8), (NH4)2SO4 (1.26), monosodium glutamate (9.8), FeSO4·7H2O (0.18), MgSO4·7H2O (0.72) and trace element solution (1.44 mL). The trace elements solution contained (in g.L−1 deionized and distilled water): H2SO4 (20.4), monosodium citrate·1H2O (50), ZnSO4·7H2O (16.75), CuSO4·5H2O (2.5), MnCl2·4H2O (1.5), H3BO3 (2), and Na2MoO4·2H2O (2) . Antifoam 204  was used at concentration of 1:1000 v/v. Bioreactors were inoculated (10% v/v) and operated at 28 °C; aeration at 0.6 VVM was provided and pH was maintained at 6.8 by addition of NaOH 3M and HCl 3M. Reactors were equipped with pH (Polylite Plus) dissolved oxygen (DO–VisiFerm) probes , O2, CO2 gas sensors and exhaust gas analyzer .s et al. . CultivaS. clavuligerus adapts differently to motion patterns and shear forces [−1 with a defined medium prepared as follows (in g.L−1 deionized and distilled water): glycerol (120.0), K2HPO4 (2.0), (NH4)2SO4 (8.0), until a final volume of 7.8 L was reached. During the batch operation DO was not controlled, only minimum DO was set at 20% to avoid anoxia. During fed-batch operation DO was maintained rather constant at 62 ± 5%. Culture samples (2 mL) were taken at 12 h intervals and centrifuged at 15,000 rpm and 4 °C for 10 min; wet biomass was washed with 0.9% NaCl, centrifuged and dried overnight at 75 °C for dry cell weight (DCW) determination.It has been reported that r forces . Therefo® GmbH, Aschaffenburg, Germany) operated with a flow rate of 1 mL.min−1 at 30 °C. The mobile phase consisted of H2PO4  and methanol (HPLC grade). Analyses were performed using the gradient method described by Ramirez-Malule [CA concentration in supernatant samples was determined in a HPLC  with a diode array detector (DAD), using a Zorbax Eclipse XDB-C-18 chromatographic column (Agilent Technologies) and a C-18 guard column  were used, and operated at a flow rate of 1 mL.min−1 and 40 °C. Mobile phase consisted of NaH2PO4  as polar eluent and a solution of methanol (45% vol.), acetonitrile (45% vol.) and water (10% vol.) as nonpolar eluent [Glycerol, glycolysis and TCA intermediates were quantified in a HPLC  with a refractive index detector (RID) and operated at 15 °C using a HyperREZ™ XP carbohydrate H+ column  at a constant flow rate of 0.5 mL.minle phase . Quantifr eluent . Semi-quS. clavuligerus in order to improve the in silico representation of its metabolism in comparison to previously reported GEMs. It considers the current state-of-the-art in genetics and biochemistry. The reconstruction process was based on an initial functional and high-quality universal model, in which infeasible reactions for S. clavuligerus were removed and constraints were added [Firstly, the aim of this study was to develop a novel GEM for re added . HoweverThe previous GEM share a common origin, the model iMM865 reported by Medema et al. . The derS. clavuligerus named iDG1237 consisted of 2177 reactions, including 543 internal/external metabolite exchange reactions and 1237 annotated genes. The metabolites were annotated according with their correspondent BiGG identifiers; similarly, the genes were annotated with their Refseq identifiers when available. The model consistency statistics for the iDG1237 model and the previous models for S. clavuligerus are presented in The resulting GEM of S. clavuligerus.The improved connectivity of the model is reflected in a lower number of dead-end metabolites. In the case of the iDG1237 GEM, the number of dead-end metabolites is considerably lower (3%) compared to previously reported GEMs (~27%). Additionally, the number of zero-flux reactions and inconsistent coupling was approximately 80% lower than in previous reconstructions. Therefore, the full consistent coupling allows better determination of relationships among reactions and pathways, connections between nutritional factors and desired metabolites, and analysis of potential knockouts, as well as further regulatory and expression studies ,44. The S. clavuligerus in a chemostat mode, using the experimental data published by Bushell et al. [ex,Glycv), glutamate , and phosphate  were constrained according to experimental data [expμ) and in silico (μ) growth rates, CA secretion fluxes  and cumulative mean square error (MSE), between the experimental and in silico data, are presented in 2 demand and CO2 excretion were also considered in the model evaluation , growth rate and CA accumulation were higher in HSS cultivations  than the one observed at HSS (11.9 g.L−1). The glycerol and glutamate concentration time courses are presented in −1, respectively. Similarly, the maximum uptake fluxes of glutamate were 1.34 and 1.29 mmol.(g DCW.h)−1 during a short time span in the batch stage.Experimental results of growth, CA, phosphate and metabolite secretion under high shear stress (HSS) and low shear stress (LSS) conditions are shown in ivations a,b. The S. clavuligerus, potentially limiting the oxygen diffusion from the media to the intracellular environment [The phosphate limitation was expected to start between 30 and 40 h and the specific CA production typically increased linked to phosphate depletion as observed in ironment . In LSS ironment . When inStreptomyces species like S. coelicolor and S. clavuligerus [Organic acid secretion in streptomycetes b–g is reuligerus ,47. In tL-arginine h is deriDuring growth, some accumulation of oxaloacetate is expected f due to S. clavuligerus cultivations in HSS and LSS conditions, six metabolic scenarios corresponding to different phases observed during the cultivation were considered for the in silico metabolic flux analysis. The complete results of the FBA simulations are available in the Based on the experimental results for Experimental results showed that growth, nutrient uptake and metabolite secretion were essentially the same in both bioreactors, during the first 37 h of cultivation. Two different growth scenarios (SC1 and SC2) were observed in absence of nutrient limitation during the initial batch phase (0–37 h). From 37 h onwards, the effect of nutritional and environmental conditions on growth rate and CA biosynthesis was more pronounced. Then, two metabolic scenarios (SC3 and SC5) observed under HSS conditions, and two under LSS (SC4 and SC6) were retained as representative of the fed-batch cultivation stages covering the time interval 37–93 h. SC3 and SC4 represent growth in the presence of high glycerol and low glutamate availabilities under phosphate limitation and different RQ, as observed in the HSS and LSS cultivations. SC5 and SC6 simulate the growth on glycerol after glutamate and phosphate depletions at different RQ values. Although extracellular concentrations of phosphate and its uptake are never strictly zero given the utilization of phosphate storages during phosphate scarcity, the scenarios of phosphate limitation are characterized by a very low phosphate uptake that likely approaches to zero and consequently decreases the growth rate. Thus, scenarios of phosphate limitation SC3–SC6 were simulated by approximating the exchange flux to zero.The scenarios with RQ = 1 (SC 4 and SC6) were observed under LSS conditions linked to lower oxygen uptake compared to carbon dioxide generation. The lower and upper bounds of the exchange fluxes for medium components were constrained between −1 and 1, respectively. The main nutrient uptakes, i.e., glycerol, glutamate, phosphate and ammonium, were set as equality constraints according to the experimentally observed fluxes, since these are the main exchange fluxes in the network. In the case of the simulations with RQ = 1, the carbon dioxide exchange flux was also constrained to satisfy the RQ constraint. The constraints of exchange fluxes for glycerol, glutamate, ammonium and phosphate, as well as simulation results for growth rate, CA and oxygen exchange fluxes are summarized in The simulation of SC1 showed that flux ratio between the second phase of the glycolysis and first oxidation in the TCA cycle was close to 1.0, indicating a high activity of the TCA cycle and balanced oxidative metabolism. This is consistent with the high nitrogen and carbon uptakes during the early stages of cultivation. In those scenarios, the oxidative direction of TCA cycle was preferred to promote anabolism and growth. FBA indicates that anaplerotic reactions catalyzed by PPC, citrate lyase (CITL) and the glyoxylate shunt are not activated under such conditions.2 generation. Previous reports suggested that RQ values between 1 and 1.2 are characteristic of growth without nutrient limitation, while values out of this range are associated to nitrogen, oxygen or phosphate limitations affecting also the growth rate [−1).As expected, SC2 reflects the highest metabolic activity and growth rates in silico, which is consistent with the experimental results. The experimentally verified increase of glycerol and ammonium uptakes, used as constraints in silico, leads to an RQ of 1.2 due to the increase in the COwth rate ,50. Anab−1) was observed in SC3, that is, growth under phosphate limitation and low glutamate uptake. This scenario was macroscopically characterized by a decrease in growth rate due to the low phosphate availability and hence, lower carbon and oxygen uptakes, causing a decline in the RQ down to 0.94 [CA production varies because of a nutrient-specific effect in each metabolic scenario. The highest reaction flux towards the CA pathway (0.03 mmol (g DCW.h) to 0.94 . Oxygen The calculated fluxes of reactions dependent on glutamate and related to the urea cycle in SC3 were up to 1.7-fold higher than those calculated for SC4. The carbon flux towards asparagine synthase (ASNS) decreased as consequence of the high fluxes in L-aspartate and L-glutamine synthesis via the urea cycle. These FBA results are consistent with the experimentally observed low accumulations of L-arginine, L-aspartate, L-glutamine and L-asparagine under HSS conditions in stirred tank bioreactor h–j, sincIn scenarios of growth under glutamate and phosphate depletions (SC5 and SC6), the flux decrease in TCA and urea cycles was higher in the oxygen restricted scenario (SC6). In contrast, in SC3 and SC4 scenarios the constrained exchange flux of L-glutamate fueled the fluxes in the urea cycle. In SC5 and SC6 these fluxes were more dependent on glycolysis and TCA, leading to a drop in the fluxes of amino acids metabolism and hence, the CA pathway. Thus, in the oxygen constrained scenarios (SC4 and SC6), the slowdown of TCA and urea cycles, as well as amino acid metabolism and CA biosynthesis, predicted in silico, suggested that intracellular limitation of oxygen in LSS cultivations causes a general drop in fluxes along central metabolism, which correlates with the experimentally observed accumulation of pyruvate, oxaloacetate, malate, and amino acids. Moreover, as a physiological objective of growth, the use of oxygen is prioritized to sustain biomass synthesis and anabolism rather than specialized metabolite synthesis. The main carbon fluxes along central metabolism are summarized in S. clavuligerus [Some differences between phosphate limited and non-limited scenarios were predicted in silico. High phosphate conditions repress both, CA and cephamycin C biosynthesis, in uligerus . Since puligerus . They woIn the case of SC3 and SC4 scenarios, the biosynthesis of specialized metabolites might constitute a metabolic sink playing a role in growth regulation under high carbon and nitrogen availability, coexisting with a phosphate limitation. FBA simulations of the SC3 scenario demonstrated that, besides stimulation of TCA and CA biosynthesis, fluxes through ATP synthase and NADH dehydrogenase also increase compared to the oxygen constrained scenario SC4. Interestingly, the lowest fluxes through ATP synthase and NADH dehydrogenase were observed in silico in the scenario of glutamate and phosphate exhaustion (SC5), coinciding with moderate CA production in HSS conditions. In contrast, SC6 did not show reaction fluxes toward the CA pathway while the fluxes of respiratory chain dehydrogenases and ATP production were almost 10% higher than in SC5. Under these conditions CA biosynthesis seems to have a similar metabolic scenario to the synthesis of Type II antibiotics. CA biosynthesis  involvesIn silico, FBA showed that phosphate limitation causes a stoichiometric increase in the reaction fluxes in several glutamate-dependent reactions, contributing to supply fluxes of Pi and/or PPi to other reactions in the network. Additionally, the reactions in the CA pathway catalyzed by CEAS and BLS involve Pi and PPi as by-products. PPi is further hydrolyzed by the inorganic diphosphatase (PPA), whose flux increases up to 43% under P-limitation in silico. FBA results suggest that L-glutamate availability promotes the carbon flux towards CA biosynthesis in a scenario of high oxygen uptake, since L-arginine as C-5 precursor of CA is derived from L-glutamate via the urea cycle. Indeed, the highest biosynthesis rate of CA was observed in the HSS cultivations when phosphate limitation and glutamate availability coexisted with high oxygen uptake.S. clavuligerus might induce this kind of cycle. The toxic impact of cephamycin C on the energetic metabolism could be counteracted by the action of a β-lactamase. Simultaneously, the β-lactamase levels would be regulated by CA as a β-lactamase inhibitor. These three systems with opposite effects would contribute to tightly regulate intracellular levels of CA and cephamycin C and, indirectly, the energetic metabolism of the bacteria. Thus, the high antibiotic synthesis rate observed in HSS cultivations is consistent with the high ATP generation calculated in silico in conditions of high intracellular oxygen and nutrients availability.Furthermore, phosphate limitation is known to trigger important adaptive responses that contribute to maintain the phosphate supply to the cells in phosphate limited scenarios. Cell growth in absence or at very low concentrations of extracellular phosphate proceeds via reutilization of intracellular phosphate. Under phosphate deficiency, mother and daughter cells share intracellular resources of phosphate from RNA, polyphosphate stores, phospholipids and teichoic acids accumulated during fast growth under high phosphate availability. During the fed-batch phase with phosphate limitation (from 60 h onwards), cells do not need these constituents and are subjected to self-degradation by means of nucleases, phosphatases and related hydrolytic enzymes, releasing inorganic phosphate, pyrophosphate, and P-containing monomers into the cytoplasm. This response is controlled by the two-component system PhoR/PhoP, which is able to induce the high-affinity phosphate transport system, phosphatases, down-regulation of phosphate consuming processes and upregulation of genes involving phosphate mediated reactions ,54. In pS. clavuligerus, using a state-of-the-art top-down approach during the network reconstruction. The resultant curated iDG1237 metabolic model showed better predictive capabilities compared with its predecessors in relation to biomass and product biosynthesis, network topology, thermodynamic consistency and simulation of metabolic scenarios of nutritional limitation. The present model constitutes a new basis for computer-aided analysis and design of CA production scenarios as well as strain engineering of S. clavuligerus.In this work, we generated an improved genome-scale metabolic model of S. clavuligerus metabolism, when cultivated at high and low shear stress conditions. Under identical scenarios of phosphate limitation, the decrease of oxygen uptake halved the carbon fluxes in TCA and urea cycles negatively impacting CA biosynthesis. Low oxygen availability in low shear stress conditions likely leads to a slowdown of TCA cycle causing overflow metabolism (secretion of acids of the acetyl-CoA node) and accumulation of TCA intermediates due to reduction of anabolism and inhibition of antibiotic production. Experimental evidence showed that the stoichiometric effect of phosphate depletion alone does not enhance CA production, since oxygen diffusion determines the activity of oxidative and energetic metabolism. In this regard, antibiotic biosynthesis might have an important role in regulating the energetic balance of the bacteria under phosphate limitation.The in silico and experimental results of this study provide insights regarding the nutritional regulation of CA biosynthesis and the effects of intracellular oxygen availability in S. clavuligerus. Further exploration of metabolic scenarios considering nutritional and genetic regulation of metabolism could contribute to the design of suitable conditions to optimize CA production and construct genetically engineered CA-overproducing strains.The present combined experimental and modelling approach highlighted the importance of the metabolic relationship between the TCA cycle, amino acid biosynthesis and oxygen uptake under phosphate limitation during antibiotic production in


Yarrowia lipolytica is a non-conventional yeast with promising industrial potentials for lipids and citrate production. It is also widely used for studying mitochondrial respiration due to a respiratory chain like those of mammalian cells. In this study we used a genome-scale model (GEM) of Y. lipolytica metabolism and performed a dynamic Flux Balance Analysis (dFBA) algorithm to analyze and identify metabolic levers associated with citrate optimization. Analysis of fluxes at stationary growth phase showed that carbon flux derived from glucose is rewired to citric acid production and lipid accumulation, whereas the oxidative phosphorylation (OxPhos) shifted to the alternative respiration mode through alternative oxidase (AOX) protein. Simulations of optimized citrate secretion flux resulted in a pronounced lipid oxidation along with reactive oxygen species (ROS) generation and AOX flux inhibition. Then, we experimentally challenged AOX inhibition by adding n-Propyl Gallate (nPG), a specific AOX inhibitor, on Y. lipolytica batch cultures at stationary phase. Our results showed a twofold overproduction of citrate (20.5 g/L) when nPG is added compared to 10.9 g/L under control condition (no nPG addition). These results suggest that ROS management, especially through AOX activity, has a pivotal role on citrate/lipid flux balance in Y. lipolytica. All taken together, we thus provide for the first time, a key for the understanding of a predominant metabolic mechanism favoring citrate overproduction in Y. lipolytica at the expense of lipids accumulation. Yarrowia lipolytica is a non-conventional yeast usually isolated from dairy products, oil and water environments2. This oleaginous yeast is emerging as an important cell factory for lipid production4. Indeed, over 50–70% of its dry cell weight accounts for lipid accumulation6, and even 90% of its biomass as lipids has been obtain for an engineered Y. lipolytica strain7. Y. lipolytica wild type strains isolated are Generally Recognized As Safe (GRAS) from the American Food and Drug Administration (FDA) and Qualified Presumption of Safety (QPS) from European Food Safety Authority (EFSA)9. It is used as platform for the production of proteins 2 and organic acids 10.11. This production is carried out mainly by microbial fermentation of diverse carbon sources 12. The mold Aspergillus niger is practically the only microorganism used at industrial scale with nearly 90% of the total production11. However, the direct use of the A. niger on a food matrix is not feasible since it is not GRAS and presents a high risk of contamination.Citric acid is the most widely used organic acid in the world with an annual production of the purified molecule estimated at 1.8 million tonsY. lipolytica genome and genome-scale models (GEM) allowed investigations of the cells physiology and cellular metabolism involved in citric acid secretion and intracellular lipid accumulation19. Production of extracellular citric acid or intracellular lipid is triggered by the imbalance between carbon sources in excess and limited biogenic substrates 20. The mostly used parameter to trigger this metabolic shift is a N-limitation (N-lim) in culture medium, allowing a high C/N ratio thus resulting in citrate secretion from an overflow metabolism at high glucose concentration21. Isocitrate dehydrogenase (IDH), a reversible Krebs enzyme involved in isocitrate to α-ketoglutarate conversion, is reported as key enzyme for lipid accumulation and citrate production in oleaginous microorganisms24. Authors proposed that upon N-lim, adenosine monophosphate (AMP) deaminase enzyme catalyze AMP to IMP and NH3 conversion to compensate for nitrogen depletion. Lower intracellular AMP leads to IDH inhibition and both isocitrate and citrate accumulation. Then citrate and isocitrate are excreted to extracellular medium but citrate can also be converted to acetyl-CoA, used as precursor for lipid synthesis26.The completion of the Y. lipolytica cultures29. Indeed, it has been showed that increased oxygen mass transfer rate (OTR) improves up to threefold citrate production by Y. lipolytica W29 strain28. Similarly, recent investigations led to citrate optimization by controlling the dissolved oxygen concentration (pO2)29. Finally, in this older work, authors reported that citrate overproduction is inversely correlated to the cyanide-resistance respiratory pathway on Candida/Yarrowia lipolytica30. Cyanide resistance pathway is mainly present in plants and fungi and involves an alternative oxidase (AOX) protein32; along with II NADH dehydrogenase (NDH2e), both part of the uncoupled ΔΨ-independent mitochondrial respiration34. The exact mechanism involving AOX on citrate production is not clearly determined but NDH2e-AOX pathway has been proposed as defense mechanism against Reactive Oxygen Species (ROS) accumulation in Y. lipolytica at stationary phase35. Although mitochondria are the main sources of ROS, other cytoplasmic proteins have recently been characterized as sources of ROS. This is the case of the long chain fatty alcohol oxidase (FAO). FAOs are located in the endoplasmic reticulum and participate in the oxidation of long chain alkanes or fatty acids, and production of long-chain aldehyde and hydrogen peroxide (H2O2) They have been mainly studied in industrial yeasts Candida tropicalis or Candida cloacae36 and recently identified in Yarrowia lipolytica37.Recent studies highlighted the key role of oxygen on citrate optimized production in Y. lipolytica at stationary phase is favored over lipid accumulation38. Recent studies have implemented strategies for controlling substrate feeding rate for lipid accumulation preventing the production of citric acid21. The authors managed to identify a range of N/C ratios favoring the production of lipid without citric acid excretion. Similarly, a GEM of Y. lipolytica has been proposed in combination with dynamic Flux Balance Analysis (dFBA), a computational algorithm, to study environmental conditions favorable for lipid accumulation over citric acid production13. These authors found that the cell specific oxygen consumption rate (rO2) is reduced during lipid accumulation. Applying a fed-batch strategy under reduced dissolved oxygen concentration, from 50 to 1%, they improved lipid accumulation, from 200 mg/gDCW to 400 mg/gDCW and avoid citrate excretion. Computational strategies such as dFBA allow to analyze genome-scale reconstructed metabolic networks and to run knock-out or environment-based optimization strategies for biomass of metabolites production40.When glucose is used as a sole carbon source, citric acid production by 41. The mathematical description of the metabolic reactions relies on the stoichiometries of reactants and products and does not require enzyme kinetics parameters. Dynamic flux balance analysis (dFBA) extends the FBA framework to help model how metabolic states change over time and interact with their environment. The method was developed by Varma and Palsson to predict the behavior of E. coli during several batch runs42. It was then formalized by Mahadevan et al. who presented two different approaches to dynamic flux balance analysis, called the dynamic optimization approach (DOA) and the static optimization approach (SOA)43. The DOA method optimizes over the entire time period of interest to obtain time profiles of fluxes and metabolite levels using non-linear programming problem. The SOA method divides time in discrete intervals and a new FBA problem is solved at time t after updating the external conditions according to the FBA solution at time t − 1.FBA predicts flux balances based on constraints and objective functions for biochemical networks verifying steady-state assumptioniNL895 model was the first genome-wide metabolic network of Y. lipolytica15. This model is based on the old consensus model of Saccharomyces cerevisiae, to which was added the lipid network. The iYL619_PCP model was released the same year and experimentally validated by studying growth on glucose and mineral medium16. This GEM was updated with more detailed reactions and became iYL_2.0. It has been used to optimize the accumulation of triacylglycerol (TAG)18. Similarly, the model iMK735 was developed to study conditions for lipid optimization in Y. lipolytica13. This model was validated with dFBA on mineral medium with glucose or glycerol as sole carbon source. The iYali4 model was constructed from the consensus network of S. cerevisiae44, iNL895 and iYL619_PCP. The model has been applied to the study of amino acid metabolism and the overflow phenomenon associated to lipid accumulation17. We consider that iYali4 model is the most complete regarding lipid metabolism, compared to previous models, and has been updated based on the genome sequence of the strain Y. lipolytica W29 used in this study45.Five GEMs are known from the literature so far. The Yali4 GEM and dFBA SOA strategies with COBRA Toolbox under MATLAB to analyze flux distributions associated with citrate production and alternative oxidase (AOX) protein activity. For this end, we adjusted the iYali4 model with the mitochondrial AOX reaction identified in Y. lipolytica47 and performed dFBA to identify metabolic pathways contributing to citrate optimization, using gurobi solver (Gurobi Optimizer) for linear programming (LP).Here, we used the Yarrowia lipolytica W29 wild-type strain was used in this study. It is from CIRM-Levures collection and was provided by Micalis, INRA  and stored at − 80 °C on 50% (v/v) glycerol.The 2SO4; 6 KH2PO4; 1.5 MgSO4·7H2O; 0.02 CuSO4-5H2O; 0.01 MnSO4·H2O; 0.0105 ZnCl2; 0.0035 FeSO4·7H2O; CaCl2·2H2O; 0.00025 D-Biotin; 0.001 D-L-Panthotenic acid, 0.001 Nicotinic Acid; 0.00625 Myo-Inositol; 0.001 Thiamin, 0.001 Pyridoxine; 0.0002 para-Aminobenzoic Acid. Glucose was used as carbon source and added to a final concentration of 50 g/L.Two media were used in this study. The YPD medium is composed of 10 g/L yeast extract, 10 g/L peptone  and 20 g/L glucose . The mineral medium  was adapted from Ochoa-Estopier et al. (2014) and Moeller et al. (2007) with the following components (g/L): 1 (NH4)All pre-cultures were cultivated in 200 mL Erlenmeyer flasks on YPD medium at pH 6 and incubated on a rotary shaker at 28 °C and 100 rpm. Culture broth was taken at exponential growth phase, after 16–18 h of cultivation, centrifuged and washed in a 9 g/L NaCl prior to inoculation in mineral medium for both bioreactors and shaked flasks culture.Bioreactor culture (n = 1) were performed in the 7 L Applikon system. The temperature was maintained at 28 °C and pH at 6 by the addition of 5 M NaOH. Dissolved oxygen was maintained above 20% from air saturation by controling the stirrer speed between 300–600 rpm and aeration at 2 vvm of air and dioxygen from 0 to 1 vvm. An antifoaming agent (B200 K) was added to 0.09% v/v at inoculation.Culture in Erlenmeyer flask (n = 1) were performed at the same condition as the pre-culture, on a rotary shaker at 28 °C. The pH of the culture was maintained between 5 and 6 by manually and periodically adding 300 µL of 5 M NaOH in sterile condition.n-propyl Gallate (nPG) stock solution were prepared on 70% ethanol and periodically added to cultures, to a final 400 µM concentration. It is a well-known inhibitor of the alternative oxidase (AOX) enzyme and already used to study mitochondrial respiration in Yarrowia lipolytica35.40 mM 600 nm for the calculation of extracellular metabolic fluxes per gram of dry cell weight (gDCW). We found 0.62 gDCW/L concentration of biomass with DO600 nm = 1, for Y. lipolytica W29 grown on mineral media.Cell growth was followed by a spectrophotometer with calculation of yeast optical density (OD) at 600 nm. Dried biomass was carried out and calibrated against the DOg for 5 min, aliquoted in 1 mL microtubes  and stored at − 20 °C until further analysis. 500 µL Nanosep centrifugal tubes  were used to filter the supernatant prior to metabolites quantification by High Performance Liquid Chromatography (HPLC) using ion chromatography system (Thermo Scientific ICS 5000+). IonPac AS11-2 × 250 mm column , IonPac AG11-2 × 500 mm pre-column  and AERS 500, 2 mm  were used for organic acids  quantification and with the following conditions: 35 °C column temperature, 0.5 mL/min NaOH (100 mM) eluant flow with gradient concentrations. Glucose concentration was determined with the Dionex CarboPac PA1 column 4 × 50 mm (Thermo Scientific) equipped with amperometric detection. Residual ammonium (NH4+) was quantified by a colorimetric essay , USA).For the determination of extracellular concentrations, 5 mL of the fermentation broth was centrifuged at 5×iYali4 the GEM of Y. lipolytica by Kerkhoven et al., and an updated version for Y. lipolytica W29 to study citrate optimization. Growth rate on glucose and nitrogen-limited mineral medium was predicted by the model based on glucose specific consumption rate adequately fitted to the experimental results  reaction. So we added the AOX reaction as part of the electron transfer chain (ETC), based on the hypothesis that this enzyme has a protective effect against ROS generation in Y. lipolytica and probably on citrate production35. The stoichiometry of AOX reaction were determined from literature and in coherence with iYali4 ETC reaction: ubiquinol + 0.25 02 =  > ubiquinone + 0.5 H2O32. AOX reaction is doesn’t contribute to proton pumping across the mitochondrial membrane48.We used ts Table . It was Yarrowia lipolytica in mineral medium for kinetic parameters determination. These cultures were running in nitrogen-limited (N-lim) conditions to favor citrate production. Glucose was used as carbon source. Initial two glucose concentrations were accessed in order to determine the N/C ratio effect on cells specific growth rate (µmax) and other kinetic physiological parameters  is totally consumed (between 28 and 30 h of culture). Citrate and isocitrate specific production rates are higher under low N/C ratio batch cultivation. For the remaining of our investigations, we considered the higher N/C ratio condition to avoid the glucose inhibition effect at 100 g/L.We performed a series of bioreactor batch cultivations of rs Table . SpecifiYali4 GEM accuracy on predicting Y. lipolytica growth. The experimentally determined kinetic parameters such as specific glucose and oxygen uptake at the higher N/C (0.00204) condition were used as constrains to predict cell growth behavior. The model predicts a growth rate of 0.052 h−1, with low 0.616% error . A second stable growth phase, with a µmax2 of 0.0240 ± 0.0013 h−1 is observed thereafter until the culture reached stationary phase, at 96–100 h. Up to 6 gDCW/L of biomass concentration has been observed. Citrate production clearly started upon nitrogen starvation and cell growth limitation. It’s mainly produced during the cell growth stationary phase and reached 10.9 g/L at the end of cell cultivation. Lower isocitrate concentration of 1.3 g/L was then observed. After 170 h of culture, residual 5 g/L of glucose remained in the medium  is the mostly used limitation parameter to trigger lipid accumulation and citrate production by Yali4 model with the aim to simulate our experimental results. Experimental initial glucose concentration (50 g/L) and uptake rate (0.64 mmol/gDCW/h) were first set in the model according to the experimental data. Slightly adjusting the specific glucose uptake rate down to 0.60 mmol/gDCW/h allowed to better fit the experimental curve. The alternative oxidase (AOX) reaction flux was fixed to zero during the growth phase, as reported by Guerrero-Castillo et al., and free-bounded during the stationary phase50. Therefore, a modified dynamicFBA.m MATLAB function has been proposed to allow further dFBA simulations when growth rate reaches the stationary phase (µ = 0). Then, the initial objective function of biomass optimization during the growth phase was changed to “lipid accumulation” as it’s experimentally observed upon stationary phase. Therefore, our dFBA model permitted prediction of biomass and citrate production in good agreement with the experimental results  but looks closer if we consider the average of the whole culture, i.e. the mean µ of the two successive growth phases (0.062 h−1).The initial biomass concentration was set to 0.06 gDCW/L based on experimental data. Then we applied the dynamic Flux Balance Analysis (dFBA) algorithm to lts Fig. a. Nevert+ and oxygen specific consumption rates are respectively 0.468 mmol/gDCW/h and 1.54 mmol/gDCW/h at exp-phase, and both drop to 0 and 0.217 mmol/gDCW/h respectively at stat-phase. Carbon dioxide (CO2) is produced only on exp-phase , and it was constrained to 0.39 mmol/gDCW/h at stationary growth phase (stat-phase). Predicted NH4When the simulated growth reaches stat-phase, Krebs enzymes activity seem to sustain mitochondrial citrate accumulation. Pyruvate dehydrogenase (PDH) activity is decreased from 0.672 mmol/gDCW/h at exp-phase to 0.120 mmol/gDCW/h at stat-phase. It remains the dominant mitochondrial Acetyl-CoA supplier, joined with mitochondrial malate dehydrogenase which furnishes oxaloacetate for citrate synthesis , citrate-oxoglutarate (CIT-OXO), citrate-isocitrate (CIT-ICIT) and citrate-malate (CIT-MAL). The model predicts inactive CIT-PEP on both phases. During growth phase, the model predicts mitochondrial to cytosolic citrate fluxes through CIT-MAL transporter and a lower inverse CIT-ICIT flux contributing to cytosolic isocitrate. During stat-phase, the net cytosolic citrate flux is ensured by CIT-OXO antiport since the positive CIT-MAL flux is totally reversed to mitochondria through CIT-ICIT antiport  with a specific 0.013 mmol/gDCW/h flux rate. This result also emphasizes that the NADH2e-AOX alternative route for NADH oxidation and O2 reduction is inactive when citrate is overproduced during the stationary phase , a well-known inhibitor of AOX, at 72 h then repeated every 24 h. Experimental results show optimized citrate production in the nPG-implemented medium  of carbon overflow resulting in increased extracellular citrate production. We first restricted our study to Krebs enzymes, ETC complexes and reactions involved in the citrate pathway. Our results show that PDH-PC-CS route is the main contributor of carbon overflow to mitochondrial citrate accumulation. These simulated enzymes activities are proportional to citrate production rate Fig. . Likewisse Figs. , 6. Base51. The dFBA model of Y. lipolytica also was also used to predict the effect of adding various Krebs intermediates such as α-ketoglutarate, malate and oxaloacetate for citrate optimization. Whereas simulations reported an improved citrate production (data not showed), these results weren’t experimentally confirmed, compared to the control , another well-known and used inhibitor of AOXAspergillus niger and Yarrowia lipolytica by modulating mitochondrial metabolism with specific effector compounds or by cell engineering strategies53. Our predicted results show that the oxidative phosphorylation (OxPhos) pathway is globally reduced when the cell culture reaches the stationary phase  reaction provided by the fatty alcohol oxidase gene (FAO) consumes O2 at stationary phase and triggers the oxidation of cytosolic alcohols. Theses reaction is accompanied by the production of hydrogen peroxide (H2O2) as major ROS species. FAO gene has been recently identified in Y. lipolytica as key in ω-oxidation of long-chain fatty acids37. One may consider a global mechanism in Y. lipolytica where citrate is mainly used for lipids accumulation at the entry in stationary phase, followed by ω and β-oxidation of fatty acids upon lipid saturation and exposure to free oxygen species. Fatty acids oxidation is thus thought to trigger cell defense mechanisms such as catalase (CAT) and alternative NADH2e-AOX oxidase to circumvent ROS accumulation  confirm the hypothesis that AOX may contribute to clearing ROS species and improving cell survival.A recent study of citrate production in Yali4 model of Yarrowia lipolytica W29 strain metabolism to predict favorable metabolic conditions for citrate optimization. The model first predicted carbon overflow to lipid accumulation and citrate production during stationary phase. Y. lipolytica respiration is drastically decreased during citrate production phase and shifts from OxPhos to the alternative ΔΨ-independent pathway ensured by NADH2e/AOX route. Isocitrate dehydrogenase and aconitase are predicted to operate in the backward direction and favor mitochondrial citrate accumulation. Simulated overproduction of citrate is accompanied by inhibition of the NADH2e/AOX pathway as well as increased lipid oxidation and ROS production. The prediction of citrate overproduction has been confirmed experimentally by inhibition of AOX protein. We also challenged the importance of ROS in balancing lipid accumulation and citrate production fluxes by adding glutathione to Y. lipolytica culture in the presence of nPG. Our results showed a global inhibition of citrate production. We propose AOX gene as a target for metabolic engineering and industrial production of citrate in food and pharmaceutical industries.We applied dFBA algorithm to the existing Supplementary Information.