scholarly journals Charting the metabolic landscape of the facultative methylotroph Bacillus methanolicus

2019 ◽  
Author(s):  
Baudoin Delépine ◽  
Marina Gil López ◽  
Marc Carnicer ◽  
Cláudia M. Vicente ◽  
Volker F. Wendisch ◽  
...  
Keyword(s):  
Metabolic Flux ◽  
Reaction Rates ◽  
Computational Method ◽  
Flux Analysis ◽  
Industrial Chemistry ◽  
Facultative Methylotroph ◽  
Cell Factories ◽  
Bacillus Methanolicus ◽  
Metabolic States

ABSTRACTBacillus methanolicus MGA3 is a thermotolerant and relatively fast-growing methylotroph able to secrete large quantities of glutamate and lysine. These natural characteristics make B. methanolicus a good candidate to become a new industrial chassis organism, especially in a methanol-based economy. This has motivated a number of omics studies of B. methanolicus at the genome, transcript, protein and metabolic levels. Intriguingly, the only substrates known to support B. methanolicus growth as sole source of carbon and energy are methanol, mannitol, and to a lesser extent glucose and arabitol. We hypothesized that comparing methylotrophic and non-methylotrophic metabolic states at the flux level would yield new insights into MGA3 metabolism. 13C metabolic flux analysis (13C-MFA) is a powerful computational method to estimate carbon flows from substrate to biomass (i.e. the in vivo reaction rates of the central metabolic pathways) from experimental labeling data. In this study, we designed and performed a 13C-MFA of the facultative methylotroph B. methanolicus MGA3 growing on methanol, mannitol and arabitol to compare the associated metabolic states. The results obtained validate previous findings on the methylotrophy of B. methanolicus, allowed us to characterize the assimilation pathway of one of the studied carbon sources, and provide a better overall understanding of this strain.IMPORTANCEMethanol is cheap, easy to transport and can be produced both from renewable and fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as B. methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories, or to design methylotrophic capability in other strains already used by the industry.

scholarly journals Charting the Metabolic Landscape of the Facultative Methylotroph Bacillus methanolicus

mSystems ◽  
2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Baudoin Delépine ◽  
Marina Gil López ◽  
Marc Carnicer ◽  
Cláudia M. Vicente ◽  
Volker F. Wendisch ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Carbon Source ◽  
Industrial Chemistry ◽  
Content Type ◽  
Facultative Methylotroph ◽  
Cell Factories ◽  
Bacillus Methanolicus ◽  
Methanol Economy ◽  
Natural Strains ◽  
Potential Carbon

Methanol is inexpensive, is easy to transport, and can be produced both from renewable and from fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as Bacillus methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories or to design methylotrophic capability in other strains already used by the industry.

scholarly journals Robustifying Experimental Tracer Design for13C-Metabolic Flux Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Martin Beyß ◽  
Victor D. Parra-Peña ◽  
Howard Ramirez-Malule ◽  
Katharina Nöh
Keyword(s):  
Experimental Design ◽  
Prior Knowledge ◽  
Metabolic Flux Analysis ◽  
Metabolic Flux ◽  
Streptomyces Clavuligerus ◽  
Reaction Rates ◽  
Computational Method ◽  
Flux Analysis ◽  
Metabolic Reaction ◽  
Diverse Range

13C metabolic flux analysis (MFA) has become an indispensable tool to measure metabolic reaction rates (fluxes) in living organisms, having an increasingly diverse range of applications. Here, the choice of the13C labeled tracer composition makes the difference between an information-rich experiment and an experiment with only limited insights. To improve the chances for an informative labeling experiment, optimal experimental design approaches have been devised for13C-MFA, all relying on some a priori knowledge about the actual fluxes. If such prior knowledge is unavailable, e.g., for research organisms and producer strains, existing methods are left with a chicken-and-egg problem. In this work, we present a general computational method, termed robustified experimental design (R-ED), to guide the decision making about suitable tracer choices when prior knowledge about the fluxes is lacking. Instead of focusing on one mixture, optimal for specific flux values, we pursue a sampling based approach and introduce a new design criterion, which characterizes the extent to which mixtures are informative in view of all possible flux values. The R-ED workflow enables the exploration of suitable tracer mixtures and provides full flexibility to trade off information and cost metrics. The potential of the R-ED workflow is showcased by applying the approach to the industrially relevant antibiotic producer Streptomyces clavuligerus, where we suggest informative, yet economic labeling strategies.

scholarly journals In vivo 13C MRS in the mouse brain at 14.1 Tesla and metabolic flux quantification under infusion of [1,6-13C2]glucose

2017 ◽  
Vol 38 (10) ◽  
pp. 1701-1714 ◽  
Author(s):  
Marta Lai ◽  
Bernard Lanz ◽  
Carole Poitry-Yamate ◽  
Jackeline F Romero ◽  
Corina M Berset ◽  
...  
Keyword(s):  
Mouse Brain ◽  
Metabolic Flux ◽  
Direct Detection ◽  
Tricarboxylic Acid Cycle ◽  
Quantitative Information ◽  
Glutamine Metabolism ◽  
Resonance Spectroscopy ◽  
Flux Analysis ◽  
Carboxylase Activity

In vivo 13C magnetic resonance spectroscopy (MRS) enables the investigation of cerebral metabolic compartmentation while, e.g. infusing 13C-labeled glucose. Metabolic flux analysis of 13C turnover previously yielded quantitative information of glutamate and glutamine metabolism in humans and rats, while the application to in vivo mouse brain remains exceedingly challenging. In the present study, 13C direct detection at 14.1 T provided highly resolved in vivo spectra of the mouse brain while infusing [1,6-13C2]glucose for up to 5 h. 13C incorporation to glutamate and glutamine C4, C3, and C2 and aspartate C3 were detected dynamically and fitted to a two-compartment model: flux estimation of neuron-glial metabolism included tricarboxylic acid cycle (TCA) flux in astrocytes (Vg = 0.16 ± 0.03 µmol/g/min) and neurons (VTCAn = 0.56 ± 0.03 µmol/g/min), pyruvate carboxylase activity (VPC = 0.041 ± 0.003 µmol/g/min) and neurotransmission rate (VNT = 0.084 ± 0.008 µmol/g/min), resulting in a cerebral metabolic rate of glucose (CMRglc) of 0.38 ± 0.02 µmol/g/min, in excellent agreement with that determined with concomitant 18F-fluorodeoxyglucose positron emission tomography (18FDG PET).We conclude that modeling of neuron-glial metabolism in vivo is accessible in the mouse brain from 13C direct detection with an unprecedented spatial resolution under [1,6-13C2]glucose infusion.

scholarly journals Bayesian metabolic flux analysis reveals intracellular flux couplings

2019 ◽  
Vol 35 (14) ◽  
pp. i548-i557 ◽  
Author(s):  
Markus Heinonen ◽  
Maria Osmala ◽  
Henrik Mannerström ◽  
Janne Wallenius ◽  
Samuel Kaski ◽  
...  
Keyword(s):  
Steady State ◽  
Metabolic Flux Analysis ◽  
Metabolic Flux ◽  
Reaction Network ◽  
Reaction Rates ◽  
Supplementary Information ◽  
Flux Analysis ◽  
Metabolic Reaction ◽  
Metabolic Systems ◽  
Genome Scale

AbstractMotivationMetabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.ResultsWe introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.Availability and implementationThe COBRA compatible software is available at github.com/markusheinonen/bamfa.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals 2H and 13C metabolic flux analysis elucidates in vivo thermodynamics of the ED pathway in Zymomonas mobilis

2019 ◽  
Vol 54 ◽  
pp. 301-316 ◽  
Author(s):  
Tyler B. Jacobson ◽  
Paul A. Adamczyk ◽  
David M. Stevenson ◽  
Matthew Regner ◽  
John Ralph ◽  
...  
Keyword(s):  
Metabolic Flux Analysis ◽  
Zymomonas Mobilis ◽  
Metabolic Flux ◽  
Flux Analysis ◽  
13C Metabolic Flux Analysis

scholarly journals iMTBGO: An Algorithm for Integrating Metabolic Networks with Transcriptomes Based on Gene Ontology Analysis

2019 ◽  
Vol 20 (4) ◽  
pp. 252-259
Author(s):  
Zhitao Mao ◽  
Hongwu Ma
Keyword(s):  
Gene Expression ◽  
Metabolic Networks ◽  
Metabolic Flux ◽  
Network Models ◽  
Reaction Rates ◽  
Marker Genes ◽  
Published Data ◽  
Flux Analysis ◽  
Prediction Errors ◽  
Balance Analysis

Background:Constraint-based metabolic network models have been widely used in phenotypic prediction and metabolic engineering design. In recent years, researchers have attempted to improve prediction accuracy by integrating regulatory information and multiple types of “omics” data into this constraint-based model. The transcriptome is the most commonly used data type in integration, and a large number of FBA (flux balance analysis)-based integrated algorithms have been developed.Methods and Results:We mapped the Kcat values to the tree structure of GO terms and found that the Kcat values under the same GO term have a higher similarity. Based on this observation, we developed a new method, called iMTBGO, to predict metabolic flux distributions by constraining reaction boundaries based on gene expression ratios normalized by marker genes under the same GO term. We applied this method to previously published data and compared the prediction results with other metabolic flux analysis methods which also utilize gene expression data. The prediction errors of iMTBGO for both growth rates and fluxes in the central metabolic pathways were smaller than those of earlier published methods.Conclusion:Considering the fact that reaction rates are not only determined by genes/expression levels, but also by the specific activities of enzymes, the iMTBGO method allows us to make more precise predictions of metabolic fluxes by using expression values normalized based on GO.

scholarly journals Physiological Dynamic Compression Regulates Central Energy Metabolism in Primary Human Chondrocytes

2018 ◽  
Author(s):  
Daniel Salinas ◽  
Brendan M. Mumey ◽  
Ronald K. June
Keyword(s):  
Mechanical Loading ◽  
Metabolic Flux ◽  
Dynamic Compression ◽  
Building Blocks ◽  
Essential Amino Acids ◽  
Flux Analysis ◽  
Central Metabolism ◽  
Osteoarthritic Chondrocytes ◽  
Components Analysis

AbstractChondrocytes use the pathways of central metabolism to synthesize molecular building blocks and energy for cartilage homeostasis. An interesting feature of the in vivo chondrocyte environment is the cyclical loading generated in various activities (e.g. walking). However, it is unknown if central metabolism is altered by mechanical loading. We hypothesized that physiological dynamic compression alters central metabolism in chondrocytes to promote production of amino acid precursors for matrix synthesis. We measured the expression of central metabolites (e.g. glucose, its derivatives, and relevant co-factors) for primary human osteoarthritic chondrocytes in response to 0-30 minutes of compression. To analyze the data, we used principal components analysis and ANOVA simultaneous components analysis, as well as metabolic flux analysis. Compression induced metabolic responses consistent with our hypothesis. Additionally, these data show that chondrocyte samples from different patient donors exhibit different sensitivity to compression. Most important, we find that grade IV osteoarthritic chondrocytes are capable of synthesizing non-essential amino acids and precursors in response to mechanical loading. These results suggest that further advances in metabolic engineering of chondrocyte mechanotransduction may yield novel translational strategies for cartilage repair.

scholarly journals In Vivo Metabolism of [1,6-13C2]Glucose Reveals Distinct Neuroenergetic Functionality between Mouse Hippocampus and Hypothalamus

Metabolites ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Antoine Cherix ◽  
Rajesh Sonti ◽  
Bernard Lanz ◽  
Hongxia Lei
Keyword(s):  
Metabolic Flux ◽  
Aerobic Glycolysis ◽  
Resonance Spectroscopy ◽  
Flux Analysis ◽  
Gamma Aminobutyric Acid ◽  
Atp Production ◽  
Functional Features ◽  
Metabolic Dependence ◽  
The Brain

Glucose is a major energy fuel for the brain, however, less is known about specificities of its metabolism in distinct cerebral areas. Here we examined the regional differences in glucose utilization between the hypothalamus and hippocampus using in vivo indirect 13C magnetic resonance spectroscopy (1H-[13C]-MRS) upon infusion of [1,6-13C2]glucose. Using a metabolic flux analysis with a 1-compartment mathematical model of brain metabolism, we report that compared to hippocampus, hypothalamus shows higher levels of aerobic glycolysis associated with a marked gamma-aminobutyric acid-ergic (GABAergic) and astrocytic metabolic dependence. In addition, our analysis suggests a higher rate of ATP production in hypothalamus that is accompanied by an excess of cytosolic nicotinamide adenine dinucleotide (NADH) production that does not fuel mitochondria via the malate-aspartate shuttle (MAS). In conclusion, our results reveal significant metabolic differences, which might be attributable to respective cell populations or functional features of both structures.

scholarly journals Red blood cells in hemorrhagic shock: a critical role for glutaminolysis in fueling alanine transamination in rats

2017 ◽  
Vol 1 (17) ◽  
pp. 1296-1305 ◽  
Author(s):  
Julie A. Reisz ◽  
Anne L. Slaughter ◽  
Rachel Culp-Hill ◽  
Ernest E. Moore ◽  
Christopher C. Silliman ◽  
...  
Keyword(s):  
Hemorrhagic Shock ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Metabolic Flux ◽  
Critical Role ◽  
Metabolic Reprogramming ◽  
Flux Analysis ◽  
Sprague Dawley ◽  
Life Years

Abstract Red blood cells (RBCs) are the most abundant host cell in the human body and play a critical role in oxygen transport and systemic metabolic homeostasis. Hypoxic metabolic reprogramming of RBCs in response to high-altitude hypoxia or anaerobic storage in the blood bank has been extensively described. However, little is known about the RBC metabolism following hemorrhagic shock (HS), the most common preventable cause of death in trauma, the global leading cause of total life-years lost. Metabolomics analyses were performed through ultra-high pressure liquid chromatography–mass spectrometry on RBCs from Sprague-Dawley rats undergoing HS (mean arterial pressure [MAP], <30 mm Hg) in comparison with sham rats (MAP, >80 mm Hg). Steady-state measurements were accompanied by metabolic flux analysis upon tracing of in vivo–injected 13C15N-glutamine or inhibition of glutaminolysis using the anticancer drug CB-839. RBC metabolic phenotypes recapitulated the systemic metabolic reprogramming observed in plasma from the same rodent model. Results indicate that shock RBCs rely on glutamine to fuel glutathione (GSH) synthesis and pyruvate transamination, whereas abrogation of glutaminolysis conferred early mortality and exacerbated lactic acidosis and systemic accumulation of succinate, a predictor of mortality in the military and civilian critically ill populations. Glutamine is here identified as an essential amine group donor in HS RBCs, plasma, liver, and lungs, providing additional rationale for the central role glutaminolysis plays in metabolic reprogramming and survival following severe hemorrhage.

scholarly journals Amplified Expression of Fructose 1,6-Bisphosphatase in Corynebacterium glutamicum Increases In Vivo Flux through the Pentose Phosphate Pathway and Lysine Production on Different Carbon Sources

2005 ◽  
Vol 71 (12) ◽  
pp. 8587-8596 ◽  
Author(s):  
Judith Becker ◽  
Corinna Klopprogge ◽  
Oskar Zelder ◽  
Elmar Heinzle ◽  
Christoph Wittmann
Keyword(s):  
Corynebacterium Glutamicum ◽  
Pentose Phosphate Pathway ◽  
Metabolic Flux ◽  
Carbon Sources ◽  
Pentose Phosphate ◽  
Metabolic Effects ◽  
Flux Analysis ◽  
Lysine Production ◽  
Fructose 1,6 Bisphosphatase

ABSTRACT The overexpression of fructose 1,6-bisphosphatase (FBPase) in Corynebacterium glutamicum leads to significant improvement of lysine production on different sugars. Amplified expression of FBPase via the promoter of the gene encoding elongation factor TU (EFTU) increased the lysine yield in the feedback-deregulated lysine-producing strain C. glutamicum lysCfbr by 40% on glucose and 30% on fructose or sucrose. Additionally formation of the by-products glycerol and dihydroxyacetone was significantly reduced in the PEFTUfbp mutant. As revealed by 13C metabolic flux analysis on glucose the overexpression of FBPase causes a redirection of carbon flux from glycolysis toward the pentose phosphate pathway (PPP) and thus leads to increased NADPH supply. Normalized to an uptake flux of glucose of 100%, the relative flux into the PPP was 56% for C. glutamicum lysCfbr PEFTUfbp and 46% for C. glutamicum lysCfb r . The flux for NADPH supply was 180% in the PEFTUfbp strain and only 146% in the parent strain. Amplification of FBPase increases the production of lysine via an increased supply of NADPH. Comparative studies with another mutant containing the sod promoter upstream of the fbp gene indicate that the expression level of FBPase relates to the extent of the metabolic effects. The overexpression of FBPase seems useful for starch- and molasses-based industrial lysine production with C. glutamicum. The redirection of flux toward the PPP should also be interesting for the production of other NADPH-demanding compounds as well as for products directly stemming from the PPP.

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