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Background: Myceliophthora thermophila has been engineered as a significant cell factory for malic acid production, yet strategies to further enhance production remain unclear and lack rational guidance. 13C-MFA (13C metabolic flux analysis) offers a means to analyze cellular metabolic mechanisms and pinpoint critical nodes for improving product synthesis. Here, we employed 13C-MFA to investigate the metabolic flux distribution of a high-malic acid-producing strain of M. thermophila and attempted to decipher the crucial bottlenecks in the metabolic pathways. Results: Compared with the wild-type strain, the high-Malic acid-producing strain M. thermophila JG207 exhibited greater glucose uptake and carbon dioxide evolution rates but lower oxygen uptake rates and biomass yields. Consistent with these phenotypes, the 13C-MFA results showed that JG207 displayed elevated flux through the EMP pathway and downstream TCA cycle, along with reduced oxidative phosphorylation flux, thereby providing more precursors and NADH for malic acid synthesis. Furthermore, based on the 13C-MFA results, we conducted oxygen-limited culture and nicotinamide nucleotide transhydrogenase (NNT) gene knockout experiments to increase the cytoplasmic NADH level, both of which were shown to be beneficial for malic acid accumulation. Conclusions: This work elucidates and validates the key node for achieving high malic acid production in M. thermophila. We propose effective fermentation strategies and genetic modifications for enhancing malic acid production. These findings offer valuable guidance for the rational design of future cell factories aimed at improving malic acid yields. [ABSTRACT FROM AUTHOR]

Background: Flux Balance Analysis (FBA) is a key metabolic modeling method used to simulate cellular metabolism under steady-state conditions. Its simplicity and versatility have led to various strategies incorporating transcriptomic and proteomic data into FBA, successfully predicting flux distribution and phenotypic results. However, despite these advances, the untapped potential lies in leveraging gene-related connections like co-expression patterns for valuable insights. Results: To fill this gap, we introduce ICON-GEMs, an innovative constraint-based model to incorporate gene co-expression network into the FBA model, facilitating more precise determination of flux distributions and functional pathways. In this study, transcriptomic data from both Escherichia coli and Saccharomyces cerevisiae were integrated into their respective genome-scale metabolic models. A comprehensive gene co-expression network was constructed as a global view of metabolic mechanism of the cell. By leveraging quadratic programming, we maximized the alignment between pairs of reaction fluxes and the correlation of their corresponding genes in the co-expression network. The outcomes notably demonstrated that ICON-GEMs outperformed existing methodologies in predictive accuracy. Flux variabilities over subsystems and functional modules also demonstrate promising results. Furthermore, a comparison involving different types of biological networks, including protein–protein interactions and random networks, reveals insights into the utilization of the co-expression network in genome-scale metabolic engineering. Conclusion: ICON-GEMs introduce an innovative constrained model capable of simultaneous integration of gene co-expression networks, ready for board application across diverse transcriptomic data sets and multiple organisms. It is freely available as open-source at https://github.com/ThummaratPaklao/ICOM-GEMs.git. [ABSTRACT FROM AUTHOR]

Background: Cancer cells undergo cellular adaptation through metabolic reprogramming to sustain survival and rapid growth under various stress conditions. However, how brain tumors modulate their metabolic flexibility in the naturally serine/glycine (S/G)-deficient brain microenvironment remain unknown. Methods: We used a range of primary/stem-like and established glioblastoma (GBM) cell models in vitro and in vivo. To identify the regulatory mechanisms of S/G deprivation-induced metabolic flexibility, we employed high-throughput RNA-sequencing, transcriptomic analysis, metabolic flux analysis, metabolites analysis, chromatin immunoprecipitation (ChIP), luciferase reporter, nuclear fractionation, cycloheximide-chase, and glucose consumption. The clinical significances were analyzed in the genomic database (GSE4290) and in human GBM specimens. Results: The high-throughput RNA-sequencing and transcriptomic analysis demonstrate that the de novo serine synthesis pathway (SSP) and glycolysis are highly activated in GBM cells under S/G deprivation conditions. Mechanistically, S/G deprivation rapidly induces reactive oxygen species (ROS)-mediated AMP-activated protein kinase (AMPK) activation and AMPK-dependent hypoxia-inducible factor (HIF)-1α stabilization and transactivation. Activated HIF-1α in turn promotes the expression of SSP enzymes phosphoglycerate dehydrogenase (PHGDH), phosphoserine aminotransferase 1 (PSAT1), and phosphoserine phosphatase (PSPH). In addition, the HIF-1α-induced expression of glycolytic genes (GLUT1, GLUT3, HK2, and PFKFB2) promotes glucose uptake, glycolysis, and glycolytic flux to fuel SSP, leading to elevated de novo serine and glycine biosynthesis, NADPH/NADP+ ratio, and the proliferation and survival of GBM cells. Analyses of human GBM specimens reveal that the levels of overexpressed PHGDH, PSAT1, and PSPH are positively correlated with levels of AMPK T172 phosphorylation and HIF-1α expression and the poor prognosis of GBM patients. Conclusion: Our findings reveal that metabolic stress-enhanced glucose-derived de novo serine biosynthesis is a critical metabolic feature of GBM cells, and highlight the potential to target SSP for treating human GBM. [ABSTRACT FROM AUTHOR]

Coenzyme Q10 (CoQ10) is crucial for human beings, especially in the fields of biology and medicine. The aim of this experiment was to investigate the conditions for increasing CoQ10 production. At present, microbial fermentation is the main production method of CoQ10, and the production process of microbial CoQ10 metabolism control fermentation is very critical. Metabolic flux is one of the most important determinants of cell physiology in metabolic engineering. Metabolic flux analysis (MFA) is used to estimate the intracellular flux in metabolic networks. In this experiment, Rhodobacter sphaeroides was used as the research object to analyze the effects of aqueous ammonia (NH3·H2O) and calcium carbonate (CaCO3) on the metabolic flux of CoQ10. When CaCO3 was used to adjust the pH, the yield of CoQ10 was 274.43 mg·L−1 (8.71 mg·g−1 DCW), which was higher than that of NH3·H2O adjustment. The results indicated that when CaCO3 was used to adjust pH, more glucose-6-phosphate (G6P) entered the pentose phosphate (HMP) pathway and produced more NADPH, which enhanced the synthesis of CoQ10. At the chorismic acid node, more metabolic fluxes were involved in the synthesis of p-hydroxybenzoic acid (pHBA; the synthetic precursor of CoQ10), enhancing the anabolic flow of CoQ10. In addition, Ca2+ produced by the reaction of CaCO3 with organic acids promotes the synthesis of CoQ10. In summary, the use of CaCO3 adjustment is more favorable for the synthesis of CoQ10 by R. sphaeroides than NH3·H2O adjustment. The migration of metabolic flux caused by the perturbation of culture conditions was analyzed to compare the changes in the distribution of intracellular metabolic fluxes for the synthesis of CoQ10. Thus, the main nodes of the metabolic network were identified as G6P and chorismic acid. This provides a theoretical basis for the modification of genes related to the CoQ10 synthesis pathway. [ABSTRACT FROM AUTHOR]

Background: "ATP wasting" has been observed in 13C metabolic flux analyses of Saccharomyces cerevisiae, a yeast strain commonly used to produce ethanol. Some strains of S. cerevisiae, such as the sake strain Kyokai 7, consume approximately two-fold as much ATP as laboratory strains. Increased ATP consumption may be linked to the production of ethanol, which helps regenerate ATP. Results: This study was conducted to enhance ethanol and 2,3-butanediol (2,3-BDO) production in the S. cerevisiae strains, ethanol-producing strain BY318 and 2,3-BDO-producing strain YHI030, by expressing the fructose-1,6-bisphosphatase (FBPase) and ATP synthase (ATPase) genes to induce ATP dissipation. The introduction of a futile cycle for ATP consumption in the pathway was achieved by expressing various FBPase and ATPase genes from Escherichia coli and S. cerevisiae in the yeast strains. The production of ethanol and 2,3-BDO was evaluated using high-performance liquid chromatography and gas chromatography, and fermentation tests were performed on synthetic media under aerobic conditions in batch culture. The results showed that in the BY318-opt_ecoFBPase (expressing opt_ecoFBPase) and BY318-ATPase (expressing ATPase) strains, specific glucose consumption was increased by 30% and 42%, respectively, and the ethanol production rate was increased by 24% and 45%, respectively. In contrast, the YHI030-opt_ecoFBPase (expressing opt_ecoFBPase) and YHI030-ATPase (expressing ATPase) strains showed increased 2,3-BDO yields of 26% and 18%, respectively, and the specific production rate of 2,3-BDO was increased by 36%. Metabolomic analysis confirmed the introduction of the futile cycle. Conclusion: ATP wasting may be an effective strategy for improving the fermentative biosynthetic capacity of S. cerevisiae, and increased ATP consumption may be a useful tool in some alcohol-producing strains. [ABSTRACT FROM AUTHOR]

Background: Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results: To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions: Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies. [ABSTRACT FROM AUTHOR]

Background: Redox signaling and energy metabolism are known to be involved in controlling the balance between self-renewal and proliferation/differentiation of stem cells. In this study we investigated metabolic and redox changes occurring during in vitro human dental pulp stem cells (hDPSCs) osteoblastic (OB) differentiation and tested on them the impact of the reactive oxygen species (ROS) signaling. Methods: hDPSCs were isolated from dental pulp and subjected to alkaline phosphatase and alizarin red staining, q-RT-PCR, and western blotting analysis of differentiation markers to assess achievement of osteogenic/odontogenic differentiation. Moreover, a combination of metabolic flux analysis and confocal cyto-imaging was used to profile the metabolic phenotype and to evaluate the redox tone of hDPSCs. Results: In differentiating hDPSCs we observed the down-regulation of the mitochondrial respiratory chain complexes expression since the early phase of the process, confirmed by metabolic flux analysis, and a reduction of the basal intracellular peroxide level in its later phase. In addition, dampened glycolysis was observed, thereby indicating a lower energy-generating phenotype in differentiating hDPSCs. Treatment with the ROS scavenger Trolox, applied in the early-middle phases of the process, markedly delayed OB differentiation of hDPSCs assessed as ALP activity, Runx2 expression, mineralization capacity, expression of stemness and osteoblast marker genes (Nanog, Lin28, Dspp, Ocn) and activation of ERK1/2. In addition, the antioxidant partly prevented the inhibitory effect on cell metabolism observed following osteogenic induction. Conclusions: Altogether these results provided evidence that redox signaling, likely mediated by peroxide species, influenced the stepwise osteogenic expansion/differentiation of hDPSCs and contributed to shape its accompanying metabolic phenotype changes thus improving their efficiency in bone regeneration and repair. [ABSTRACT FROM AUTHOR]

Background: Saccharomyces boulardii is a probiotic yeast that exhibits antimicrobial and anti-toxin activities. Although S. boulardii has been clinically used for decades to treat gastrointestinal disorders, several studies have reported weak or no beneficial effects of S. boulardii administration in some cases. These conflicting results of S. boulardii efficacity may be due to nutrient deficiencies in the intestine that make it difficult for S. boulardii to maintain its metabolic activity. Results: To enable S. boulardii to overcome any nutritional deficiencies in the intestine, we constructed a S. boulardii strain that could metabolize l-fucose, a major component of mucin in the gut epithelium. The fucU, fucI, fucK, and fucA from Escherichia coli and HXT4 from S. cerevisiae were overexpressed in S. boulardii. The engineered S. boulardii metabolized l-fucose and produced 1,2-propanediol under aerobic and anaerobic conditions. It also produced large amounts of 1,2-propanediol under strict anaerobic conditions. An in silico genome-scale metabolic model analysis was performed to simulate the growth of S. boulardii on l-fucose, and elementary flux modes were calculated to identify critical metabolic reactions for assimilating l-fucose. As a result, we found that the engineered S. boulardii consumes l-fucose via (S)-lactaldehyde-(S)-lactate-pyruvate pathway, which is highly oxygen dependent. Conclusion: To the best of our knowledge, this is the first study in which S. cerevisiae and S. boulardii strains capable of metabolizing l-fucose have been constructed. This strategy could be used to enhance the metabolic activity of S. boulardii and other probiotic microorganisms in the gut. [ABSTRACT FROM AUTHOR]

Background: Electro-fermentation (EF) is an emerging tool for bioprocess intensification. Benefits are especially expected for bioprocesses in which the cells are enabled to exchange electrons with electrode surfaces directly. It has also been demonstrated that the use of electrical energy in BES can increase bioprocess performance by indirect secondary effects. In this case, the electricity is used to alter process parameters and indirectly activate desired pathways. In many bioprocesses, oxidation-reduction potential (ORP) is a crucial process parameter. While C. pasteurianum fermentation of glycerol has been shown to be significantly influenced electrochemically, the underlying mechanisms are not clear. To this end, we developed a system for the electrochemical control of ORP in continuous culture to quantitatively study the effects of ORP alteration on C. pasteurianum by metabolic flux analysis (MFA), targeted metabolomics, sensitivity and regulation analysis. Results: In the ORP range of −462 mV to −250 mV, the developed algorithm enabled a stable anodic electrochemical control of ORP at desired set-points and a fixed dilution rate of 0.1 h−1. An overall increase of 57% in the molar yield for 1,3-propanediol was observed by an ORP increase from −462 to −250 mV. MFA suggests that C. pasteurianum possesses and uses cellular energy generation mechanisms in addition to substrate-level phosphorylation. The sensitivity analysis showed that ORP exerted its strongest impact on the reaction of pyruvate-ferredoxin-oxidoreductase. The regulation analysis revealed that this influence is mainly of a direct nature. Hence, the observed metabolic shifts are primarily caused by direct inhibition of the enzyme upon electrochemical production of oxygen. A similar effect was observed for the enzyme pyruvate-formate-lyase at elevated ORP levels. Conclusions: The results show that electrochemical ORP alteration is a suitable tool to steer the metabolism of C. pasteurianum and increase product yield for 1,3-propanediol in continuous culture. The approach might also be useful for application with further anaerobic or anoxic bioprocesses. However, to maximize the technique's efficiency, it is essential to understand the chemistry behind the ORP change and how the microbial system responds to it by transmitted or direct effects. [ABSTRACT FROM AUTHOR]

Background: Saccharomyces cerevisiae generally consumes glucose to produce ethanol accompanied by the main by-products of glycerol, acetic acid, and lactic acid. The minimization of the formation of by-products in S. cerevisiae was an effective way to improve the economic viability of the bioethanol industry. In this study, S. cerevisiae GPD2, FPS1, ADH2, and DLD3 genes were knocked out by the Clustered Regularly Interspaced Short Palindromic Repeats Cas9 (CRISPR-Cas9) approach. The mechanism of gene deletion affecting ethanol metabolism was further elucidated based on metabolic flux and transcriptomics approaches. Results: The engineered S. cerevisiae with gene deletion of GPD2, FPS1, ADH2, and DLD3 was constructed by the CRISPR-Cas9 approach. The ethanol content of engineered S. cerevisiae GPD2 Delta FPS1 Delta ADH2 Delta DLD3 Delta increased by 18.58% with the decrease of glycerol, acetic acid, and lactic acid contents by 22.32, 8.87, and 16.82%, respectively. The metabolic flux analysis indicated that the carbon flux rethanol in engineered strain increased from 60.969 to 63.379. The sequencing-based RNA-Seq transcriptomics represented 472 differential expression genes (DEGs) were identified in engineered S. cerevisiae, in which 195 and 277 genes were significantly up-regulated and down-regulated, respectively. The enriched pathways of up-regulated genes were mainly involved in the energy metabolism of carbohydrates, while the down-regulated genes were mainly enriched in acid metabolic pathways. Conclusions: The yield of ethanol in engineered S. cerevisiae increased with the decrease of the by-products including glycerol, acetic acid, and lactic acid. The deletion of genes GPD2, FPS1, ADH2, and DLD3 resulted in the redirection of carbon flux. [ABSTRACT FROM AUTHOR]

Background: Photosynthesis close interacts with respiration and nitrogen assimilation, which determine the photosynthetic efficiency of a leaf. Accurately quantifying the metabolic fluxes in photosynthesis, respiration and nitrogen assimilation benefit the design of photosynthetic efficiency improvement. To accurately estimate metabolic fluxes, time-series data including leaf metabolism and isotopic abundance changes should be collected under precisely controlled environments. But for isotopic labelled leaves under defined environments the, time cost of manually sampling usually longer than the turnover time of several intermediates in photosynthetic metabolism. In this case, the metabolic or physiological status of leaf sample would change during the sampling, and the accuracy of metabolomics data could be compromised. Results: Here we developed an integrated isotopic labeling and freeze sampling apparatus (ILSA), which could finish freeze sampling automatically in 0.05 s. ILSA can not only be used for sampling of photosynthetic metabolism measurement, but also suit for leaf isotopic labeling experiments under controlled environments ([CO2] and light). Combined with HPLC–MS/MS as the metabolic measurement method, we demonstrated: (1) how pool-size of photosynthetic metabolites change in dark-accumulated rice leaf, and (2) variation in photosynthetic metabolic flux between rice and Arabidopsis thaliana. Conclusions: The development of ILSA supports the photosynthetic research on metabolism and metabolic flux analysis and provides a new tool for the study of leaf physiology. [ABSTRACT FROM AUTHOR]

Background: Metabolic adaptations can allow cancer cells to survive DNA-damaging chemotherapy. This unmet clinical challenge is a potential vulnerability of cancer. Accordingly, there is an intense search for mechanisms that modulate cell metabolism during anti-tumor therapy. We set out to define how colorectal cancer CRC cells alter their metabolism upon DNA replication stress and whether this provides opportunities to eliminate such cells more efficiently. Methods: We incubated p53-positive and p53-negative permanent CRC cells and short-term cultured primary CRC cells with the topoisomerase-1 inhibitor irinotecan and other drugs that cause DNA replication stress and consequently DNA damage. We analyzed pro-apoptotic mitochondrial membrane depolarization and cell death with flow cytometry. We evaluated cellular metabolism with immunoblotting of electron transport chain (ETC) complex subunits, analysis of mitochondrial mRNA expression by qPCR, MTT assay, measurements of oxygen consumption and reactive oxygen species (ROS), and metabolic flux analysis with the Seahorse platform. Global metabolic alterations were assessed using targeted mass spectrometric analysis of extra- and intracellular metabolites. Results: Chemotherapeutics that cause DNA replication stress induce metabolic changes in p53-positive and p53-negative CRC cells. Irinotecan enhances glycolysis, oxygen consumption, mitochondrial ETC activation, and ROS production in CRC cells. This is connected to increased levels of electron transport chain complexes involving mitochondrial translation. Mass spectrometric analysis reveals global metabolic adaptations of CRC cells to irinotecan, including the glycolysis, tricarboxylic acid cycle, and pentose phosphate pathways. P53-proficient CRC cells, however, have a more active metabolism upon DNA replication stress than their p53-deficient counterparts. This metabolic switch is a vulnerability of p53-positive cells to irinotecan-induced apoptosis under glucose-restricted conditions. Conclusion: Drugs that cause DNA replication stress increase the metabolism of CRC cells. Glucose restriction might improve the effectiveness of classical chemotherapy against p53-positive CRC cells. The topoisomerase-1 inhibitor irinotecan and other chemotherapeutics that cause DNA damage induce metabolic adaptations in colorectal cancer (CRC) cells irrespective of their p53 status. Irinotecan enhances the glycolysis and oxygen consumption in CRC cells to deliver energy and biomolecules necessary for DNA repair and their survival. Compared to p53-deficient cells, p53-proficient CRC cells have a more active metabolism and use their intracellular metabolites more extensively. This metabolic switch creates a vulnerability to chemotherapy under glucose-restricted conditions for p53-positive cells. [ABSTRACT FROM AUTHOR]

Background: The metabolic phenotype of stem cells is increasingly recognized as a hallmark of their pluripotency with mitochondrial and oxygen-related metabolism playing a not completely defined role in this context. In a previous study, we reported the ectopic expression of myoglobin (MB) in bone marrow-derived hematopoietic stem/progenitor cells. Here, we have extended the analysis to mesenchymal stem cells (MSCs) isolated from different tissues. Methods: MSCs were isolated from human placental membrane, mammary adipose tissue and dental pulp and subjected to RT-PCR, Western blotting and mass spectrometry to investigate the expression of MB. A combination of metabolic flux analysis and cyto-imaging was used to profile the metabolic phenotype and the mitochondria dynamics in the different MSCs. Results: As for the hematopoietic stem/progenitor cells, the expression of Mb was largely driven by an alternative transcript with the protein occurring both in the monomer and in the dimer forms as confirmed by mass spectrometry analysis. Comparing the metabolic fluxes between neonatal placental membrane-derived and adult mammary adipose tissue-derived MSCs, we showed a significantly more active bioenergetics profile in the former that correlated with a larger co-localization of myoglobin with the mitochondrial compartment. Differences in the structure of the mitochondrial network as well as in the expression of factors controlling the organelle dynamics were also observed between neonatal and adult mesenchymal stem cells. Finally, the expression of myoglobin was found to be strongly reduced following osteogenic differentiation of dental pulp-derived MSCs, while it was upregulated following reprogramming of human fibroblasts to induce pluripotent stem cells. Conclusions: Ectopic expression of myoglobin in tissues other than muscle raises the question of understanding its function therein. Properties in addition to the canonical oxygen storage/delivery have been uncovered. Finding of Mb expressed via an alternative gene transcript in the context of different stem cells with metabolic phenotypes, its loss during differentiation and recovery in iPSCs suggest a hitherto unappreciated role of Mb in controlling the balance between aerobic metabolism and pluripotency. Understanding how Mb contributes through modulation of the mitochondrial physiology to the stem cell biology paves the way to novel perspectives in regenerative medicine as well as in cancer stem cell therapy. [ABSTRACT FROM AUTHOR]

Background: Most in vitro cancer cell experiments have been performed using 2D models. However, 3D spheroid cultures are increasingly favored for being more representative of in vivo tumor conditions. To overcome the translational challenges with 2D cell cultures, 3D systems better model more complex cell-to-cell contact and nutrient levels present in a tumor, improving our understanding of cancer complexity. Despite this need, there are few reports on how 3D cultures differ metabolically from 2D cultures. Methods: Well-described cell lines from colorectal cancer (HCT116 and SW948) and pancreatic ductal adenocarcinoma (Panc-1 and MIA-Pa-Ca-2) were used to investigate metabolism in 3D spheroid models. The metabolic variation under normal glucose conditions were investigated comparing 2D and 3D cultures by metabolic flux analysis and expression of key metabolic proteins. Results: We find significant differences in glucose metabolism of 3D cultures compared to 2D cultures, both related to glycolysis and oxidative phosphorylation. Spheroids have higher ATP-linked respiration in standard nutrient conditions and higher non-aerobic ATP production in the absence of supplemented glucose. In addition, ATP-linked respiration is significantly inversely correlated with OCR/ECAR (p = 0.0096). Mitochondrial transport protein, TOMM20, expression decreases in all spheroid models compared to 2D, and monocarboxylate transporter (MCT) expression increases in 3 of the 4 spheroid models. Conclusions: In this study of CRC and PDAC cell lines, we demonstrate that glucose metabolism in 3D spheroids differs significantly from 2D cultures, both in terms of glycolytic and oxidative phosphorylation metrics. The metabolic phenotype shift from 2D to 3D culture in one cell line is greater than the phenotypic differences between each cell line and tumor source. The results herein emphasize the need to use 3D cell models for investigating nutrient utilization and metabolic flux for a better understanding of tumor metabolism and potential metabolic therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: Electric energy is not collected and utilized in biobutanol fermentation. The reason is that the yields of electron shuttles and nanowires are not enough to gather and transfer all electrons to the electrode in liquid fermentation. However, the solid matrix of the adsorption carrier may be conducive to the collection and transfer of electrons because of its good adsorption and conductivity. Therefore, this first-attempt study coupled microbial fuel cell (MFC) with adsorption carrier solid-state fermentation (ACSF). In addition, the effect and mechanism of adsorption carrier solid-state fermentation on power generation were explored. Results: The power generation performance and fermentation performance were improved by ACSF. The power density by polyurethane and carbon felt carrier solid-state fermentation (PC) was 12 times that by no carrier fermentation (NC). The biobutanol yield of absorbent cotton and carbon felt carrier solid-state fermentation (ACC) was increased by 36.86%. Moreover, the mechanism was explored via metabolic flux analysis, cyclic voltammetry and scanning electron microscopy. The results of metabolic flux analysis showed that more electrons were produced and more carbon flowed to biobutanol production. The cyclic voltammetry results revealed that more riboflavin was produced to enhance extracellular electron transport (EET) by ACSF. The scanning electron microscopy image showed that the adsorption capacity and aggregation degree of bacteria were increased on the electrode and nanowires were observed by ACSF. Conclusions: A new fermentation mode was established by coupling MFC with ACSF to improve substrate utilization, which will provide crucial insights into the fermentation industry. In addition, the ACSF is an effective method to enhance power generation performance and fermentation performance. [ABSTRACT FROM AUTHOR]

Background: Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO2. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO2-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear. Results: Here, we developed a comprehensive approach for 13C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains. Conclusions: The developed approach, based on parallel 13C tracer studies with GC–MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO2 fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of 13C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments. [ABSTRACT FROM AUTHOR]

Background: Depression is one of the most common and untreated comorbidities in chronic obstructive pulmonary disease (COPD), and is associated with poor health outcomes (e.g. increased hospitalization/exacerbation rates). Although metabolic disturbances have been suggested in depressed non-diseased conditions, comprehensive metabolic phenotyping has never been conducted in those with COPD. We examined whether depressed COPD patients have certain clinical/functional features and exhibit a specific amino acid phenotype which may guide the development of targeted (nutritional) therapies.Methods: Seventy-eight outpatients with moderate to severe COPD (GOLD II-IV) were stratified based on presence of depression using a validated questionnaire. Lung function, disease history, habitual physical activity and protein intake, body composition, cognitive and physical performance, and quality of life were measured. Comprehensive metabolic flux analysis was conducted by pulse stable amino acid isotope administration. We obtained blood samples to measure postabsorptive kinetics (production and clearance rates) and plasma concentrations of amino acids by LC-MS/MS. Data are expressed as mean [95% CI]. Stats were done by graphpad Prism 9.1.0. ɑ < 0.05.Results: The COPD depressed (CD, n = 27) patients on average had mild depression, were obese (BMI: 31.7 [28.4, 34.9] kg/m2), and were characterized by shorter 6-min walk distance (P = 0.055), physical inactivity (P = 0.03), and poor quality of life (P = 0.01) compared to the non-depressed COPD (CN, n = 51) group. Lung function, disease history, body composition, cognitive performance, and daily protein intake were not different between the groups. In the CD group, plasma branched chain amino acid concentration (BCAA) was lower (P = 0.02), whereas leucine (P = 0.01) and phenylalanine (P = 0.003) clearance rates were higher. Reduced values were found for tyrosine plasma concentration (P = 0.005) even after adjustment for the large neutral amino acid concentration (= sum BCAA, tyrosine, phenylalanine and tryptophan) as a marker of dopamine synthesis (P = 0.048).Conclusion: Mild depression in COPD is associated with poor daily performance and quality of life, and a set of metabolic changes in depressed COPD that include perturbation of large neutral amino acids, specifically the BCAAs. Trial registration clinicaltrials.gov: NCT01787682, 11 February 2013-Retrospectively registered; NCT02770092, 12 May 2016-Retrospectively registered; NCT02780219, 23 May 2016-Retrospectively registered; NCT03796455, 8 January 2019-Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: The identification of novel targets is of paramount importance to develop more effective drugs and improve the treatment of non-small cell lung cancer (NSCLC), the leading cause of cancer-related deaths worldwide. Since cells alter their metabolic rewiring during tumorigenesis and along cancer progression, targeting key metabolic players and metabolism-associated proteins represents a valuable approach with a high therapeutic potential. Metabolic fitness relies on the functionality of heat shock proteins (HSPs), molecular chaperones that facilitate the correct folding of metabolism enzymes and their assembly in macromolecular structures. Methods: Gene fitness was determined by bioinformatics analysis from available datasets from genetic screenings. HSPD1 expression was evaluated by immunohistochemistry from formalin-fixed paraffin-embedded tissues from NSCLC patients. Real-time proliferation assays with and without cytotoxicity reagents, colony formation assays and cell cycle analyses were used to monitor growth and drug sensitivity of different NSCLC cells in vitro. In vivo growth was monitored with subcutaneous injections in immune-deficient mice. Cell metabolic activity was analyzed through extracellular metabolic flux analysis. Specific knockouts were introduced by CRISPR/Cas9. Results: We show heat shock protein family D member 1 (HSPD1 or HSP60) as a survival gene ubiquitously expressed in NSCLC and associated with poor patients' prognosis. HSPD1 knockdown or its chemical disruption by the small molecule KHS101 induces a drastic breakdown of oxidative phosphorylation, and suppresses cell proliferation both in vitro and in vivo. By combining drug profiling with transcriptomics and through a whole-genome CRISPR/Cas9 screen, we demonstrate that HSPD1-targeted anti-cancer effects are dependent on oxidative phosphorylation and validated molecular determinants of KHS101 sensitivity, in particular, the creatine-transporter SLC6A8 and the subunit of the cytochrome c oxidase complex COX5B. Conclusions: These results highlight mitochondrial metabolism as an attractive target and HSPD1 as a potential theranostic marker for developing therapies to combat NSCLC. [ABSTRACT FROM AUTHOR]

Background: A precise map of the metabolic fluxome, the closest surrogate to the physiological phenotype, is becoming progressively more important in the metabolic engineering of photosynthetic organisms for biofuel and biomass production. For photosynthetic organisms, the state-of-the-art method for this purpose is instationary 13C fluxomics, which has arisen as a sibling of transcriptomics or proteomics. Instationary 13C data processing requires solving high-dimensional nonlinear differential equations and leads to large computational and time costs when its scope is expanded to a genome-scale metabolic network. Result: Here, we present a parallelized method to model instationary 13C labeling data. The elementary metabolite unit (EMU) framework is reorganized to allow treating individual mass isotopomers and breaking up of their networks into strongly connected components (SCCs). A variable domain parallel algorithm is introduced to process ordinary differential equations in a parallel way. 15-fold acceleration is achieved for constant-step-size modeling and ~ fivefold acceleration for adaptive-step-size modeling. Conclusion: This algorithm is universally applicable to isotope granules such as EMUs and cumomers and can substantially accelerate instationary 13C fluxomics modeling. It thus has great potential to be widely adopted in any instationary 13C fluxomics modeling. [ABSTRACT FROM AUTHOR]

Background: The development of somatic reprogramming, especially purely chemical reprogramming, has significantly advanced biological research. And chemical-induced extraembryonic endoderm-like (ciXEN) cells have been confirmed to be an indispensable intermediate stage of chemical reprogramming. They resemble extraembryonic endoderm (XEN) cells in terms of transcriptome, reprogramming potential, and developmental ability in vivo. However, the other characteristics of ciXEN cells and the effects of chemicals and bFGF on the in vitro culture of ciXEN cells have not been systematically reported. Methods: Chemicals and bFGF in combination with Matrigel were used to induce the generation of ciXEN cells derived from mouse embryonic fibroblasts (MEFs). RNA sequencing was utilised to examine the transcriptome of ciXEN cells, and PCR/qPCR assays were performed to evaluate the mRNA levels of the genes involved in this study. Hepatic functions were investigated by periodic acid-Schiff staining and indocyanine green assay. Lactate production, ATP detection, and extracellular metabolic flux analysis were used to analyse the energy metabolism of ciXEN cells. Results: ciXEN cells expressed XEN-related genes, exhibited high proliferative capacity, had the ability to differentiate into visceral endoderm in vitro, and possessed the plasticity allowing for their differentiation into induced hepatocytes (iHeps). Additionally, the upregulated biological processes of ciXEN cells compared to those in MEFs focused on metabolism, but their energy production was independent of glycolysis. Furthermore, without the cocktail of chemicals and bFGF, which are indispensable for the generation of ciXEN cells, induced XEN (iXEN) cells remained the expression of XEN markers, the high proliferative capacity, and the plasticity to differentiate into iHeps in vitro. Conclusions: ciXEN cells had high plasticity, and energy metabolism was reconstructed during chemical reprogramming, but it did not change from aerobic oxidation to glycolysis. And the cocktail of chemicals and bFGF were non-essential for the in vitro culture of ciXEN cells. [ABSTRACT FROM AUTHOR]

Background: Thermotolerance is a highly desirable trait of microbial cell factories and has been the focus of extensive research. Yeast usually tolerate only a narrow temperature range and just two species, Kluyveromyces marxianus and Ogataea polymorpha have been described to grow at reasonable rates above 40 °C. However, the complex mechanisms of thermotolerance in yeast impede its full comprehension and the rare physiological data at elevated temperatures has so far not been matched with corresponding metabolic analyses. Results: To elaborate on the metabolic network response to increased fermentation temperatures of up to 49 °C, comprehensive physiological datasets of several Kluyveromyces and Ogataea strains were generated and used for 13C-metabolic flux analyses. While the maximum growth temperature was very similar in all investigated strains, the metabolic network response to elevated temperatures was not conserved among the different species. In fact, metabolic flux distributions were remarkably irresponsive to increasing temperatures in O. polymorpha, while the K. marxianus strains exhibited extensive flux rerouting at elevated temperatures. Conclusions: While a clear mechanism of thermotolerance is not deducible from the fluxome level alone, the generated data can be valued as a knowledge repository for using temperature to modulate the metabolic activity towards engineering goals. [ABSTRACT FROM AUTHOR]

Coenzyme Q 10 (CoQ 10 ) is crucial for human beings, especially in the fields of biology and medicine. The aim of this experiment was to investigate the conditions for increasing CoQ 10 production. At present, microbial fermentation is the main production method of CoQ 10 , and the production process of microbial CoQ 10 metabolism control fermentation is very critical. Metabolic flux is one of the most important determinants of cell physiology in metabolic engineering. Metabolic flux analysis (MFA) is used to estimate the intracellular flux in metabolic networks. In this experiment, Rhodobacter sphaeroides was used as the research object to analyze the effects of aqueous ammonia (NH 3 ·H 2 O) and calcium carbonate (CaCO 3 ) on the metabolic flux of CoQ 10 . When CaCO 3 was used to adjust the pH, the yield of CoQ 10 was 274.43 mg·L -1 (8.71 mg·g -1 DCW), which was higher than that of NH 3 ·H 2 O adjustment. The results indicated that when CaCO 3 was used to adjust pH, more glucose-6-phosphate (G6P) entered the pentose phosphate (HMP) pathway and produced more NADPH, which enhanced the synthesis of CoQ 10 . At the chorismic acid node, more metabolic fluxes were involved in the synthesis of p-hydroxybenzoic acid (pHBA; the synthetic precursor of CoQ 10 ), enhancing the anabolic flow of CoQ 10 . In addition, Ca 2+ produced by the reaction of CaCO 3 with organic acids promotes the synthesis of CoQ 10 . In summary, the use of CaCO 3 adjustment is more favorable for the synthesis of CoQ 10 by R. sphaeroides than NH 3 ·H 2 O adjustment. The migration of metabolic flux caused by the perturbation of culture conditions was analyzed to compare the changes in the distribution of intracellular metabolic fluxes for the synthesis of CoQ 10 . Thus, the main nodes of the metabolic network were identified as G6P and chorismic acid. This provides a theoretical basis for the modification of genes related to the CoQ 10 synthesis pathway., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Determining the value of kinetic constants for a metabolic system in the exact physiological conditions is an extremely hard task. However, this kind of information is of pivotal relevance to effectively simulate a biological phenomenon as complex as metabolism. Results: To overcome this issue, we propose to investigate emerging properties of ensembles of sets of kinetic constants leading to the biological readout observed in different experimental conditions. To this aim, we exploit information retrievable from constraint-based analyses (i.e. metabolic flux distributions at steady state) with the goal to generate feasible values for kinetic constants exploiting the mass action law. The sets retrieved from the previous step will be used to parametrize a mechanistic model whose simulation will be performed to reconstruct the dynamics of the system (until reaching the metabolic steady state) for each experimental condition. Every parametrization that is in accordance with the expected metabolic phenotype is collected in an ensemble whose features are analyzed to determine the emergence of properties of a phenotype. In this work we apply the proposed approach to identify ensembles of kinetic parameters for five metabolic phenotypes of E. Coli, by analyzing five different experimental conditions associated with the ECC2comp model recently published by Hädicke and collaborators. Conclusions: Our results suggest that the parameter values of just few reactions are responsible for the emergence of a metabolic phenotype. Notably, in contrast with constraint-based approaches such as Flux Balance Analysis, the methodology used in this paper does not require to assume that metabolism is optimizing towards a specific goal. [ABSTRACT FROM AUTHOR]

Background: Azotobacter vinelandii is a bacterium that produces alginate and polyhydroxybutyrate (P3HB); however, the role of NAD(P)H/NAD(P)+ ratios on the metabolic fluxes through biosynthesis pathways of these biopolymers remains unknown. The aim of this study was to evaluate the NAD(P)H/NAD(P)+ ratios and the metabolic fluxes involved in alginate and P3HB biosynthesis, under oxygen-limiting and non-limiting oxygen conditions. Results: The results reveal that changes in the oxygen availability have an important effect on the metabolic fluxes and intracellular NADPH/NADP+ ratio, showing that at the lowest OTR (2.4 mmol L-1 h-1), the flux through the tricarboxylic acid (TCA) cycle decreased 27.6-fold, but the flux through the P3HB biosynthesis increased 6.6-fold in contrast to the cultures without oxygen limitation (OTR = 14.6 mmol L-1 h-1). This was consistent with the increase in the level of transcription of phbB and the P3HB biosynthesis. In addition, under conditions without oxygen limitation, there was an increase in the carbon uptake rate (twofold), as well as in the flux through the pentose phosphate (PP) pathway (4.8-fold), compared to the condition of 2.4 mmol L-1 h-1. At the highest OTR condition, a decrease in the NADPH/NADP+ ratio of threefold was observed, probably as a response to the high respiration rate induced by the respiratory protection of the nitrogenase under diazotrophic conditions, correlating with a high expression of the uncoupled respiratory chain genes (ndhII and cydA) and induction of the expression of the genes encoding the nitrogenase complex (nifH). Conclusions: We have demonstrated that changes in oxygen availability affect the internal redox state of the cell and carbon metabolic fluxes. This also has a strong impact on the TCA cycle and PP pathway as well as on alginate and P3HB biosynthetic fluxes. [ABSTRACT FROM AUTHOR]

Background: The halophilic bacterium Chromohalobacter salexigens is a natural producer of ectoines, compatible solutes with current and potential biotechnological applications. As production of ectoines is an osmoregulated process that draws away TCA intermediates, bacterial metabolism needs to be adapted to cope with salinity changes. To explore and use C. salexigens as cell factory for ectoine(s) production, a comprehensive knowledge at the systems level of its metabolism is essential. For this purpose, the construction of a robust and high-quality genome-based metabolic model of C. salexigens was approached. Results: We generated and validated a high quality genome-based C. salexigens metabolic model (iFP764). This comprised an exhaustive reconstruction process based on experimental information, analysis of genome sequence, manual re-annotation of metabolic genes, and in-depth refinement. The model included three compartments (periplasmic, cytoplasmic and external medium), and two salinity-specific biomass compositions, partially based on experimental results from C. salexigens. Using previous metabolic data as constraints, the metabolic model allowed us to simulate and analyse the metabolic osmoadaptation of C. salexigens under conditions for low and high production of ectoines. The iFP764 model was able to reproduce the major metabolic features of C. salexigens. Flux Balance Analysis (FBA) and Monte Carlo Random sampling analysis showed salinity-specific essential metabolic genes and different distribution of fluxes and variation in the patterns of correlation of reaction sets belonging to central C and N metabolism, in response to salinity. Some of them were related to bioenergetics or production of reducing equivalents, and probably related to demand for ectoines. Ectoines metabolic reactions were distributed according to its correlation in four modules. Interestingly, the four modules were independent both at low and high salinity conditions, as they did not correlate to each other, and they were not correlated with other subsystems. Conclusions: Our validated model is one of the most complete curated networks of halophilic bacteria. It is a powerful tool to simulate and explore C. salexigens metabolism at low and high salinity conditions, driving to low and high production of ectoines. In addition, it can be useful to optimize the metabolism of other halophilic bacteria for metabolite production. [ABSTRACT FROM AUTHOR]

Background: Production directly from carbon dioxide by engineered cyanobacteria is one of the promising technologies for sustainable future. Previously, we have successfully achieved 1,3-propanediol (1,3-PDO) production using Synechococcus elongatus PCC 7942 with a synthetic metabolic pathway. The strain into which the synthetic metabolic pathway was introduced produced 3.48 mM (0.265 g/L) 1,3-PDO and 14.3 mM (1.32 g/L) glycerol during 20 days of incubation. In this study, the productivities of 1,3-PDO were improved by gene disruption selected by screening with in silico simulation. Methods: First, a stoichiometric metabolic model was applied to prediction of cellular metabolic flux distribution in a 1,3-PDO-producing strain of S. elongatus PCC 7942. A genome-scale model of S. elongatus PCC 7942 constructed by Knoop was modified by the addition of a synthetic metabolic pathway for 1,3-PDO production. Next, the metabolic flux distribution predicted by metabolic flux balance analysis (FBA) was used for in silico simulation of gene disruption. As a result of gene disruption simulation, NADPH dehydrogenase 1 (NDH-1) complexes were found by screening to be the most promising candidates for disruption to improve 1,3-PDO production. The effect of disruption of the gene encoding a subunit of the NDH-1 complex was evaluated in the 1,3-PDO-producing strain. Results and Conclusions: During 20 days of incubation, the ndhF1-null 1,3-PDO-producing strain showed the highest titers: 4.44 mM (0.338 g/L) 1,3-PDO and 30.3 mM (2.79 g/L) glycerol. In this study, we successfully improved 1,3-PDO productivity on the basis of in silico simulation of gene disruption. [ABSTRACT FROM AUTHOR]

Background: Multiplex control of metabolic pathway genes is essential for maximizing product titers and conversion yields of fuels, chemicals, and pharmaceuticals in metabolic engineering. To achieve this goal, artificial transcriptional regulators, such as clustered regularly interspaced short palindromic repeats (CRISPR) interference (CRISPRi), have been developed to specifically repress genes of interest. Results: In this study, we deployed a tunable CRISPRi system for multiplex repression of competing pathway genes and, thus, directed carbon flux toward production of molecules of interest in Escherichia coli. The tunable CRISPRi system with an array of sgRNAs successfully repressed four endogenous genes (pta, frdA, ldhA, and adhE) individually and in double, triple, or quadruple combination that are involved in the formation of byproducts (acetate, succinate, lactate, and ethanol) and the consumption of NADH in E. coli. Single-target CRISPRi effectively reduced the amount of each byproduct and, interestingly, pta repression also decreased ethanol production (41%), whereas ldhA repression increased ethanol production (197%). CRISPRi-mediated multiplex repression of competing pathway genes also resulted in simultaneous reductions of acetate, succinate, lactate, and ethanol production in E. coli. Among 15 conditions repressing byproduct-formation genes, we chose the quadruple-target CRISPRi condition to produce n-butanol in E. coli as a case study. When heterologous n-butanol-pathway enzymes were introduced into E. coli simultaneously repressing the expression of the pta, frdA, ldhA, and adhE genes via CRISPRi, n-butanol yield and productivity increased up to 5.4- and 3.2-fold, respectively. Conclusions: We demonstrated the tunable CRISPRi system to be a robust platform for multiplex modulation of endogenous gene expression that can be used to enhance biosynthetic pathway productivity, with n-butanol as the test case. CRISPRi applications potentially enable the development of microbial "smart cell" factories capable of producing other industrially valuable products. [ABSTRACT FROM AUTHOR]

Background: Malaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug, artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms. Results: Here, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites, including folate and polyamines. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistant parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood. Conclusion: Using this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites. [ABSTRACT FROM AUTHOR]

Background: The increase in glycerol obtained as a byproduct of biodiesel has encouraged the production of new industrial products, such as 1,3-propanediol (PDO), using biotechnological transformation via bacteria like Clostridium butyricum. However, despite the increasing role of Clostridium butyricum as a bio-production platform, its metabolism remains poorly modeled. Results: We reconstructed iCbu641, the first genome-scale metabolic (GSM) model of a PDO producer Clostridium strain, which included 641 genes, 365 enzymes, 891 reactions, and 701 metabolites. We found an enzyme expression prediction of nearly 84% after comparison of proteomic data with flux distribution estimation using flux balance analysis (FBA). The remaining 16% corresponded to enzymes directionally coupled to growth, according to flux coupling findings (FCF). The fermentation data validation also revealed different phenotype states that depended on culture media conditions; for example, Clostridium maximizes its biomass yield per enzyme usage under glycerol limitation. By contrast, under glycerol excess conditions, Clostridium grows sub-optimally, maximizing biomass yield while minimizing both enzyme usage and ATP production. We further evaluated perturbations in the GSM model through enzyme deletions and variations in biomass composition. The GSM predictions showed no significant increase in PDO production, suggesting a robustness to perturbations in the GSM model. We used the experimental results to predict that co-fermentation was a better alternative than iCbu641 perturbations for improving PDO yields. Conclusions: The agreement between the predicted and experimental values allows the use of the GSM model constructed for the PDO-producing Clostridium strain to propose new scenarios for PDO production, such as dynamic simulations, thereby reducing the time and costs associated with experimentation. [ABSTRACT FROM AUTHOR]

Background: The metabolic engineering of Saccharomyces cerevisiae for the production of succinic acid has progressed dramatically, and a series of high-producing hosts are available. At low cultivation pH and high titers, the product transport can become bidirectional, i.e. the acid is reentering the cell and is again exported or even catabolized. Here, a quantitative approach for the identification of product recycling fluxes is developed. Results: The metabolic flux distributions at two time-points of the fermentation process were analyzed. 13C labeled succinic acid was added to the extracellular space and intracellular enrichments were measured and subsequently used for the estimation of metabolic fluxes. The labeling was introduced by a labeling switch experiment, leading to an immediate labeling of about 85% of the acid while keeping the total acid concentration constant. Within 100 s significant labeling enrichment of the TCA cycle intermediates fumarate, iso-citrate and α-ketoglutarate was observed, while no labeling was detected for malate and citrate. These findings suggest that succinic acid is rapidly exchanged over the cellular membrane and enters the oxidative TCA cycle. Remarkably, in the oxidative direction malate 13C enrichment was not detected, indicating that there is no flux going through this metabolite pool. Using flux modeling and thermodynamic assumptions on compartmentation it was concluded that malate must be predominantly cytosolic while fumarate and iso-citrate were more dominant in the mitochondria. Conclusions: Adding labeled product without changing the extracellular environment allowed to quantify intracellular metabolic fluxes under high producing conditions and identify product degradation cycles. In the specific case of succinic acid production, compartmentation was found to play a major role, i.e. the presence of metabolic activity in two different cellular compartments lead to intracellular product degradation reducing the yield. We also observed that the flux from glucose to succinic acid branches at two points in metabolism: (1) At the level of pyruvate, and (2) at cytosolic malate which was not expected. [ABSTRACT FROM AUTHOR]

Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis. [ABSTRACT FROM AUTHOR]

Background: Production of 3-hydroxypropionic acid (3-HP) through the malonyl-CoA pathway has yielded promising results in Pichia pastoris (Komagataella phaffii), demonstrating the potential of this cell factory to produce this platform chemical and other acetyl-CoA-derived products using glycerol as a carbon source. However, further metabolic engineering of the original P. pastoris 3-HP-producing strains resulted in unexpected outcomes, e.g., significantly lower product yield and/or growth rate. To gain an understanding on the metabolic constraints underlying these observations, the fluxome (metabolic flux phenotype) of ten 3-HP-producing P. pastoris strains has been characterized using a high throughput 13 C-metabolic flux analysis platform. Such platform enabled the operation of an optimised workflow to obtain comprehensive maps of the carbon flux distribution in the central carbon metabolism in a parallel-automated manner, thereby accelerating the time-consuming strain characterization step in the design-build-test-learn cycle for metabolic engineering of P. pastoris., Results: We generated detailed maps of the carbon fluxes in the central carbon metabolism of the 3-HP producing strain series, revealing the metabolic consequences of different metabolic engineering strategies aimed at improving NADPH regeneration, enhancing conversion of pyruvate into cytosolic acetyl-CoA, or eliminating by-product (arabitol) formation. Results indicate that the expression of the POS5 NADH kinase leads to a reduction in the fluxes of the pentose phosphate pathway reactions, whereas an increase in the pentose phosphate pathway fluxes was observed when the cytosolic acetyl-CoA synthesis pathway was overexpressed. Results also show that the tight control of the glycolytic flux hampers cell growth due to limited acetyl-CoA biosynthesis. When the cytosolic acetyl-CoA synthesis pathway was overexpressed, the cell growth increased, but the product yield decreased due to higher growth-associated ATP costs. Finally, the six most relevant strains were also cultured at pH 3.5 to assess the effect of a lower pH on their fluxome. Notably, similar metabolic fluxes were observed at pH 3.5 compared to the reference condition at pH 5., Conclusions: This study shows that existing fluoxomics workflows for high-throughput analyses of metabolic phenotypes can be adapted to investigate P. pastoris, providing valuable information on the impact of genetic manipulations on the metabolic phenotype of this yeast. Specifically, our results highlight the metabolic robustness of P. pastoris's central carbon metabolism when genetic modifications are made to increase the availability of NADPH and cytosolic acetyl-CoA. Such knowledge can guide further metabolic engineering of these strains. Moreover, insights into the metabolic adaptation of P. pastoris to an acidic pH have also been obtained, showing the capability of the fluoxomics workflow to assess the metabolic impact of environmental changes., (© 2023. The Author(s).)

Background: Flux analyses, including flux balance analysis (FBA) and 13C-metabolic flux analysis (13C-MFA), offer direct insights into cell metabolism, and have been widely used to characterize model and non-model microbial species. Nonetheless, constructing the 13C-MFA model and performing flux calculation are demanding for new learners, because they require knowledge of metabolic networks, carbon transitions, and computer programming. To facilitate and standardize the 13C-MFA modeling work, we set out to publish a user-friendly and programmingfree platform (WUFlux) for flux calculations in MATLAB®. Results: We constructed an open-source platform for steady-state 13C-MFA. Using GUIDE (graphical user interface design environment) in MATLAB, we built a user interface that allows users to modify models based on their own experimental conditions. WUFlux is capable of directly correcting mass spectrum data of TBDMS (N-tertbutyldimethylsilyl-N-methyltrifluoroacetamide)-derivatized proteinogenic amino acids by removing background noise. To simplify 13C-MFA of different prokaryotic species, the software provides several metabolic network templates, including those for chemoheterotrophic bacteria and mixotrophic cyanobacteria. Users can modify the network and constraints, and then analyze the microbial carbon and energy metabolisms of various carbon substrates (e.g., glucose, pyruvate/lactate, acetate, xylose, and glycerol). WUFlux also offers several ways of visualizing the flux results with respect to the constructed network. To validate our model's applicability, we have compared and discussed the flux results obtained from WUFlux and other MFA software. We have also illustrated how model constraints of cofactor and ATP balances influence fluxome results. Conclusion: Open-source software for 13C-MFA, WUFlux, with a user-friendly interface and easy-to-modify templates, is now available at http://www.13cmfa.org/or (http://tang.eece.wustl.edu/ToolDevelopment.htm). We will continue documenting curated models of non-model microbial species and improving WUFlux performance. [ABSTRACT FROM AUTHOR]

Background: The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. Results: In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10% range). Conclusions: The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations. [ABSTRACT FROM AUTHOR]

Background: Glycerol, a byproduct of biodiesel, has become a readily available and inexpensive carbon source for the production of high-value products. However, the main drawback of glycerol utilization is the low consumption rate and shortage of NADPH formation, which may limit the production of NADPH-requiring products. To overcome these problems, we constructed a carbon catabolite repression-negative ΔptsGglpK* mutant by both blocking a key glucose PTS transporter and enhancing the glycerol conversion. The mutant can recover normal growth by co-utilization of glycerol and glucose after loss of glucose PTS transporter. To reveal the metabolic potential of the ΔptsGglpK* mutant, this study examined the flux distributions and regulation of the co-metabolism of glycerol and glucose in the mutant. Results: By labeling experiments using [1,3-13C]glycerol and [1-13C]glucose, 13C metabolic flux analysis was employed to decipher the metabolisms of both the wild-type strain and the ΔptsGglpK* mutant in chemostat cultures. When cells were maintained at a low dilution rate (0.1 h-1), the two strains showed similar fluxome profiles. When the dilution rate was increased, both strains upgraded their pentose phosphate pathway, glycolysis and anaplerotic reactions, while the ΔptsGglpK* mutant was able to catabolize much more glycerol than glucose (more than tenfold higher). Compared with the wild-type strain, the mutant repressed its flux through the TCA cycle, resulting in higher acetate overflow. The regulation of fluxomes was consistent with transcriptional profiling of several key genes relevant to the TCA cycle and transhydrogenase, namely gltA, icdA, sdhA and pntA. In addition, cofactor fluxes and their pool sizes were determined. The ΔptsGglpK* mutant affected the redox NADPH/NADH state and reduced the ATP level. Redox signaling activated the ArcA regulatory system, which was responsible for TCA cycle repression. Conclusions: This work employs both 13C-MFA and transcription/metabolite analysis for quantitative investigation of the co-metabolism of glycerol and glucose in the ΔptsGglpK* mutant. The ArcA regulatory system dominates the control of flux redistribution. The ΔptsGglpK* mutant can be used as a platform for microbial cell factories for the production of biofuels and biochemicals, since most of fuel molecule (e.g., alcohols) synthesis requires excess reducing equivalents. [ABSTRACT FROM AUTHOR]

Background: Two variants of Methylobacterium extorquens AM1 demonstrated a trade-off between growth rate and biomass yield. In addition, growth rate and biomass yield were also affected by supplementation of growth medium with different amounts of cobalt. The metabolism changes relating to these growth phenomena as well as the trade-off were investigated in this study. 13C metabolic flux analysis was used to generate a detailed central carbon metabolic flux map with both absolute and normalized flux values. Results: The major differences between the two variants occurred at the formate node as well as within C3-C4 inter-conversion pathways. Higher relative fluxes through formyltetrahydrofolate ligase, phosphoenolpyruvate carboxylase, and malic enzyme led to higher biomass yield, while higher relative fluxes through pyruvate kinase and pyruvate dehydrogenase led to higher growth rate. These results were then tested by phenotypic studies on three mutants (null pyk, null pck mutant and null dme mutant) in both variants, which agreed with the model prediction. Conclusions: In this study, 13C metabolic flux analysis for two strain variants of M. extorquens AM1 successfully identified metabolic pathways contributing to the trade-off between cell growth and biomass yield. Phenotypic analysis of mutants deficient in corresponding genes supported the conclusion that C3-C4 inter-conversion strategies were the major response to the trade-off. [ABSTRACT FROM AUTHOR]

Background: Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Results: Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples. Conclusions: The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations. [ABSTRACT FROM AUTHOR]

Background: The flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function. To quantify the functional relevance of individual biochemical reactions, functional centrality has been introduced based on cooperative game theory and structural modeling. It was shown to be capable to determine metabolic control properties utilizing only structural information. Here, we demonstrate the capability of functional centrality to predict changes in the flux phenotype. Results: We use functional centrality to successfully predict changes of metabolic flux triggered by switches in the environment. The predictions via functional centrality improve upon predictions using control-effective fluxes, another measure aiming at capturing metabolic control using structural information. Conclusions: The predictions of flux changes via functional centrality corroborate the capability of the measure to gain a mechanistic understanding of metabolic control from the structure of metabolic networks. [ABSTRACT FROM AUTHOR]

Background: Given its high surplus and low cost, glycerol has emerged as interesting carbon substrate for the synthesis of value-added chemicals. The soil bacterium Pseudomonas putida KT2440 can use glycerol to synthesize medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHA), a class of biopolymers of industrial interest. Here, glycerol metabolism in P. putida KT2440 was studied on the level of gene expression (transcriptome) and metabolic fluxes (fluxome), using precisely adjusted chemostat cultures, growth kinetics and stoichiometry, to gain a systematic understanding of the underlying metabolic and regulatory network. Results: Glycerol-grown P. putida KT2440 has a maintenance energy requirement [0.039 (mmolglycerol (gCDW h)-1)] that is about sixteen times lower than that of other bacteria, such as Escherichia coli, which provides a great advantage to use this substrate commercially. The shift from carbon (glycerol) to nitrogen (ammonium) limitation drives the modulation of specific genes involved in glycerol metabolism, transport electron chain, sensors to assess the energy level of the cell, and PHA synthesis, as well as changes in flux distribution to increase the precursor availability for PHA synthesis (Entner-Doudoroff pathway and pyruvate metabolism) and to reduce respiration (glyoxylate shunt). Under PHA-producing conditions (N-limitation), a higher PHA yield was achieved at low dilution rate (29.7 wt% of CDW) as compared to a high rate (12.8 wt% of CDW). By-product formation (succinate, malate) was specifically modulated under these regimes. On top of experimental data, elementary flux mode analysis revealed the metabolic potential of P. putida KT2440 to synthesize PHA and identified metabolic engineering targets towards improved production performance on glycerol. Conclusion: This study revealed the complex interplay of gene expression levels and metabolic fluxes under PHAand non-PHA producing conditions using the attractive raw material glycerol as carbon substrate. This knowledge will form the basis for the development of future metabolically engineered hyper-PHA-producing strains derived from the versatile bacterium P. putida KT2440. [ABSTRACT FROM AUTHOR]

Background: Non-negative linear combinations of elementary flux modes (EMs) describe all feasible reaction flux distributions for a given metabolic network under the quasi steady state assumption. However, only a small subset of EMs contribute to the physiological state of a given cell. Results: In this paper, a method is proposed that identifies the subset of EMs that best explain the physiological state captured in reaction flux data, referred to as principal EMs (PEMs), given a pre-specified universe of EM candidates. The method avoids the evaluation of all possible combinations of EMs by using a branch and bound approach which is computationally very efficient. The performance of the method is assessed using simulated and experimental data of Pichia pastoris and experimental fluxome data of Saccharomyces cerevisiae. The proposed method is benchmarked against principal component analysis (PCA), commonly used to study the structure of metabolic flux data sets. Conclusions: The overall results show that the proposed method is computationally very effective in identifying the subset of PEMs within a large set of EM candidates (cases with ~100 and ~1000 EMs were studied). In contrast to the principal components in PCA, the identified PEMs have a biological meaning enabling identification of the key active pathways in a cell as well as the conditions under which the pathways are activated. This method clearly outperforms PCA in the interpretability of flux data providing additional insights into the underlying regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Background: Expression of cell phenotypes highly depends on metabolism that supplies matter and energy. To achieve proper utilisation of the different metabolic pathways, metabolism is tightly regulated by a complex regulatory network composed of diverse biological entities (genes, transcripts, proteins, signallingmolecules. . . ). The integrated analysis of both regulatory and metabolic networks appears very insightful but is not straightforward because of the distinct characteristics of both networks. The classical method used for metabolic flux analysis is Flux Balance Analysis (FBA), which is constraint-based and relies on the assumption of steady-state metabolite concentrations throughout the network. Regarding regulatory networks, a broad spectrum of methods are dedicated to their analysis although logical modelling remains the major method to take charge of large-scale networks. Results: We present FlexFlux, an application implementing a new way to combine the analysis of both metabolic and regulatory networks, based on simulations that do not require kinetic parameters and can be applied to genome-scale networks. FlexFlux is based on seeking regulatory network steady-states by performing synchronous updates of multi-state qualitative initial values. FlexFlux is then able to use the calculated steady-state values as constraints for metabolic flux analyses using FBA. As input, FlexFlux uses the standards Systems Biology Markup Language (SBML) and SBML Qualitative Models Package ("qual") extension (SBML-qual) file formats and provides a set of FBA based functions. Conclusions: FlexFlux is an open-source java software with executables and full documentation available online at http://lipm-bioinfo.toulouse.inra.fr/flexflux/. It can be defined as a research tool that enables a better understanding of both regulatory and metabolic networks based on steady-state simulations. FlexFlux integrates well in the flux analysis ecosystem thanks to the support of standard file formats and can thus be used as a complementary tool to existing software featuring other types of analyses. [ABSTRACT FROM AUTHOR]

Background: High-throughput screening methods assume that the output measured is representative of changes in metabolic flux toward the desired product and is not affected by secondary phenotypes. However, metabolic engineering can result in unintended phenotypes that may go unnoticed in initial screening. The red pigment lycopene, a carotenoid with antioxidant properties, has been used as a reporter of isoprenoid pathway flux in metabolic engineering for over a decade. Lycopene production is known to vary between wild-type Escherichia coli hosts, but the reasons behind this variation have never been fully elucidated. Results: In an examination of six E. coli strains we observed that strains also differ in their capacity for increased lycopene production in response to metabolic engineering. A combination of genetic complementation, quantitative SWATH proteomics, and biochemical analysis in closely-related strains was used to examine the mechanistic reasons for variation in lycopene accumulation. This study revealed that rpoS, a gene previously identified in lycopene production association studies, exerts its effect on lycopene accumulation not through modulation of pathway flux, but through alteration of cellular oxidative status. Specifically, absence of rpoS results in increased accumulation of reactive oxygen species during late log and stationary phases. This change in cellular redox has no effect on isoprenoid pathway flux, despite the presence of oxygen-sensitive iron-sulphur cluster enzymes and the heavy redox requirements of the methylerythritol phosphate pathway. Instead, decreased cellular lycopene in the ?rpoS strain is caused by degradation of lycopene in the presence of excess reactive oxygen species. Conclusions: Our results demonstrate that lycopene is not a reliable indicator of isoprenoid pathway flux in the presence of oxidative stress, and suggest that caution should be exercised when using lycopene as a screening tool in genome-wide metabolic engineering studies. More extensive use of systems biology for strain analysis will help elucidate such unpredictable side-effects in metabolic engineering projects. [ABSTRACT FROM AUTHOR]

Background: A universal feature of metabolic networks is their hourglass or bow-tie structure on cellular level. This architecture reflects the conversion of multiple input nutrients into multiple biomass components via a small set of precursor metabolites. However, it is yet unclear to what extent this structural feature is the result of natural selection. Results: We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networks can be calculated for different environmental conditions. We observe a significant structural reshaping of metabolic networks for a toy-network and E. coli core metabolism if we increase the share of invested resources for switching between different nutrient conditions. Here, hub nodes emerge and the optimal network structure becomes bow-tie-like as a consequence of limited cellular resource constraint. We confirm this theoretical finding by comparing the reconstructed metabolic networks of bacterial species with respect to their lifestyle. Conclusions: We show that bow-tie structure can give a system-level fitness advantage to organisms that live in highly competitive and fluctuating environments. Here, limitation of cellular resources can lead to an efficiencyflexibility tradeoff where it pays off for the organism to shorten catabolic pathways if they are frequently activated and deactivated. As a consequence, generalists that shuttle between diverse environmental conditions should have a more predominant bow-tie structure than specialists that visit just a few isomorphic habitats during their life cycle. [ABSTRACT FROM AUTHOR]

Background: Isotope labeling experiments (ILEs) are increasingly used to investigate the functioning of metabolic systems. Some enzymes are subject to kinetic isotope effects (KIEs) which modulate reaction rates depending on the isotopic composition of their substrate(s). KIEs may therefore affect both the propagation of isotopes through metabolic networks and their operation, and ultimately jeopardize the biological value of ILEs. However, the actual impact of KIEs on metabolism has never been investigated at the system level. Results: First, we developed a framework which integrates KIEs into kinetic and isotopic models of metabolism, thereby accounting for their system-wide effects on metabolite concentrations, metabolic fluxes, and isotopic patterns. Then, we applied this framework to assess the impact of KIEs on the central carbon metabolism of Escherichia coli in the context of 13C-ILEs, under different situations commonly encountered in laboratories. Results showed that the impact of KIEs strongly depends on the label input and on the variable considered but is significantly lower than expected intuitively from measurements on isolated enzymes. The global robustness of both the metabolic operation and isotopic patterns largely emerge from intrinsic properties of metabolic networks, such as the distribution of control across the network and bidirectional isotope exchange. Conclusions: These results demonstrate the necessity of investigating the impact of KIEs at the level of the entire system, contradict previous hypotheses that KIEs would have a strong effect on isotopic distributions and on flux determination, and strengthen the biological value of 13C-ILEs. The proposed modeling framework is generic and can be used to investigate the impact of all the isotopic tracers (2H, 13C, 15N, 18O, etc.) on different isotopic datasets and metabolic systems. By allowing the integration of isotopic and metabolomics data collected under stationary and/or non-stationary conditions, it may also assist interpretations of ILEs and facilitate the development of more accurate kinetic models with improved explicative and predictive capabilities. [ABSTRACT FROM AUTHOR]

Unlike xylose-converting natural yeasts, recombinant strains of Saccharomyces cerevisiae expressing the same xylose assimilation pathway produce under anaerobic conditions xylitol rather than ethanol from xylose at low specific xylose conversion rates. Despite intense research efforts over the last two decades, differences in these phenotypes cannot be explained by current metabolic and kinetic models. To improve our understanding how metabolic flux of xylose carbon to ethanol is controlled, we developed a novel kinetic model based on enzyme mechanisms and applied quantitative metabolite profiling together with enzyme activity analysis to study xylose-to-ethanol metabolisms of Candida tenuis CBS4435 (qxylose = 0.10 g/gdc/h, 25 °C; Yethanol = 0.44 g/g; Yxylitol = 0.09 g/g) and the recombinant S. cerevisiae strain BP000 (qxylose = 0.07 g/gdc/h, 30 °C; Yethanol = 0.24 g/g; Yxylitol = 0.43 g/g), both expressing the same xylose reductase (XR), comprehensively. Results: Results from strain-to-strain metabolic control analysis indicated that activity levels of XR and the maximal flux capacity of the upper glycolysis (UG; both = tenfold higher in CBS4435) contributed predominantly to phenotype differentiation while reactions from the oxidative pentose phosphate pathway played minor roles. Intracellular metabolite profiles supported results obtained from kinetic modeling and indicated a positive correlation between pool sizes of UG metabolites and carbon flux through the UG. For CBS4435, fast carbon flux through the UG could be associated with an allosteric control of 6-phosphofructokinase (PFK) activity by fructose 6-phosphate. The ability of CBS4435 to keep UG metabolites at high levels could be explained by low glycerol 3-phosphate phosphatase (GPP, 17-fold lower in CBS4435) and high XR activities. Conclusions: By applying a systems biology approach in which we combined results obtained from metabolic control analysis based on kinetic modeling with data obtained from quantitative metabolite profiling and enzyme activity analyses, we could provide new insights into metabolic and kinetic interactions contributing to the control of carbon flux from xylose to ethanol. Supported by evidences presented two new targets, PFK and GPP, could be identified that aside from XR play pivotal roles in phenotype differentiation. Design of efficient and fast microbial ethanol producers in the future can certainly benefit from results presented in this study. [ABSTRACT FROM AUTHOR]

Background: Aspergillus niger is widely used for enzyme production and achievement of high enzyme production depends on the comprehensive understanding of cell's metabolic regulation mechanisms. Results: In this paper, we investigate the metabolic differences and regulation mechanisms between a high glucoamylase-producing strain A. niger DS03043 and its wild-type parent strain A. niger CBS513.88 via an integrated isotope-assisted metabolomics and 13C metabolic flux analysis approach. We found that A. niger DS03043 had higher cell growth, glucose uptake, and glucoamylase production rates but lower oxalic acid and citric acid secretion rates. In response to above phenotype changes, A. niger DS03043 was characterized by an increased carbon flux directed to the oxidative pentose phosphate pathway in contrast to reduced flux through TCA cycle, which were confirmed by consistent changes in pool sizes of metabolites. A higher ratio of ATP over AMP in the high producing strain might contribute to the increase in the PP pathway flux as glucosephosphate isomerase was inhibited at higher ATP concentrations. A. niger CBS513.88, however, was in a higher redox state due to the imbalance of NADH regeneration and consumption, resulting in the secretion of oxalic acid and citric acid, as well as the accumulation of intracellular OAA and PEP, which may in turn result in the decrease in the glucose uptake rate. Conclusions: The application of integrated metabolomics and 13C metabolic flux analysis highlights the regulation mechanisms of energy and redox metabolism on flux redistribution in A. niger. [ABSTRACT FROM AUTHOR]

Background: Metabolic derangement is a key hallmark of major traumatic injury. The recent introduction of mass spectrometry-based metabolomics technologies in the field of trauma shed new light on metabolic aberrations in plasma that are triggered by trauma and hemorrhagic shock. Alteration in metabolites associated with catabolism, acidosis and hyperglycemia have been identified. However, the mechanisms underlying fluxes driving such metabolic adaptations remain elusive. Methods: A bolus of U-13C-glucose was injected in Sprague–Dawley rats at different time points. Plasma extracts were analyzed via ultra-high performance liquid chromatography-mass spectrometry to detect quantitative fluctuations in metabolite levels as well as to trace the distribution of heavy labeled carbon isotopologues. Results: Rats experiencing trauma did not show major plasma metabolic aberrations. However, trauma/hemorrhagic shock triggered severe metabolic derangement, resulting in increased glucose levels, lactate and carboxylic acid accumulation. Isotopologue distributions in late Krebs cycle metabolites (especially succinate) suggested a blockade at complex I and II of the electron transport chain, likely due to mitochondrial uncoupling. Urate increased after trauma and hemorrhage. Increased levels of unlabeled mannitol and citramalate, metabolites of potential bacterial origin, were also observed in trauma/hemorrhagic shock rats, but not trauma alone or controls. Conclusions: These preliminary results are consistent with observations we have recently obtained in humans, and expand upon our early results on rodent models of trauma and hemorrhagic shock by providing the kinetics of glucose fluxes after trauma and hemorrhage. Despite the preliminary nature of this study, owing to the limited number of biological replicates, results highlight a role for shock, rather than trauma alone, in eliciting systemic metabolic aberrations. This study provides the foundation for tracing experiments in rat models of trauma. The goal is to improve our understanding of substrate specific metabolic derangements in trauma/hemorrhagic shock, so as to design resuscitative strategies tailored toward metabolic alterations and the severity of trauma. [ABSTRACT FROM AUTHOR]

Background: Understanding the metabolism of the microbial host is essential for the development and optimization of whole-cell based biocatalytic processes, as it dictates production efficiency. This is especially true for redox biocatalysis where metabolically active cells are employed because of the cofactor/cosubstrate regenerative capacity endogenous in the host. Recombinant Escherichia coli was used for overproducing proline-4-hydroxylase (P4H), a dioxygenase catalyzing the hydroxylation of free L-proline into trans-4-hydroxy-L-proline with α-ketoglutarate (α-KG) as cosubstrate. In this whole-cell biocatalyst, central carbon metabolism provides the required cosubstrate α-KG, coupling P4H biocatalytic performance directly to carbon metabolism and metabolic activity. By applying both experimental and computational biology tools, such as metabolic engineering and 13C-metabolic flux analysis (13C-MFA), we investigated and quantitatively described the physiological, metabolic, and bioenergetic response of the whole-cell biocatalyst to the targeted bioconversion and identified possible metabolic bottlenecks for further rational pathway engineering. Results: A proline degradation-deficient E. coli strain was constructed by deleting the putA gene encoding proline dehydrogenase. Whole-cell biotransformations with this mutant strain led not only to quantitative proline hydroxylation but also to a doubling of the specific trans-4-L-hydroxyproline (hyp) formation rate, compared to the wild type. Analysis of carbon flux through central metabolism of the mutant strain revealed that the increased α-KG demand for P4H activity did not enhance the α-KG generating flux, indicating a tightly regulated TCA cycle operation under the conditions studied. In the wild type strain, P4H synthesis and catalysis caused a reduction in biomass yield. Interestingly, the AputA strain additionally compensated the associated ATP and NADH loss by reducing maintenance energy demands at comparably low glucose uptake rates, instead of increasing the TCA activity. Conclusions: The putA knockout in recombinant E. coli BL21(DE3)(pLysS) was found to be promising for productive P4H catalysis not only in terms of biotransformation yield, but also regarding the rates for biotransformation and proline uptake and the yield of hyp on the energy source. The results indicate that, upon a putA knockout, the coupling of the TCA-cycle to proline hydroxylation via the cosubstrate α-KG becomes a key factor constraining and a target to further improve the efficiency of α-KG-dependent biotransformations. [ABSTRACT FROM AUTHOR]

Background: Microbial communities adapt to environmental conditions for optimizing metabolic flux. Such adaption may include cooperative mechanisms eventually resulting in phenotypic observables as emergent properties that cannot be attributed to an individual species alone. Understanding the molecular basis of cross-species cooperation adds to utilization of microbial communities in industrial applications including metal bioleaching and bioremediation processes. With significant advancements in metagenomics the composition of microbial communities became amenable for integrative analysis on the level of entangled molecular processes involving more than one species, in turn offering a data matrix for analyzing the molecular basis of cooperative phenomena. Methods: We present an analysis framework aligned with a dynamical hierarchies concept for unraveling emergent properties in microbial communities, and exemplify this approach for a co-culture setting of At. ferrooxidans and At. thiooxidans. This minimum microbial community demonstrates a significant increase in bioleaching efficiency compared to the activity of individual species, involving mechanisms of the thiosulfate, the polysulfide and the iron oxidation pathway. Results: Populating gene-centric data structures holding rich functional annotation and interaction information allows deriving network models at the functional level coupling energy production and transport processes of both microbial species. Applying a network segmentation approach on the interaction network of ortholog genes covering energy production and transport proposes a set of specific molecular processes of relevance in bioleaching. The resulting molecular process model essentially involves functionalities such as iron oxidation, nitrogen metabolism and proton transport, complemented by sulfur oxidation and nitrogen metabolism, as well as a set of ion transporter functionalities. At. ferrooxidans-specific genes embedded in the molecular model representation hold gene functions supportive for ammonia utilization as well as for biofilm formation, resembling key elements for effective chalcopyrite bioleaching as emergent property in the co-culture situation. Conclusions: Analyzing the entangled molecular processes of a microbial community on the level of segmented, gene-centric interaction networks allows identification of core molecular processes and functionalities adding to our mechanistic understanding of emergent properties of microbial consortia. [ABSTRACT FROM AUTHOR]

Background Constraint-based modeling of genome-scale metabolic network reconstructions has become a widely used approach in computational biology. Flux coupling analysis is a constraint-based method that analyses the impact of single reaction knockouts on other reactions in the network. Results We present an extension of flux coupling analysis for double and multiple gene or reaction knockouts, and develop corresponding algorithms for an in silico simulation. To evaluate our method, we perform a full single and double knockout analysis on a selection of genome-scale metabolic network reconstructions and compare the results. Software A prototype implementation of double knockout simulation is available at http://hoverboard.io/L4FC. [ABSTRACT FROM AUTHOR]