Mapping photoautotrophic metabolism with isotopically nonstationary (13)C flux analysis

A quantitative description of light-limited cyanobacterial growth using flux balance analysis

The metabolism of phototrophic cyanobacteria is an integral part of global biogeochemical cycles, and the capability of cyanobacteria to assimilate atmospheric CO2 into organic carbon has manifold potential applications for a sustainable biotechnology. To elucidate the properties of cyanobacterial metabolism and growth, computational reconstructions of genome-scale metabolic networks play an increasingly important role. Here, we present an updated reconstruction of the metabolic network of the cyanobacterium Synechocystis sp. PCC 6803 and its quantitative evaluation using flux balance analysis (FBA). To overcome limitations of conventional FBA, and to allow for the integration of experimental analyses, we develop a novel approach to describe light absorption and light utilization within the framework of FBA. Our approach incorporates photoinhibition and a variable quantum yield into the constraint-based description of light-limited phototrophic growth. We show that the resulting model is capable of predicting quantitative properties of cyanobacterial growth, including photosynthetic oxygen evolution and the ATP/NADPH ratio required for growth and cellular maintenance. Our approach retains the computational and conceptual simplicity of FBA and is readily applicable to other phototrophic microorganisms.

Glycosyltransferase Slr1064 regulates carbon metabolism by modulating the levels of UDP-GlcNAc in Synechocystis sp. PCC 6803

Glycosyltransferases (GTs) are enzymes that transfer sugars to various targets. They play important roles in diverse biological processes, including photosynthesis, cell motility, exopolysaccharide biosynthesis, and lipid metabolism; however, their involvement in regulating carbon metabolism in Synechocystis sp. PCC 6803 has not been reported. We identified a novel GT protein, Slr1064, involved in carbon metabolism. The effect of slr1064 deletion on the growth of Synechocystis cells and functional mechanisms of Slr1064 on carbon metabolism were thoroughly investigated through physiological, biochemistry, proteomic, and metabolic analyses. We found that this GT, which is mainly distributed in the membrane compartment, is essential for the growth of Synechocystis under heterotrophic and mixotrophic conditions, but not under autotrophic conditions. The deletion of slr1064 hampers the turnover rate of Gap2 under mixotrophic conditions and disrupts the assembly of the PRK/GAPDH/CP12 complex under dark culture conditions. Additionally, UDP-GlcNAc, the pivotal metabolite responsible for the O-GlcNAc modification of GAPDH, is downregulated in the Δslr1064. Our work provides new insights into the role of GTs in carbon metabolism in Synechocystis and elucidate the mechanism by which carbon metabolism is regulated in this important model organism.

The primary carbon metabolism in cyanobacteria and its regulation

Cyanobacteria are the only prokaryotes capable of performing oxygenic photosynthesis. Many cyanobacterial strains can live in different trophic modes, ranging from photoautotrophic and heterotrophic to mixotrophic growth. However, the regulatory mechanisms allowing a flexible switch between these lifestyles are poorly understood. As anabolic fixation of CO2 in the Calvin-Benson-Bassham (CBB) cycle and catabolic sugar-degradation pathways share intermediates and enzymatic capacity, a tight regulatory network is required to enable simultaneous opposed metabolic fluxes. The Entner-Doudoroff (ED) pathway was recently predicted as one glycolytic route, which cooperates with other pathways in glycogen breakdown. Despite low carbon flux through the ED pathway, metabolite analyses of mutants deficient in the ED pathway revealed a distinct phenotype pointing at a strong regulatory impact of this route. The small Cp12 protein downregulates the CBB cycle in darkness by inhibiting phosphoribulokinase and glyceraldehyde 3-phosphate dehydrogenase. New results of metabolomic and redox level analyses on strains with Cp12 variants extend the known role of Cp12 regulation towards the acclimation to external glucose supply under diurnal conditions as well as to fluctuations in CO2 levels in the light. Moreover, carbon and nitrogen metabolism are closely linked to maintain an essential C/N homeostasis. The small protein PirC was shown to be an important regulator of phosphoglycerate mutase, which identified this enzyme as central branching point for carbon allocation from CBB cycle towards lower glycolysis. Altered metabolite levels in the mutant ΔpirC during nitrogen starvation experiments confirm this regulatory mechanism. The elucidation of novel mechanisms regulating carbon allocation at crucial metabolic branching points could identify ways for targeted redirection of carbon flow towards desired compounds, and thus help to further establish cyanobacteria as green cell factories for biotechnological applications with concurrent utilization of sunlight and CO2.

Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light

Carbon capture and biochemical storage are some of the primary drivers of photosynthetic yield and productivity. To elucidate the mechanisms governing carbon allocation, we designed a photosynthetic light response test system for genetic and metabolic carbon assimilation tracking, using microalgae as simplified plant models. The systems biology mapping of high light-responsive photophysiology and carbon utilization dynamics between two variants of the same Picochlorum celeri species, TG1 and TG2 elucidated metabolic bottlenecks and transport rates of intermediates using instationary 13C-fluxomics. Simultaneous global gene expression dynamics showed 73% of the annotated genes responding within one hour, elucidating a singular, diel-responsive transcription factor, closely related to the CCA1/LHY clock genes in plants, with significantly altered expression in TG2. Transgenic P. celeri TG1 cells expressing the TG2 CCA1/LHY gene, showed 15% increase in growth rates and 25% increase in storage carbohydrate content, supporting a coordinating regulatory function for a single transcription factor.

Pyruvate kinase 2 from Synechocystis sp. PCC 6803 increased substrate affinity via glucose-6-phosphate and ribose-5-phosphate for phosphoenolpyruvate consumption

Pyruvate kinase (Pyk, EC 2.7.1.40) is a glycolytic enzyme that generates pyruvate and adenosine triphosphate (ATP) from phosphoenolpyruvate (PEP) and adenosine diphosphate (ADP), respectively. Pyk couples pyruvate and tricarboxylic acid metabolisms. Synechocystis sp. PCC 6803 possesses two pyk genes (encoded pyk1, sll0587 and pyk2, sll1275). A previous study suggested that pyk2 and not pyk1 is essential for cell viability; however, its biochemical analysis is yet to be performed. Herein, we biochemically analyzed Synechocystis Pyk2 (hereafter, SyPyk2). The optimum pH and temperature of SyPyk2 were 7.0 and 55 °C, respectively, and the Km values for PEP and ADP under optimal conditions were 1.5 and 0.053 mM, respectively. SyPyk2 is activated in the presence of glucose-6-phosphate (G6P) and ribose-5-phosphate (R5P); however, it remains unaltered in the presence of adenosine monophosphate (AMP) or fructose-1,6-bisphosphate. These results indicate that SyPyk2 is classified as PykA type rather than PykF, stimulated by sugar monophosphates, such as G6P and R5P, but not by AMP. SyPyk2, considering substrate affinity and effectors, can play pivotal roles in sugar catabolism under nonphotosynthetic conditions.

A Ribulose-5-phosphate Shunt from the Calvin-Benson Cycle to Methylerythritol Phosphate Pathway for Enhancing Photosynthetic Terpenoid Production

Cyanobacteria are attractive hosts for photosynthetic terpenoid production, using CO2 as the sole carbon source. Although the methylerythritol phosphate (MEP) pathway is superior to the mevalonate pathway for cyanobacterial terpenoid synthesis, the first reaction of the MEP pathway, which is catalyzed by 1-deoxy-d-xylulose-5-phosphate (DXP) synthase, involves complex regulation and carbon loss. Here, we constructed a direct route linking ribulose-5-phosphate (Ru5P) in the Calvin-Benson (CB) cycle with DXP in the MEP pathway in a cyanobacterium to increase the terpenoid yield from CO2 and bypass the DXS-targeted regulations. By employing the adaptive laboratory evolution, we identified new RibB variants including RibB 90-92del with a high activity of synthesizing DXP from Ru5P. These RibB variants were introduced into Synechococcus elongatus, resulting in the significantly increased photosynthetic production of isopentenol. The 13C tracer experiments demonstrated a direct carbon flow from Ru5P in the CB cycle to the MEP pathway; thus, this direct route was denoted as the Ru5P shunt. The strain harboring the Ru5P shunt produced 105.2 mg L-1 of isopentenol with an average rate of 17.5 mg L-1 d-1 under continuous light conditions, which is higher than those ever reported for five-carbon alcohol production by photoautotrophic microorganisms. Utilization of the Ru5P shunt in cyanobacterial cells also improved the pinene production, which demonstrates that this shunt can be used to enhance the photosynthetic production of diverse terpenoids.

The Calvin Benson cycle in bacteria: New insights from systems biology

The Calvin Benson cycle in phototrophic and chemolithoautotrophic bacteria has ecological and biotechnological importance, which has motivated study of its regulation. I review recent advances in our understanding of how the Calvin Benson cycle is regulated in bacteria and the technologies used to elucidate regulation and modify it, and highlight differences between and photoautotrophic and chemolithoautotrophic models. Systems biology studies have shown that in oxygenic phototrophic bacteria, Calvin Benson cycle enzymes are extensively regulated at post-transcriptional and post-translational levels, with multiple enzyme activities connected to cellular redox status through thioredoxin. In chemolithoautotrophic bacteria, regulation is primarily at the transcriptional level, with effector metabolites transducing cell status, though new methods should now allow facile, proteome-wide exploration of biochemical regulation in these models. A biotechnological objective is to enhance CO2 fixation in the cycle and partition that carbon to a product of interest. Flux control of CO2 fixation is distributed over multiple enzymes, and attempts to modulate gene Calvin cycle gene expression show a robust homeostatic regulation of growth rate, though the synthesis rates of products can be significantly increased. Therefore, de-regulation of cycle enzymes through protein engineering may be necessary to increase fluxes. Non-canonical Calvin Benson cycles, if implemented with synthetic biology, could have reduced energy demand and enzyme loading, thus increasing the attractiveness of these bacteria for industrial applications.

Effects of n-butanol production on metabolism and the photosystem in Synecococcus elongatus PCC 7942 based on metabolic flux and target proteome analyses

Although n-butanol (BuOH) is an ideal fuel because of its superior physical properties, it has toxicity to microbes. Previously, a Synechococcus elongatus PCC 7942 derivative strain that produces BuOH from CO2 was developed by introducing six heterologous genes (BUOH-SE strain). To identify the bottleneck in BuOH production, the effects of BuOH production and its toxicity on central metabolism and the photosystem were investigated. Parental (WT) and BUOH-SE strains were cultured under autotrophic conditions. Consistent with the results of a previous study, BuOH production was observed only in the BUOH-SE strain. Isotopically non-stationary 13C-metabolic flux analysis revealed that the CO2 fixation rate was much larger than the BuOH production rate in the BUOH-SE strain (1.70 vs 0.03 mmol gDCW-1 h-1), implying that the carbon flow for BuOH biosynthesis was less affected by the entire flux distribution. No large difference was observed in the flux of metabolism between the WT and BUOH-SE strains. Contrastingly, in the photosystem, the chlorophyll content and maximum O2 evolution rate per dry cell weight of the BUOH-SE strain were decreased to 81% and 43% of the WT strain, respectively. Target proteome analysis revealed that the amounts of some proteins related to antennae (ApcA, ApcD, ApcE, and CpcC), photosystem II (PsbB, PsbU, and Psb28-2), and cytochrome b6f complex (PetB and PetC) in photosystems decreased in the BUOH-SE strain. The activation of photosynthesis would be a novel approach for further enhancing BuOH production in S. elongatus PCC 7942.

Daylength variation affects growth, photosynthesis, leaf metabolism, partitioning, and metabolic fluxes

Daylength, a seasonal and latitudinal variable, exerts a substantial impact on plant growth. However, the relationship between daylength and growth is nonproportional, suggesting the existence of adaptive mechanisms. Thus, our study aimed to comprehensively investigate the adaptive strategies employed by plants in response to daylength variation. We grew false flax (Camelina sativa) plants, a model oilseed crop, under long-day (LD) and short-day (SD) conditions and used growth measurements, gas exchange measurements, and isotopic labeling techniques, including 13C, 14C, and 2H2O, to determine responses to different daylengths. Our findings revealed that daylength influences various growth parameters, photosynthetic physiology, carbon partitioning, metabolic fluxes, and metabolite levels. SD plants employed diverse mechanisms to compensate for reduced CO2 fixation in the shorter photoperiod. These mechanisms included enhanced photosynthetic rates and reduced respiration in the light (RL), leading to increased shoot investment. Additionally, SD plants exhibited reduced rates of the glucose 6-phosphate (G6P) shunt and greater partitioning of sugars into starch, thereby sustaining carbon availability during the longer night. Isotopic labeling results further demonstrated substantial alterations in the partitioning of amino acids and TCA cycle intermediates between rapidly and slowly turning over pools. Overall, the results point to multiple developmental, physiological, and metabolic ways in which plants adapt to different daylengths to maintain growth.

Metabolic engineering of Synechococcus elongatus 7942 for enhanced sucrose biosynthesis

The capability of cyanobacteria to produce sucrose from CO2 and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain. We used targeted metabolomics, 13C metabolic flux analysis (MFA), and genome-scale modeling (GSM) as complementary approaches to elucidate differences in cellular resource allocation by quantifying metabolic profiles of three cyanobacterial cultures - wild-type S. elongatus 7942 without salt stress (WT), wild-type with salt stress (WT/NaCl), and the cscB-overexpressing strain with salt stress (cscB/NaCl) - all under photoautotrophic conditions. We quantified the substantial rewiring of metabolic fluxes in WT/NaCl and cscB/NaCl cultures relative to WT and identified a metabolic bottleneck limiting carbon fixation and sucrose biosynthesis. This bottleneck was subsequently mitigated through heterologous overexpression of glyceraldehyde-3-phosphate dehydrogenase in an engineered sucrose-secreting strain. Our study also demonstrates that combining 13C-MFA and GSM is a useful strategy to both extend the coverage of MFA beyond central metabolism and to improve the accuracy of flux predictions provided by GSM.

Isotopically non-stationary 13 C metabolic flux analysis of two closely related fast-growing cyanobacteria, Synechococcus elongatus PCC 11801 and 11802

Synechococcus elongatus PCC 11801 and 11802 are closely related cyanobacterial strains that are fast-growing and tolerant to high light and temperature. These strains hold significant promise as chassis for photosynthetic production of chemicals from carbon dioxide. A detailed quantitative understanding of the central carbon pathways would be a reference for future metabolic engineering studies with these strains. We conducted isotopic non-stationary 13 C metabolic flux analysis to quantitively assess the metabolic potential of these two strains. This study highlights key similarities and differences in the central carbon flux distribution between these and other model/non-model strains. The two strains demonstrated a higher Calvin-Benson-Bassham (CBB) cycle flux coupled with negligible flux through the oxidative pentose phosphate pathway and the photorespiratory pathway and lower anaplerosis fluxes under photoautotrophic conditions. Interestingly, PCC 11802 shows the highest CBB cycle and pyruvate kinase flux values among those reported in cyanobacteria. The unique tricarboxylic acid (TCA) cycle diversion in PCC 11801 makes it ideal for the large-scale production of TCA cycle-derived chemicals. Additionally, dynamic labeling transients were measured for intermediates of amino acid, nucleotide, and nucleotide sugar metabolism. Overall, this study provides the first detailed metabolic flux maps of S. elongatus PCC 11801 and 11802, which may aid metabolic engineering efforts in these strains.

Optimal energy and redox metabolism in the cyanobacterium Synechocystis sp. PCC 6803

Understanding energy and redox homeostasis and carbon partitioning is crucial for systems metabolic engineering of cell factories. Carbon metabolism alone cannot achieve maximal accumulation of metabolites in production hosts, since an efficient production of target molecules requires energy and redox balance, in addition to carbon flow. The interplay between cofactor regeneration and heterologous production in photosynthetic microorganisms is not fully explored. To investigate the optimality of energy and redox metabolism, while overproducing alkenes-isobutene, isoprene, ethylene and 1-undecene, in the cyanobacterium Synechocystis sp. PCC 6803, we applied stoichiometric metabolic modelling. Our network-wide analysis indicates that the rate of NAD(P)H regeneration, rather than of ATP, controls ATP/NADPH ratio, and thereby bioproduction. The simulation also implies that energy and redox balance is interconnected with carbon and nitrogen metabolism. Furthermore, we show that an auxiliary pathway, composed of serine, one-carbon and glycine metabolism, supports cellular redox homeostasis and ATP cycling. The study revealed non-intuitive metabolic pathways required to enhance alkene production, which are mainly driven by a few key reactions carrying a high flux. We envision that the presented comparative in-silico metabolic analysis will guide the rational design of Synechocystis as a photobiological production platform of target chemicals.

FreeFlux: A Python Package for Time-Efficient Isotopically Nonstationary Metabolic Flux Analysis

13C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accepted 13C-flux tools, such as INCA and 13CFLUX2, are developed in a closed-source environment. While several open-source packages or software are available, they are either computationally inefficient or only suitable for flux estimation at isotopic steady state. To address the need for a time-efficient computational tool for the more complicated flux analysis at an isotopically nonstationary state, especially for understanding the single-carbon substrate metabolism, we present FreeFlux. FreeFlux is an open-source Python package that performs labeling pattern simulation and flux analysis at both isotopic steady state and transient state, enabling a more comprehensive analysis of cellular metabolism. FreeFlux provides a set of interfaces to manipulate the objects abstracted from a labeling experiment and computational process, making it easy to integrate into other programs or pipelines. The flux estimation by FreeFlux is fast and reliable, and its validity has been confirmed by comparison with results from other computational tools using both synthetic and experimental data. FreeFlux is freely available at https://github.com/Chaowu88/freeflux with a detailed online tutorial and documentation provided at https://freeflux.readthedocs.io/en/latest/index.html.

Rewiring carbon flow in Synechocystis PCC 6803 for a high rate of CO2-to-ethanol under an atmospheric environment

Cyanobacteria are an excellent microbial photosynthetic platform for sustainable carbon dioxide fixation. One bottleneck to limit its application is that the natural carbon flow pathway almost transfers CO₂ to glycogen/biomass other than designed biofuels such as ethanol. Here, we used engineered Synechocystis sp. PCC 6803 to explore CO₂-to-ethanol potential under atmospheric environment. First, we investigated the effects of two heterologous genes (pyruvate decarboxylase and alcohol dehydrogenase) on ethanol biosynthesis and optimized their promoter. Furthermore, the main carbon flow of the ethanol pathway was strengthened by blocking glycogen storage and pyruvate-to-phosphoenolpyruvate backflow. To recycle carbon atoms that escaped from the tricarboxylic acid cycle, malate was artificially guided back into pyruvate, which also created NADPH balance and promoted acetaldehyde conversion into ethanol. Impressively, we achieved high-rate ethanol production (248 mg/L/day at early 4 days) by fixing atmospheric CO₂. Thus, this study exhibits the proof-of-concept that rewiring carbon flow strategies could provide an efficient cyanobacterial platform for sustainable biofuel production from atmospheric CO₂.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Dark accumulation of downstream glycolytic intermediates initiates robust photosynthesis in cyanobacteria

Photosynthesis must maintain stability and robustness throughout fluctuating natural environments. In cyanobacteria, dark-to-light transition leads to drastic metabolic changes from dark respiratory metabolism to CO2 fixation through the Calvin-Benson-Bassham (CBB) cycle using energy and redox equivalents provided by photosynthetic electron transfer. Previous studies have shown that catabolic metabolism supports the smooth transition into CBB cycle metabolism. However, metabolic mechanisms for robust initiation of photosynthesis are poorly understood due to lack of dynamic metabolic characterizations of dark-to-light transitions. Here, we show rapid dynamic changes (on a time scale of seconds) in absolute metabolite concentrations and 13C tracer incorporation after strong or weak light irradiation in the cyanobacterium Synechocystis sp. PCC 6803. Integration of this data enabled estimation of time-resolved nonstationary metabolic flux underlying CBB cycle activation. This dynamic metabolic analysis indicated that downstream glycolytic intermediates, including phosphoglycerate and phosphoenolpyruvate, accumulate under dark conditions as major substrates for initial CO2 fixation. Compared with wild-type Synechocystis, significant decreases in the initial oxygen evolution rate were observed in 12 h dark preincubated mutants deficient in glycogen degradation or oxidative pentose phosphate pathways. Accordingly, the degree of decrease in the initial oxygen evolution rate was proportional to the accumulated pool size of glycolytic intermediates. These observations indicate that the accumulation of glycolytic intermediates is essential for efficient metabolism switching under fluctuating light environments.

Chlamydomonas mutants lacking chloroplast TRIOSE PHOSPHATE TRANSPORTER3 are metabolically compromised and light-sensitive

Modulation of photoassimilate export from the chloroplast is essential for controlling the distribution of fixed carbon in the cell and maintaining optimum photosynthetic rates. In this study we identified chloroplast TRIOSE PHOSPHATE/PHOSPHATE TRANSLOCATOR2 (CreTPT2) and CreTPT3 in the green alga Chlamydomonas (Chlamydomonas reinhardtii), which exhibit similar substrate specificities but whose encoding genes are differentially expressed over the diurnal cycle. We focused mostly on CreTPT3 because of its high level of expression and the severe phenotype exhibited by tpt3 relative to tpt2 mutants. Null mutants for CreTPT3 had a pleiotropic phenotype that affected growth, photosynthetic activities, metabolite profiles, carbon partitioning, and organelle-specific accumulation of H2O2. These analyses demonstrated that CreTPT3 is a dominant conduit on the chloroplast envelope for the transport of photoassimilates. In addition, CreTPT3 can serve as a safety valve that moves excess reductant out of the chloroplast and appears to be essential for preventing cells from experiencing oxidative stress and accumulating reactive oxygen species, even under low/moderate light intensities. Finally, our studies indicate subfunctionalization of the CreTPT transporters and suggest that there are differences in managing the export of photoassimilates from the chloroplasts of Chlamydomonas and vascular plants.

Integrated Proteomic and Metabolomic Analyses Show Differential Effects of Glucose Availability in Marine Synechococcus and Prochlorococcus

We compared changes induced by the addition of 100 nM and 5 mM glucose on the proteome and metabolome complements in Synechococcus sp. strains WH8102, WH7803, and BL107 and Prochlorococcus sp. strains MED4, SS120, and MIT9313, grown either under standard light conditions or in darkness. Our results suggested that glucose is metabolized by these cyanobacteria, using primarily the oxidative pentoses and Calvin pathways, while no proof was found for the involvement of the Entner-Doudoroff pathway in this process. We observed differences in the effects of glucose availability, both between genera and between Prochlorococcus MED4 and SS120 strains, which might be related to their specific adaptations to the environment. We found evidence for fermentation in Prochlorococcus sp. strain SS120 and Synechococcus sp. strain WH8102 after 5 mM glucose addition. Our results additionally suggested that marine cyanobacteria can detect nanomolar glucose concentrations in the environment and that glucose might be used to sustain metabolism under darkness. Furthermore, the KaiB and KaiC proteins were also affected in Synechococcus sp. WH8102, pointing to a direct link between glucose assimilation and circadian rhythms in marine cyanobacteria. In conclusion, our study provides a wide overview on the metabolic effects induced by glucose availability in representative strains of the diverse marine picocyanobacteria, providing further evidence for the importance of mixotrophy in marine picocyanobacteria. IMPORTANCE Glucose uptake by marine picocyanobacteria has been previously described and strongly suggests they are mixotrophic organisms (capable of using energy from the sun to make organic matter, but also to directly use organic matter from the environment when available). However, a detailed analysis of the effects of glucose addition on the proteome and metabolome of these microorganisms had not been carried out. Here, we analyzed three Prochlorococcus sp. and three Synechococcus sp. strains which were representative of several marine picocyanobacterial clades. We observed differential features in the effects of glucose availability, depending on both the genus and strain; our study illuminated the strategies utilized by these organisms to metabolize glucose and showed unexpected links to other pathways, such as circadian regulation. Furthermore, we found glucose addition had profound effects in the microbiome, favoring the growth of coexisting heterotrophic bacteria.

Isotopically non-stationary metabolic flux analysis of heterotrophic Arabidopsis thaliana cell cultures

Fluxes are the ultimate phenotype of metabolism and their accurate quantification is fundamental to any understanding of metabolic networks. Steady state metabolic flux analysis has been the method of choice for quantifying fluxes in heterotrophic cells, but it is unable to measure fluxes during short-lived metabolic states, such as a transient oxidative load. Isotopically non-stationary metabolic flux analysis (INST-MFA) can be performed over shorter timescales (minutes - hours) and might overcome this limitation. INST-MFA has recently been applied to photosynthesising leaves, but agriculturally important tissues such as roots and storage organs, or plants during the night are heterotrophic. Here we outline the application of INST-MFA to heterotrophic plant cells. Using INST-MFA we were able to identify changes in the fluxes supported by phosphoenolpyruvate carboxylase and malic enzyme under oxidative load, highlighting the potential of INST-MFA to measure fluxes during short-lived metabolic states. We discuss the challenges in applying INST-MFA, and highlight further development required before it can be routinely used to quantify fluxes in heterotrophic plant cells.

Metabolic Engineering Design Strategies for Increasing Carbon Fluxes Relevant for Biosynthesis in Cyanobacteria

Cyanobacteria are promising microbial cell factories for the direct production of biochemicals and biofuels from CO2. Through genetic and metabolic engineering, they can be modified to produce a variety of both natural and non-natural compounds. To enhance the yield of these products, various design strategies have been developed. In this chapter, strategies used to enhance metabolic fluxes towards common precursors used in biosynthesis, including pyruvate, acetyl-CoA, malonyl-CoA, TCA cycle intermediates, and aromatics, are discussed. Additionally, strategies related to cofactor availability and mixotrophic conditions for bioproduction are also summarize.

Millet-inspired systems metabolic engineering of NUE in crops

The use of nitrogen (N) fertilizers in agriculture has a great ability to increase crop productivity. However, their excessive use has detrimental effects on the environment. Therefore, it is necessary to develop crop varieties with improved nitrogen use efficiency (NUE) that require less N but have substantial yields. Orphan crops such as millets are cultivated in limited regions and are well adapted to lower input conditions. Therefore, they serve as a rich source of beneficial traits that can be transferred into major crops to improve their NUE. This review highlights the tremendous potential of systems biology to unravel the enzymes and pathways involved in the N metabolism of millets, which can open new possibilities to generate transgenic crops with improved NUE.

Quantitative insight into the metabolism of isoprene-producing Synechocystis sp. PCC 6803 using steady state 13C-MFA

Cyanobacteria are photosynthetic bacteria, widely studied for the conversion of atmospheric carbon dioxide to useful platform chemicals. Isoprene is one such industrially important chemical, primarily used for production of synthetic rubber and biofuels. Synechocystis sp. PCC 6803, a genetically amenable cyanobacterium, produces isoprene on heterologous expression of isoprene synthase gene, albeit in very low quantities. Rationalized metabolic engineering to re-route the carbon flux for enhanced isoprene production requires in-dept knowledge of the metabolic flux distribution in the cell. Hence, in the present study, we undertook steady state ¹³C-metabolic flux analysis of glucose-tolerant wild-type (GTN) and isoprene-producing recombinant (ISP) Synechocystis sp. to understand and compare the carbon flux distribution in the two strains. The R-values for amino acids, flux analysis predictions and gene expression profiles emphasized predominance of Calvin cycle and glycogen metabolism in GTN. Alternatively, flux analysis predicted higher activity of the anaplerotic pathway through phosphoenolpyruvate carboxylase and malic enzyme in ISP. The striking difference in the Calvin cycle, glycogen metabolism and anaplerotic pathway activity in GTN and ISP suggested a possible role of energy molecules (ATP and NADPH) in regulating the carbon flux distribution in GTN and ISP. This claim was further supported by the transcript level of selected genes of the electron transport chain. This study provides the first quantitative insight into the carbon flux distribution of isoprene-producing cyanobacterium, information critical for developing Synechocystis sp. as a single cell factory for isoprenoid/terpenoid production.

On the rate of phytoplankton respiration in the light

The rate of algal and cyanobacterial respiration in the light is an important ecophysiological term that remains to be completely characterized and quantified. To address this issue, we exploited process-specific decarboxylation rates from flux balance analysis and isotopically nonstationary metabolic flux analysis. Our study, based on published data, suggested that decarboxylation is about 22% of net CO2 assimilation when the tricarboxylic acid cycle is completely open (characterized by the commitment of alpha ketoglutarate to amino acid synthesis and very low rates of succinate formation). This estimate was supported by calculating the decarboxylation rates required to synthesize the major components of biomass (proteins, lipids, and carbohydrates) at their typical abundance. Of the 22 CO2 molecules produced by decarboxylation (normalized to net assimilation = 100), approximately 13 were from pyruvate and 3 were from isocitrate. The remaining six units of decarboxylation were in the amino acid synthesis pathways outside the tricarboxylic acid cycle. A small additional flux came from photorespiration, decarboxylations of six phosphogluconate in the oxidative pentose phosphate pathway, and decarboxylations in the syntheses of lower-abundance compounds, including pigments and ribonucleic acids. This general approach accounted for the high decarboxylation rates in algae and cyanobacteria compared to terrestrial plants. It prompts a simple speculation for the origin of the Kok effect and helps constrain the photoautotrophic respiration rate, in the light, in the euphotic zone of the ocean and lakes.

13C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple ¹³C-labeled compounds, including ¹³C-bicarbonate, ¹³C-glucose, and ¹³C-glutamine, were used as tracers during the sample collection and the cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (-80 °C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (-24 °C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (∼0 °C) is less effective, as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (-65 °C) prior to centrifugation causes significant metabolite loss. This study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

Quantitative metabolic fluxes regulated by trans-omic networks

Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.

Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness

Stable isotope-assisted metabolic flux analysis (MFA) is a powerful method to estimate carbon flow and partitioning in metabolic networks. At its core, MFA is a parameter estimation problem wherein the fluxes and metabolite pool sizes are model parameters that are estimated, via optimization, to account for measurements of steady-state or isotopically-nonstationary isotope labeling patterns. As MFA problems advance in scale, they require efficient computational methods for fast and robust convergence. The structure of the MFA problem enables it to be cast as an equality-constrained nonlinear program (NLP), where the equality constraints are constructed from the MFA model equations, and the objective function is defined as the sum of squared residuals (SSR) between the model predictions and a set of labeling measurements. This NLP can be solved by using an algebraic modeling language (AML) that offers state-of-the-art optimization solvers for robust parameter estimation and superior scalability to large networks. When implemented in this manner, the optimization is performed with no distinction between state variables and model parameters. During each iteration of such an optimization, the system state is updated instead of being calculated explicitly from scratch, and this occurs concurrently with improvement in the model parameter estimates. This optimization approach starkly contrasts with traditional “shooting” methods where the state variables and model parameters are kept distinct and the system state is computed afresh during each iteration of a stepwise optimization. Our NLP formulation uses the MFA modeling framework of Wiechert et al. [1], which is amenable to incorporation of the model equations into an NLP. The NLP constraints consist of balances on either elementary metabolite units (EMUs) or cumomers. In this formulation, both the steady-state and isotopically-nonstationary MFA (inst-MFA) problems may be solved as an NLP. For the inst-MFA case, the ordinary differential equation (ODE) system describing the labeling dynamics is transcribed into a system of algebraic constraints for the NLP using collocation. This large-scale NLP may be solved efficiently using an NLP solver implemented on an AML. In our implementation, we used the reduced gradient solver CONOPT, implemented in the General Algebraic Modeling System (GAMS). The NLP framework is particularly advantageous for inst-MFA, scaling well to large networks with many free parameters, and having more robust convergence properties compared to the shooting methods that compute the system state and sensitivities at each iteration. Additionally, this NLP approach supports the use of tandem-MS data for both steady-state and inst-MFA when the cumomer framework is used. We assembled a software, eiFlux, written in Python and GAMS that uses the NLP approach and supports both steady-state and inst-MFA. We demonstrate the effectiveness of the NLP formulation on several examples, including a genome-scale inst-MFA model, to highlight the scalability and robustness of this approach. In addition to typical inst-MFA applications, we expect that this framework and our associated software, eiFlux, will be particularly useful for applying inst-MFA to complex MFA models, such as those developed for eukaryotes (e.g. algae) and co-cultures with multiple cell types.

Isotope-assisted metabolic flux analysis (MFA) is a computationally intensive parameter estimation problem. Isotopically nonstationary MFA (inst-MFA) represents the most computationally burdensome MFA application. We present the formulation of the steady-state and inst-MFA problems as equality-constrained nonlinear programs (NLPs), solved by a state-of-the-art solver implemented in an algebraic modeling language. We show that this formulation leads to robust convergence properties compared to traditional approaches, particularly for inst-MFA. We developed a software, eiFlux that uses the NLP formulation to perform both steady-state and inst-MFA. We demonstrate the application of eiFlux on several examples, including a genome-scale inst-MFA model, and show that it has robust optimal convergence even when started from a very poor initial guess for the parameters. eiFlux is implemented using the Python programming language and the General Algebraic Modeling System (GAMS), using the CONOPT solver. eiFlux is available upon request, pending institutional approval, and is free for academic use.

Probing the metabolism of γ-glutamyl peptides in cyanobacteria via metabolite profiling and 13 C labeling

Cyanobacteria are attractive model organisms for the study of photosynthesis and diurnal metabolism and as hosts for photoautotrophic production of chemicals. Exposure to bright light or environmental pollutants and a diurnal lifestyle of these prokaryotes may result in significant oxidative stress. Glutathione is a widely studied γ-glutamyl peptide that plays a key role in managing oxidative stress and detoxification of xenobiotics in cyanobacteria. The functional role and biosynthesis pathways of this tripeptide have been studied in detail in various phyla, including cyanobacteria. However, other γ-glutamyl peptides remain largely unexplored. We use an integrated approach to identify a number of γ-glutamyl peptides based on signature mass fragments and mass shifts in them in ¹³ C and ¹⁵ N enriched metabolite extracts. The newly identified compounds include γ-glutamyl dipeptides and derivatives of glutathione. Carbon backbones of the former turn over much faster than that of glutathione, suggesting that they follow a distinct biosynthesis pathway. Further, transients of isotopic ¹³ C enrichment show positional labeling in these peptides, which allows us to delineate the alternative biosynthesis pathways. Importantly, the amino acid of γ-glutamyl dipeptides shows much faster turnover compared to the glutamate moiety. The significant accumulation of γ-glutamyl dipeptides under slow-growth conditions combined with the results from dynamic ¹³ C labeling suggests that these compounds may act as reservoirs of amino acids in cyanobacteria.

Computational Framework for Machine-Learning-Enabled 13C Fluxomics

¹³C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for ¹³C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical ¹³C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

Metabolomics-based engineering for biofuel and bio-based chemical production in microalgae and cyanobacteria: A review

Metabolomics, an essential tool in modern synthetic biology based on the design-build-test-learn platform, is useful for obtaining a detailed understanding of cellular metabolic mechanisms through comprehensive analyses of the metabolite pool size and its dynamic changes. Metabolomics is critical to the design of a rational metabolic engineering strategy by determining the rate-limiting reaction and assimilated carbon distribution in a biosynthetic pathway of interest. Microalgae and cyanobacteria are promising photosynthetic producers of biofuels and bio-based chemicals, with high potential for developing a bioeconomic society through bio-based carbon neutral manufacturing. Metabolomics technologies optimized for photosynthetic organisms have been developed and utilized in various microalgal and cyanobacterial species. This review provides a concise overview of recent achievements in photosynthetic metabolomics, emphasizing the importance of microalgal and cyanobacterial cell factories that satisfy industrial requirements.

Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets

Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary ¹³C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Metabolic flux analysis results show that resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.

Metabolic flux analysis of the non-transitory starch tradeoff for lipid production in mature tobacco leaves

The metabolic plasticity of tobacco leaves has been demonstrated via the generation of transgenic plants that can accumulate over 30% dry weight as triacylglycerols. In investigating the changes in carbon partitioning in these high lipid-producing (HLP) leaves, foliar lipids accumulated stepwise over development. Interestingly, non-transient starch was observed to accumulate with plant age in WT but not HLP leaves, with a drop in foliar starch concurrent with an increase in lipid content. The metabolic carbon tradeoff between starch and lipid was studied using 13CO2-labeling experiments and isotopically nonstationary metabolic flux analysis, not previously applied to the mature leaves of a crop. Fatty acid synthesis was investigated through assessment of acyl-acyl carrier proteins using a recently derived quantification method that was extended to accommodate isotopic labeling. Analysis of labeling patterns and flux modeling indicated the continued production of unlabeled starch, sucrose cycling, and a significant contribution of NADP-malic enzyme to plastidic pyruvate production for the production of lipids in HLP leaves, with the latter verified by enzyme activity assays. The results suggest an inherent capacity for a developmentally regulated carbon sink in tobacco leaves and may in part explain the uniquely successful leaf lipid engineering efforts in this crop.

Carbon flux through photosynthesis and central carbon metabolism show distinct patterns between algae, C3 and C4 plants

Photosynthesis-related pathways are regarded as a promising avenue for crop improvement. Whilst empirical studies have shown that photosynthetic efficiency is higher in microalgae than in C3 or C4 crops, the underlying reasons remain unclear. Using a tailor-made microfluidics labelling system to supply 13CO2 at steady state, we investigated in vivo labelling kinetics in intermediates of the Calvin Benson cycle and sugar, starch, organic acid and amino acid synthesis pathways, and in protein and lipids, in Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii, which is the fastest growing green alga on record. We estimated flux patterns in these algae and compared them with published and new data from C3 and C4 plants. Our analyses identify distinct flux patterns supporting faster growth in photosynthetic cells, with some of the algae exhibiting faster ribulose 1,5-bisphosphate regeneration and increased fluxes through the lower glycolysis and anaplerotic pathways towards the tricarboxylic acid cycle, amino acid synthesis and lipid synthesis than in higher plants.

Channeling Anabolic Side Products toward the Production of Nonessential Metabolites: Stable Malate Production in Synechocystis sp. PCC6803

Powered by (sun)light to oxidize water, cyanobacteria can directly convert atmospheric CO₂ into valuable carbon-based compounds and meanwhile release O₂ to the atmosphere. As such, cyanobacteria are promising candidates to be developed as microbial cell factories for the production of chemicals. Nevertheless, similar to other microbial cell factories, engineered cyanobacteria may suffer from production instability. The alignment of product formation with microbial fitness is a valid strategy to tackle this issue. We have described previously the "FRUITS" algorithm for the identification of metabolites suitable to be coupled to growth (i.e., side products in anabolic reactions) in the model cyanobacterium Synechocystis. sp PCC6803. However, the list of candidate metabolites identified using this algorithm can be somewhat limiting, due to the inherent structure of metabolic networks. Here, we aim at broadening the spectrum of candidate compounds beyond the ones predicted by FRUITS, through the conversion of a growth-coupled metabolite to downstream metabolites via thermodynamically favored conversions. We showcase the feasibility of this approach for malate production using fumarate as the growth-coupled substrate in Synechocystis mutants. A final titer of ∼1.2 mM was achieved for malate during photoautotrophic batch cultivations. Under prolonged continuous cultivation, the most efficient malate-producing strain can maintain its productivity for at least 45 generations, sharply contrasting with other producing Synechocystis strains engineered with classical approaches. Our study also opens a new possibility for extending the stable production concept to derivatives of growth-coupled metabolites, increasing the list of suitable target compounds.

The Entner-Doudoroff Pathway Contributes to Glycogen Breakdown During High to Low CO2 Shifts in the Cyanobacterium Synechocystis sp. PCC 6803

Cyanobacteria perform plant-like oxygenic photosynthesis to convert inorganic carbon into organic compounds and can also use internal carbohydrate reserves under specific conditions. A mutant collection with defects in different routes for sugar catabolism was studied to analyze which of them is preferentially used to degrade glycogen reserves in light-exposed cells of Synechocystis sp. PCC 6803 shifted from high to low CO₂ conditions. Mutants defective in the glycolytic Embden-Meyerhof-Parnas pathway or in the oxidative pentose-phosphate (OPP) pathway showed glycogen levels similar to wild type under high CO₂ (HC) conditions and were able to degrade it similarly after shifts to low CO₂ (LC) conditions. In contrast, the mutant Δeda, which is defective in the glycolytic Entner-Doudoroff (ED) pathway, accumulated elevated glycogen levels under HC that were more slowly consumed during the LC shift. In consequence, the mutant Δeda showed a lowered ability to respond to the inorganic carbon shifts, displayed a pronounced lack in the reactivation of growth when brought back to HC, and differed significantly in its metabolite composition. Particularly, Δeda accumulated enhanced levels of proline, which is a well-known metabolite to maintain redox balances via NADPH levels in many organisms under stress conditions. We suggest that deletion of eda might promote the utilization of the OPP shunt that dramatically enhance NADPH levels. Collectively, the results point at a major regulatory contribution of the ED pathway for the mobilization of glycogen reserves during rapid acclimation to fluctuating CO₂ conditions.

Cyanobacteria as cell factories: the roles of host and pathway engineering and translational research

Cyanobacteria, a group of photoautotrophic prokaryotes, are attractive hosts for the sustainable production of chemicals from carbon dioxide and sunlight. However, the rates, yields, and titers have remained well below those needed for commercial deployment. We argue that the following areas will be central to the development of cyanobacterial cell factories: engineered and well-characterized host strains, model-guided pathway design, and advanced synthetic biology tools. Although several foundational studies report improved strain properties, translational research will be needed to develop engineered hosts and deploy them for metabolic engineering. Further, the recent developments in metabolic modeling and synthetic biology of cyanobacteria will enable nimble strategies for strain improvement with the complete cycle of design, build, test, and learn.

Cycling between growth and production phases increases cyanobacteria bioproduction of lactate

Decoupling growth from product synthesis is a promising strategy to increase carbon partitioning and maximize productivity in cell factories. However, reduction in both substrate uptake rate and metabolic activity in the production phase are an underlying problem for upscaling. Here, we used CRISPR interference to repress growth in lactate-producing Synechocystis sp. PCC 6803. Carbon partitioning to lactate in the production phase exceeded 90%, but CO₂ uptake was severely reduced compared to uptake during the growth phase. We characterized strains during the onset of growth arrest using transcriptomics and proteomics. Multiple genes involved in ATP homeostasis were regulated once growth was inhibited, which suggests an alteration of energy charge that may lead to reduced substrate uptake. In order to overcome the reduced metabolic activity and take advantage of increased carbon partitioning, we tested a novel production strategy that involved alternating growth arrest and recovery by periodic addition of an inducer molecule to activate CRISPRi. Using this strategy, we maintained lactate biosynthesis in Synechocystis for 30 days in a constant light turbidostat cultivation. Cumulative lactate titers were also increased by 100% compared to a constant growth-arrest regime, and reached 1 g/L. Further, the cultivation produced lactate for 30 days, compared to 20 days for the non-growth arrest cultivation. Periodic growth arrest could be applicable for other products, and in cyanobacteria, could be linked to internal circadian rhythms that persist in constant light.

Probing Light-Dependent Regulation of the Calvin Cycle Using a Multi-Omics Approach

Photoautotrophic microorganisms are increasingly explored for the conversion of atmospheric carbon dioxide into biomass and valuable products. The Calvin-Benson-Bassham (CBB) cycle is the primary metabolic pathway for net CO₂ fixation within oxygenic photosynthetic organisms. The cyanobacteria, Synechocystis sp. PCC 6803, is a model organism for the study of photosynthesis and a platform for many metabolic engineering efforts. The CBB cycle is regulated by complex mechanisms including enzymatic abundance, intracellular metabolite concentrations, energetic cofactors and post-translational enzymatic modifications that depend on the external conditions such as the intensity and quality of light. However, the extent to which each of these mechanisms play a role under different light intensities remains unclear. In this work, we conducted non-targeted proteomics in tandem with isotopically non-stationary metabolic flux analysis (INST-MFA) at four different light intensities to determine the extent to which fluxes within the CBB cycle are controlled by enzymatic abundance. The correlation between specific enzyme abundances and their corresponding reaction fluxes is examined, revealing several enzymes with uncorrelated enzyme abundance and their corresponding flux, suggesting flux regulation by mechanisms other than enzyme abundance. Additionally, the kinetics of ¹³C labeling of CBB cycle intermediates and estimated inactive pool sizes varied significantly as a function of light intensity suggesting the presence of metabolite channeling, an additional method of flux regulation. These results highlight the importance of the diverse methods of regulation of CBB enzyme activity as a function of light intensity, and highlights the importance of considering these effects in future kinetic models.

Recent advances in metabolic engineering-integration of in silico design and experimental analysis of metabolic pathways

Microorganisms are widely used to produce valuable compounds. Because thousands of metabolic reactions occur simultaneously and many metabolic reactions are related to target production and cell growth, the development of a rational design method for metabolic pathway modification to optimize target production is needed. In this paper, recent advances in metabolic engineering are reviewed, specifically considering computational pathway modification design and experimental evaluation of metabolic fluxes by ¹³C-metabolic flux analysis. Computational tools for seeking effective gene deletion targets and recruiting heterologous genes are described in flux balance analysis approaches. A kinetic model and adaptive laboratory evolution were applied to identify and eliminate the rate-limiting step in metabolic pathways. Data science-based approaches for process monitoring and control are described to maximize the performance of engineered cells in bioreactors.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

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An open-source Python package, mfapy, is developed for ¹³C-MFA.

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mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

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mfapy has a flexibility and extensibility to support various data analysis procedures.

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Computer simulations of ¹³C-MFA experiments is supported for experimental design.

Current knowledge and recent advances in understanding metabolism of the model cyanobacterium Synechocystis sp. PCC 6803

Cyanobacteria are key organisms in the global ecosystem, useful models for studying metabolic and physiological processes conserved in photosynthetic organisms, and potential renewable platforms for production of chemicals. Characterizing cyanobacterial metabolism and physiology is key to understanding their role in the environment and unlocking their potential for biotechnology applications. Many aspects of cyanobacterial biology differ from heterotrophic bacteria. For example, most cyanobacteria incorporate a series of internal thylakoid membranes where both oxygenic photosynthesis and respiration occur, while CO2 fixation takes place in specialized compartments termed carboxysomes. In this review, we provide a comprehensive summary of our knowledge on cyanobacterial physiology and the pathways in Synechocystis sp. PCC 6803 (Synechocystis) involved in biosynthesis of sugar-based metabolites, amino acids, nucleotides, lipids, cofactors, vitamins, isoprenoids, pigments and cell wall components, in addition to the proteins involved in metabolite transport. While some pathways are conserved between model cyanobacteria, such as Synechocystis, and model heterotrophic bacteria like Escherichia coli, many enzymes and/or pathways involved in the biosynthesis of key metabolites in cyanobacteria have not been completely characterized. These include pathways required for biosynthesis of chorismate and membrane lipids, nucleotides, several amino acids, vitamins and cofactors, and isoprenoids such as plastoquinone, carotenoids, and tocopherols. Moreover, our understanding of photorespiration, lipopolysaccharide assembly and transport, and degradation of lipids, sucrose, most vitamins and amino acids, and haem, is incomplete. We discuss tools that may aid our understanding of cyanobacterial metabolism, notably CyanoSource, a barcoded library of targeted Synechocystis mutants, which will significantly accelerate characterization of individual proteins.

Production of succinate by engineered strains of Synechocystis PCC 6803 overexpressing phosphoenolpyruvate carboxylase and a glyoxylate shunt

BACKGROUND

Cyanobacteria are promising hosts for the production of various industrially important compounds such as succinate. This study focuses on introduction of the glyoxylate shunt, which is naturally present in only a few cyanobacteria, into Synechocystis PCC 6803. In order to test its impact on cell metabolism, engineered strains were evaluated for succinate accumulation under conditions of light, darkness and anoxic darkness. Each condition was complemented by treatments with 2-thenoyltrifluoroacetone, an inhibitor of succinate dehydrogenase enzyme, and acetate, both in nitrogen replete and deplete medium.

RESULTS

We were able to introduce genes encoding the glyoxylate shunt, aceA and aceB, encoding isocitrate lyase and malate synthase respectively, into a strain of Synechocystis PCC 6803 engineered to overexpress phosphoenolpyruvate carboxylase. Our results show that complete expression of the glyoxylate shunt results in higher extracellular succinate accumulation compared to the wild type control strain after incubation of cells in darkness and anoxic darkness in the presence of nitrate. Addition of the inhibitor 2-thenoyltrifluoroacetone increased succinate titers in all the conditions tested when nitrate was available. Addition of acetate in the presence of the inhibitor further increased the succinate accumulation, resulting in high levels when phosphoenolpyruvate carboxylase was overexpressed, compared to control strain. However, the highest succinate titer was obtained after dark incubation of an engineered strain with a partial glyoxylate shunt overexpressing isocitrate lyase in addition to phosphoenolpyruvate carboxylase, with only 2-thenoyltrifluoroacetone supplementation to the medium.

CONCLUSIONS

Heterologous expression of the glyoxylate shunt with its central link to the tricarboxylic acid cycle (TCA) for acetate assimilation provides insight on the coordination of the carbon metabolism in the cell. Phosphoenolpyruvate carboxylase plays an important role in directing carbon flux towards the TCA cycle.

Exploring the metabolic fate of propanol in industrial erythromycin-producing strain via 13C labeling experiments and enhancement of erythromycin production by rational metabolic engineering of Saccharopolyspora erythraea

Propanol had been widely used as a precursor for erythromycin synthesis in industrial production. However, the knowledge on the exact metabolic fate of propanol was still unclear. In the present study, the metabolic fate of propanol in industrial erythromycin-producing strain Saccharopolyspora erythraea E3 was explored via 13C labeling experiments. An unexpected pathway in which propanol was channeled into tricarboxylic acid cycle was uncovered, resulting in uneconomic catabolism of propanol. By deleting the sucC gene, which encodes succinyl-CoA synthetase that catalyse a reaction in the unexpected propanol utilization pathway, a novel strain E3-ΔsucC was constructed. The strain E3-ΔsucC showed a significant enhancement in erythromycin production in the chemically defined medium compared to E3 (786.61 vs 392.94 mg/L). Isotopically nonstationary 13C metabolic flux analysis were employed to characterize the metabolic differences between Saccharopolyspora erythraea E3 and E3-ΔsucC. The results showed that compared with the starting strain E3, the fluxes of pentose phosphate pathway in E3-△sucC increased by almost 200%. The flux of the metabolic reaction catalyzed by succinyl-CoA synthetase in E3-ΔsucC was almost zero, while the glyoxylate bypass flux significantly increased. These new insights into the precursor utilization of antibiotic biosynthesis by rational metabolic engineering in Saccharopolyspora erythraea provided the new vision in increasing industrial production of secondary metabolites.

Liquid Chromatography Methods for Separation of Polar and Charged Intracellular Metabolites for 13C Metabolic Flux Analysis

Accurate quantification of mass isotopolog distribution (MID) of intracellular metabolites is a key requirement for ¹³C metabolic flux analysis (¹³C-MFA). Liquid chromatography coupled with mass spectrometry (LC/MS) has emerged as a frontrunner technique that combines two orthogonal separation strategies. While metabolomics requires separation of monoisotopic peaks, ¹³C-MFA imposes additional demands for chromatographic separation as isotopologs of metabolites significantly add to the number of analytes. In this protocol chapter, we discuss two liquid chromatography methods, namely, reverse phase ion-pairing and hydrophilic interaction chromatography (HILIC) that together can separate a wide variety of metabolites that are typically used for ¹³C metabolic flux analysis.

A new insight into role of phosphoketolase pathway in Synechocystis sp. PCC 6803

Phosphoketolase (PKET) pathway is predominant in cyanobacteria (around 98%) but current opinion is that it is virtually inactive under autotrophic ambient CO₂ condition (AC-auto). This creates an evolutionary paradox due to the existence of PKET pathway in obligatory photoautotrophs. We aim to answer the paradox with the aid of bioinformatic analysis along with metabolic, transcriptomic, fluxomic and mutant data integrated into a multi-level kinetic model. We discussed the problems linked to neglected isozyme, pket2 (sll0529) and inconsistencies towards the explanation of residual flux via PKET pathway in the case of silenced pket1 (slr0453) in Synechocystis sp. PCC 6803. Our in silico analysis showed: (1) 17% flux reduction via RuBisCO for Δpket1 under AC-auto, (2) 11.2–14.3% growth decrease for Δpket2 in turbulent AC-auto, and (3) flux via PKET pathway reaching up to 252% of the flux via phosphoglycerate mutase under AC-auto. All results imply that PKET pathway plays a crucial role under AC-auto by mitigating the decarboxylation occurring in OPP pathway and conversion of pyruvate to acetyl CoA linked to EMP glycolysis under the carbon scarce environment. Finally, our model predicted that PKETs have low affinity to S7P as a substrate.

Novel allosteric inhibition of phosphoribulokinase identified by ensemble kinetic modeling of Synechocystis sp. PCC 6803 metabolism

The present study attempted a computer simulation of the metabolism of a model cyanobacteria, Synechocystis sp. PCC 6803 (PCC 6803) to predict allosteric inhibitions that are likely to occur in photoautotrophic and mixotrophic conditions as well as in a metabolically engineered strain. PCC 6803 is a promising host for direct biochemical production from CO₂; however, further investigation of allosteric regulation is required for rational metabolic engineering to produce target compounds. Herein, ensemble modeling of microbial metabolism was applied to build accurate predictive models by synthesizing the results of multiple models with different parameter sets into a single score to identify plausible allosteric inhibitions. The data driven-computer simulation using metabolic flux, enzyme abundance, and metabolite concentration data successfully identified candidates for allosteric inhibition. The enzyme assay experiment using the recombinant protein confirmed isocitrate was a non-competitive inhibitor of phosphoribulokinase as a novel allosteric regulation of cyanobacteria metabolism.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.

Unconventional biochemical regulation of the oxidative pentose phosphate pathway in the model cyanobacterium Synechocystis sp. PCC 6803

Metabolite production from carbon dioxide using sugar catabolism in cyanobacteria has been in the spotlight recently. Synechocystis sp. PCC 6803 (Synechocystis 6803) is the most studied cyanobacterium for metabolite production. Previous in vivo analyses revealed that the oxidative pentose phosphate (OPP) pathway is at the core of sugar catabolism in Synechocystis 6803. However, the biochemical regulation of the OPP pathway enzymes in Synechocystis 6803 remains unknown. Therefore, we characterized a key enzyme of the OPP pathway, glucose-6-phosphate dehydrogenase (G6PDH), and related enzymes from Synechocystis 6803. Synechocystis 6803 G6PDH was inhibited by citrate in the oxidative tricarboxylic acid (TCA) cycle. Citrate has not been reported as an inhibitor of G6PDH before. Similarly, 6-phosphogluconate dehydrogenase, the other enzyme from Synechocystis 6803 that catalyzes the NADPH-generating reaction in the OPP pathway, was inhibited by citrate. To understand the physiological significance of this inhibition, we characterized succinic semialdehyde dehydrogenase (SSADH) from Synechocystis 6803 (SySSADH), which catalyzes one of the NAD(P)H generating reactions in the oxidative TCA cycle. Similar to isocitrate dehydrogenase from Synechocystis 6803, SySSADH specifically catalyzed the NADPH-generating reaction and was not inhibited by citrate. The activity of SySSADH was lower than that of other bacterial SSADHs. Previous and this studies revealed that unlike the OPP pathway, the oxidative TCA cycle is a pathway with low efficiency in NADPH generation in Synechocystis 6803. It has, thus, been suggested that to avoid NADPH overproduction, the OPP pathway dehydrogenase activity is repressed when the flow of the oxidative TCA cycle increases in Synechocystis 6803.