Golden Standard: a complete standard, portable, and interoperative MoClo tool for model and non-model proteobacteria.

Modular cloning has become a benchmark technology in synthetic biology. However, a notable disparity exists between its remarkable development and the need for standardization to facilitate seamless interoperability among systems. The field is thus impeded by an overwhelming proliferation of organism-specific systems that frequently lack compatibility. To overcome these issues, we present Golden Standard (GS), a Type IIS assembly method underpinned by the Standard European Vector Architecture. GS unlocks modular cloning applications for most bacteria, and delivers combinatorial multi-part assembly to create genetic circuits of up to twenty transcription units (TUs). Reliance on MoClo syntax renders GS fully compatible with many existing tools and it sets the path towards efficient reusability of available part libraries and assembled TUs. GS was validated in terms of DNA assembly, portability, interoperability and phenotype engineering in α-, ß-, γ- and δ-proteobacteria. Furthermore, we provide a computational pipeline for parts characterization that was used to assess the performance of GS parts. To promote community-driven development of GS, we provide a dedicated web-portal including a repository of parts, vectors, and Wizard and Setup tools that guide users in designing constructs. Overall, GS establishes an open, standardized framework propelling the progress of synthetic biology as a whole.

SEVA 4.0: an update of the Standard European Vector Architecture database for advanced analysis and programming of bacterial phenotypes.

The SEVA platform (https://seva-plasmids.com) was launched one decade ago, both as a database (DB) and as a physical repository of plasmid vectors for genetic analysis and engineering of Gram-negative bacteria with a structure and nomenclature that follows a strict, fixed architecture of functional DNA segments. While the current update keeps the basic features of earlier versions, the platform has been upgraded not only with many more ready-to-use plasmids but also with features that expand the range of target species, harmonize DNA assembly methods and enable new applications. In particular, SEVA 4.0 includes (i) a sub-collection of plasmids for easing the composition of multiple DNA segments with MoClo/Golden Gate technology, (ii) vectors for Gram-positive bacteria and yeast and [iii] off-the-shelf constructs with built-in functionalities. A growing collection of plasmids that capture part of the standard-but not its entirety-has been compiled also into the DB and repository as a separate corpus (SEVAsib) because of its value as a resource for constructing and deploying phenotypes of interest. Maintenance and curation of the DB were accompanied by dedicated diffusion and communication channels that make the SEVA platform a popular resource for genetic analyses, genome editing and bioengineering of a large number of microorganisms.

Bdellovibrio's prey-independent lifestyle is fueled by amino acids as a carbon source.

Identifying the nutritional requirements and growth conditions of microorganisms is crucial for determining their applicability in industry and understanding their role in clinical ecology. Predatory bacteria such as Bdellovibrio bacteriovorus have emerged as promising tools for combating infections by human bacterial pathogens due to their natural killing features. Bdellovibrio's lifecycle occurs inside prey cells, using the cytoplasm as a source of nutrients and energy. However, this lifecycle supposes a challenge when determining the specific uptake of metabolites from the prey to complete the growth inside cells, a process that has not been completely elucidated. Here, following a model-based approach, we illuminate the ability of B. bacteriovorus to replicate DNA, increase biomass, and generate adenosine triphosphate (ATP) in an amino acid-based rich media in the absence of prey, keeping intact its predatory capacity. In this culture, we determined the main carbon sources used and their preference, being glutamate, serine, aspartate, isoleucine, and threonine. This study offers new insights into the role of predatory bacteria in natural environments and establishes the basis for developing new Bdellovibrio applications using appropriate metabolic and physiological methodologies. KEY POINTS: • Amino acids support axenic lifestyle of Bdellovibrio bacteriovorus. • B. bacteriovorus preserves its predatory ability when growing in the absence of prey.

New Insights on Metabolic Features of Bacillus subtilis Based on Multistrain Genome-Scale Metabolic Modeling.

Bacillus subtilis is an effective workhorse for the production of many industrial products. The high interest aroused by B. subtilis has guided a large metabolic modeling effort of this species. Genome-scale metabolic models (GEMs) are powerful tools for predicting the metabolic capabilities of a given organism. However, high-quality GEMs are required in order to provide accurate predictions. In this work, we construct a high-quality, mostly manually curated genome-scale model for B. subtilis (iBB1018). The model was validated by means of growth performance and carbon flux distribution and provided significantly more accurate predictions than previous models. iBB1018 was able to predict carbon source utilization with great accuracy while identifying up to 28 metabolites as potential novel carbon sources. The constructed model was further used as a tool for the construction of the panphenome of B. subtilis as a species, by means of multistrain genome-scale reconstruction. The panphenome space was defined in the context of 183 GEMs representative of 183 B. subtilis strains and the array of carbon sources sustaining growth. Our analysis highlights the large metabolic versatility of the species and the important role of the accessory metabolism as a driver of the panphenome, at a species level.

Optimized De Novo Eriodictyol Biosynthesis in Streptomyces albidoflavus Using an Expansion of the Golden Standard Toolkit for Its Use in Actinomycetes.

Eriodictyol is a hydroxylated flavonoid displaying multiple pharmaceutical activities, such as antitumoral, antiviral or neuroprotective. However, its industrial production is limited to extraction from plants due to its inherent limitations. Here, we present the generation of a Streptomyces albidoflavus bacterial factory edited at the genome level for an optimized de novo heterologous production of eriodictyol. For this purpose, an expansion of the Golden Standard toolkit (a Type IIS assembly method based on the Standard European Vector Architecture (SEVA)) has been created, encompassing a collection of synthetic biology modular vectors (adapted for their use in actinomycetes). These vectors have been designed for the assembly of transcriptional units and gene circuits in a plug-and-play manner, as well as for genome editing using CRISPR-Cas9-mediated genetic engineering. These vectors have been used for the optimization of the eriodictyol heterologous production levels in S. albidoflavus by enhancing the flavonoid-3'-hydroxylase (F3'H) activity (by means of a chimera design) and by replacing three native biosynthetic gene clusters in the bacterial chromosome with the plant genes matBC (involved in extracellular malonate uptake and its intracellular activation into malonyl-CoA), therefore allowing more malonyl-CoA to be devoted to the heterologous production of plant flavonoids in this bacterial factory. These experiments have allowed an increase in production of 1.8 times in the edited strain (where the three native biosynthetic gene clusters have been deleted) in comparison with the wild-type strain and a 13 times increase in eriodictyol overproduction in comparison with the non-chimaera version of the F3'H enzyme.

The metabolic potential of plastics as biotechnological carbon sources - Review and targets for the future.

The plastic crisis requires drastic measures, especially for the plastics' end-of-life. Mixed plastic fractions are currently difficult to recycle, but microbial metabolism might open new pathways. With new technologies for degradation of plastics to oligo- and monomers, these carbon sources can be used in biotechnology for the upcycling of plastic waste to valuable products, such as bioplastics and biosurfactants. We briefly summarize well-known monomer degradation pathways and computed their theoretical yields for industrially interesting products. With this information in hand, we calculated replacement scenarios of existing fossil-based synthesis routes for the same products. Thereby, we highlight fossil-based products for which plastic monomers might be attractive alternative carbon sources. Notably, not the highest yield of product on substrate of the biochemical route, but rather the (in-)efficiency of the petrochemical routes (i.e., carbon, energy use) determines the potential of biochemical plastic upcycling. Our results might serve as a guide for future metabolic engineering efforts towards a sustainable plastic economy.

Providing new insights on the biphasic lifestyle of the predatory bacterium Bdellovibrio bacteriovorus through genome-scale metabolic modeling.

In this study we analyze the growth-phase dependent metabolic states of Bdellovibrio bacteriovorus by constructing a fully compartmented, mass and charge-balanced genome-scale metabolic model of this predatory bacterium (iCH457). Considering the differences between life cycle phases driving the growth of this predator, growth-phase condition-specific models have been generated allowing the systematic study of its metabolic capabilities. Using these computational tools, we have been able to analyze, from a system level, the dynamic metabolism of the predatory bacteria as the life cycle progresses. We provide computational evidences supporting potential axenic growth of B. bacteriovorus's in a rich medium based on its encoded metabolic capabilities. Our systems-level analysis confirms the presence of "energy-saving" mechanisms in this predator as well as an abrupt metabolic shift between the attack and intraperiplasmic growth phases. Our results strongly suggest that predatory bacteria's metabolic networks have low robustness, likely hampering their ability to tackle drastic environmental fluctuations, thus being confined to stable and predictable habitats. Overall, we present here a valuable computational testbed based on predatory bacteria activity for rational design of novel and controlled biocatalysts in biotechnological/clinical applications.

High-quality genome-scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities.

Genome-scale reconstructions of metabolism are computational species-specific knowledge bases able to compute systemic metabolic properties. We present a comprehensive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440 that greatly expands computable predictions of its metabolic states. The reconstruction represents a significant reactome expansion over available reconstructed bacterial metabolic networks. Specifically, iJN1462 (i) incorporates several hundred additional genes and associated reactions resulting in new predictive capabilities, including new nutrients supporting growth; (ii) was validated by in vivo growth screens that included previously untested carbon (48) and nitrogen (41) sources; (iii) yielded gene essentiality predictions showing large accuracy when compared with a knock-out library and Bar-seq data; and (iv) allowed mapping of its network to 82 P. putida sequenced strains revealing functional core that reflect the large metabolic versatility of this species, including aromatic compounds derived from lignin. Thus, this study provides a thoroughly updated metabolic reconstruction and new computable phenotypes for P. putida, which can be leveraged as a first step toward understanding the pan metabolic capabilities of Pseudomonas.

Metabolic reconstruction of Pseudomonas chlororaphis ATCC 9446 to understand its metabolic potential as a phenazine-1-carboxamide-producing strain.

Pseudomonas chlororaphis is a plant-associated bacterium with reported antagonistic activity against different organisms and plant growth-promoting properties. P. chlororaphis possesses exciting biotechnological features shared with another Pseudomonas with a nonpathogenic phenotype. Part of the antagonistic role of P. chlororaphis is due to its production of a wide variety of phenazines. To expand the knowledge of the metabolic traits of this organism, we constructed the first experimentally validated genome-scale model of P. chlororaphis ATCC 9446, containing 1267 genes and 2289 reactions, and analyzed strategies to maximize its potential for the production of phenazine-1-carboxamide (PCN). The resulting model also describes the capability of P. chlororaphis to carry out the denitrification process and its ability to consume sucrose (Scr), trehalose, mannose, and galactose as carbon sources. Additionally, metabolic network analysis suggested fatty acids as the best carbon source for PCN production. Moreover, the optimization of PCN production was performed with glucose and glycerol. The optimal PCN production phenotype requires an increased carbon flux in TCA and glutamine synthesis. Our simulations highlight the intrinsic H2O2 flux associated with PCN production, which may generate cellular stress in an overproducing strain. These results suggest that an improved antioxidative strategy could lead to optimal performance of phenazine-producing strains of P. chlororaphis. KEY POINTS : • This is the first publication of a metabolic model for a strain of P. chlororaphis. • Genome-scale model is worthy tool to increase the knowledge of a non model organism. • Fluxes simulations indicate a possible effect of H2O2 on phenazines production. • P. chlororaphis can be a suitable model for a wide variety of compounds.

Influence of the Crc global regulator on substrate uptake rates and the distribution of metabolic fluxes in Pseudomonas putida KT2440 growing in a complete medium.

When the soil bacterium Pseudomonas putida grows in a complete medium, it prioritizes the assimilation of preferred carbon sources, optimizing its metabolism and growth. This regulatory process is orchestrated by the Crc and Hfq proteins. The present work examines the changes that occur in metabolic fluxes when the crc gene is inactivated and cells grow exponentially in LB complete medium. Analyses were performed at three different moments during exponential growth, examining the assimilation rates for the compounds present in LB, changes in the proteome, and the changes in metabolic fluxes predicted by the iJN1411 metabolic model for P. putida KT2440. During the early exponential phase, consumption rates for sugars, many organic acids and most amino acids were higher in a Crc-null strain than in the wild type, leading to an overflow of the metabolic pathways and the leakage of pyruvate and acetate. These accelerated consumption rates decreased during the mid-exponential phase, when cells mostly used sugars and alanine. At later times, pyruvate was recovered from the medium and utilized. The higher consumption rates of the Crc-null strain reduced the growth rate. The lack of the Crc/Hfq regulatory system thus led to unbalanced metabolism with poorly optimized metabolic fluxes.

Pseudomonas putida KT2440 metabolism undergoes sequential modifications during exponential growth in a complete medium as compounds are gradually consumed.

Pseudomonas putida is a soil bacterium with a versatile and robust metabolism. When confronted with mixtures of carbon sources, it prioritizes the utilization of the preferred compounds, optimizing metabolism and growth. This response is particularly strong when growing in a complex medium such as LB. This work examines the changes occurring in P. putida KT2440 metabolic fluxes, while it grows exponentially in LB medium and sequentially consumes the compounds available. Integrating the uptake rates for each compound at three different moments during the exponential growth with the changes observed in the proteome, and with the metabolic fluxes predicted by the iJN1411 metabolic model for this strain, allowed the metabolic rearrangements that occurred to be determined. The results indicate that the bacterium changes significantly the configuration of its metabolism during the early, mid and late exponential phases of growth. Sugars served as an energy source during the early phase and later as energy and carbon source. The configuration of the tricarboxylic acids cycle varied during growth, providing no energy in the early phase, and turning to a reductive mode in the mid phase and to an oxidative mode later on. This work highlights the dynamism and flexibility of P. putida metabolism.

FLYCOP: metabolic modeling-based analysis and engineering microbial communities.

Motivation: Synthetic microbial communities begin to be considered as promising multicellular biocatalysts having a large potential to replace engineered single strains in biotechnology applications, in pharmaceutical, chemical and living architecture sectors. In contrast to single strain engineering, the effective and high-throughput analysis and engineering of microbial consortia face the lack of knowledge, tools and well-defined workflows. This manuscript contributes to fill this important gap with a framework, called FLYCOP (FLexible sYnthetic Consortium OPtimization), which contributes to microbial consortia modeling and engineering, while improving the knowledge about how these communities work. FLYCOP selects the best consortium configuration to optimize a given goal, among multiple and diverse configurations, in a flexible way, taking temporal changes in metabolite concentrations into account. Results: In contrast to previous systems optimizing microbial consortia, FLYCOP has novel characteristics to face up to new problems, to represent additional features and to analyze events influencing the consortia behavior. In this manuscript, FLYCOP optimizes a Synechococcus elongatus-Pseudomonas putida consortium to produce the maximum amount of bio-plastic (PHA, polyhydroxyalkanoate), and highlights the influence of metabolites exchange dynamics in a four auxotrophic Escherichia coli consortium with parallel growth. FLYCOP can also provide an explanation about biological evolution driving evolutionary engineering endeavors by describing why and how heterogeneous populations emerge from monoclonal ones. Availability and implementation: Code reproducing the study cases described in this manuscript are available on-line: https://github.com/beatrizgj/FLYCOP. Supplementary information: Supplementary data are available at Bioinformatics online.

The Crc/CrcZ-CrcY global regulatory system helps the integration of gluconeogenic and glycolytic metabolism in Pseudomonas putida.

In metabolically versatile bacteria, carbon catabolite repression (CCR) facilitates the preferential assimilation of the most efficient carbon sources, improving growth rates and fitness. In Pseudomonas putida, the Crc and Hfq proteins and the CrcZ and CrcY small RNAs, which are believed to antagonize Crc/Hfq, are key players in CCR. Unlike that seen in other bacterial species, succinate and glucose elicit weak CCR in this bacterium. In the present work, metabolic, transcriptomic and constraint-based metabolic flux analyses were combined to clarify whether P. putida prefers succinate or glucose, and to identify the role of the Crc protein in the metabolism of these compounds. When provided simultaneously, succinate was consumed faster than glucose, although both compounds were metabolized. CrcZ and CrcY levels were lower when both substrates were present than when only one was provided, suggesting a role for Crc in coordinating metabolism of these compounds. Flux distribution analysis suggested that, when both substrates are present, Crc works to organize a metabolism in which carbon compounds flow in opposite directions: from glucose to pyruvate, and from succinate to pyruvate. Thus, our results support that Crc not only favours the assimilation of preferred compounds, but balances carbon fluxes, optimizing metabolism and growth.

Adaptive Evolution of Thermotoga maritima Reveals Plasticity of the ABC Transporter Network.

Thermotoga maritima is a hyperthermophilic anaerobe that utilizes a vast network of ABC transporters to efficiently metabolize a variety of carbon sources to produce hydrogen. For unknown reasons, this organism does not metabolize glucose as readily as it does glucose di- and polysaccharides. The leading hypothesis implicates the thermolability of glucose at the physiological temperatures at which T. maritima lives. After a 25-day laboratory evolution, phenotypes were observed with growth rates up to 1.4 times higher than and glucose utilization rates exceeding 50% those of the wild type. Genome resequencing revealed mutations in evolved cultures related to glucose-responsive ABC transporters. The native glucose ABC transporter, GluEFK, has more abundant transcripts either as a result of gene duplication-amplification or through mutations to the operator sequence regulating this operon. Conversely, BglEFGKL, a transporter of beta-glucosides, is substantially downregulated due to a nonsense mutation to the solute binding protein or due to a deletion of the upstream promoter. Analysis of the ABC2 uptake porter families for carbohydrate and peptide transport revealed that the solute binding protein, often among the transcripts detected at the highest levels, is predominantly downregulated in the evolved cultures, while the membrane-spanning domain and nucleotide binding components are less varied. Similar trends were observed in evolved strains grown on glycerol, a substrate that is not dependent on ABC transporters. Therefore, improved growth on glucose is achieved through mutations favoring GluEFK expression over BglEFGKL, and in lieu of carbon catabolite repression, the ABC transporter network is modulated to achieve improved growth fitness.

Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis.

Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will therefore require a systems understanding of photosynthetic processes. We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that describes key photosynthetic processes in mechanistic detail. We performed an exhaustive in silico analysis of the reconstructed photosynthetic process under different light and inorganic carbon (Ci) conditions as well as under genetic perturbations. Our key results include the following. (i) We identified two main states of the photosynthetic apparatus: a Ci-limited state and a light-limited state. (ii) We discovered nine alternative electron flow pathways that assist the photosynthetic linear electron flow in optimizing the photosynthesis performance. (iii) A high degree of cooperativity between alternative pathways was found to be critical for optimal autotrophic metabolism. Although pathways with high photosynthetic yield exist for optimizing growth under suboptimal light conditions, pathways with low photosynthetic yield guarantee optimal growth under excessive light or Ci limitation. (iv) Photorespiration was found to be essential for the optimal photosynthetic process, clarifying its role in high-light acclimation. Finally, (v) an extremely high photosynthetic robustness drives the optimal autotrophic metabolism at the expense of metabolic versatility and robustness. The results and modeling approach presented here may promote a better understanding of the photosynthetic process. They can also guide bioengineering projects toward optimal biofuel production in photosynthetic organisms.

A model-driven approach to upcycling recalcitrant feedstocks in Pseudomonas putida by decoupling PHA production from nutrient limitation.

Bacterial polyhydroxyalkanoates (PHAs) have emerged as promising eco-friendly alternatives to petroleum-based plastics since they are synthesized from renewable resources and offer exceptional properties. However, their production is limited to the stationary growth phase under nutrient-limited conditions, requiring customized strategies and costly two-phase bioprocesses. In this study, we tackle these challenges by employing a model-driven approach to reroute carbon flux and remove regulatory constraints using synthetic biology. We construct a collection of Pseudomonas putida-overproducing strains at the expense of plastics and lignin-related compounds using growth-coupling approaches. PHA production was successfully achieved during growth phase, resulting in the production of up to 46% PHA/cell dry weight while maintaining a balanced carbon-to-nitrogen ratio. Our strains are additionally validated under an upcycling scenario using enzymatically hydrolyzed polyethylene terephthalate as a feedstock. These findings have the potential to revolutionize PHA production and address the global plastic crisis by overcoming the complexities of traditional PHA production bioprocesses.

Characterization of Limnospira platensis PCC 9108 R-M and CRISPR-Cas systems.

The filamentous cyanobacterium Limnospira platensis, formerly known as Arthrospira platensis or spirulina, is one of the most commercially important species of microalgae. Due to its high nutritional value, pharmacological and industrial applications it is extensively cultivated on a large commercial scale. Despite its widespread use, its precise manipulation is still under development due to the lack of effective genetic protocols. Genetic transformation of Limnospira has been attempted but the methods reported have not been generally reproducible in other laboratories. Knowledge of the transformation defense mechanisms is essential for understanding its physiology and for broadening their applications. With the aim to understand more about the genetic defenses of L. platensis, in this work we have identified the restriction-modification and CRISPR-Cas systems and we have cloned and characterized thirteen methylases. In parallel, we have also characterized the methylome and orphan methyltransferases using genome-wide analysis of DNA methylation patterns and RNA-seq. The identification and characterization of these enzymes will be a valuable resource to know how this strain avoids being genetically manipulated and for further genomics studies.

Non-atherosclerotic acute cardiac syndromes: spontaneous coronary artery dissection and Takotsubo syndrome. Comparison of long-term clinical outcomes.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) and Takotsubo syndrome (TTS) constitute two common causes of nonatherosclerotic acute cardiac syndrome particularly frequent in women. Currently, there is no information comparing long-term clinical outcomes in unselected patients with these conditions. METHODS: We compared the baseline characteristics, in-hospital outcomes, and the 12-month and long-term clinical outcomes of two large prospective registries on SCAD and TTS. RESULTS: A total of 289 SCAD and 150 TTS patients were included; 89% were women. TTS patients were older with a higher prevalence of cardiovascular risk factors. Precipitating triggers were more frequent in TTS patients, while emotional triggers and depressive disorders were more common in the SCAD group. Left ventricular ejection fraction was lower in TTS patients, but SCAD patients showed higher cardiac biomarkers. In-hospital events (43.3% vs. 5.2%, P <0.01) occurred more frequently in TTS patients. TTS patients also presented more frequent major adverse events at 12-month (14.7% vs. 7.1%, HR 5.3, 95% CI: 2.4-11.7, P <0.01) and long-term (median 36 vs. 31 months, P =0.41) follow-up (25.8% vs. 9.6%, HR 4.5, 95% CI: 2.5-8.2, P <0.01). Atrial fibrillation was also more frequent in TTS patients. Moreover, TTS patients presented a higher 12-month and long-term mortality (5.6% vs. 0.7%, P =0.01; and 12.6% vs. 0.7%, P <0.01) mainly driven by noncardiovascular deaths. CONCLUSION: Compared to SCAD, TTS patients are older and present more cardiovascular risk factors but less frequent depressive disorder or emotional triggers. TTS patients have a worse in-hospital, mid-term, and long-term prognosis with higher noncardiac mortality than SCAD patients.

Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii.

BACKGROUND: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H2/CO2, and more importantly on synthesis gas (H2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. RESULTS: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. CONCLUSIONS: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.

Highlighting the potential of Synechococcus elongatus PCC 7942 as platform to produce α-linolenic acid through an updated genome-scale metabolic modeling.

Cyanobacteria are prokaryotic organisms that capture energy from sunlight using oxygenic photosynthesis and transform CO2 into products of interest such as fatty acids. Synechococcus elongatus PCC 7942 is a model cyanobacterium efficiently engineered to accumulate high levels of omega-3 fatty acids. However, its exploitation as a microbial cell factory requires a better knowledge of its metabolism, which can be approached by using systems biology tools. To fulfill this objective, we worked out an updated, more comprehensive, and functional genome-scale model of this freshwater cyanobacterium, which was termed iMS837. The model includes 837 genes, 887 reactions, and 801 metabolites. When compared with previous models of S. elongatus PCC 7942, iMS837 is more complete in key physiological and biotechnologically relevant metabolic hubs, such as fatty acid biosynthesis, oxidative phosphorylation, photosynthesis, and transport, among others. iMS837 shows high accuracy when predicting growth performance and gene essentiality. The validated model was further used as a test-bed for the assessment of suitable metabolic engineering strategies, yielding superior production of non-native omega-3 fatty acids such as α-linolenic acid (ALA). As previously reported, the computational analysis demonstrated that fabF overexpression is a feasible metabolic target to increase ALA production, whereas deletion and overexpression of fabH cannot be used for this purpose. Flux scanning based on enforced objective flux, a strain-design algorithm, allowed us to identify not only previously known gene overexpression targets that improve fatty acid synthesis, such as Acetyl-CoA carboxylase and ß-ketoacyl-ACP synthase I, but also novel potential targets that might lead to higher ALA yields. Systematic sampling of the metabolic space contained in iMS837 identified a set of ten additional knockout metabolic targets that resulted in higher ALA productions. In silico simulations under photomixotrophic conditions with acetate or glucose as a carbon source boosted ALA production levels, indicating that photomixotrophic nutritional regimens could be potentially exploited in vivo to improve fatty acid production in cyanobacteria. Overall, we show that iMS837 is a powerful computational platform that proposes new metabolic engineering strategies to produce biotechnologically relevant compounds, using S. elongatus PCC 7942 as non-conventional microbial cell factory.