scholarly journals Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions

2021 ◽  
Vol 17 (1) ◽  
pp. e1007694
Author(s):  
Claudio Tomi-Andrino ◽  
Rupert Norman ◽  
Thomas Millat ◽  
Philippe Soucaille ◽  
Klaus Winzer ◽  
...  
Keyword(s):  
Experimental Data ◽  
In Silico ◽  
Physicochemical Parameters ◽  
Metabolic Flux ◽  
Growth Conditions ◽  
Central Carbon Metabolism ◽  
Centrality Measures ◽  
Flux Analysis ◽  
Metabolomics Data

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.

scholarly journals Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions

2020 ◽  
Author(s):  
Claudio Tomi-Andrino ◽  
Rupert Norman ◽  
Thomas Millat ◽  
Philippe Soucaille ◽  
Klaus Winzer ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Flux Analysis ◽  
In Silico ◽  
Physicochemical Parameters ◽  
Metabolic Flux ◽  
Living Systems ◽  
Flux Analysis ◽  
Flux Balance ◽  
Metabolic Fluxes ◽  
Balance Analysis

AbstractMetabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.Author summaryBiotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

scholarly journals Quantitative analysis of the physiological contributions of glucose to the TCA cycle

2019 ◽  
Author(s):  
Shiyu Liu ◽  
Ziwei Dai ◽  
Daniel E. Cooper ◽  
David G. Kirsch ◽  
Jason W. Locasale
Keyword(s):  
Quantitative Analysis ◽  
Metabolic Flux ◽  
Isotope Labeling ◽  
Tca Cycle ◽  
Central Carbon Metabolism ◽  
Flux Analysis ◽  
Experimental Conditions ◽  
The Tca Cycle ◽  
Metabolic Physiology

ABSTRACTThe carbon source for catabolism in vivo is a fundamental question in metabolic physiology. Limited by data and rigorous mathematical analysis, controversy exists over the nutritional sources for carbon in the tricarboxylic acid (TCA) cycle under physiological settings. Using isotope-labeling data in vivo across several experimental conditions, we construct multiple models of central carbon metabolism and develop methods based on metabolic flux analysis (MFA) to solve for the preferences of glucose, lactate, and other nutrients used in the TCA cycle across many tissues. We show that in nearly all circumstances, glucose contributes more than lactate as a nutrient source for the TCA cycle. This conclusion is verified in different animal strains from different studies, different administrations of 13C glucose, and is extended to multiple tissue types. Thus, this quantitative analysis of organismal metabolism defines the relative contributions of nutrient fluxes in physiology, provides a resource for analysis of in vivo isotope tracing data, and concludes that glucose is the major nutrient used for catabolism in mammals.

scholarly journals Bifunctional Malic/Malolactic Enzyme Provides a Novel Mechanism for NADPH-Balancing in Bacillus subtilis

mBio ◽  
2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Manuel Hörl ◽  
Tobias Fuhrer ◽  
Nicola Zamboni
Keyword(s):  
Bacillus Subtilis ◽  
Metabolic Flux ◽  
Central Carbon Metabolism ◽  
Flux Analysis ◽  
Content Type ◽  
Malolactic Enzyme ◽  
First Time

ABSTRACT The redox cofactor NADPH is required as a reducing equivalent in about 100 anabolic reactions throughout metabolism. To ensure fitness under all conditions, the demand is fulfilled by a few dehydrogenases in central carbon metabolism that reduce NADP+ with electrons derived from the catabolism of nutrients. In the case of Bacillus subtilis growing on glucose, quantitative flux analyses indicate that NADPH production largely exceeds biosynthetic needs, suggesting a hitherto unknown mechanism for NADPH balancing. We investigated the role of the four malic enzymes present in B. subtilis that could bring about a metabolic cycle for transhydrogenation of NADPH into NADH. Using quantitative 13C metabolic flux analysis, we found that isoform YtsJ alone contributes to NADPH balancing in vivo and demonstrated relevant NADPH-oxidizing activity by YtsJ in vitro. To our surprise, we discovered that depending on NADPH, YtsJ switches activity from a pyruvate-producing malic enzyme to a lactate-generating malolactic enzyme. This switch in activity allows YtsJ to adaptively compensate for cellular NADPH over- and underproduction upon demand. Finally, NADPH-dependent bifunctional activity was also detected in the YtsJ homolog in Escherichia coli MaeB. Overall, our study extends the known redox cofactor balancing mechanisms by providing first-time evidence that the type of catalyzed reaction by an enzyme depends on metabolite abundance. IMPORTANCE A new mechanism for NADPH balancing was discovered in Bacillus subtilis. It pivots on the bifunctional enzyme YtsJ, which is known to catalyze NADP-dependent malate decarboxylation. We found that in the presence of excessive NADPH, the same enzyme switches to malolactic activity and creates a transhydrogenation cycle that ultimately converts NADPH to NADH. This provides a regulated mechanism to immediately adjust NADPH/NADP+ in response to instantaneous needs.

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 Manually curated genome-scale reconstruction of the metabolic network of Bacillus megaterium DSM319

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Javad Aminian-Dehkordi ◽  
Seyyed Mohammad Mousavi ◽  
Arezou Jafari ◽  
Ivan Mijakovic ◽  
Sayed-Amir Marashi
Keyword(s):  
Experimental Data ◽  
Metabolic Network ◽  
Bacillus Megaterium ◽  
In Silico ◽  
Metabolic Model ◽  
Growth Behavior ◽  
Industrial Biotechnology ◽  
Flux Analysis ◽  
A Genome ◽  
Genome Scale

AbstractBacillus megaterium is a microorganism widely used in industrial biotechnology for production of enzymes and recombinant proteins, as well as in bioleaching processes. Precise understanding of its metabolism is essential for designing engineering strategies to further optimize B. megaterium for biotechnology applications. Here, we present a genome-scale metabolic model for B. megaterium DSM319, iJA1121, which is a result of a metabolic network reconciliation process. The model includes 1709 reactions, 1349 metabolites, and 1121 genes. Based on multiple-genome alignments and available genome-scale metabolic models for other Bacillus species, we constructed a draft network using an automated approach followed by manual curation. The refinements were performed using a gap-filling process. Constraint-based modeling was used to scrutinize network features. Phenotyping assays were performed in order to validate the growth behavior of the model using different substrates. To verify the model accuracy, experimental data reported in the literature (growth behavior patterns, metabolite production capabilities, metabolic flux analysis using 13C glucose and formaldehyde inhibitory effect) were confronted with model predictions. This indicated a very good agreement between in silico results and experimental data. For example, our in silico study of fatty acid biosynthesis and lipid accumulation in B. megaterium highlighted the importance of adopting appropriate carbon sources for fermentation purposes. We conclude that the genome-scale metabolic model iJA1121 represents a useful tool for systems analysis and furthers our understanding of the metabolism of B. megaterium.

scholarly journals Advances in metabolic flux analysis toward genome-scale profiling of higher organisms

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Georg Basler ◽  
Alisdair R. Fernie ◽  
Zoran Nikoloski
Keyword(s):  
Large Scale ◽  
Metabolic Flux ◽  
Cell Types ◽  
Flux Analysis ◽  
Metabolic Labeling ◽  
Modeling Framework ◽  
Metabolomics Data ◽  
Technological Advances ◽  
A Genome ◽  
Genome Scale

Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.

scholarly journals Regulation of lamin properties and functions: does phosphorylation do it all?

Open Biology ◽  
2015 ◽  
Vol 5 (11) ◽  
pp. 150094 ◽  
Author(s):  
Magdalena Machowska ◽  
Katarzyna Piekarowicz ◽  
Ryszard Rzepecki
Keyword(s):  
Gene Expression ◽  
Experimental Data ◽  
Chromatin Structure ◽  
In Silico ◽  
Building Blocks ◽  
Model Organisms ◽  
Intracellular Signalling Pathway ◽  
Evolutionarily Conserved ◽  
Structure Regulation

The main functions of lamins are their mechanical and structural roles as major building blocks of the karyoskeleton. They are also involved in chromatin structure regulation, gene expression, intracellular signalling pathway modulation and development. All essential lamin functions seem to depend on their capacity for assembly or disassembly after the receipt of specific signals, and after specific, selective and precisely regulated interactions through their various domains. Reversible phosphorylation of lamins is crucial for their functions, so it is important to understand how lamin polymerization and interactions are modulated, and which sequences may undergo such modifications. This review combines experimental data with results of our in silico analyses focused on lamin phosphorylation in model organisms to show the presence of evolutionarily conserved sequences and to indicate specific in vivo phosphorylations that affect particular functions.

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 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.

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