Utilizing microbial metabolite in catalytic cascade synthesis of conjugated oligomers for In-Situ regulation of biological activity

Despite the advances of multistep enzymatic cascade reactions, their incorporation with abiotic reactions in living organisms remains challenging in synthetic biology. Herein, we combined microbial metabolic pathways and Pd-catalyzed processes for in-situ generation of bioactive conjugated oligomers. Our biocompatible one-pot coupling reaction utilized the fermentation process of engineered E. coli that converted glucose to styrene, which participated in the Pd-catalyzed Heck reaction for in-situ synthesis of conjugated oligomers. This process serves a great interest in understanding resistance evolution by utilizing the inhibitory activity of the synthesized conjugated oligomers. The approach allows for the in-situ combination of biological metabolism and CC coupling reactions, opening up new possibilities for the biosynthesis of unnatural molecules and enabling the in-situ regulation of the bioactivity of the obtained products.

How many Mutations are needed to Evolve the Chemical Makeup of a Synthetic Cell?

The chemical evolution of a synthetic cell endowed with a synthetic amino acid as building block, analog to tryptophan, required the emergence of key mutations in genes involved in, inter alia, the general stress response, amino acid metabolism, stringent response, and chemotaxis. Understanding adaptation mechanisms to non-canonical biomass components will inform strategies for engineering synthetic metabolic pathways and cells.

Segmentation and evaluation of pathway module efficiency: Quantitative approach to monitor and overcome evolving bottlenecks in xylose to ethanol pathway

Engineering microbes that can efficiently ferment xylose to ethanol is critical to the development of renewable fuels from lignocellulosic biomass. To accelerate the strain optimization process, a method termed Segmentation and Evaluation of Pathway Module Efficiency (SEPME) was developed to enable rapid and iterative identification and removal of metabolic bottlenecks. Using SEPME, the overall pathway was segmented into two modules: the upstream xylose assimilation pathway and the downstream pentose phosphate pathway, glycolysis, and fermentation. The efficiencies of both modules were then quantified to identify the rate controlling module, followed by analyses of control coefficients, reaction rates, and byproduct concentrations to narrow down targets within the module. SEPME analysis revealed that as the strain was engineered with increasing xylose-to-ethanol yields, the bottlenecks shifted within a module and across the two modules. Guided by SEPME, these bottlenecks were removed one by one, and a strain approaching the theoretical ethanol yield was obtained.

Biosynthesis of l-histidine from marine biomass-derived galactans in metabolically engineered Corynebacterium glutamicum

l-Histidine plays significant roles in the food and pharmaceutical industries, and its demand has been steadily increasing recently. As demand for l-histidine continues, the development of eco-friendly processes is required. To pursue this goal, D-galactose, a primary component of red algae, was employed as a carbon source for synthesizing l-histidine. To harness this marine biomass, κ-carrageenan was preferentially hydrolyzed to obtain D-galactose using κ-carrageenase (CgkA) and iduronate-2-sulfatase (IdsA3). Subsequently, l-histidine production was enhanced by modifying precursor pathways in Corynebacterium glutamicum. The resulting strain, TDPH6 exhibited a remarkable 2.15-fold increase in l-histidine production compared to TDP. Furthermore, a galactose utilization system was introduced and named TDPH6G2. During fermentation, this strain efficiently consumed 100 % of the D-galactose and synthesized 0.395 g/L of l-histidine. In conclusion, this study presents a sustainable approach to L-histidine synthesis by introducing a galactose utilization system into C. glutamicum.

Next-generation feedstocks methanol and ethylene glycol and their potential in industrial biotechnology

Microbial fermentation processes are expected to play an important role in reducing dependence on fossil-based raw materials for the production of everyday chemicals. In order to meet the growing demand for biotechnological products in the future, alternative carbon sources that do not compete with human nutrition must be exploited. The chemical conversion of the industrially emitted greenhouse gas CO2 into microbially utilizable platform chemicals such as methanol represents a sustainable strategy for the utilization of an abundant carbon source and has attracted enormous scientific interest in recent years. A relatively new approach is the microbial synthesis of products from the C2-compound ethylene glycol, which can also be synthesized from CO2 and non-edible biomass and, in addition, can be recovered from plastic waste. Here we summarize the main chemical routes for the synthesis of methanol and ethylene glycol from sustainable resources and give an overview of recent metabolic engineering work for establishing natural and synthetic microbial assimilation pathways. The different metabolic routes for C1 and C2 alcohol-dependent bioconversions were compared in terms of their theoretical maximum yields and their oxygen requirements for a wide range of value-added products. Assessment of the process engineering challenges for methanol and ethylene glycol-based fermentations underscores the theoretical advantages of new synthetic metabolic routes and advocates greater consideration of ethylene glycol, a C2 substrate that has received comparatively little attention to date.

Current status of metabolic engineering of microorganisms for bioethanol production by effective utilization of pentose sugars of lignocellulosic biomass

Lignocellulosic biomass, consisting of homo- and heteropolymeric sugars, acts as a substrate for the generation of valuable biochemicals and biomaterials. The readily available hexoses are easily utilized by microbes due to the presence of transporters and native metabolic pathways. But, utilization of pentose sugar viz., xylose and arabinose are still challenging due to several reasons including (i) the absence of the particular native pathways and transporters, (ii) the presence of inhibitors, and (iii) lower uptake of pentose sugars. These challenges can be overcome by manipulating metabolic pathways/glycosidic enzymes cascade by using genetic engineering tools involving inverse-metabolic engineering, ex-vivo isomerization, Adaptive Laboratory Evolution, Directed Metabolic Engineering, etc. Metabolic engineering of bacteria and fungi for the utilization of pentose sugars for bioethanol production is the focus area of research in the current decade. This review outlines current approaches to biofuel development and strategies involved in the metabolic engineering of different microbes that can uptake pentose for bioethanol production.

RespectM revealed metabolic heterogeneity powers deep learning for reshaping the DBTL cycle

Synthetic biology, relying on Design-Build-Test-Learn (DBTL) cycle, aims to solve medicine, manufacturing, and agriculture problems. However, the DBTL cycle's Learn (L) step lacks predictive power for the behavior of biological systems, resulting from the incompatibility between sparse testing data and chaotic metabolic networks. Herein, we develop a method, "RespectM," based on mass spectrometry imaging, which is able to detect metabolites at a rate of 500 cells per hour with high efficiency. In this study, 4,321 single cell level metabolomics data were acquired, representing metabolic heterogeneity. An optimizable deep neural network was applied to learn from metabolic heterogeneity and a "heterogeneity-powered learning (HPL)" based model was trained as well. By testing the HPL based model, we suggest minimal operations to achieve high triglyceride production for engineering. The HPL strategy could revolutionize rational design and reshape the DBTL cycle.

Engineered Artificial Membraneless Organelles in Saccharomyces cerevisiae To Enhance Chemical Production

Microbial cell factories provide a green and sustainable opportunity to produce value-added products from renewable feedstock. However, the leakage of toxic or volatile intermediates decreases the efficiency of microbial cell factories. In this study, membraneless organelles (MLOs) were reconstructed in Saccharomyces cerevisiae by the disordered protein sequence A-IDPs. A regulation system was designed to spatiotemporally regulate the size and rigidity of MLOs. Manipulating the MLO size of strain ZP03-FM, the amounts of assimilated methanol and malate were increased by 162 % and 61 %, respectively. Furthermore, manipulating the MLO rigidity in strain ZP04-RB made acetyl-coA synthesis from oxidative glycolysis change to non-oxidative glycolysis; consequently, CO₂ release decreased by 35 % and the n-butanol yield increased by 20 %. This artificial MLO provides a strategy for the co-localization of enzymes to channel C₁ starting materials into value-added chemicals.

Effective production of Poly(3-hydroxybutyrate-co-4-hydroxybutyrate) by engineered Halomonas bluephagenesis grown on glucose and 1,4-Butanediol

Halomonas bluephagenesis has been engineered to produce flexible copolymers P34HB or poly(3-hydroxybutyrate-co-4-hydroxybutyrate) from glucose and petrol-chemical precursor, γ-butyrolactone. Herein, gene cluster aldD-dhaT was constructed in recombinant H. bluephagenesis for catalyzing 1,4-butanediol (BDO) into 4-hydroxybutyrate, which could grow to 86 g L^-1 dry cell mass (DCM) containing 77 wt% P(3HB-co-14 mol% 4HB) in 7-L bioreactor fed with glucose and bio-based BDO. Furthermore, 4HB monomer ratio could be increased to 16 mol% by engineered H. bluephagenesis TDH4-WZY254 with defected outer-membrane. Upon deletion of 4HB degradation pathway, followed by aldD-dhaT integration, the resulted H. bluephagenesis TDB141ΔAC was grown to 95 g L^-1 DCM containing 79 wt% P(3HB-co-14 mol% 4HB) with a BDO conversion efficiency of 86% under fed-batch fermentation. Notably, 4HB molar ratio can be significantly improved to 21 mol% with negligible effects on cell growth and P34HB synthesis by adding 50% more BDO. This study successfully demonstrated a fully bio-based P34HB effectively produced by H. bluephagenesis.

Construction and Optimization of the de novo Biosynthesis Pathway of Mogrol in Saccharomyces Cerevisiae

Mogrol plays important roles in antihyperglycemic and antilipidemic through activating the AMP-activated protein kinase pathway. Although the synthesis pathway of mogrol in Siraitia grosvenorii has been clarified, few studies have focused on improving mogrol production. This study employed a modular engineerin g strategy to improve mogrol production in a yeast chassis cell. First, a de novo synthesis pathway of mogrol in Saccharomyces cerevisiae was constructed. Then, the metabolic flux of each synthetic module in mogrol metabolism was systematically optimized, including the enhancement of the precursor supply, inhibition of the sterol synthesis pathway using the Clustered Regularly Interspaced Short Palindromic Repeats Interference system (CRISPRi), and optimization of the expression and reduction system of P450 enzymes. Finally, the mogrol titer was increased to 9.1 μg/L, which was 455-fold higher than that of the original strain. The yeast strains engineered in this work can serve as the basis for creating an alternative way for mogrol production in place of extraction from S. grosvenorii.

Zymomonas mobilis as an emerging biotechnological chassis for the production of industrially relevant compounds

Zymomonas mobilis is a well-recognized ethanologenic bacterium with outstanding characteristics which make it a promising platform for the biotechnological production of relevant building blocks and fine chemicals compounds. In the last years, research has been focused on the physiological, genetic, and metabolic engineering strategies aiming at expanding Z. mobilis ability to metabolize lignocellulosic substrates toward biofuel production. With the expansion of the Z. mobilis molecular and computational modeling toolbox, the potential of this bacterium as a cell factory has been thoroughly explored. The number of genomic, transcriptomic, proteomic, and fluxomic data that is becoming available for this bacterium has increased. For this reason, in the forthcoming years, systems biology is expected to continue driving the improvement of Z. mobilis for current and emergent biotechnological applications. While the existing molecular toolbox allowed the creation of stable Z. mobilis strains with improved traits for pinpointed biotechnological applications, the development of new and more flexible tools is crucial to boost the engineering capabilities of this bacterium. Novel genetic toolkits based on the CRISPR-Cas9 system and recombineering have been recently used for the metabolic engineering of Z. mobilis. However, they are mostly at the proof-of-concept stage and need to be further improved.

Microbial Biosynthesis of L-Malic Acid and Related Metabolic Engineering Strategies: Advances and Prospects

Malic acid, a four-carbon dicarboxylic acid, is widely used in the food, chemical and medical industries. As an intermediate of the TCA cycle, malic acid is one of the most promising building block chemicals that can be produced from renewable sources. To date, chemical synthesis or enzymatic conversion of petrochemical feedstocks are still the dominant mode for malic acid production. However, with increasing concerns surrounding environmental issues in recent years, microbial fermentation for the production of L-malic acid was extensively explored as an eco-friendly production process. The rapid development of genetic engineering has resulted in some promising strains suitable for large-scale bio-based production of malic acid. This review offers a comprehensive overview of the most recent developments, including a spectrum of wild-type, mutant, laboratory-evolved and metabolically engineered microorganisms for malic acid production. The technological progress in the fermentative production of malic acid is presented. Metabolic engineering strategies for malic acid production in various microorganisms are particularly reviewed. Biosynthetic pathways, transport of malic acid, elimination of byproducts and enhancement of metabolic fluxes are discussed and compared as strategies for improving malic acid production, thus providing insights into the current state of malic acid production, as well as further research directions for more efficient and economical microbial malic acid production.

Recent advances in the microbial production of isopentanol (3-Methyl-1-butanol)

As the effects of climate change become increasingly severe, metabolic engineers and synthetic biologists are looking towards greener sources for transportation fuels. The design and optimization of microorganisms to produce gasoline, diesel, and jet fuel compounds from renewable feedstocks can significantly reduce dependence on fossil fuels and thereby produce fewer emissions. Over the past two decades, a tremendous amount of research has contributed to the development of microbial strains to produce advanced fuel compounds, including branched-chain higher alcohols (BCHAs) such as isopentanol (3-methyl-1-butanol; 3M1B) and isobutanol (2-methyl-1-propanol). In this review, we provide an overview of recent advances in the development of microbial strains for the production of isopentanol in both conventional and non-conventional hosts. We also highlight metabolic engineering strategies that may be employed to enhance product titers, reduce end-product toxicity, and broaden the substrate range to non-sugar carbon sources. Finally, we offer glimpses into some promising future directions in the development of isopentanol producing microbial strains.

Structural basis for selective inhibition of human serine hydroxymethyltransferase by secondary bile acid conjugate

Bile acids are metabolites of cholesterol that facilitate lipid digestion and absorption in the small bowel. Bile acids work as agonists of receptors to regulate their own metabolism. Bile acids also regulate other biological systems such as sugar metabolism, intestinal multidrug resistance, and adaptive immunity. However, numerous physiological roles of bile acids remain undetermined. In this study, we solved the crystal structure of human serine hydroxymethyltransferase (hSHMT) in complex with an endogenous secondary bile acid glycine conjugate. The specific interaction between hSHMT and the ligand was demonstrated using mutational analyses, biophysical measurements, and structure-activity relationship studies, suggesting that secondary bile acid conjugates may act as modulators of SHMT activity.

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The crystal structures of hSHMT in complex with secondary bile acid glycine conjugate

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Specific interactions between hSHMT and secondary bile acid conjugate were validated

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Biological role of bile acids as modulators for one-carbon metabolism is suggested

Recombination machinery engineering for precise genome editing in methylotrophic yeast Ogataea polymorpha

Methanol biotransformation can expand biorefinery substrate spectrum other than biomass by using methylotrophic microbes. Ogataea (Hansenula) polymorpha, a representative methylotrophic yeast, attracts much attention due to its thermotolerance, but the low homologous recombination (HR) efficiency hinders its precise genetic manipulation during cell factory construction. Here, recombination machinery engineering (rME) is explored for enhancing HR activity together with establishing an efficient CRISPR-Cas9 system in O. polymorpha. Overexpression of HR-related proteins and down-regulation of non-homologous end joining (NHEJ) increased HR rates from 20%-30% to 60%-70%. With these recombination perturbation mutants, a competition between HR and NHEJ is observed. This HR up-regulated system has been applied for homologous integration of large fragments and in vivo assembly of multiple fragments, which enables the production of fatty alcohols in O. polymorpha. These findings will simplify genetic engineering in non-conventional yeasts and facilitate the adoption of O. polymorpha as an attractive cell factory for industrial application.

Machine learning for metabolic engineering: A review

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.

A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria

Machine learning has recently emerged as a promising tool for inferring multi-omic relationships in biological systems. At the same time, genome-scale metabolic models (GSMMs) can be integrated with such multi-omic data to refine phenotypic predictions. In this work, we use a multi-omic machine learning pipeline to analyze a GSMM of Synechococcus sp. PCC 7002, a cyanobacterium with large potential to produce renewable biofuels. We use regularized flux balance analysis to observe flux response between conditions across photosynthesis and energy metabolism. We then incorporate principal-component analysis, k-means clustering, and LASSO regularization to reduce dimensionality and extract key cross-omic features. Our results suggest that combining metabolic modeling with machine learning elucidates mechanisms used by cyanobacteria to cope with fluctuations in light intensity and salinity that cannot be detected using transcriptomics alone. Furthermore, GSMMs introduce critical mechanistic details that improve the performance of omic-based machine learning methods.

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A pipeline for metabolic modeling in Synechococcus sp. PCC 7002 is presented

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Metabolic fluxes display clear differences in pathway activity across conditions

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Omic-informed GSMMs provide critical mechanistic details within machine learning

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Combining GSMM and machine learning improves methods based on transcriptomics alone

Exposure to Air Pollution Disrupts Circadian Rhythm through Alterations in Chromatin Dynamics

Particulate matter ≤2.5μm (PM_2.5) air pollution is a leading environmental risk factor contributing disproportionately to the global burden of non-communicable disease. We compared impact of chronic exposure to PM_2.5 alone, or with light at night exposure (LL) on metabolism. PM_2.5 induced peripheral insulin resistance, circadian rhythm (CR) dysfunction, and metabolic and brown adipose tissue (BAT) dysfunction, akin to LL (with no additive interaction between PM_2.5 and LL). Transcriptomic analysis of liver and BAT revealed widespread but unique alterations in CR genes, with evidence for differentially accessible promoters and enhancers of CR genes in response to PM_2.5 by ATAC-seq. The histone deacetylases 2, 3, and 4 were downregulated with PM_2.5 exposure, with increased promoter occupancy by the histone acetyltransferase p300 as evidenced by ChIP-seq. These findings suggest a previously unrecognized role of PM_2.5 in promoting CR disruption and metabolic dysfunction through epigenetic regulation of circadian targets.

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Air pollution disrupts the circadian rhythm (CR) similar to light at night

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Dysregulated circadian genes result in insulin resistance and metabolic diseases

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PM_2.5 alters chromatin structure of circadian genes at regulatory regions

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PM_2.5 alters chromatin structure by recruiting histone acetyl transferase (HAT), p300

Enzyme-Constrained Models and Omics Analysis of Streptomyces coelicolor Reveal Metabolic Changes that Enhance Heterologous Production

Many biosynthetic gene clusters (BGCs) require heterologous expression to realize their genetic potential, including silent and metagenomic BGCs. Although the engineered Streptomyces coelicolor M1152 is a widely used host for heterologous expression of BGCs, a systemic understanding of how its genetic modifications affect the metabolism is lacking and limiting further development. We performed a comparative analysis of M1152 and its ancestor M145, connecting information from proteomics, transcriptomics, and cultivation data into a comprehensive picture of the metabolic differences between these strains. Instrumental to this comparison was the application of an improved consensus genome-scale metabolic model (GEM) of S. coelicolor. Although many metabolic patterns are retained in M1152, we find that this strain suffers from oxidative stress, possibly caused by increased oxidative metabolism. Furthermore, precursor availability is likely not limiting polyketide production, implying that other strategies could be beneficial for further development of S. coelicolor for heterologous production of novel compounds.

Applying Non-canonical Redox Cofactors in Fermentation Processes

Fermentation processes are used to sustainably produce chemicals and as such contribute to the transition to a circular economy. The maximum theoretical yield of a conversion can only be approached if all electrons present in the substrate end up in the product. Control over the electrons is therefore crucial. However, electron transfer via redox cofactors results in a diffuse distribution of electrons over metabolism. To overcome this challenge, we propose to apply non-canonical redox cofactors (NRCs) in metabolic networks: cofactors that channel electrons exclusively from substrate to product, forming orthogonal circuits for electron transfer.

Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories

Transcription factor-based biosensors naturally occur in metabolic pathways to maintain cell growth and to provide a robust response to environmental fluctuations. Extended metabolic biosensors, i.e., the cascading of a bio-conversion pathway and a transcription factor (TF) responsive to the downstream effector metabolite, provide sensing capabilities beyond natural effectors for implementing context-aware synthetic genetic circuits and bio-observers. However, the engineering of such multi-step circuits is challenged by stability and robustness issues. In order to streamline the design of TF-based biosensors in metabolic pathways, here we investigate the response of a genetic circuit combining a TF-based extended metabolic biosensor with an antithetic integral circuit, a feedback controller that achieves robustness against environmental fluctuations. The dynamic response of an extended biosensor-based regulated flavonoid pathway is analyzed in order to address the issues of biosensor tuning of the regulated pathway under industrial biomanufacturing operating constraints.

Perspectives and new directions for bioprocess optimization using Zymomonas mobilis in the ethanol production

Zymomonas mobilis is an ethanologenic microbe that has a demonstrated potential for use in lignocellulosic biorefineries for bioethanol production. Z. mobilis exhibits a number of desirable characteristics for use as an ethanologenic microbe, with capabilities for metabolic engineering and bioprocess modification. Many advanced genetic tools, including mutation techniques, screening methods and genome editing have been successively performed to improve various Z. mobilis strains as potential consolidated ethanologenic microbes. Many bioprocess strategies have also been applied to this organism for bioethanol production. Z. mobilis biofilm reactors have been modified with various benefits, including high bacterial populations, less fermentation times, high productivity, high cell stability, resistance to the high concentration of substrates and toxicity, and higher product recovery. We suggest that Z. mobilis biofilm reactors could be used in bioethanol production using lignocellulosic substrates under batch, continuous and repeated batch processes.

A Sustainable Chemicals Manufacturing Paradigm Using CO2 and Renewable H2

The chemical industry must decarbonize to align with UN Sustainable Development Goals. A shift toward circular economies makes CO2 an attractive feedstock for producing chemicals, provided renewable H2 is available through technologies such as supercritical water (scH2O) gasification. Furthermore, high carbon and energy efficiency is paramount to favorable techno-economics, which poses a challenge to chemo-catalysis. This study demonstrates continuous gas fermentation of CO2 and H2 by the cell factory, Cupriavidus necator, to (R,R)-2,3-butanediol and isopropanol as case studies. Although a high carbon efficiency of 0.75 [(C-mol product)/(C-mol CO2)] is exemplified, the poor energy efficiency of biological CO2 fixation requires ∼8 [(mol H2)/(mol CO2)], which is techno-economically infeasible for producing commodity chemicals. Heat integration between exothermic gas fermentation and endothermic scH2O gasification overcomes this energy inefficiency. This study unlocks the promise of sustainable manufacturing using renewable feedstocks by combining the carbon efficiency of bio-catalysis with energy efficiency enforced through process engineering.

Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli

The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite’s production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment.

Flux Balance Analysis for Media Optimization and Genetic Targets to Improve Heterologous Siderophore Production

Siderophores are small molecule metal chelators secreted in sparse quantities by their native microbial hosts but can be engineered for enhanced production from heterologous hosts like Escherichia coli. These molecules have been proved to be capable of binding heavy metals of commercial and/or environmental interest. In this work, we incorporated, as needed, the appropriate pathways required to produce several siderophores (anguibactin, vibriobactin, bacillibactin, pyoverdine, and enterobactin) into the base E. coli K-12 MG1655 metabolic network model to computationally predict, via flux balance analysis methodologies, gene knockout targets, gene over-expression targets, and media modifications capable of improving siderophore reaction flux. E. coli metabolism proved supportive for the underlying production mechanisms of various siderophores. Within such a framework, the gene deletion and over-expression targets identified, coupled with complementary insights from medium optimization predictions, portend experimental implementation to both enable and improve heterologous siderophore production. Successful production of siderophores would then spur novel metal-binding applications.

Computation-Driven Analysis of Model Polyextremo-tolerant Fungus Exophiala dermatitidis: Defensive Pigment Metabolic Costs and Human Applications

The polyextremotolerant black yeast Exophiala dermatitidis is a tractable model system for investigation of adaptations that support growth under extreme conditions. Foremost among these adaptations are melanogenesis and carotenogenesis. A particularly important question is their metabolic production cost. However, investigation of this issue has been hindered by a relatively poor systems-level understanding of E. dermatitidis metabolism. To address this challenge, a genome-scale model (iEde2091) was developed. Using iEde2091, carotenoids were found to be more expensive to produce than melanins. Given their overlapping protective functions, this suggests that carotenoids have an underexplored yet important role in photo-protection. Furthermore, multiple defensive pigments with overlapping functions might allow E. dermatitidis to minimize cost. Because iEde2091 revealed that E. dermatitidis synthesizes the same melanins as humans and the active sites of the key tyrosinase enzyme are highly conserved this model may enable a broader understanding of melanin production across kingdoms.

Tuning the Binding Affinity of Heme-Responsive Biosensor for Precise and Dynamic Pathway Regulation

Current challenge for dynamic pathway control in metabolic engineering is enabling the components of the artificial regulatory system to be tunable. Here, we designed and built a heme-responsive regulatory system containing a heme biosensor HrtR and CRISPRi to regulate chemicals production while maintaining the intracellular heme homeostasis. A series of engineered biosensors with varied sensitivity and threshold were obtained by semi-rational design with site saturated mutation of HrtR. The modified metabolite-binding affinity of HrtR was confirmed by heme titration and molecular dynamic simulation. Dynamic regulation pattern of the system was validated by the fluctuation of gene expression and intracellular heme concentration. The efficiency of this regulatory system was proved by improving the 5-aminolevulinic acid (ALA) production to 5.35g/L, the highest yield in batch fermentation of Escherichia coli. This system was also successfully used in improving porphobilinogen (PBG) and porphyrins biosynthesis and can be applied in many other biological processes.

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Designed and built a heme-responsive regulatory system employing HrtR and CRISPRi

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Turning the binding affinity of HrtR by site saturation mutations

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Optimizing the system to achieve dynamic regulation of target genes

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The system was applied to the ALA, PBG, and porphyrins production

High-Efficiency Multi-site Genomic Editing of Pseudomonas putida through Thermoinducible ssDNA Recombineering

Application of single-stranded DNA recombineering for genome editing of species other than enterobacteria is limited by the efficiency of the recombinase and the action of endogenous mismatch repair (MMR) systems. In this work we have set up a genetic system for entering multiple changes in the chromosome of the biotechnologically relevant strain EM42 of Pseudomononas putida. To this end high-level heat-inducible co-transcription of the rec2 recombinase and P. putida's allele mutLE36KPP was designed under the control of the PL/cI857 system. Cycles of short thermal shifts followed by transformation with a suite of mutagenic oligos delivered different types of genomic changes at frequencies up to 10% per single modification. The same approach was instrumental to super-diversify short chromosomal portions for creating libraries of functional genomic segments-e.g., ribosomal-binding sites. These results enabled multiplexing of genome engineering of P. putida, as required for metabolic reprogramming of this important synthetic biology chassis.

Engineered Biosynthesis of Alkyne-Tagged Polyketides by Type I PKSs

Polyketides produced by modular polyketide synthases (PKSs) are important small molecules widely used as drugs, pesticides, and biological probes. Tagging these polyketides with a clickable functionality enables the visualization, diversification, and mode of action study through bio-orthogonal chemistry. We report the de novo biosynthesis of alkyne-tagged polyketides by modular type I PKSs through starter unit engineering. Specifically, we use JamABC, a terminal alkyne biosynthetic machinery from the jamaicamide B biosynthetic pathway, in combination with representative modular PKSs. We demonstrate that JamABC works as a trans loading system for engineered type I PKSs to produce alkyne-tagged polyketides. In addition, the production efficiency can be improved by enhancing the interactions between the carrier protein (JamC) and PKSs using docking domains and site-directed mutagenesis of JamC. This work thus provides engineering guidelines and strategies that are applicable to additional modular type I PKSs to produce targeted alkyne-tagged metabolites for chemical and biological applications.

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Alkyne-tagged polyketides are de novo biosynthesized using type I PKSs

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Docking domains and ACP mutagenesis improve alkyne starter unit translocation

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Docking domains, but not ACP mutagenesis, perturb alkyne biosynthetic machinery

MOMO - multi-objective metabolic mixed integer optimization: application to yeast strain engineering

BACKGROUND

In this paper, we explore the concept of multi-objective optimization in the field of metabolic engineering when both continuous and integer decision variables are involved in the model. In particular, we propose a multi-objective model that may be used to suggest reaction deletions that maximize and/or minimize several functions simultaneously. The applications may include, among others, the concurrent maximization of a bioproduct and of biomass, or maximization of a bioproduct while minimizing the formation of a given by-product, two common requirements in microbial metabolic engineering.

RESULTS

Production of ethanol by the widely used cell factory Saccharomyces cerevisiae was adopted as a case study to demonstrate the usefulness of the proposed approach in identifying genetic manipulations that improve productivity and yield of this economically highly relevant bioproduct. We did an in vivo validation and we could show that some of the predicted deletions exhibit increased ethanol levels in comparison with the wild-type strain.

CONCLUSIONS

The multi-objective programming framework we developed, called MOMO, is open-source and uses POLYSCIP (Available at http://polyscip.zib.de/). as underlying multi-objective solver. MOMO is available at http://momo-sysbio.gforge.inria.fr.

Cell Membrane and Electron Transfer Engineering for Improved Synthesis of Menaquinone-7 in Bacillus subtilis

The formation of biofilm facilitates the synthesis of valuable natural product menaquinone-7 (MK-7) in static culture of Bacillus subtilis, whereas the essential role and mechanism of biofilm in MK-7 synthesis have not been revealed. Herein, comparative transcriptomics show that the formation of biofilm affected MK-7 synthesis by changing the transcription levels of signal receptor (BSU02010), transmembrane transporter (BSU29340, BSU03070), and signal transduction (BSU02630). Moreover, we also found that oxalate decarboxylase OxdC has an important effect on electron generation and MK-7 synthesis, when the transcriptional level of NADH dehydrogenase decreases in static culture. Our results revealed that cell membrane and electron transfer are important factors in promoting MK-7 synthesis.

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Transcriptome analysis shows the relationship between biofilm and MK-7 synthesis

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Electron transfer significantly affects the synthesis of MK-7

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Oxalate decarboxylase OxdC plays a role in electron generation and MK-7 synthesis

Auxotrophic Selection Strategy for Improved Production of Coenzyme B12 in Escherichia coli

The production of coenzyme B₁₂ using well-characterized microorganisms, such as Escherichia coli, has recently attracted considerable attention to meet growing demands of coenzyme B₁₂ in various applications. In the present study, we designed an auxotrophic selection strategy and demonstrated the enhanced production of coenzyme B₁₂ using a previously engineered coenzyme B₁₂-producing E. coli strain. To select a high producer, the coenzyme B₁₂-independent methionine synthase (metE) gene was deleted in E. coli, thus limiting its methionine synthesis to only that via coenzyme B₁₂-dependent synthase (encoded by metH). Following the deletion of metE, significantly enhanced production of the specific coenzyme B₁₂ validated the coenzyme B₁₂-dependent auxotrophic growth. Further precise tuning of the auxotrophic system by varying the expression of metH substantially increased the cell biomass and coenzyme B₁₂ production, suggesting that our strategy could be effectively applied to E. coli and other coenzyme B₁₂-producing strains.

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The auxotrophic selection strategy was applied to coenzyme B₁₂ production

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Coenzyme B₁₂-independent methionine synthase was deleted for auxotroph system

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The auxotrophic strategy could significantly enhance the coenzyme B₁₂ production

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Optimization of the auxotroph system further enhanced the coenzyme B₁₂ production

Advanced Strategies for Production of Natural Products in Yeast

Natural products account for more than 50% of all small-molecule pharmaceutical agents currently in clinical use. However, low availability often becomes problematic when a bioactive natural product is promising to become a pharmaceutical or leading compound. Advances in synthetic biology and metabolic engineering provide a feasible solution for sustainable supply of these compounds. In this review, we have summarized current progress in engineering yeast cell factories for production of natural products, including terpenoids, alkaloids, and phenylpropanoids. We then discuss advanced strategies in metabolic engineering at three different dimensions, including point, line, and plane (corresponding to the individual enzymes and cofactors, metabolic pathways, and the global cellular network). In particular, we comprehensively discuss how to engineer cofactor biosynthesis for enhancing the biosynthesis efficiency, other than the enzyme activity. Finally, current challenges and perspective are also discussed for future engineering direction.

System-Level Analysis of Lignin Valorization in Lignocellulosic Biorefineries

We study the economics and energy efficiency of biorefineries employing lignin valorization. We use superstructure-based process synthesis to study different configurations under different types of constraints. Using optimization, we examine the impact of various parameters for lignin valorization such as bioproduct selling price, production cost, conversion coefficient, and energy requirement. The results show that the optimal strategy leading to a minimum ethanol selling price (MESP) of $3.44/GGE does not include lignin valorization. Results indicate that under certain scenarios, the optimal biorefinery strategies with lignin valorization tend to be energy deficient, and thus the optimal pretreatment technology may switch from γ-valerolactone-based deconstruction to ammonia fiber expansion. Further analysis is performed to study how improvements in combinations of selected parameters can lead to lower cost for a thermal-neural biorefinery.

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Developed optimization model to evaluate biorefinery with lignin valorization

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Studied impact of technical, economic, and energy parameters on economics

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Lignin utilization is optimized to achieve a thermal-neutral biorefinery

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Established technology targets for economic and energetic feasibility

Computational Tools for Discovering and Engineering Natural Product Biosynthetic Pathways

Natural products (NPs), also known as secondary metabolites, are produced in bacteria, fungi, and plants. NPs represent a rich source of antibacterial, antifungal, and anticancer agents. Recent advances in DNA sequencing technologies and bioinformatics unveiled nature's great potential for synthesizing numerous NPs that may confer unprecedented structural and biological features. However, discovering novel bioactive NPs by genome mining remains a challenge. Moreover, even with interesting bioactivity, the low productivity of many NPs significantly limits their practical applications. Here we discuss the progress in developing bioinformatics tools for efficient discovery of bioactive NPs. In addition, we highlight computational methods for optimizing the productivity of NPs of pharmaceutical importance.

Application of Stable Isotope Tracing to Elucidate Metabolic Dynamics During Yarrowia lipolytica α-Ionone Fermentation

Targeted metabolite analysis in combination with ¹³C-tracing is a convenient strategy to determine pathway activity in biological systems; however, metabolite analysis is limited by challenges in separating and detecting pathway intermediates with current chromatographic methods. Here, a hydrophilic interaction chromatography tandem mass spectrometry approach was developed for improved metabolite separation, isotopologue analysis, and quantification. The physiological responses of a Yarrowia lipolytica strain engineered to produce ∼400 mg/L α-ionone and temporal changes in metabolism were quantified (e.g., mevalonate secretion, then uptake) indicating bottleneck shifts in the engineered pathway over the course of fermentation. Dynamic labeling results indicated limited tricarboxylic acid cycle label incorporation and, combined with a measurable ATP shortage during the high ionone production phase, suggested that electron transport and oxidative phosphorylation may limit energy supply and strain performance. The results provide insights into terpenoid pathway metabolic dynamics of non-model yeasts and offer guidelines for sensor development and modular engineering.

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A HILIC method is demonstrated for efficient separation of 57 cellular metabolites

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Production of α-ionone was ∼400 mg/L in bench-top bioreactors

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Engineered Y. lipolytica secreted then consumed mevalonate during fermentation

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Oxidative phosphorylation may limit performance in high-cell-density fermentations

OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models

Stoichiometric metabolic modeling, particularly genome-scale models (GSMs), is now an indispensable tool for systems biology. The model reconstruction process typically involves collecting information from public databases; however, incomplete systems knowledge leaves gaps in any reconstruction. Current tools for addressing gaps use databases of biochemical functionalities to address gaps on a per-metabolite basis and can provide multiple solutions but cannot avoid thermodynamically infeasible cycles (TICs), invariably requiring lengthy manual curation. To address these limitations, this work introduces an optimization-based multi-step method named OptFill, which performs TIC-avoiding whole-model gapfilling. We applied OptFill to three fictional prokaryotic models of increasing sizes and to a published GSM of Escherichia coli, iJR904. This application resulted in holistic and infeasible cycle-free gapfilling solutions. In addition, OptFill can be adapted to automate inherent TICs identification in any GSM. Overall, OptFill can address critical issues in automated development of high-quality GSMs.

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This work presents an alternative to state-of-the-art methods for gapfilling

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Unlike current methods, this method is holistic and infeasible cycle free

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This method is applied to three tests and one published model

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This method might also be used to address infeasible cycling

Modification of RSF1010-Based Broad-Host-Range Plasmids for Improved Conjugation and Cyanobacterial Bioprospecting

To facilitate the genetic engineering of diverse cyanobacterial strains, we have modified broad-host-range RSF1010-based plasmids to improve transmissibility, increase copy number, and facilitate cloning. RSF1010-based plasmids replicate in diverse bacterial strains but produce low amounts of useable DNA for cloning. We previously engineered a mobAY25F mutation in RSF1010-based plasmids that improved cloning but decreased conjugation efficiency. Here, we engineered RSF1010-based plasmids to restore conjugation efficiency, which was demonstrated in three diverse laboratory strains of cyanobacteria. We then used an improved RSF1010-based plasmid in mating experiments with cultured samples of wild cyanobacteria. This plasmid, which confers antibiotic resistance and carries a yfp reporter gene, allowed selection of exconjugant cyanobacteria and facilitated the isolation of genetically tractable strains from mixed wild cultures. Improved RSF1010 vectors can be used for bioprospecting genetically tractable strains and are compatible with the CYANO-VECTOR cloning system, a versatile toolbox for constructing plasmids for cyanobacterial genetic engineering.

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An RSF1010 mobAY25F mutation facilitates plasmid cloning but reduces conjugation

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Addition of an RK2-bom site improves conjugation efficiency of mobAY25F vectors

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A helper plasmid carrying the mobA gene improves conjugation efficiency of mobAY25F

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Improved RSF1010-based vectors can be used for bioprospecting of cyanobacteria

Genome-driven cell engineering review: in vivo and in silico metabolic and genome engineering

Producing 'designer cells' with specific functions is potentially feasible in the near future. Recent developments, including whole-cell models, genome design algorithms and gene editing tools, have advanced the possibility of combining biological research and mathematical modelling to further understand and better design cellular processes. In this review, we will explore computational and experimental approaches used for metabolic and genome design. We will highlight the relevance of modelling in this process, and challenges associated with the generation of quantitative predictions about cell behaviour as a whole: although many cellular processes are well understood at the subsystem level, it has proved a hugely complex task to integrate separate components together to model and study an entire cell. We explore these developments, highlighting where computational design algorithms compensate for missing cellular information and underlining where computational models can complement and reduce lab experimentation. We will examine issues and illuminate the next steps for genome engineering.

Application of Nonphosphorylative Metabolism as an Alternative for Utilization of Lignocellulosic Biomass

Production of chemicals via fermentation has been evolving over the past 30 years in search of economically viable systems. Thus far, there have been few industrially relevant chemicals that have seen commercialization, examples being lactic acid and ethanol. Currently, many of these fermentation processes still compete with food sources. In order to reduce this competition fermentation of alternative feedstocks, such as lignocellulosic biomass must to be utilized. Hemicellulosic sugars can be employed effectively for the production of chemicals by incorporating nonphosphorylative metabolism. This review covers nonphosphorylative metabolism, the pathways and enzymes involved, as well as the products that have been produced using nonphosphorylative metabolism.

High-throughput evaluation of synthetic metabolic pathways

A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.

Cloning and functional characterization of three branch point oxidosqualene cyclases from Withania somnifera (L.) dunal

Oxidosqualene cyclases (OSCs) positioned at a key metabolic subdividing junction execute indispensable enzymatic cyclization of 2,3-oxidosqualene for varied triterpenoid biosynthesis. Such branch points present favorable gene targets for redirecting metabolic flux toward specific secondary metabolites. However, detailed information regarding the candidate OSCs covering different branches and their regulation is necessary for the desired genetic manipulation. The aim of the present study, therefore, was to characterize members of OSC superfamily from Withania somnifera (Ws), a medicinal plant of immense repute known to synthesize a large array of biologically active steroidal lactone triterpenoids called withanolides. Three full-length OSC cDNAs, β-amyrin synthase (WsOSC/BS), lupeol synthase (WsOSC/LS), and cycloartenol synthase (WsOSC/CS), having open reading frames of 2289, 2268, and 2277 bp, were isolated. Heterologous expression in Schizosaccharomyces pombe, LC-MS analyses, and kinetic studies confirmed their monofunctionality. The three WsOSCs were found to be spatially regulated at transcriptional level with WsOSC/CS being maximally expressed in leaf tissue. Promoter analysis of three WsOSCs genes resulted in identification of distinct cis-regulatory elements. Further, transcript profiling under methyl jasmonate, gibberellic acid, and yeast extract elicitations displayed differential transcriptional regulation of each of the OSCs. Changes were also observed in mRNA levels under elicitations and further substantiated with protein expression levels by Western blotting. Negative regulation by yeast extract resulted in significant increase in withanolide content. Empirical evidence suggests that repression of competitive branch OSCs like WsOSC/BS and WsOSC/LS possibly leads to diversion of substrate pool toward WsOSC/CS for increased withanolide production.

Introduction of a synthetic CO₂-fixing photorespiratory bypass into a cyanobacterium

Global photosynthetic productivity is limited by the enzymatic assimilation of CO2 into organic carbon compounds. Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), the carboxylating enzyme of the Calvin-Benson cycle, poorly discriminates between CO2 and O2, leading to photorespiration and the loss of fixed carbon and nitrogen. With the advent of synthetic biology, it is now feasible to design, synthesize, and introduce biochemical pathways in vivo. We engineered a synthetic photorespiratory bypass based on the 3-hydroxypropionate bi-cycle into the model cyanobacterium, Synechococcus elongatus sp. PCC 7942. The heterologously expressed cycle is designed to function as both a photorespiratory bypass and an additional CO2-fixing pathway, supplementing the Calvin-Benson cycle. We demonstrate the function of all six introduced enzymes and identify bottlenecks to be targeted in subsequent bioengineering. These results have implications for efforts to improve photosynthesis and for the "green" production of high value products of biotechnological interest.

Engineering hydrogen gas production from formate in a hyperthermophile by heterologous production of an 18-subunit membrane-bound complex

Biohydrogen gas has enormous potential as a source of reductant for the microbial production of biofuels, but its low solubility and poor gas mass transfer rates are limiting factors. These limitations could be circumvented by engineering biofuel production in microorganisms that are also capable of generating H2 from highly soluble chemicals such as formate, which can function as an electron donor. Herein, the model hyperthermophile, Pyrococcus furiosus, which grows optimally near 100 °C by fermenting sugars to produce H2, has been engineered to also efficiently convert formate to H2. Using a bacterial artificial chromosome vector, the 16.9-kb 18-gene cluster encoding the membrane-bound, respiratory formate hydrogen lyase complex of Thermococcus onnurineus was inserted into the P. furiosus chromosome and expressed as a functional unit. This enabled P. furiosus to utilize formate as well as sugars as an H2 source and to do so at both 80° and 95 °C, near the optimum growth temperature of the donor (T. onnurineus) and engineered host (P. furiosus), respectively. This accomplishment also demonstrates the versatility of P. furiosus for metabolic engineering applications.

Non-growing Rhodopseudomonas palustris increases the hydrogen gas yield from acetate by shifting from the glyoxylate shunt to the tricarboxylic acid cycle

When starved for nitrogen, non-growing cells of the photosynthetic bacterium Rhodopseudomonas palustris continue to metabolize acetate and produce H2, an important industrial chemical and potential biofuel. The enzyme nitrogenase catalyzes H2 formation. The highest H2 yields are obtained when cells are deprived of N2 and thus use available electrons to synthesize H2 as the exclusive product of nitrogenase. To understand how R. palustris responds metabolically to increase H2 yields when it is starved for N2, and thus not growing, we tracked changes in biomass composition and global transcript levels. In addition to a 3.5-fold higher H2 yield by non-growing cells we also observed an accumulation of polyhydroxybutyrate to over 30% of the dry cell weight. The transcriptome of R. palustris showed down-regulation of biosynthetic processes and up-regulation of nitrogen scavenging mechanisms in response to N2 starvation but gene expression changes did not point to metabolic activities that could generate the reductant necessary to explain the high H2 yield. We therefore tracked (13)C-labeled acetate through central metabolic pathways. We found that non-growing cells shifted their metabolism to use the tricarboxylic acid cycle to metabolize acetate in contrast to growing cells, which used the glyoxylate cycle exclusively. This shift enabled cells to more fully oxidize acetate, providing the necessary reducing power to explain the high H2 yield.

Bioengineered Chinese hamster ovary cells with Golgi-targeted 3-O-sulfotransferase-1 biosynthesize heparan sulfate with an antithrombin-binding site

HS3st1 (heparan sulfate 3-O-sulfotransferase isoform-1) is a critical enzyme involved in the biosynthesis of the antithrombin III (AT)-binding site in the biopharmaceutical drug heparin. Heparin is a highly sulfated glycosaminoglycan that shares a common biosynthetic pathway with heparan sulfate (HS). Although only granulated cells, such as mast cells, biosynthesize heparin, all animal cells are capable of biosynthesizing HS. As part of an effort to bioengineer CHO cells to produce heparin, we previously showed that the introduction of both HS3st1 and NDST2 (N-deacetylase/N-sulfotransferase isoform-2) afforded HS with a very low level of anticoagulant activity. This study demonstrated that untargeted HS3st1 is broadly distributed throughout CHO cells and forms no detectable AT-binding sites, whereas Golgi-targeted HS3st1 localizes in the Golgi and results in the formation of a single type of AT-binding site and high anti-factor Xa activity (137 ± 36 units/mg). Moreover, stable overexpression of HS3st1 also results in up-regulation of 2-O-, 6-O-, and N-sulfo group-containing disaccharides, further emphasizing a previously unknown concerted interplay between the HS biosynthetic enzymes and suggesting the need to control the expression level of all of the biosynthetic enzymes to produce heparin in CHO cells.

Identification of a bifunctional maize C- and O-glucosyltransferase

Flavonoids accumulate in plant vacuoles usually as O-glycosylated derivatives, but several species can also synthesize flavonoid C-glycosides. Recently, we demonstrated that a flavanone 2-hydroxylase (ZmF2H1, CYP93G5) converts flavanones to the corresponding 2-hydroxy derivatives, which are expected to serve as substrates for C-glycosylation. Here, we isolated a cDNA encoding a UDP-dependent glycosyltransferase (UGT708A6), and its activity was characterized by in vitro and in vivo bioconversion assays. In vitro assays using 2-hydroxyflavanones as substrates and in vivo activity assays in yeast co-expressing ZmF2H1 and UGT708A6 show the formation of the flavones C-glycosides. UGT708A6 can also O-glycosylate flavanones in bioconversion assays in Escherichia coli as well as by in vitro assays with the purified recombinant protein. Thus, UGT708A6 is a bifunctional glycosyltransferase that can produce both C- and O-glycosidated flavonoids, a property not previously described for any other glycosyltransferase.

Publishing 13C metabolic flux analysis studies: a review and future perspectives

(13)C-Metabolic flux analysis ((13)C-MFA) is a powerful model-based analysis technique for determining intracellular metabolic fluxes in living cells. It has become a standard tool in many labs for quantifying cell physiology, e.g., in metabolic engineering, systems biology, biotechnology, and biomedical research. With the increasing number of (13)C-MFA studies published each year, it is now ever more important to provide practical guidelines for performing and publishing (13)C-MFA studies so that quality is not sacrificed as the number of publications increases. The main purpose of this paper is to provide an overview of good practices in (13)C-MFA, which can eventually be used as minimum data standards for publishing (13)C-MFA studies. The motivation for this work is two-fold: (1) currently, there is no general consensus among researchers and journal editors as to what minimum data standards should be required for publishing (13)C-MFA studies; as a result, there are great discrepancies in terms of quality and consistency; and (2) there is a growing number of studies that cannot be reproduced or verified independently due to incomplete information provided in these publications. This creates confusion, e.g. when trying to reconcile conflicting results, and hinders progress in the field. Here, we review current status in the (13)C-MFA field and highlight some of the shortcomings with regards to (13)C-MFA publications. We then propose a checklist that encompasses good practices in (13)C-MFA. We hope that these guidelines will be a valuable resource for the community and allow (13)C-flux studies to be more easily reproduced and accessed by others in the future.

Kinetic isotope effects significantly influence intracellular metabolite (13) C labeling patterns and flux determination

Rigorous mathematical modeling of carbon-labeling experiments allows estimation of fluxes through the pathways of central carbon metabolism, yielding powerful information for basic scientific studies as well as for a wide range of applications. However, the mathematical models that have been developed for flux determination from (13) C labeling data have commonly neglected the influence of kinetic isotope effects on the distribution of (13) C label in intracellular metabolites, as these effects have often been assumed to be inconsequential. We have used measurements of the (13) C isotope effects on the pyruvate dehydrogenase enzyme from the literature to model isotopic fractionation at the pyruvate node and quantify the modeling errors expected to result from the assumption that isotope effects are negligible. We show that under some conditions kinetic isotope effects have a significant impact on the (13) C labeling patterns of intracellular metabolites, and the errors associated with neglecting isotope effects in (13) C-metabolic flux analysis models can be comparable in size to measurement errors associated with GC-MS. Thus, kinetic isotope effects must be considered in any rigorous assessment of errors in (13) C labeling data, goodness-of-fit between model and data, confidence intervals of estimated metabolic fluxes, and statistical significance of differences between estimated metabolic flux distributions.

Identification of a pair of phospholipid:diacylglycerol acyltransferases from developing flax (Linum usitatissimum L.) seed catalyzing the selective production of trilinolenin

The oil from flax (Linum usitatissimum L.) has high amounts of α-linolenic acid (ALA; 18:3(cis)(Δ9,12,15)) and is one of the richest sources of omega-3 polyunsaturated fatty acids (ω-3-PUFAs). To produce ∼57% ALA in triacylglycerol (TAG), it is likely that flax contains enzymes that can efficiently transfer ALA to TAG. To test this hypothesis, we conducted a systematic characterization of TAG-synthesizing enzymes from flax. We identified several genes encoding acyl-CoA:diacylglycerol acyltransferases (DGATs) and phospholipid:diacylglycerol acyltransferases (PDATs) from the flax genome database. Due to recent genome duplication, duplicated gene pairs have been identified for all genes except DGAT2-2. Analysis of gene expression indicated that two DGAT1, two DGAT2, and four PDAT genes were preferentially expressed in flax embryos. Yeast functional analysis showed that DGAT1, DGAT2, and two PDAT enzymes restored TAG synthesis when produced recombinantly in yeast H1246 strain. The activity of particular PDAT enzymes (LuPDAT1 and LuPDAT2) was stimulated by the presence of ALA. Further seed-specific expression of flax genes in Arabidopsis thaliana indicated that DGAT1, PDAT1, and PDAT2 had significant effects on seed oil phenotype. Overall, this study indicated the existence of unique PDAT enzymes from flax that are able to preferentially catalyze the synthesis of TAG containing ALA acyl moieties. The identified LuPDATs may have practical applications for increasing the accumulation of ALA and other polyunsaturated fatty acids in oilseeds for food and industrial applications.